Sample records for model validation streamflow
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Simulating streamflow and water table depth with a coupled hydrological model
Directory of Open Access Journals (Sweden)
Alphonce Chenjerayi Guzha
2010-09-01
Full Text Available A coupled model integrating MODFLOW and TOPNET with the models interacting through the exchange of recharge and baseflow and river-aquifer interactions was developed and applied to the Big Darby Watershed in Ohio, USA. Calibration and validation results show that there is generally good agreement between measured streamflow and simulated results from the coupled model. At two gauging stations, average goodness of fit (R2, percent bias (PB, and Nash Sutcliffe efficiency (ENS values of 0.83, 11.15%, and 0.83, respectively, were obtained for simulation of streamflow during calibration, and values of 0.84, 8.75%, and 0.85, respectively, were obtained for validation. The simulated water table depths yielded average R2 values of 0.77 and 0.76 for calibration and validation, respectively. The good match between measured and simulated streamflows and water table depths demonstrates that the model is capable of adequately simulating streamflows and water table depths in the watershed and also capturing the influence of spatial and temporal variation in recharge.
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An Hourly Streamflow Forecasting Model Coupled with an Enforced Learning Strategy
Directory of Open Access Journals (Sweden)
Ming-Chang Wu
2015-10-01
Full Text Available Floods, one of the most significant natural hazards, often result in loss of life and property. Accurate hourly streamflow forecasting is always a key issue in hydrology for flood hazard mitigation. To improve the performance of hourly streamflow forecasting, a methodology concerning the development of neural network (NN based models with an enforced learning strategy is proposed in this paper. Firstly, four different NNs, namely back propagation network (BPN, radial basis function network (RBFN, self-organizing map (SOM, and support vector machine (SVM, are used to construct streamflow forecasting models. Through the cross-validation test, NN-based models with superior performance in streamflow forecasting are detected. Then, an enforced learning strategy is developed to further improve the performance of the superior NN-based models, i.e., SOM and SVM in this study. Finally, the proposed flow forecasting model is obtained. Actual applications are conducted to demonstrate the potential of the proposed model. Moreover, comparison between the NN-based models with and without the enforced learning strategy is performed to evaluate the effect of the enforced learning strategy on model performance. The results indicate that the NN-based models with the enforced learning strategy indeed improve the accuracy of hourly streamflow forecasting. Hence, the presented methodology is expected to be helpful for developing improved NN-based streamflow forecasting models.
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Christiansen, Daniel E.
2012-01-01
The U.S. Geological Survey, in cooperation with the Iowa Department of Natural Resources, conducted a study to examine techniques for estimation of daily streamflows using hydrological models and statistical methods. This report focuses on the use of a hydrologic model, the U.S. Geological Survey's Precipitation-Runoff Modeling System, to estimate daily streamflows at gaged and ungaged locations. The Precipitation-Runoff Modeling System is a modular, physically based, distributed-parameter modeling system developed to evaluate the impacts of various combinations of precipitation, climate, and land use on surface-water runoff and general basin hydrology. The Cedar River Basin was selected to construct a Precipitation-Runoff Modeling System model that simulates the period from January 1, 2000, to December 31, 2010. The calibration period was from January 1, 2000, to December 31, 2004, and the validation periods were from January 1, 2005, to December 31, 2010 and January 1, 2000 to December 31, 2010. A Geographic Information System tool was used to delineate the Cedar River Basin and subbasins for the Precipitation-Runoff Modeling System model and to derive parameters based on the physical geographical features. Calibration of the Precipitation-Runoff Modeling System model was completed using a U.S. Geological Survey calibration software tool. The main objective of the calibration was to match the daily streamflow simulated by the Precipitation-Runoff Modeling System model with streamflow measured at U.S. Geological Survey streamflow gages. The Cedar River Basin daily streamflow model performed with a Nash-Sutcliffe efficiency ranged from 0.82 to 0.33 during the calibration period, and a Nash-Sutcliffe efficiency ranged from 0.77 to -0.04 during the validation period. The Cedar River Basin model is meeting the criteria of greater than 0.50 Nash-Sutcliffe and is a good fit for streamflow conditions for the calibration period at all but one location, Austin, Minnesota
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Haj, Adel E.; Christiansen, Daniel E.; Hutchinson, Kasey J.
2015-10-14
The U.S. Geological Survey, in cooperation with the Iowa Department of Natural Resources, constructed Precipitation-Runoff Modeling System models to estimate daily streamflow for nine river basins in eastern Iowa that drain into the Mississippi River. The models are part of a suite of methods for estimating daily streamflow at ungaged sites. The Precipitation-Runoff Modeling System is a deterministic, distributed- parameter, physical-process-based modeling system developed to evaluate the response of streamflow and general drainage basin hydrology to various combinations of climate and land use. Calibration and validation periods used in each basin mostly were October 1, 2002, through September 30, 2012, but differed depending on the period of record available for daily mean streamflow measurements at U.S. Geological Survey streamflow-gaging stations.
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Free internet datasets for streamflow modelling using SWAT in the Johor river basin, Malaysia
International Nuclear Information System (INIS)
Tan, M L
2014-01-01
Streamflow modelling is a mathematical computational approach that represents terrestrial hydrology cycle digitally and is used for water resources assessment. However, such modelling endeavours require a large amount of data. Generally, governmental departments produce and maintain these data sets which make it difficult to obtain this data due to bureaucratic constraints. In some countries, the availability and quality of geospatial and climate datasets remain a critical issue due to many factors such as lacking of ground station, expertise, technology, financial support and war time. To overcome this problem, this research used public domain datasets from the Internet as ''input'' to a streamflow model. The intention is simulate daily and monthly streamflow of the Johor River Basin in Malaysia. The model used is the Soil and Water Assessment Tool (SWAT). As input free data including a digital elevation model (DEM), land use information, soil and climate data were used. The model was validated by in-situ streamflow information obtained from Rantau Panjang station for the year 2006. The coefficient of determination and Nash-Sutcliffe efficiency were 0.35/0.02 for daily simulated streamflow and 0.92/0.21 for monthly simulated streamflow, respectively. The results show that free data can provide a better simulation at a monthly scale compared to a daily basis in a tropical region. A sensitivity analysis and calibration procedure should be conducted in order to maximize the ''goodness-of-fit'' between simulated and observed streamflow. The application of Internet datasets promises an acceptable performance of streamflow modelling. This research demonstrates that public domain data is suitable for streamflow modelling in a tropical river basin within acceptable accuracy
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Free internet datasets for streamflow modelling using SWAT in the Johor river basin, Malaysia
Tan, M. L.
2014-02-01
Streamflow modelling is a mathematical computational approach that represents terrestrial hydrology cycle digitally and is used for water resources assessment. However, such modelling endeavours require a large amount of data. Generally, governmental departments produce and maintain these data sets which make it difficult to obtain this data due to bureaucratic constraints. In some countries, the availability and quality of geospatial and climate datasets remain a critical issue due to many factors such as lacking of ground station, expertise, technology, financial support and war time. To overcome this problem, this research used public domain datasets from the Internet as "input" to a streamflow model. The intention is simulate daily and monthly streamflow of the Johor River Basin in Malaysia. The model used is the Soil and Water Assessment Tool (SWAT). As input free data including a digital elevation model (DEM), land use information, soil and climate data were used. The model was validated by in-situ streamflow information obtained from Rantau Panjang station for the year 2006. The coefficient of determination and Nash-Sutcliffe efficiency were 0.35/0.02 for daily simulated streamflow and 0.92/0.21 for monthly simulated streamflow, respectively. The results show that free data can provide a better simulation at a monthly scale compared to a daily basis in a tropical region. A sensitivity analysis and calibration procedure should be conducted in order to maximize the "goodness-of-fit" between simulated and observed streamflow. The application of Internet datasets promises an acceptable performance of streamflow modelling. This research demonstrates that public domain data is suitable for streamflow modelling in a tropical river basin within acceptable accuracy.
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Effect of monthly areal rainfall uncertainty on streamflow simulation
Ndiritu, J. G.; Mkhize, N.
2017-08-01
Areal rainfall is mostly obtained from point rainfall measurements that are sparsely located and several studies have shown that this results in large areal rainfall uncertainties at the daily time step. However, water resources assessment is often carried out a monthly time step and streamflow simulation is usually an essential component of this assessment. This study set out to quantify monthly areal rainfall uncertainties and assess their effect on streamflow simulation. This was achieved by; i) quantifying areal rainfall uncertainties and using these to generate stochastic monthly areal rainfalls, and ii) finding out how the quality of monthly streamflow simulation and streamflow variability change if stochastic areal rainfalls are used instead of historic areal rainfalls. Tests on monthly rainfall uncertainty were carried out using data from two South African catchments while streamflow simulation was confined to one of them. A non-parametric model that had been applied at a daily time step was used for stochastic areal rainfall generation and the Pitman catchment model calibrated using the SCE-UA optimizer was used for streamflow simulation. 100 randomly-initialised calibration-validation runs using 100 stochastic areal rainfalls were compared with 100 runs obtained using the single historic areal rainfall series. By using 4 rain gauges alternately to obtain areal rainfall, the resulting differences in areal rainfall averaged to 20% of the mean monthly areal rainfall and rainfall uncertainty was therefore highly significant. Pitman model simulations obtained coefficient of efficiencies averaging 0.66 and 0.64 in calibration and validation using historic rainfalls while the respective values using stochastic areal rainfalls were 0.59 and 0.57. Average bias was less than 5% in all cases. The streamflow ranges using historic rainfalls averaged to 29% of the mean naturalised flow in calibration and validation and the respective average ranges using stochastic
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Validation of streamflow measurements made with M9 and RiverRay acoustic Doppler current profilers
Boldt, Justin A.; Oberg, Kevin A.
2015-01-01
The U.S. Geological Survey (USGS) Office of Surface Water (OSW) previously validated the use of Teledyne RD Instruments (TRDI) Rio Grande (in 2007), StreamPro (in 2006), and Broadband (in 1996) acoustic Doppler current profilers (ADCPs) for streamflow (discharge) measurements made by the USGS. Two new ADCPs, the SonTek M9 and the TRDI RiverRay, were first used in the USGS Water Mission Area programs in 2009. Since 2009, the OSW and USGS Water Science Centers (WSCs) have been conducting field measurements as part of their stream-gaging program using these ADCPs. The purpose of this paper is to document the results of USGS OSW analyses for validation of M9 and RiverRay ADCP streamflow measurements. The OSW required each participating WSC to make comparison measurements over the range of operating conditions in which the instruments were used until sufficient measurements were available. The performance of these ADCPs was evaluated for validation and to identify any present and potential problems. Statistical analyses of streamflow measurements indicate that measurements made with the SonTek M9 ADCP using firmware 2.00–3.00 or the TRDI RiverRay ADCP using firmware 44.12–44.15 are unbiased, and therefore, can continue to be used to make streamflow measurements in the USGS stream-gaging program. However, for the M9 ADCP, there are some important issues to be considered in making future measurements. Possible future work may include additional validation of streamflow measurements made with these instruments from other locations in the United States and measurement validation using updated firmware and software.
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Lee, Hak Su; Seo, Dong-Jun; Liu, Yuqiong; McKee, Paul; Corby, Robert
2010-05-01
State updating of distributed hydrologic models via assimilation of streamflow data is subject to "overfitting" because large dimensionality of the state space of the model may render the assimilation problem seriously underdetermined. To examine the issue in the context of operational hydrology, we carried out a set of real-world experiments in which we assimilate streamflow data at interior and/or outlet locations into gridded SAC and kinematic-wave routing models of the U.S. National Weather Service (NWS) Research Distributed Hydrologic Model (RDHM). We used for the experiments nine basins in the southern plains of the U.S. The experiments consist of selectively assimilating streamflow at different gauge locations, outlet and/or interior, and carrying out both dependent and independent validation. To assess the sensitivity of the quality of assimilation-aided streamflow simulation to the reduced dimensionality of the state space, we carried out data assimilation at spatially semi-distributed or lumped scale and by adjusting biases in precipitation and potential evaporation at a 6-hourly or larger scale. In this talk, we present the results and findings.
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Testing and modelling autoregressive conditional heteroskedasticity of streamflow processes
Directory of Open Access Journals (Sweden)
W. Wang
2005-01-01
Full Text Available Conventional streamflow models operate under the assumption of constant variance or season-dependent variances (e.g. ARMA (AutoRegressive Moving Average models for deseasonalized streamflow series and PARMA (Periodic AutoRegressive Moving Average models for seasonal streamflow series. However, with McLeod-Li test and Engle's Lagrange Multiplier test, clear evidences are found for the existence of autoregressive conditional heteroskedasticity (i.e. the ARCH (AutoRegressive Conditional Heteroskedasticity effect, a nonlinear phenomenon of the variance behaviour, in the residual series from linear models fitted to daily and monthly streamflow processes of the upper Yellow River, China. It is shown that the major cause of the ARCH effect is the seasonal variation in variance of the residual series. However, while the seasonal variation in variance can fully explain the ARCH effect for monthly streamflow, it is only a partial explanation for daily flow. It is also shown that while the periodic autoregressive moving average model is adequate in modelling monthly flows, no model is adequate in modelling daily streamflow processes because none of the conventional time series models takes the seasonal variation in variance, as well as the ARCH effect in the residuals, into account. Therefore, an ARMA-GARCH (Generalized AutoRegressive Conditional Heteroskedasticity error model is proposed to capture the ARCH effect present in daily streamflow series, as well as to preserve seasonal variation in variance in the residuals. The ARMA-GARCH error model combines an ARMA model for modelling the mean behaviour and a GARCH model for modelling the variance behaviour of the residuals from the ARMA model. Since the GARCH model is not followed widely in statistical hydrology, the work can be a useful addition in terms of statistical modelling of daily streamflow processes for the hydrological community.
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Modeling multisite streamflow dependence with maximum entropy copula
Hao, Z.; Singh, V. P.
2013-10-01
Synthetic streamflows at different sites in a river basin are needed for planning, operation, and management of water resources projects. Modeling the temporal and spatial dependence structure of monthly streamflow at different sites is generally required. In this study, the maximum entropy copula method is proposed for multisite monthly streamflow simulation, in which the temporal and spatial dependence structure is imposed as constraints to derive the maximum entropy copula. The monthly streamflows at different sites are then generated by sampling from the conditional distribution. A case study for the generation of monthly streamflow at three sites in the Colorado River basin illustrates the application of the proposed method. Simulated streamflow from the maximum entropy copula is in satisfactory agreement with observed streamflow.
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Lee, H.; Seo, D.-J.; Liu, Y.; Koren, V.; McKee, P.; Corby, R.
2012-01-01
State updating of distributed rainfall-runoff models via streamflow assimilation is subject to overfitting because large dimensionality of the state space of the model may render the assimilation problem seriously under-determined. To examine the issue in the context of operational hydrology, we carry out a set of real-world experiments in which streamflow data is assimilated into gridded Sacramento Soil Moisture Accounting (SAC-SMA) and kinematic-wave routing models of the US National Weather Service (NWS) Research Distributed Hydrologic Model (RDHM) with the variational data assimilation technique. Study basins include four basins in Oklahoma and five basins in Texas. To assess the sensitivity of data assimilation performance to dimensionality reduction in the control vector, we used nine different spatiotemporal adjustment scales, where state variables are adjusted in a lumped, semi-distributed, or distributed fashion and biases in precipitation and potential evaporation (PE) are adjusted hourly, 6-hourly, or kept time-invariant. For each adjustment scale, three different streamflow assimilation scenarios are explored, where streamflow observations at basin interior points, at the basin outlet, or at both interior points and the outlet are assimilated. The streamflow assimilation experiments with nine different basins show that the optimum spatiotemporal adjustment scale varies from one basin to another and may be different for streamflow analysis and prediction in all of the three streamflow assimilation scenarios. The most preferred adjustment scale for seven out of nine basins is found to be the distributed, hourly scale, despite the fact that several independent validation results at this adjustment scale indicated the occurrence of overfitting. Basins with highly correlated interior and outlet flows tend to be less sensitive to the adjustment scale and could benefit more from streamflow assimilation. In comparison to outlet flow assimilation, interior flow
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Pokhrel, Prafulla; Wang, Q. J.; Robertson, David E.
2013-10-01
Seasonal streamflow forecasts are valuable for planning and allocation of water resources. In Australia, the Bureau of Meteorology employs a statistical method to forecast seasonal streamflows. The method uses predictors that are related to catchment wetness at the start of a forecast period and to climate during the forecast period. For the latter, a predictor is selected among a number of lagged climate indices as candidates to give the "best" model in terms of model performance in cross validation. This study investigates two strategies for further improvement in seasonal streamflow forecasts. The first is to combine, through Bayesian model averaging, multiple candidate models with different lagged climate indices as predictors, to take advantage of different predictive strengths of the multiple models. The second strategy is to introduce additional candidate models, using rainfall and sea surface temperature predictions from a global climate model as predictors. This is to take advantage of the direct simulations of various dynamic processes. The results show that combining forecasts from multiple statistical models generally yields more skillful forecasts than using only the best model and appears to moderate the worst forecast errors. The use of rainfall predictions from the dynamical climate model marginally improves the streamflow forecasts when viewed over all the study catchments and seasons, but the use of sea surface temperature predictions provide little additional benefit.
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Inferring Soil Moisture Memory from Streamflow Observations Using a Simple Water Balance Model
Orth, Rene; Koster, Randal Dean; Seneviratne, Sonia I.
2013-01-01
Soil moisture is known for its integrative behavior and resulting memory characteristics. Soil moisture anomalies can persist for weeks or even months into the future, making initial soil moisture a potentially important contributor to skill in weather forecasting. A major difficulty when investigating soil moisture and its memory using observations is the sparse availability of long-term measurements and their limited spatial representativeness. In contrast, there is an abundance of long-term streamflow measurements for catchments of various sizes across the world. We investigate in this study whether such streamflow measurements can be used to infer and characterize soil moisture memory in respective catchments. Our approach uses a simple water balance model in which evapotranspiration and runoff ratios are expressed as simple functions of soil moisture; optimized functions for the model are determined using streamflow observations, and the optimized model in turn provides information on soil moisture memory on the catchment scale. The validity of the approach is demonstrated with data from three heavily monitored catchments. The approach is then applied to streamflow data in several small catchments across Switzerland to obtain a spatially distributed description of soil moisture memory and to show how memory varies, for example, with altitude and topography.
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Genetic Algorithm Based Framework for Automation of Stochastic Modeling of Multi-Season Streamflows
Srivastav, R. K.; Srinivasan, K.; Sudheer, K.
2009-05-01
Synthetic streamflow data generation involves the synthesis of likely streamflow patterns that are statistically indistinguishable from the observed streamflow data. The various kinds of stochastic models adopted for multi-season streamflow generation in hydrology are: i) parametric models which hypothesize the form of the periodic dependence structure and the distributional form a priori (examples are PAR, PARMA); disaggregation models that aim to preserve the correlation structure at the periodic level and the aggregated annual level; ii) Nonparametric models (examples are bootstrap/kernel based methods), which characterize the laws of chance, describing the stream flow process, without recourse to prior assumptions as to the form or structure of these laws; (k-nearest neighbor (k-NN), matched block bootstrap (MABB)); non-parametric disaggregation model. iii) Hybrid models which blend both parametric and non-parametric models advantageously to model the streamflows effectively. Despite many of these developments that have taken place in the field of stochastic modeling of streamflows over the last four decades, accurate prediction of the storage and the critical drought characteristics has been posing a persistent challenge to the stochastic modeler. This is partly because, usually, the stochastic streamflow model parameters are estimated by minimizing a statistically based objective function (such as maximum likelihood (MLE) or least squares (LS) estimation) and subsequently the efficacy of the models is being validated based on the accuracy of prediction of the estimates of the water-use characteristics, which requires large number of trial simulations and inspection of many plots and tables. Still accurate prediction of the storage and the critical drought characteristics may not be ensured. In this study a multi-objective optimization framework is proposed to find the optimal hybrid model (blend of a simple parametric model, PAR(1) model and matched block
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Wavelet-linear genetic programming: A new approach for modeling monthly streamflow
Ravansalar, Masoud; Rajaee, Taher; Kisi, Ozgur
2017-06-01
The streamflows are important and effective factors in stream ecosystems and its accurate prediction is an essential and important issue in water resources and environmental engineering systems. A hybrid wavelet-linear genetic programming (WLGP) model, which includes a discrete wavelet transform (DWT) and a linear genetic programming (LGP) to predict the monthly streamflow (Q) in two gauging stations, Pataveh and Shahmokhtar, on the Beshar River at the Yasuj, Iran were used in this study. In the proposed WLGP model, the wavelet analysis was linked to the LGP model where the original time series of streamflow were decomposed into the sub-time series comprising wavelet coefficients. The results were compared with the single LGP, artificial neural network (ANN), a hybrid wavelet-ANN (WANN) and Multi Linear Regression (MLR) models. The comparisons were done by some of the commonly utilized relevant physical statistics. The Nash coefficients (E) were found as 0.877 and 0.817 for the WLGP model, for the Pataveh and Shahmokhtar stations, respectively. The comparison of the results showed that the WLGP model could significantly increase the streamflow prediction accuracy in both stations. Since, the results demonstrate a closer approximation of the peak streamflow values by the WLGP model, this model could be utilized for the simulation of cumulative streamflow data prediction in one month ahead.
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Holmes, Robert R.; Singh, Vijay P.
2016-01-01
Autonomous direct determination of a continuous time series of streamflow is not economically feasible at present (2014). As such, surrogates are used to derive a continuous time series of streamflow. The derivation process entails developing a streamflow rating, which can range from a simple, single-valued relation between stage and streamflow to a fully dynamic one-dimensional model based on hydraulics of the flow.
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Climate model assessment of changes in winter-spring streamflow timing over North America
Kam, Jonghun; Knutson, Thomas R.; Milly, Paul C. D.
2018-01-01
Over regions where snow-melt runoff substantially contributes to winter-spring streamflows, warming can accelerate snow melt and reduce dry-season streamflows. However, conclusive detection of changes and attribution to anthropogenic forcing is hindered by brevity of observational records, model uncertainty, and uncertainty concerning internal variability. In this study, a detection/attribution of changes in mid-latitude North American winter-spring streamflow timing is examined using nine global climate models under multiple forcing scenarios. In this study, robustness across models, start/end dates for trends, and assumptions about internal variability is evaluated. Marginal evidence for an emerging detectable anthropogenic influence (according to four or five of nine models) is found in the north-central U.S., where winter-spring streamflows have been coming earlier. Weaker indications of detectable anthropogenic influence (three of nine models) are found in the mountainous western U.S./southwestern Canada and in extreme northeastern U.S./Canadian Maritimes. In the former region, a recent shift toward later streamflows has rendered the full-record trend toward earlier streamflows only marginally significant, with possible implications for previously published climate change detection findings for streamflow timing in this region. In the latter region, no forced model shows as large a shift toward earlier streamflow timing as the detectable observed shift. In other (including warm, snow-free) regions, observed trends are typically not detectable, although in the U.S. central plains we find detectable delays in streamflow, which are inconsistent with forced model experiments.
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STREAMFLOW AND WATER QUALITY REGRESSION MODELING ...
African Journals Online (AJOL)
... downstream Obigbo station show: consistent time-trends in degree of contamination; linear and non-linear relationships for water quality models against total dissolved solids (TDS), total suspended sediment (TSS), chloride, pH and sulphate; and non-linear relationship for streamflow and water quality transport models.
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Fenicia, Fabrizio; Kavetski, Dmitri; Savenije, Hubert H. G.; Pfister, Laurent
2016-02-01
This paper explores the development and application of distributed hydrological models, focusing on the key decisions of how to discretize the landscape, which model structures to use in each landscape element, and how to link model parameters across multiple landscape elements. The case study considers the Attert catchment in Luxembourg—a 300 km2 mesoscale catchment with 10 nested subcatchments that exhibit clearly different streamflow dynamics. The research questions are investigated using conceptual models applied at hydrologic response unit (HRU) scales (1-4 HRUs) on 6 hourly time steps. Multiple model structures are hypothesized and implemented using the SUPERFLEX framework. Following calibration, space/time model transferability is tested using a split-sample approach, with evaluation criteria including streamflow prediction error metrics and hydrological signatures. Our results suggest that: (1) models using geology-based HRUs are more robust and capture the spatial variability of streamflow time series and signatures better than models using topography-based HRUs; this finding supports the hypothesis that, in the Attert, geology exerts a stronger control than topography on streamflow generation, (2) streamflow dynamics of different HRUs can be represented using distinct and remarkably simple model structures, which can be interpreted in terms of the perceived dominant hydrologic processes in each geology type, and (3) the same maximum root zone storage can be used across the three dominant geological units with no loss in model transferability; this finding suggests that the partitioning of water between streamflow and evaporation in the study area is largely independent of geology and can be used to improve model parsimony. The modeling methodology introduced in this study is general and can be used to advance our broader understanding and prediction of hydrological behavior, including the landscape characteristics that control hydrologic response, the
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A watershed modeling approach to streamflow reconstruction from tree-ring records
International Nuclear Information System (INIS)
Saito, Laurel; Biondi, Franco; Salas, Jose D; Panorska, Anna K; Kozubowski, Tomasz J
2008-01-01
Insight into long-term changes of streamflow is critical for addressing implications of global warming for sustainable water management. To date, dendrohydrologists have employed sophisticated regression techniques to extend runoff records, but this empirical approach cannot directly test the influence of watershed factors that alter streamflow independently of climate. We designed a mechanistic watershed model to calculate streamflows at annual timescales using as few inputs as possible. The model was calibrated for upper reaches of the Walker River, which straddles the boundary between the Sierra Nevada of California and the Great Basin of Nevada. Even though the model incorporated simplified relationships between precipitation and other components of the hydrologic cycle, it predicted water year streamflows with correlations of 0.87 when appropriate precipitation values were used
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Farmer, William H.; Knight, Rodney R.; Eash, David A.; Kasey J. Hutchinson,; Linhart, S. Mike; Christiansen, Daniel E.; Archfield, Stacey A.; Over, Thomas M.; Kiang, Julie E.
2015-08-24
Daily records of streamflow are essential to understanding hydrologic systems and managing the interactions between human and natural systems. Many watersheds and locations lack streamgages to provide accurate and reliable records of daily streamflow. In such ungaged watersheds, statistical tools and rainfall-runoff models are used to estimate daily streamflow. Previous work compared 19 different techniques for predicting daily streamflow records in the southeastern United States. Here, five of the better-performing methods are compared in a different hydroclimatic region of the United States, in Iowa. The methods fall into three classes: (1) drainage-area ratio methods, (2) nonlinear spatial interpolations using flow duration curves, and (3) mechanistic rainfall-runoff models. The first two classes are each applied with nearest-neighbor and map-correlated index streamgages. Using a threefold validation and robust rank-based evaluation, the methods are assessed for overall goodness of fit of the hydrograph of daily streamflow, the ability to reproduce a daily, no-fail storage-yield curve, and the ability to reproduce key streamflow statistics. As in the Southeast study, a nonlinear spatial interpolation of daily streamflow using flow duration curves is found to be a method with the best predictive accuracy. Comparisons with previous work in Iowa show that the accuracy of mechanistic models with at-site calibration is substantially degraded in the ungaged framework.
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Wu, Pan; Wang, Xu-Sheng; Liang, Sihai
2018-06-01
Though extensive researches were conducted in the source region of the Yellow River (SRYR) to analyse climate change influence on streamflow, however, few researches concentrate on streamflow of the sub-basin above the Huangheyan station in the SRYR (HSRYR) where a water retaining dam was built in the outlet in 1999. To improve the reservoir regulation strategies, this study analysed streamflow change of the HSRYR in a mesoscale. A tank model (TM) was proposed and calibrated with monthly observation streamflow from 1991 to 1998. In the validation period, though there is a simulation deviation during the water storage and power generation period, simulated streamflow agrees favourably with observation data from 2008 to 2013. The model was further validated by two inside lakes area obtained from Landsat 5, 7, 8 datasets from 2000 to 2014, and significant correlations were found between the simulated lake outlet runoff and respective lake area. Then 21 Global Climate Models (GCM) ensembled data of three emission scenarios (SRA2, SRA1B and SRB1) were downscaled and used as input to the TM to simulate the runoff change of three benchmark periods 2011-2030 (2020s), 2046-2065 (2050s), 2080-2099 (2090s), respectively. Though temperature increase dramatically, these projected results similarly indicated that streamflow shows an increase trend in the long term. Runoff increase is mainly caused by increasing precipitation and decreasing evaporation. Water resources distribution is projected to change from summer-autumn dominant to autumn winter dominant. Annual lowest runoff will occur in May caused by earlier snow melting and increasing evaporation in March. According to the obtained results, winter runoff should be artificially stored by reservoir regulation in the future to prevent zero-flow occurrent in May. This research is helpful for water resources management and provides a better understand of streamflow change caused by climate change in the future.
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SWAT application in intensive irrigation systems: Model modification, calibration and validation
Dechmi, Farida; Burguete, Javier; Skhiri, Ahmed
2012-11-01
SummaryThe Soil and Water Assessment Tool (SWAT) is a well established, distributed, eco-hydrologic model. However, using the study case of an agricultural intensive irrigated watershed, it was shown that all the model versions are not able to appropriately reproduce the total streamflow in such system when the irrigation source is outside the watershed. The objective of this study was to modify the SWAT2005 version for correctly simulating the main hydrological processes. Crop yield, total streamflow, total suspended sediment (TSS) losses and phosphorus load calibration and validation were performed using field survey information and water quantity and quality data recorded during 2008 and 2009 years in Del Reguero irrigated watershed in Spain. The goodness of the calibration and validation results was assessed using five statistical measures, including the Nash-Sutcliffe efficiency (NSE). Results indicated that the average annual crop yield and actual evapotranspiration estimations were quite satisfactory. On a monthly basis, the values of NSE were 0.90 (calibration) and 0.80 (validation) indicating that the modified model could reproduce accurately the observed streamflow. The TSS losses were also satisfactorily estimated (NSE = 0.72 and 0.52 for the calibration and validation steps). The monthly temporal patterns and all the statistical parameters indicated that the modified SWAT-IRRIG model adequately predicted the total phosphorus (TP) loading. Therefore, the model could be used to assess the impacts of different best management practices on nonpoint phosphorus losses in irrigated systems.
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Partitioning uncertainty in streamflow projections under nonstationary model conditions
Chawla, Ila; Mujumdar, P. P.
2018-02-01
Assessing the impacts of Land Use (LU) and climate change on future streamflow projections is necessary for efficient management of water resources. However, model projections are burdened with significant uncertainty arising from various sources. Most of the previous studies have considered climate models and scenarios as major sources of uncertainty, but uncertainties introduced by land use change and hydrologic model assumptions are rarely investigated. In this paper an attempt is made to segregate the contribution from (i) general circulation models (GCMs), (ii) emission scenarios, (iii) land use scenarios, (iv) stationarity assumption of the hydrologic model, and (v) internal variability of the processes, to overall uncertainty in streamflow projections using analysis of variance (ANOVA) approach. Generally, most of the impact assessment studies are carried out with unchanging hydrologic model parameters in future. It is, however, necessary to address the nonstationarity in model parameters with changing land use and climate. In this paper, a regression based methodology is presented to obtain the hydrologic model parameters with changing land use and climate scenarios in future. The Upper Ganga Basin (UGB) in India is used as a case study to demonstrate the methodology. The semi-distributed Variable Infiltration Capacity (VIC) model is set-up over the basin, under nonstationary conditions. Results indicate that model parameters vary with time, thereby invalidating the often-used assumption of model stationarity. The streamflow in UGB under the nonstationary model condition is found to reduce in future. The flows are also found to be sensitive to changes in land use. Segregation results suggest that model stationarity assumption and GCMs along with their interactions with emission scenarios, act as dominant sources of uncertainty. This paper provides a generalized framework for hydrologists to examine stationarity assumption of models before considering them
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Artificial Neural Network Models for Long Lead Streamflow Forecasts using Climate Information
Kumar, J.; Devineni, N.
2007-12-01
developed between the identified predictors and the predictand. Predictors used are the scores of Principal Components Analysis (PCA). The models were tested and validated. The feed- forward multi-layer perceptron (MLP) type neural networks trained using the back-propagation algorithms are employed in the current study. The performance of the ANN-model forecasts are evaluated using various performance evaluation measures such as correlation coefficient, root mean square error (RMSE). The preliminary results shows that ANNs are efficient to forecast long lead time streamflows using climatic predictors.
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Directory of Open Access Journals (Sweden)
J. C. Ochoa-Rivera
2002-01-01
Full Text Available A model for multivariate streamflow generation is presented, based on a multilayer feedforward neural network. The structure of the model results from two components, the neural network (NN deterministic component and a random component which is assumed to be normally distributed. It is from this second component that the model achieves the ability to incorporate effectively the uncertainty associated with hydrological processes, making it valuable as a practical tool for synthetic generation of streamflow series. The NN topology and the corresponding analytical explicit formulation of the model are described in detail. The model is calibrated with a series of monthly inflows to two reservoir sites located in the Tagus River basin (Spain, while validation is performed through estimation of a set of statistics that is relevant for water resources systems planning and management. Among others, drought and storage statistics are computed and compared for both the synthetic and historical series. The performance of the NN-based model was compared to that of a standard autoregressive AR(2 model. Results show that NN represents a promising modelling alternative for simulation purposes, with interesting potential in the context of water resources systems management and optimisation. Keywords: neural networks, perceptron multilayer, error backpropagation, hydrological scenario generation, multivariate time-series..
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Selective Tree-ring Models: A Novel Method for Reconstructing Streamflow Using Tree Rings
Foard, M. B.; Nelson, A. S.; Harley, G. L.
2017-12-01
Surface water is among the most instrumental and vulnerable resources in the Northwest United States (NW). Recent observations show that overall water quantity is declining in streams across the region, while extreme flooding events occur more frequently. Historical streamflow models inform probabilities of extreme flow events (flood or drought) by describing frequency and duration of past events. There are numerous examples of tree-rings being utilized to reconstruct streamflow in the NW. These models confirm that tree-rings are highly accurate at predicting streamflow, however there are many nuances that limit their applicability through time and space. For example, most models predict streamflow from hydrologically altered rivers (e.g. dammed, channelized) which may hinder our ability to predict natural prehistoric flow. They also have a tendency to over/under-predict extreme flow events. Moreover, they often neglect to capture the changing relationships between tree-growth and streamflow over time and space. To address these limitations, we utilized national tree-ring and streamflow archives to investigate the relationships between the growth of multiple coniferous species and free-flowing streams across the NW using novel species-and site-specific streamflow models - a term we coined"selective tree-ring models." Correlation function analysis and regression modeling were used to evaluate the strengths and directions of the flow-growth relationships. Species with significant relationships in the same direction were identified as strong candidates for selective models. Temporal and spatial patterns of these relationships were examined using running correlations and inverse distance weighting interpolation, respectively. Our early results indicate that (1) species adapted to extreme climates (e.g. hot-dry, cold-wet) exhibit the most consistent relationships across space, (2) these relationships weaken in locations with mild climatic variability, and (3) some
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Wang, Q. J.; Robertson, D. E.; Chiew, F. H. S.
2009-05-01
Seasonal forecasting of streamflows can be highly valuable for water resources management. In this paper, a Bayesian joint probability (BJP) modeling approach for seasonal forecasting of streamflows at multiple sites is presented. A Box-Cox transformed multivariate normal distribution is proposed to model the joint distribution of future streamflows and their predictors such as antecedent streamflows and El Niño-Southern Oscillation indices and other climate indicators. Bayesian inference of model parameters and uncertainties is implemented using Markov chain Monte Carlo sampling, leading to joint probabilistic forecasts of streamflows at multiple sites. The model provides a parametric structure for quantifying relationships between variables, including intersite correlations. The Box-Cox transformed multivariate normal distribution has considerable flexibility for modeling a wide range of predictors and predictands. The Bayesian inference formulated allows the use of data that contain nonconcurrent and missing records. The model flexibility and data-handling ability means that the BJP modeling approach is potentially of wide practical application. The paper also presents a number of statistical measures and graphical methods for verification of probabilistic forecasts of continuous variables. Results for streamflows at three river gauges in the Murrumbidgee River catchment in southeast Australia show that the BJP modeling approach has good forecast quality and that the fitted model is consistent with observed data.
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Artificial intelligence based models for stream-flow forecasting: 2000-2015
Yaseen, Zaher Mundher; El-shafie, Ahmed; Jaafar, Othman; Afan, Haitham Abdulmohsin; Sayl, Khamis Naba
2015-11-01
The use of Artificial Intelligence (AI) has increased since the middle of the 20th century as seen in its application in a wide range of engineering and science problems. The last two decades, for example, has seen a dramatic increase in the development and application of various types of AI approaches for stream-flow forecasting. Generally speaking, AI has exhibited significant progress in forecasting and modeling non-linear hydrological applications and in capturing the noise complexity in the dataset. This paper explores the state-of-the-art application of AI in stream-flow forecasting, focusing on defining the data-driven of AI, the advantages of complementary models, as well as the literature and their possible future application in modeling and forecasting stream-flow. The review also identifies the major challenges and opportunities for prospective research, including, a new scheme for modeling the inflow, a novel method for preprocessing time series frequency based on Fast Orthogonal Search (FOS) techniques, and Swarm Intelligence (SI) as an optimization approach.
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Historical Trends in Mean and Extreme Runoff and Streamflow Based on Observations and Climate Models
Directory of Open Access Journals (Sweden)
Behzad Asadieh
2016-05-01
Full Text Available To understand changes in global mean and extreme streamflow volumes over recent decades, we statistically analyzed runoff and streamflow simulated by the WBM-plus hydrological model using either observational-based meteorological inputs from WATCH Forcing Data (WFD, or bias-corrected inputs from five global climate models (GCMs provided by the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP. Results show that the bias-corrected GCM inputs yield very good agreement with the observation-based inputs in average magnitude of runoff and streamflow. On global average, the observation-based simulated mean runoff and streamflow both decreased about 1.3% from 1971 to 2001. However, GCM-based simulations yield increasing trends over that period, with an inter-model global average of 1% for mean runoff and 0.9% for mean streamflow. In the GCM-based simulations, relative changes in extreme runoff and extreme streamflow (annual maximum daily values and annual-maximum seven-day streamflow are slightly greater than those of mean runoff and streamflow, in terms of global and continental averages. Observation-based simulations show increasing trend in mean runoff and streamflow for about one-half of the land areas and decreasing trend for the other half. However, mean and extreme runoff and streamflow based on the GCMs show increasing trend for approximately two-thirds of the global land area and decreasing trend for the other one-third. Further work is needed to understand why GCM simulations appear to indicate trends in streamflow that are more positive than those suggested by climate observations, even where, as in ISI-MIP, bias correction has been applied so that their streamflow climatology is realistic.
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Directory of Open Access Journals (Sweden)
P. Wu
2018-06-01
Full Text Available Though extensive researches were conducted in the source region of the Yellow River (SRYR to analyse climate change influence on streamflow, however, few researches concentrate on streamflow of the sub-basin above the Huangheyan station in the SRYR (HSRYR where a water retaining dam was built in the outlet in 1999. To improve the reservoir regulation strategies, this study analysed streamflow change of the HSRYR in a mesoscale. A tank model (TM was proposed and calibrated with monthly observation streamflow from 1991 to 1998. In the validation period, though there is a simulation deviation during the water storage and power generation period, simulated streamflow agrees favourably with observation data from 2008 to 2013. The model was further validated by two inside lakes area obtained from Landsat 5, 7, 8 datasets from 2000 to 2014, and significant correlations were found between the simulated lake outlet runoff and respective lake area. Then 21 Global Climate Models (GCM ensembled data of three emission scenarios (SRA2, SRA1B and SRB1 were downscaled and used as input to the TM to simulate the runoff change of three benchmark periods 2011–2030 (2020s, 2046–2065 (2050s, 2080–2099 (2090s, respectively. Though temperature increase dramatically, these projected results similarly indicated that streamflow shows an increase trend in the long term. Runoff increase is mainly caused by increasing precipitation and decreasing evaporation. Water resources distribution is projected to change from summer-autumn dominant to autumn winter dominant. Annual lowest runoff will occur in May caused by earlier snow melting and increasing evaporation in March. According to the obtained results, winter runoff should be artificially stored by reservoir regulation in the future to prevent zero-flow occurrent in May. This research is helpful for water resources management and provides a better understand of streamflow change caused by climate change in the
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McCreight, J. L.; Wu, Y.; Gochis, D.; Rafieeinasab, A.; Dugger, A. L.; Yu, W.; Cosgrove, B.; Cui, Z.; Oubeidillah, A.; Briar, D.
2016-12-01
The streamflow (discharge) data assimilation capability in version 1 of the National Water Model (NWM; a WRF-Hydro configuration) is applied and evaluated in a 5-year (2011-2015) retrospective study using NLDAS2 forcing data over CONUS. This talk will describe the NWM V1 operational nudging (continuous-time) streamflow data assimilation approach, its motivation, and its relationship to this retrospective evaluation. Results from this study will provide a an analysis-based (not forecast-based) benchmark for streamflow DA in the NWM. The goal of the assimilation is to reduce discharge bias and improve channel initial conditions for discharge forecasting (though forecasts are not considered here). The nudging method assimilates discharge observations at nearly 7,000 USGS gages (at frequency up to 1/15 minutes) to produce a (univariate) discharge reanalysis (i.e. this is the only variable affected by the assimilation). By withholding 14% nested gages throughout CONUS in a separate validation run, we evaluate the downstream impact of assimilation at upstream gages. Based on this sample, we estimate the skill of the streamflow reanalysis at ungaged locations and examine factors governing the skill of the assimilation. Comparison of assimilation and open-loop runs is presented. Performance of DA under both high and low flow regimes and selected flooding events is examined. Preliminary evaluation of nudging parameter sensitivity and its relationship to flow regime will be presented.
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Novel approach for streamflow forecasting using a hybrid ANFIS-FFA model
Yaseen, Zaher Mundher; Ebtehaj, Isa; Bonakdari, Hossein; Deo, Ravinesh C.; Danandeh Mehr, Ali; Mohtar, Wan Hanna Melini Wan; Diop, Lamine; El-shafie, Ahmed; Singh, Vijay P.
2017-11-01
The present study proposes a new hybrid evolutionary Adaptive Neuro-Fuzzy Inference Systems (ANFIS) approach for monthly streamflow forecasting. The proposed method is a novel combination of the ANFIS model with the firefly algorithm as an optimizer tool to construct a hybrid ANFIS-FFA model. The results of the ANFIS-FFA model is compared with the classical ANFIS model, which utilizes the fuzzy c-means (FCM) clustering method in the Fuzzy Inference Systems (FIS) generation. The historical monthly streamflow data for Pahang River, which is a major river system in Malaysia that characterized by highly stochastic hydrological patterns, is used in the study. Sixteen different input combinations with one to five time-lagged input variables are incorporated into the ANFIS-FFA and ANFIS models to consider the antecedent seasonal variations in historical streamflow data. The mean absolute error (MAE), root mean square error (RMSE) and correlation coefficient (r) are used to evaluate the forecasting performance of ANFIS-FFA model. In conjunction with these metrics, the refined Willmott's Index (Drefined), Nash-Sutcliffe coefficient (ENS) and Legates and McCabes Index (ELM) are also utilized as the normalized goodness-of-fit metrics. Comparison of the results reveals that the FFA is able to improve the forecasting accuracy of the hybrid ANFIS-FFA model (r = 1; RMSE = 0.984; MAE = 0.364; ENS = 1; ELM = 0.988; Drefined = 0.994) applied for the monthly streamflow forecasting in comparison with the traditional ANFIS model (r = 0.998; RMSE = 3.276; MAE = 1.553; ENS = 0.995; ELM = 0.950; Drefined = 0.975). The results also show that the ANFIS-FFA is not only superior to the ANFIS model but also exhibits a parsimonious modelling framework for streamflow forecasting by incorporating a smaller number of input variables required to yield the comparatively better performance. It is construed that the FFA optimizer can thus surpass the accuracy of the traditional ANFIS model in general
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Bayesian Models for Streamflow and River Network Reconstruction using Tree Rings
Ravindranath, A.; Devineni, N.
2016-12-01
Water systems face non-stationary, dynamically shifting risks due to shifting societal conditions and systematic long-term variations in climate manifesting as quasi-periodic behavior on multi-decadal time scales. Water systems are thus vulnerable to long periods of wet or dry hydroclimatic conditions. Streamflow is a major component of water systems and a primary means by which water is transported to serve ecosystems' and human needs. Thus, our concern is in understanding streamflow variability. Climate variability and impacts on water resources are crucial factors affecting streamflow, and multi-scale variability increases risk to water sustainability and systems. Dam operations are necessary for collecting water brought by streamflow while maintaining downstream ecological health. Rules governing dam operations are based on streamflow records that are woefully short compared to periods of systematic variation present in the climatic factors driving streamflow variability and non-stationarity. We use hierarchical Bayesian regression methods in order to reconstruct paleo-streamflow records for dams within a basin using paleoclimate proxies (e.g. tree rings) to guide the reconstructions. The riverine flow network for the entire basin is subsequently modeled hierarchically using feeder stream and tributary flows. This is a starting point in analyzing streamflow variability and risks to water systems, and developing a scientifically-informed dynamic risk management framework for formulating dam operations and water policies to best hedge such risks. We will apply this work to the Missouri and Delaware River Basins (DRB). Preliminary results of streamflow reconstructions for eight dams in the upper DRB using standard Gaussian regression with regional tree ring chronologies give streamflow records that now span two to two and a half centuries, and modestly smoothed versions of these reconstructed flows indicate physically-justifiable trends in the time series.
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Directory of Open Access Journals (Sweden)
J. Y. G. Dos Santos
2014-09-01
Full Text Available This study aims to assess the impact of the land-use changes between the periods 1967−1974 and 1997−2008 on the streamflow of Tapacurá catchment (northeastern Brazil using the Soil and Water Assessment Tool (SWAT model. The results show that the most sensitive parameters were the baseflow, Manning factor, time of concentration and soil evaporation compensation factor, which affect the catchment hydrology. The model calibration and validation were performed on a monthly basis, and the streamflow simulation showed a good level of accuracy for both periods. The obtained R2 and Nash-Sutcliffe Efficiency values for each period were respectively 0.82 and 0.81 for 1967−1974, and 0.93 and 0.92 for the period 1997−2008. The evaluation of the SWAT model response to the land cover has shown that the mean monthly flow, during the rainy seasons for 1967−1974, decreased when compared to 1997−2008.
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Kolars, Kelsey A.; Vecchia, Aldo V.; Ryberg, Karen R.
2016-02-24
The Souris River Basin is a 61,000-square-kilometer basin in the Provinces of Saskatchewan and Manitoba and the State of North Dakota. In May and June of 2011, record-setting rains were seen in the headwater areas of the basin. Emergency spillways of major reservoirs were discharging at full or nearly full capacity, and extensive flooding was seen in numerous downstream communities. To determine the probability of future extreme floods and droughts, the U.S. Geological Survey, in cooperation with the North Dakota State Water Commission, developed a stochastic model for simulating Souris River Basin precipitation, evapotranspiration, and natural (unregulated) streamflow. Simulations from the model can be used in future studies to simulate regulated streamflow, design levees, and other structures; and to complete economic cost/benefit analyses.Long-term climatic variability was analyzed using tree-ring chronologies to hindcast precipitation to the early 1700s and compare recent wet and dry conditions to earlier extreme conditions. The extended precipitation record was consistent with findings from the Devils Lake and Red River of the North Basins (southeast of the Souris River Basin), supporting the idea that regional climatic patterns for many centuries have consisted of alternating wet and dry climate states.A stochastic climate simulation model for precipitation, temperature, and potential evapotranspiration for the Souris River Basin was developed using recorded meteorological data and extended precipitation records provided through tree-ring analysis. A significant climate transition was seen around1970, with 1912–69 representing a dry climate state and 1970–2011 representing a wet climate state. Although there were some distinct subpatterns within the basin, the predominant differences between the two states were higher spring through early fall precipitation and higher spring potential evapotranspiration for the wet compared to the dry state.A water
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Makkeasorn, A.; Chang, N. B.; Zhou, X.
2008-05-01
SummarySustainable water resources management is a critically important priority across the globe. While water scarcity limits the uses of water in many ways, floods may also result in property damages and the loss of life. To more efficiently use the limited amount of water under the changing world or to resourcefully provide adequate time for flood warning, the issues have led us to seek advanced techniques for improving streamflow forecasting on a short-term basis. This study emphasizes the inclusion of sea surface temperature (SST) in addition to the spatio-temporal rainfall distribution via the Next Generation Radar (NEXRAD), meteorological data via local weather stations, and historical stream data via USGS gage stations to collectively forecast discharges in a semi-arid watershed in south Texas. Two types of artificial intelligence models, including genetic programming (GP) and neural network (NN) models, were employed comparatively. Four numerical evaluators were used to evaluate the validity of a suite of forecasting models. Research findings indicate that GP-derived streamflow forecasting models were generally favored in the assessment in which both SST and meteorological data significantly improve the accuracy of forecasting. Among several scenarios, NEXRAD rainfall data were proven its most effectiveness for a 3-day forecast, and SST Gulf-to-Atlantic index shows larger impacts than the SST Gulf-to-Pacific index on the streamflow forecasts. The most forward looking GP-derived models can even perform a 30-day streamflow forecast ahead of time with an r-square of 0.84 and RMS error 5.4 in our study.
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Simulation-optimization framework for multi-site multi-season hybrid stochastic streamflow modeling
Srivastav, Roshan; Srinivasan, K.; Sudheer, K. P.
2016-11-01
A simulation-optimization (S-O) framework is developed for the hybrid stochastic modeling of multi-site multi-season streamflows. The multi-objective optimization model formulated is the driver and the multi-site, multi-season hybrid matched block bootstrap model (MHMABB) is the simulation engine within this framework. The multi-site multi-season simulation model is the extension of the existing single-site multi-season simulation model. A robust and efficient evolutionary search based technique, namely, non-dominated sorting based genetic algorithm (NSGA - II) is employed as the solution technique for the multi-objective optimization within the S-O framework. The objective functions employed are related to the preservation of the multi-site critical deficit run sum and the constraints introduced are concerned with the hybrid model parameter space, and the preservation of certain statistics (such as inter-annual dependence and/or skewness of aggregated annual flows). The efficacy of the proposed S-O framework is brought out through a case example from the Colorado River basin. The proposed multi-site multi-season model AMHMABB (whose parameters are obtained from the proposed S-O framework) preserves the temporal as well as the spatial statistics of the historical flows. Also, the other multi-site deficit run characteristics namely, the number of runs, the maximum run length, the mean run sum and the mean run length are well preserved by the AMHMABB model. Overall, the proposed AMHMABB model is able to show better streamflow modeling performance when compared with the simulation based SMHMABB model, plausibly due to the significant role played by: (i) the objective functions related to the preservation of multi-site critical deficit run sum; (ii) the huge hybrid model parameter space available for the evolutionary search and (iii) the constraint on the preservation of the inter-annual dependence. Split-sample validation results indicate that the AMHMABB model is
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A Pareto-optimal moving average multigene genetic programming model for daily streamflow prediction
Danandeh Mehr, Ali; Kahya, Ercan
2017-06-01
Genetic programming (GP) is able to systematically explore alternative model structures of different accuracy and complexity from observed input and output data. The effectiveness of GP in hydrological system identification has been recognized in recent studies. However, selecting a parsimonious (accurate and simple) model from such alternatives still remains a question. This paper proposes a Pareto-optimal moving average multigene genetic programming (MA-MGGP) approach to develop a parsimonious model for single-station streamflow prediction. The three main components of the approach that take us from observed data to a validated model are: (1) data pre-processing, (2) system identification and (3) system simplification. The data pre-processing ingredient uses a simple moving average filter to diminish the lagged prediction effect of stand-alone data-driven models. The multigene ingredient of the model tends to identify the underlying nonlinear system with expressions simpler than classical monolithic GP and, eventually simplification component exploits Pareto front plot to select a parsimonious model through an interactive complexity-efficiency trade-off. The approach was tested using the daily streamflow records from a station on Senoz Stream, Turkey. Comparing to the efficiency results of stand-alone GP, MGGP, and conventional multi linear regression prediction models as benchmarks, the proposed Pareto-optimal MA-MGGP model put forward a parsimonious solution, which has a noteworthy importance of being applied in practice. In addition, the approach allows the user to enter human insight into the problem to examine evolved models and pick the best performing programs out for further analysis.
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Ensemble streamflow assimilation with the National Water Model.
Rafieeinasab, A.; McCreight, J. L.; Noh, S.; Seo, D. J.; Gochis, D.
2017-12-01
Through case studies of flooding across the US, we compare the performance of the National Water Model (NWM) data assimilation (DA) scheme to that of a newly implemented ensemble Kalman filter approach. The NOAA National Water Model (NWM) is an operational implementation of the community WRF-Hydro modeling system. As of August 2016, the NWM forecasts of distributed hydrologic states and fluxes (including soil moisture, snowpack, ET, and ponded water) over the contiguous United States have been publicly disseminated by the National Center for Environmental Prediction (NCEP) . It also provides streamflow forecasts at more than 2.7 million river reaches up to 30 days in advance. The NWM employs a nudging scheme to assimilate more than 6,000 USGS streamflow observations and provide initial conditions for its forecasts. A problem with nudging is how the forecasts relax quickly to open-loop bias in the forecast. This has been partially addressed by an experimental bias correction approach which was found to have issues with phase errors during flooding events. In this work, we present an ensemble streamflow data assimilation approach combining new channel-only capabilities of the NWM and HydroDART (a coupling of the offline WRF-Hydro model and NCAR's Data Assimilation Research Testbed; DART). Our approach focuses on the single model state of discharge and incorporates error distributions on channel-influxes (overland and groundwater) in the assimilation via an ensemble Kalman filter (EnKF). In order to avoid filter degeneracy associated with a limited number of ensemble at large scale, DART's covariance inflation (Anderson, 2009) and localization capabilities are implemented and evaluated. The current NWM data assimilation scheme is compared to preliminary results from the EnKF application for several flooding case studies across the US.
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Uncertainties in Forecasting Streamflow using Entropy Theory
Cui, H.; Singh, V. P.
2017-12-01
Streamflow forecasting is essential in river restoration, reservoir operation, power generation, irrigation, navigation, and water management. However, there is always uncertainties accompanied in forecast, which may affect the forecasting results and lead to large variations. Therefore, uncertainties must be considered and be assessed properly when forecasting streamflow for water management. The aim of our work is to quantify the uncertainties involved in forecasting streamflow and provide reliable streamflow forecast. Despite that streamflow time series are stochastic, they exhibit seasonal and periodic patterns. Therefore, streamflow forecasting entails modeling seasonality, periodicity, and its correlation structure, and assessing uncertainties. This study applies entropy theory to forecast streamflow and measure uncertainties during the forecasting process. To apply entropy theory for streamflow forecasting, spectral analysis is combined to time series analysis, as spectral analysis can be employed to characterize patterns of streamflow variation and identify the periodicity of streamflow. That is, it permits to extract significant information for understanding the streamflow process and prediction thereof. Application of entropy theory for streamflow forecasting involves determination of spectral density, determination of parameters, and extension of autocorrelation function. The uncertainties brought by precipitation input, forecasting model and forecasted results are measured separately using entropy. With information theory, how these uncertainties transported and aggregated during these processes will be described.
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van Heeswijk, Marijke
2006-01-01
Surface water has been diverted from the Salmon Creek Basin for irrigation purposes since the early 1900s, when the Bureau of Reclamation built the Okanogan Project. Spring snowmelt runoff is stored in two reservoirs, Conconully Reservoir and Salmon Lake Reservoir, and gradually released during the growing season. As a result of the out-of-basin streamflow diversions, the lower 4.3 miles of Salmon Creek typically has been a dry creek bed for almost 100 years, except during the spring snowmelt season during years of high runoff. To continue meeting the water needs of irrigators but also leave water in lower Salmon Creek for fish passage and to help restore the natural ecosystem, changes are being considered in how the Okanogan Project is operated. This report documents development of a precipitation-runoff model for the Salmon Creek Basin that can be used to simulate daily unregulated streamflows. The precipitation-runoff model is a component of a Decision Support System (DSS) that includes a water-operations model the Bureau of Reclamation plans to develop to study the water resources of the Salmon Creek Basin. The DSS will be similar to the DSS that the Bureau of Reclamation and the U.S. Geological Survey developed previously for the Yakima River Basin in central southern Washington. The precipitation-runoff model was calibrated for water years 1950-89 and tested for water years 1990-96. The model was used to simulate daily streamflows that were aggregated on a monthly basis and calibrated against historical monthly streamflows for Salmon Creek at Conconully Dam. Additional calibration data were provided by the snowpack water-equivalent record for a SNOTEL station in the basin. Model input time series of daily precipitation and minimum and maximum air temperatures were based on data from climate stations in the study area. Historical records of unregulated streamflow for Salmon Creek at Conconully Dam do not exist for water years 1950-96. Instead, estimates of
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Evaluation of streamflow forecast for the National Water Model of U.S. National Weather Service
Rafieeinasab, A.; McCreight, J. L.; Dugger, A. L.; Gochis, D.; Karsten, L. R.; Zhang, Y.; Cosgrove, B.; Liu, Y.
2016-12-01
The National Water Model (NWM), an implementation of the community WRF-Hydro modeling system, is an operational hydrologic forecasting model for the contiguous United States. The model forecasts distributed hydrologic states and fluxes, including soil moisture, snowpack, ET, and ponded water. In particular, the NWM provides streamflow forecasts at more than 2.7 million river reaches for three forecast ranges: short (15 hr), medium (10 days), and long (30 days). In this study, we verify short and medium range streamflow forecasts in the context of the verification of their respective quantitative precipitation forecasts/forcing (QPF), the High Resolution Rapid Refresh (HRRR) and the Global Forecast System (GFS). The streamflow evaluation is performed for summer of 2016 at more than 6,000 USGS gauges. Both individual forecasts and forecast lead times are examined. Selected case studies of extreme events aim to provide insight into the quality of the NWM streamflow forecasts. A goal of this comparison is to address how much streamflow bias originates from precipitation forcing bias. To this end, precipitation verification is performed over the contributing areas above (and between assimilated) USGS gauge locations. Precipitation verification is based on the aggregated, blended StageIV/StageII data as the "reference truth". We summarize the skill of the streamflow forecasts, their skill relative to the QPF, and make recommendations for improving NWM forecast skill.
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Mohammad Safeeq; Guillaume S. Mauger; Gordon E. Grant; Ivan Arismendi; Alan F. Hamlet; Se-Yeun Lee
2014-01-01
Assessing uncertainties in hydrologic models can improve accuracy in predicting future streamflow. Here, simulated streamflows using the Variable Infiltration Capacity (VIC) model at coarse (1/16°) and fine (1/120°) spatial resolutions were evaluated against observed streamflows from 217 watersheds. In...
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Dudley, Robert W.; Nielsen, Martha G.
2011-01-01
The U.S. Geological Survey (USGS) began a study in 2008 to investigate anticipated changes in summer streamflows and stream temperatures in four coastal Maine river basins and the potential effects of those changes on populations of endangered Atlantic salmon. To achieve this purpose, it was necessary to characterize the quantity and timing of streamflow in these rivers by developing and evaluating a distributed-parameter watershed model for a part of each river basin by using the USGS Precipitation-Runoff Modeling System (PRMS). The GIS (geographic information system) Weasel, a USGS software application, was used to delineate the four study basins and their many subbasins, and to derive parameters for their geographic features. The models were calibrated using a four-step optimization procedure in which model output was evaluated against four datasets for calibrating solar radiation, potential evapotranspiration, annual and seasonal water balances, and daily streamflows. The calibration procedure involved thousands of model runs that used the USGS software application Luca (Let us calibrate). Luca uses the Shuffled Complex Evolution (SCE) global search algorithm to calibrate the model parameters. The calibrated watershed models performed satisfactorily, in that Nash-Sutcliffe efficiency (NSE) statistic values for the calibration periods ranged from 0.59 to 0.75 (on a scale of negative infinity to 1) and NSE statistic values for the evaluation periods ranged from 0.55 to 0.73. The calibrated watershed models simulate daily streamflow at many locations in each study basin. These models enable natural resources managers to characterize the timing and amount of streamflow in order to support a variety of water-resources efforts including water-quality calculations, assessments of water use, modeling of population dynamics and migration of Atlantic salmon, modeling and assessment of habitat, and simulation of anticipated changes to streamflow and water temperature
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Directory of Open Access Journals (Sweden)
F. Fundel
2013-01-01
Full Text Available Streamflow droughts, characterized by low runoff as consequence of a drought event, affect numerous aspects of life. Economic sectors that are impacted by low streamflow are, e.g., power production, agriculture, tourism, water quality management and shipping. Those sectors could potentially benefit from forecasts of streamflow drought events, even of short events on the monthly time scales or below. Numerical hydrometeorological models have increasingly been used to forecast low streamflow and have become the focus of recent research. Here, we consider daily ensemble runoff forecasts for the river Thur, which has its source in the Swiss Alps. We focus on the evaluation of low streamflow and of the derived indices as duration, severity and magnitude, characterizing streamflow droughts up to a lead time of one month.
The ECMWF VarEPS 5-member ensemble reforecast, which covers 18 yr, is used as forcing for the hydrological model PREVAH. A thorough verification reveals that, compared to probabilistic peak-flow forecasts, which show skill up to a lead time of two weeks, forecasts of streamflow droughts are skilful over the entire forecast range of one month. For forecasts at the lower end of the runoff regime, the quality of the initial state seems to be crucial to achieve a good forecast quality in the longer range. It is shown that the states used in this study to initialize forecasts satisfy this requirement. The produced forecasts of streamflow drought indices, derived from the ensemble forecasts, could be beneficially included in a decision-making process. This is valid for probabilistic forecasts of streamflow drought events falling below a daily varying threshold, based on a quantile derived from a runoff climatology. Although the forecasts have a tendency to overpredict streamflow droughts, it is shown that the relative economic value of the ensemble forecasts reaches up to 60%, in case a forecast user is able to take preventive -
Fundel, F.; Jörg-Hess, S.; Zappa, M.
2013-01-01
Streamflow droughts, characterized by low runoff as consequence of a drought event, affect numerous aspects of life. Economic sectors that are impacted by low streamflow are, e.g., power production, agriculture, tourism, water quality management and shipping. Those sectors could potentially benefit from forecasts of streamflow drought events, even of short events on the monthly time scales or below. Numerical hydrometeorological models have increasingly been used to forecast low streamflow and have become the focus of recent research. Here, we consider daily ensemble runoff forecasts for the river Thur, which has its source in the Swiss Alps. We focus on the evaluation of low streamflow and of the derived indices as duration, severity and magnitude, characterizing streamflow droughts up to a lead time of one month. The ECMWF VarEPS 5-member ensemble reforecast, which covers 18 yr, is used as forcing for the hydrological model PREVAH. A thorough verification reveals that, compared to probabilistic peak-flow forecasts, which show skill up to a lead time of two weeks, forecasts of streamflow droughts are skilful over the entire forecast range of one month. For forecasts at the lower end of the runoff regime, the quality of the initial state seems to be crucial to achieve a good forecast quality in the longer range. It is shown that the states used in this study to initialize forecasts satisfy this requirement. The produced forecasts of streamflow drought indices, derived from the ensemble forecasts, could be beneficially included in a decision-making process. This is valid for probabilistic forecasts of streamflow drought events falling below a daily varying threshold, based on a quantile derived from a runoff climatology. Although the forecasts have a tendency to overpredict streamflow droughts, it is shown that the relative economic value of the ensemble forecasts reaches up to 60%, in case a forecast user is able to take preventive action based on the forecast.
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Barlow, Paul M.; Leake, Stanley A.
2012-11-02
Groundwater is an important source of water for many human needs, including public supply, agriculture, and industry. With the development of any natural resource, however, adverse consequences may be associated with its use. One of the primary concerns related to the development of groundwater resources is the effect of groundwater pumping on streamflow. Groundwater and surface-water systems are connected, and groundwater discharge is often a substantial component of the total flow of a stream. Groundwater pumping reduces the amount of groundwater that flows to streams and, in some cases, can draw streamflow into the underlying groundwater system. Streamflow reductions (or depletions) caused by pumping have become an important water-resource management issue because of the negative impacts that reduced flows can have on aquatic ecosystems, the availability of surface water, and the quality and aesthetic value of streams and rivers. Scientific research over the past seven decades has made important contributions to the basic understanding of the processes and factors that affect streamflow depletion by wells. Moreover, advances in methods for simulating groundwater systems with computer models provide powerful tools for estimating the rates, locations, and timing of streamflow depletion in response to groundwater pumping and for evaluating alternative approaches for managing streamflow depletion. The primary objective of this report is to summarize these scientific insights and to describe the various field methods and modeling approaches that can be used to understand and manage streamflow depletion. A secondary objective is to highlight several misconceptions concerning streamflow depletion and to explain why these misconceptions are incorrect.
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Huziy, O.; Sushama, L.; Khaliq, M.; Lehner, B.; Laprise, R.; Roy, R.
2011-12-01
According to the Intergovernmental Panel on Climate Change (IPCC, 2007), an intensification of the global hydrological cycle and increase in precipitation for some regions around the world, including the northern mid- to high-latitudes, is expected in future climate. This will have an impact on mean and extreme flow characteristics, which need to be assessed for better development of adaptation strategies. Analysis of the mean and extreme streamflow characteristics for Quebec (North-eastern Canada) basins in current climate and their projected changes in future climate are assessed using a 10 member ensemble of current (1970 - 1999) and future (2041 - 2070) Canadian RCM (CRCM4) simulations. Validation of streamflow characteristics, performed by comparing modeled values with those observed, available from the Centre d'expertise hydrique du Quebec (CEHQ) shows that the model captures reasonably well the high flows. Results suggest increase in mean and 10 year return levels of 1 day high flows, which appear significant for most of the northern basins.
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Assimilating uncertain, dynamic and intermittent streamflow observations in hydrological models
Mazzoleni, Maurizio; Alfonso, Leonardo; Chacon-Hurtado, Juan; Solomatine, Dimitri
2015-09-01
Catastrophic floods cause significant socio-economical losses. Non-structural measures, such as real-time flood forecasting, can potentially reduce flood risk. To this end, data assimilation methods have been used to improve flood forecasts by integrating static ground observations, and in some cases also remote sensing observations, within water models. Current hydrologic and hydraulic research works consider assimilation of observations coming from traditional, static sensors. At the same time, low-cost, mobile sensors and mobile communication devices are becoming also increasingly available. The main goal and innovation of this study is to demonstrate the usefulness of assimilating uncertain streamflow observations that are dynamic in space and intermittent in time in the context of two different semi-distributed hydrological model structures. The developed method is applied to the Brue basin, where the dynamic observations are imitated by the synthetic observations of discharge. The results of this study show how model structures and sensors locations affect in different ways the assimilation of streamflow observations. In addition, it proves how assimilation of such uncertain observations from dynamic sensors can provide model improvements similar to those of streamflow observations coming from a non-optimal network of static physical sensors. This can be a potential application of recent efforts to build citizen observatories of water, which can make the citizens an active part in information capturing, evaluation and communication, helping simultaneously to improvement of model-based flood forecasting.
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Raso , L.; Malaterre , P.O.; Bader , J.C.
2017-01-01
International audience; This article presents an innovative streamflow process model for use in reservoir operational rule design in stochastic dual dynamic programming (SDDP). Model features, which can be applied independently, are (1) a multiplicative process model for the forward phase and its linearized version for the backward phase; and (2) a nonuniform time-step length that is inversely proportional to seasonal variability. The advantages are (1) guaranteeing positive streamflow values...
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Liu, Shulun; Li, Yuan; Pauwels, Valentijn R. N.; Walker, Jeffrey P.
2017-12-01
Rain gauges are widely used to obtain temporally continuous point rainfall records, which are then interpolated into spatially continuous data to force hydrological models. However, rainfall measurements and interpolation procedure are subject to various uncertainties, which can be reduced by applying quality control and selecting appropriate spatial interpolation approaches. Consequently, the integrated impact of rainfall quality control and interpolation on streamflow simulation has attracted increased attention but not been fully addressed. This study applies a quality control procedure to the hourly rainfall measurements obtained in the Warwick catchment in eastern Australia. The grid-based daily precipitation from the Australian Water Availability Project was used as a reference. The Pearson correlation coefficient between the daily accumulation of gauged rainfall and the reference data was used to eliminate gauges with significant quality issues. The unrealistic outliers were censored based on a comparison between gauged rainfall and the reference. Four interpolation methods, including the inverse distance weighting (IDW), nearest neighbors (NN), linear spline (LN), and ordinary Kriging (OK), were implemented. The four methods were firstly assessed through a cross-validation using the quality-controlled rainfall data. The impacts of the quality control and interpolation on streamflow simulation were then evaluated through a semi-distributed hydrological model. The results showed that the Nash–Sutcliffe model efficiency coefficient (NSE) and Bias of the streamflow simulations were significantly improved after quality control. In the cross-validation, the IDW and OK methods resulted in good interpolation rainfall, while the NN led to the worst result. In term of the impact on hydrological prediction, the IDW led to the most consistent streamflow predictions with the observations, according to the validation at five streamflow-gauged locations. The OK method
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Reconstruction of missing daily streamflow data using dynamic regression models
Tencaliec, Patricia; Favre, Anne-Catherine; Prieur, Clémentine; Mathevet, Thibault
2015-12-01
River discharge is one of the most important quantities in hydrology. It provides fundamental records for water resources management and climate change monitoring. Even very short data-gaps in this information can cause extremely different analysis outputs. Therefore, reconstructing missing data of incomplete data sets is an important step regarding the performance of the environmental models, engineering, and research applications, thus it presents a great challenge. The objective of this paper is to introduce an effective technique for reconstructing missing daily discharge data when one has access to only daily streamflow data. The proposed procedure uses a combination of regression and autoregressive integrated moving average models (ARIMA) called dynamic regression model. This model uses the linear relationship between neighbor and correlated stations and then adjusts the residual term by fitting an ARIMA structure. Application of the model to eight daily streamflow data for the Durance river watershed showed that the model yields reliable estimates for the missing data in the time series. Simulation studies were also conducted to evaluate the performance of the procedure.
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Simulating the effects of ground-water withdrawals on streamflow in a precipitation-runoff model
Zarriello, Philip J.; Barlow, P.M.; Duda, P.B.
2004-01-01
Precipitation-runoff models are used to assess the effects of water use and management alternatives on streamflow. Often, ground-water withdrawals are a major water-use component that affect streamflow, but the ability of surface-water models to simulate ground-water withdrawals is limited. As part of a Hydrologic Simulation Program-FORTRAN (HSPF) precipitation-runoff model developed to analyze the effect of ground-water and surface-water withdrawals on streamflow in the Ipswich River in northeastern Massachusetts, an analytical technique (STRMDEPL) was developed for calculating the effects of pumped wells on streamflow. STRMDEPL is a FORTRAN program based on two analytical solutions that solve equations for ground-water flow to a well completed in a semi-infinite, homogeneous, and isotropic aquifer in direct hydraulic connection to a fully penetrating stream. One analytical method calculates unimpeded flow at the stream-aquifer boundary and the other method calculates the resistance to flow caused by semipervious streambed and streambank material. The principle of superposition is used with these analytical equations to calculate time-varying streamflow depletions due to daily pumping. The HSPF model can readily incorporate streamflow depletions caused by a well or surface-water withdrawal, or by multiple wells or surface-water withdrawals, or both, as a combined time-varying outflow demand from affected channel reaches. These demands are stored as a time series in the Watershed Data Management (WDM) file. This time-series data is read into the model as an external source used to specify flow from the first outflow gate in the reach where these withdrawals are located. Although the STRMDEPL program can be run independently of the HSPF model, an extension was developed to run this program within GenScn, a scenario generator and graphical user interface developed for use with the HSPF model. This extension requires that actual pumping rates for each well be stored
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Using satellite-based rainfall estimates for streamflow modelling: Bagmati Basin
Shrestha, M.S.; Artan, Guleid A.; Bajracharya, S.R.; Sharma, R. R.
2008-01-01
In this study, we have described a hydrologic modelling system that uses satellite-based rainfall estimates and weather forecast data for the Bagmati River Basin of Nepal. The hydrologic model described is the US Geological Survey (USGS) Geospatial Stream Flow Model (GeoSFM). The GeoSFM is a spatially semidistributed, physically based hydrologic model. We have used the GeoSFM to estimate the streamflow of the Bagmati Basin at Pandhera Dovan hydrometric station. To determine the hydrologic connectivity, we have used the USGS Hydro1k DEM dataset. The model was forced by daily estimates of rainfall and evapotranspiration derived from weather model data. The rainfall estimates used for the modelling are those produced by the National Oceanic and Atmospheric Administration Climate Prediction Centre and observed at ground rain gauge stations. The model parameters were estimated from globally available soil and land cover datasets – the Digital Soil Map of the World by FAO and the USGS Global Land Cover dataset. The model predicted the daily streamflow at Pandhera Dovan gauging station. The comparison of the simulated and observed flows at Pandhera Dovan showed that the GeoSFM model performed well in simulating the flows of the Bagmati Basin.
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Christiansen, Daniel E.; Haj, Adel E.; Risley, John C.
2017-10-24
The U.S. Geological Survey, in cooperation with the Iowa Department of Natural Resources, constructed Precipitation-Runoff Modeling System models to estimate daily streamflow for 12 river basins in western Iowa that drain into the Missouri River. The Precipitation-Runoff Modeling System is a deterministic, distributed-parameter, physical-process-based modeling system developed to evaluate the response of streamflow and general drainage basin hydrology to various combinations of climate and land use. Calibration periods for each basin varied depending on the period of record available for daily mean streamflow measurements at U.S. Geological Survey streamflow-gaging stations.A geographic information system tool was used to delineate each basin and estimate initial values for model parameters based on basin physical and geographical features. A U.S. Geological Survey automatic calibration tool that uses a shuffled complex evolution algorithm was used for initial calibration, and then manual modifications were made to parameter values to complete the calibration of each basin model. The main objective of the calibration was to match daily discharge values of simulated streamflow to measured daily discharge values. The Precipitation-Runoff Modeling System model was calibrated at 42 sites located in the 12 river basins in western Iowa.The accuracy of the simulated daily streamflow values at the 42 calibration sites varied by river and by site. The models were satisfactory at 36 of the sites based on statistical results. Unsatisfactory performance at the six other sites can be attributed to several factors: (1) low flow, no flow, and flashy flow conditions in headwater subbasins having a small drainage area; (2) poor representation of the groundwater and storage components of flow within a basin; (3) lack of accounting for basin withdrawals and water use; and (4) limited availability and accuracy of meteorological input data. The Precipitation-Runoff Modeling System
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Watershed-scale modeling of streamflow change in incised montane meadows
Essaid, Hedeff I.; Hill, Barry R.
2014-01-01
Land use practices have caused stream channel incision and water table decline in many montane meadows of the Western United States. Incision changes the magnitude and timing of streamflow in water supply source watersheds, a concern to resource managers and downstream water users. The hydrology of montane meadows under natural and incised conditions was investigated using watershed simulation for a range of hydrologic conditions. The results illustrate the interdependence between: watershed and meadow hydrology; bedrock and meadow aquifers; and surface and groundwater flow through the meadow for the modeled scenarios. During the wet season, stream incision resulted in less overland flow and interflow and more meadow recharge causing a net decrease in streamflow and increase in groundwater storage relative to natural meadow conditions. During the dry season, incision resulted in less meadow evapotranspiration and more groundwater discharge to the stream causing a net increase in streamflow and a decrease in groundwater storage relative to natural meadow conditions. In general, for a given meadow setting, the magnitude of change in summer streamflow and long-term change in watershed groundwater storage due to incision will depend on the combined effect of: reduced evapotranspiration in the eroded meadow; induced groundwater recharge; replenishment of dry season groundwater storage depletion in meadow and bedrock aquifers by precipitation during wet years; and groundwater storage depletion that is not replenished by precipitation during wet years.
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Long-range forecasting of intermittent streamflow
van Ogtrop, F. F.; Vervoort, R. W.; Heller, G. Z.; Stasinopoulos, D. M.; Rigby, R. A.
2011-11-01
Long-range forecasting of intermittent streamflow in semi-arid Australia poses a number of major challenges. One of the challenges relates to modelling zero, skewed, non-stationary, and non-linear data. To address this, a statistical model to forecast streamflow up to 12 months ahead is applied to five semi-arid catchments in South Western Queensland. The model uses logistic regression through Generalised Additive Models for Location, Scale and Shape (GAMLSS) to determine the probability of flow occurring in any of the systems. We then use the same regression framework in combination with a right-skewed distribution, the Box-Cox t distribution, to model the intensity (depth) of the non-zero streamflows. Time, seasonality and climate indices, describing the Pacific and Indian Ocean sea surface temperatures, are tested as covariates in the GAMLSS model to make probabilistic 6 and 12-month forecasts of the occurrence and intensity of streamflow. The output reveals that in the study region the occurrence and variability of flow is driven by sea surface temperatures and therefore forecasts can be made with some skill.
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Long-range forecasting of intermittent streamflow
Directory of Open Access Journals (Sweden)
F. F. van Ogtrop
2011-11-01
Full Text Available Long-range forecasting of intermittent streamflow in semi-arid Australia poses a number of major challenges. One of the challenges relates to modelling zero, skewed, non-stationary, and non-linear data. To address this, a statistical model to forecast streamflow up to 12 months ahead is applied to five semi-arid catchments in South Western Queensland. The model uses logistic regression through Generalised Additive Models for Location, Scale and Shape (GAMLSS to determine the probability of flow occurring in any of the systems. We then use the same regression framework in combination with a right-skewed distribution, the Box-Cox t distribution, to model the intensity (depth of the non-zero streamflows. Time, seasonality and climate indices, describing the Pacific and Indian Ocean sea surface temperatures, are tested as covariates in the GAMLSS model to make probabilistic 6 and 12-month forecasts of the occurrence and intensity of streamflow. The output reveals that in the study region the occurrence and variability of flow is driven by sea surface temperatures and therefore forecasts can be made with some skill.
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Skilful seasonal forecasts of streamflow over Europe?
Arnal, Louise; Cloke, Hannah L.; Stephens, Elisabeth; Wetterhall, Fredrik; Prudhomme, Christel; Neumann, Jessica; Krzeminski, Blazej; Pappenberger, Florian
2018-04-01
This paper considers whether there is any added value in using seasonal climate forecasts instead of historical meteorological observations for forecasting streamflow on seasonal timescales over Europe. A Europe-wide analysis of the skill of the newly operational EFAS (European Flood Awareness System) seasonal streamflow forecasts (produced by forcing the Lisflood model with the ECMWF System 4 seasonal climate forecasts), benchmarked against the ensemble streamflow prediction (ESP) forecasting approach (produced by forcing the Lisflood model with historical meteorological observations), is undertaken. The results suggest that, on average, the System 4 seasonal climate forecasts improve the streamflow predictability over historical meteorological observations for the first month of lead time only (in terms of hindcast accuracy, sharpness and overall performance). However, the predictability varies in space and time and is greater in winter and autumn. Parts of Europe additionally exhibit a longer predictability, up to 7 months of lead time, for certain months within a season. In terms of hindcast reliability, the EFAS seasonal streamflow hindcasts are on average less skilful than the ESP for all lead times. The results also highlight the potential usefulness of the EFAS seasonal streamflow forecasts for decision-making (measured in terms of the hindcast discrimination for the lower and upper terciles of the simulated streamflow). Although the ESP is the most potentially useful forecasting approach in Europe, the EFAS seasonal streamflow forecasts appear more potentially useful than the ESP in some regions and for certain seasons, especially in winter for almost 40 % of Europe. Patterns in the EFAS seasonal streamflow hindcast skill are however not mirrored in the System 4 seasonal climate hindcasts, hinting at the need for a better understanding of the link between hydrological and meteorological variables on seasonal timescales, with the aim of improving climate-model
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Use of medium-range numerical weather prediction model output to produce forecasts of streamflow
Clark, M.P.; Hay, L.E.
2004-01-01
This paper examines an archive containing over 40 years of 8-day atmospheric forecasts over the contiguous United States from the NCEP reanalysis project to assess the possibilities for using medium-range numerical weather prediction model output for predictions of streamflow. This analysis shows the biases in the NCEP forecasts to be quite extreme. In many regions, systematic precipitation biases exceed 100% of the mean, with temperature biases exceeding 3??C. In some locations, biases are even higher. The accuracy of NCEP precipitation and 2-m maximum temperature forecasts is computed by interpolating the NCEP model output for each forecast day to the location of each station in the NWS cooperative network and computing the correlation with station observations. Results show that the accuracy of the NCEP forecasts is rather low in many areas of the country. Most apparent is the generally low skill in precipitation forecasts (particularly in July) and low skill in temperature forecasts in the western United States, the eastern seaboard, and the southern tier of states. These results outline a clear need for additional processing of the NCEP Medium-Range Forecast Model (MRF) output before it is used for hydrologic predictions. Techniques of model output statistics (MOS) are used in this paper to downscale the NCEP forecasts to station locations. Forecasted atmospheric variables (e.g., total column precipitable water, 2-m air temperature) are used as predictors in a forward screening multiple linear regression model to improve forecasts of precipitation and temperature for stations in the National Weather Service cooperative network. This procedure effectively removes all systematic biases in the raw NCEP precipitation and temperature forecasts. MOS guidance also results in substantial improvements in the accuracy of maximum and minimum temperature forecasts throughout the country. For precipitation, forecast improvements were less impressive. MOS guidance increases
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Streamflow data assimilation in SWAT model using Extended Kalman Filter
Sun, Leqiang; Nistor, Ioan; Seidou, Ousmane
2015-12-01
The Extended Kalman Filter (EKF) is coupled with the Soil and Water Assessment Tools (SWAT) model in the streamflow assimilation of the upstream Senegal River in West Africa. Given the large number of distributed variables in SWAT, only the average watershed scale variables are included in the state vector and the Hydrological Response Unit (HRU) scale variables are updated with the a posteriori/a priori ratio of their watershed scale counterparts. The Jacobian matrix is calculated numerically by perturbing the state variables. Both the soil moisture and CN2 are significantly updated in the wet season, yet they have opposite update patterns. A case study for a large flood forecast shows that for up to seven days, the streamflow forecast is moderately improved using the EKF-subsequent open loop scheme but significantly improved with a newly designed quasi-error update scheme. The former has better performances in the flood rising period while the latter has better performances in the recession period. For both schemes, the streamflow forecast is improved more significantly when the lead time is shorter.
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Historical Streamflow Series Analysis Applied to Furnas HPP Reservoir Watershed Using the SWAT Model
Directory of Open Access Journals (Sweden)
Viviane de Souza Dias
2018-04-01
Full Text Available Over the last few years, the operation of the Furnas Hydropower Plant (HPP reservoir, located in the Grande River Basin, has been threatened due to a significant reduction in inflow. In the region, hydrological modelling tools are being used and tested to support decision making and water sustainability. In this study, the streamflow was modelled in the area of direct influence of the Furnas HPP reservoir, and the Soil and Water Assessment Tool (SWAT model performance was verified for studies in the region. Analyses of sensitivity and uncertainty were undertaken using the Sequential Uncertainty Fitting algorithm (SUFI-2 with a Calibration Uncertainty Program (SWAT-CUP. The hydrological modelling, at a monthly scale, presented good results in the calibration (NS 0.86, with a slight reduction of the coefficient in the validation period (NS 0.64. The results suggested that this tool could be applied in future hydrological studies in the region of study. With the consideration that special attention should be given to the historical series used in the calibration and validation of the models. It is important to note that this region has high demands for water resources, primarily for agricultural use. Water demands must also be taken into account in future hydrological simulations. The validation of this methodology led to important contributions to the management of water resources in regions with tropical climates, whose climatological and geological reality resembles the one studied here.
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Long-range forecasting of intermittent streamflow
F. F. van Ogtrop; R. W. Vervoort; G. Z. Heller; D. M. Stasinopoulos; R. A. Rigby
2011-01-01
Long-range forecasting of intermittent streamflow in semi-arid Australia poses a number of major challenges. One of the challenges relates to modelling zero, skewed, non-stationary, and non-linear data. To address this, a statistical model to forecast streamflow up to 12 months ahead is applied to five semi-arid catchments in South Western Queensland. The model uses logistic regression through Generalised Additive Models for Location, Scale and Shape (GAMLSS) to determine th...
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Long-range forecasting of intermittent streamflow
F. F. van Ogtrop; R. W. Vervoort; G. Z. Heller; D. M. Stasinopoulos; R. A. Rigby
2011-01-01
Long-range forecasting of intermittent streamflow in semi-arid Australia poses a number of major challenges. One of the challenges relates to modelling zero, skewed, non-stationary, and non-linear data. To address this, a probabilistic statistical model to forecast streamflow 12 months ahead is applied to five semi-arid catchments in South Western Queensland. The model uses logistic regression through Generalised Additive Models for Location, Scale and Shape (GAMLSS) to determine the probabil...
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Model-Based Attribution of High-Resolution Streamflow Trends in Two Alpine Basins of Western Austria
Directory of Open Access Journals (Sweden)
Christoph Kormann
2016-02-01
Full Text Available Several trend studies have shown that hydrological conditions are changing considerably in the Alpine region. However, the reasons for these changes are only partially understood and trend analyses alone are not able to shed much light. Hydrological modelling is one possible way to identify the trend drivers, i.e., to attribute the detected streamflow trends, given that the model captures all important processes causing the trends. We modelled the hydrological conditions for two alpine catchments in western Austria (a large, mostly lower-altitude catchment with wide valley plains and a nested high-altitude, glaciated headwater catchment with the distributed, physically-oriented WaSiM-ETH model, which includes a dynamical glacier module. The model was calibrated in a transient mode, i.e., not only on several standard goodness measures and glacier extents, but also in such a way that the simulated streamflow trends fit with the observed ones during the investigation period 1980 to 2007. With this approach, it was possible to separate streamflow components, identify the trends of flow components, and study their relation to trends in atmospheric variables. In addition to trends in annual averages, highly resolved trends for each Julian day were derived, since they proved powerful in an earlier, data-based attribution study. We were able to show that annual and highly resolved trends can be modelled sufficiently well. The results provide a holistic, year-round picture of the drivers of alpine streamflow changes: Higher-altitude catchments are strongly affected by earlier firn melt and snowmelt in spring and increased ice melt throughout the ablation season. Changes in lower-altitude areas are mostly caused by earlier and lower snowmelt volumes. All highly resolved trends in streamflow and its components show an explicit similarity to the local temperature trends. Finally, results indicate that evapotranspiration has been increasing in the lower
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Hävermark, Saga; Santos Ferreira, Carla Sofia; Kalantari, Zahra; Di Baldassarre, Giuliano
2016-04-01
was calibrated for the hydrological years 2008 to 2010 and validated for the three following years using streamflow data. The impact of future land use changes was analysed by investigating the impact of the size and location of the urban areas within the catchment. Modelling results are expected to support the decision making process in planning and developing new urban areas.
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Koppa, A.; Gebremichael, M.; Yeh, W. W. G.
2017-12-01
Calibrating hydrologic models in large catchments using a sparse network of streamflow gauges adversely affects the spatial and temporal accuracy of other water balance components which are important for climate-change, land-use and drought studies. This study combines remote sensing data and the concept of Pareto-Optimality to address the following questions: 1) What is the impact of streamflow (SF) calibration on the spatio-temporal accuracy of Evapotranspiration (ET), near-surface Soil Moisture (SM) and Total Water Storage (TWS)? 2) What is the best combination of fluxes that can be used to calibrate complex hydrological models such that both the accuracy of streamflow and the spatio-temporal accuracy of ET, SM and TWS is preserved? The study area is the Mississippi Basin in the United States (encompassing HUC-2 regions 5,6,7,9,10 and 11). 2003 and 2004, two climatologically average years are chosen for calibration and validation of the Noah-MP hydrologic model. Remotely sensed ET data is sourced from GLEAM, SM from ESA-CCI and TWS from GRACE. Single objective calibration is carried out using DDS Algorithm. For Multi objective calibration PA-DDS is used. First, the Noah-MP model is calibrated using a single objective function (Minimize Mean Square Error) for the outflow from the 6 HUC-2 sub-basins for 2003. Spatial correlograms are used to compare the spatial structure of ET, SM and TWS between the model and the remote sensing data. Spatial maps of RMSE and Mean Error are used to quantify the impact of calibrating streamflow on the accuracy of ET, SM and TWS estimates. Next, a multi-objective calibration experiment is setup to determine the pareto optimal parameter sets (pareto front) for the following cases - 1) SF and ET, 2) SF and SM, 3) SF and TWS, 4) SF, ET and SM, 5) SF, ET and TWS, 6) SF, SM and TWS, 7) SF, ET, SM and TWS. The best combination of fluxes that provides the optimal trade-off between accurate streamflow and preserving the spatio
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Methods for estimating drought streamflow probabilities for Virginia streams
Austin, Samuel H.
2014-01-01
Maximum likelihood logistic regression model equations used to estimate drought flow probabilities for Virginia streams are presented for 259 hydrologic basins in Virginia. Winter streamflows were used to estimate the likelihood of streamflows during the subsequent drought-prone summer months. The maximum likelihood logistic regression models identify probable streamflows from 5 to 8 months in advance. More than 5 million streamflow daily values collected over the period of record (January 1, 1900 through May 16, 2012) were compiled and analyzed over a minimum 10-year (maximum 112-year) period of record. The analysis yielded the 46,704 equations with statistically significant fit statistics and parameter ranges published in two tables in this report. These model equations produce summer month (July, August, and September) drought flow threshold probabilities as a function of streamflows during the previous winter months (November, December, January, and February). Example calculations are provided, demonstrating how to use the equations to estimate probable streamflows as much as 8 months in advance.
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Application of the geological streamflow and Muskingum Cunge ...
African Journals Online (AJOL)
... of the geological streamflow and Muskingum Cunge models in the Yala River Basin, Kenya. ... can be represented by the application of hydrologic and hydraulic models. ... verification and streamflow routing based on a split record analysis.
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Jaeger, K. L.
2017-12-01
The U.S. Geological Survey (USGS) has developed the PRObability Of Streamflow PERmanence (PROSPER) model, a GIS-based empirical model that provides predictions of the annual probability of a stream channel having year-round flow (Streamflow permanence probability; SPP) for any unregulated and minimally-impaired stream channel in the Pacific Northwest (Washington, Oregon, Idaho, western Montana). The model provides annual predictions for 2004-2016 at a 30-m spatial resolution based on monthly or annually updated values of climatic conditions, and static physiographic variables associated with the upstream basin. Prediction locations correspond to the channel network consistent with the National Hydrography Dataset stream grid and are publicly available through the USGS StreamStats platform (https://water.usgs.gov/osw/streamstats/). In snowmelt-driven systems, the most informative predictor variable was mean upstream snow water equivalent on May 1, which highlights the influence of late spring snow cover for supporting streamflow in mountain river networks. In non-snowmelt-driven systems, the most informative variable was mean annual precipitation. Streamflow permanence probabilities varied across the study area by geography and from year-to-year. Notably lower SPP corresponded to the climatically drier subregions of the study area. Higher SPP were concentrated in coastal and higher elevation mountain regions. In addition, SPP appeared to trend with average hydroclimatic conditions, which were also geographically coherent. The year-to-year variability lends support for the growing recognition of the spatiotemporal dynamism of streamflow permanence. An analysis of three focus basins located in contrasting geographical and hydroclimatic settings demonstrates differences in the sensitivity of streamflow permanence to antecedent climate conditions as a function of geography. Consequently, results suggest that PROSPER model can be a useful tool to evaluate regions of the
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Directory of Open Access Journals (Sweden)
Zhenliang Yin
2017-07-01
Full Text Available Quantifying the long term impacts of climate and land cover change on streamflow is of great important for sustainable water resources management in inland river basins. The Soil and Water Assessment Tool (SWAT model was employed to simulate the streamflow in the upper reaches of Heihe River Basin, northwestern China, over the last half century. The Sequential Uncertainty Fitting algorithm (SUFI-2 was selected to calibrate and validate the SWAT model. The results showed that both Nash-Sutcliffe efficiency (NSE and determination coefficient (R2 were over 0.93 for calibration and validation periods, the percent bias (PBIAS of the two periods were—3.47% and 1.81%, respectively. The precipitation, average, maximum, and minimum air temperature were all showing increasing trends, with 14.87 mm/10 years, 0.30 °C/10 years, 0.27 °C/10 year, and 0.37 °C/10 years, respectively. Runoff coefficient has increased from 0.36 (averaged during 1964 to 1988 to 0.39 (averaged during 1989 to 2013. Based on the SWAT simulation, we quantified the contribution of climate and land cover change to streamflow change, indicated that the land cover change had a positive impact on river discharge by increasing 7.12% of the streamflow during 1964 to 1988, and climate change contributed 14.08% for the streamflow increasing over last 50 years. Meanwhile, the climate change impact was intensive after 2000s. The increasing of streamflow contributed to the increasing of total streamflow by 64.1% for cold season (November to following March and 35.9% for warm season (April to October. The results provide some references for dealing with climate and land cover change in an inland river basin for water resource management and planning.
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Disentangling the response of streamflow to forest management and climate
Dymond, S.; Miniat, C.; Bladon, K. D.; Keppeler, E.; Caldwell, P. V.
2016-12-01
Paired watershed studies have showcased the relationships between forests, management, and streamflow. However, classical analyses of paired-watershed studies have done little to disentangle the effects of management from overarching climatic signals, potentially masking the interaction between management and climate. Such approaches may confound our understanding of how forest management impacts streamflow. Here we use a 50-year record of streamflow and climate data from the Caspar Creek Experimental Watersheds (CCEW), California, USA to separate the effects of forest management and climate on streamflow. CCEW has two treatment watersheds that have been harvested in the past 50 years. We used a nonlinear mixed model to combine the pre-treatment relationship between streamflow and climate and the post-treatment relationship via an interaction between climate and management into one equation. Our results show that precipitation and potential evapotranspiration alone can account for >95% of the variability in pre-treatment streamflow. Including management scenarios into the model explained most of the variability in streamflow (R2 > 0.98). While forest harvesting altered streamflow in both of our modeled watersheds, removing 66% of the vegetation via selection logging using a tractor yarding system over the entire watershed had a more substantial impact on streamflow than clearcutting small portions of a watershed using cable-yarding. These results suggest that forest harvesting may result in differing impacts on streamflow and highlights the need to incorporate climate into streamflow analyses of paired-watershed studies.
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Multiobjective Optimal Algorithm for Automatic Calibration of Daily Streamflow Forecasting Model
Directory of Open Access Journals (Sweden)
Yi Liu
2016-01-01
Full Text Available Single-objection function cannot describe the characteristics of the complicated hydrologic system. Consequently, it stands to reason that multiobjective functions are needed for calibration of hydrologic model. The multiobjective algorithms based on the theory of nondominate are employed to solve this multiobjective optimal problem. In this paper, a novel multiobjective optimization method based on differential evolution with adaptive Cauchy mutation and Chaos searching (MODE-CMCS is proposed to optimize the daily streamflow forecasting model. Besides, to enhance the diversity performance of Pareto solutions, a more precise crowd distance assigner is presented in this paper. Furthermore, the traditional generalized spread metric (SP is sensitive with the size of Pareto set. A novel diversity performance metric, which is independent of Pareto set size, is put forward in this research. The efficacy of the new algorithm MODE-CMCS is compared with the nondominated sorting genetic algorithm II (NSGA-II on a daily streamflow forecasting model based on support vector machine (SVM. The results verify that the performance of MODE-CMCS is superior to the NSGA-II for automatic calibration of hydrologic model.
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Patil, Amol; Ramsankaran, RAAJ
2017-12-01
This article presents a study carried out using EnKF based assimilation of coarser-scale SMOS soil moisture retrievals to improve the streamflow simulations and forecasting performance of SWAT model in a large catchment. This study has been carried out in Munneru river catchment, India, which is about 10,156 km2. In this study, an EnkF based new approach is proposed for improving the inherent vertical coupling of soil layers of SWAT hydrological model during soil moisture data assimilation. Evaluation of the vertical error correlation obtained between surface and subsurface layers indicates that the vertical coupling can be improved significantly using ensemble of soil storages compared to the traditional static soil storages based EnKF approach. However, the improvements in the simulated streamflow are moderate, which is due to the limitations in SWAT model in reflecting the profile soil moisture updates in surface runoff computations. Further, it is observed that the durability of streamflow improvements is longer when the assimilation system effectively updates the subsurface flow component. Overall, the results of the present study indicate that the passive microwave-based coarser-scale soil moisture products like SMOS hold significant potential to improve the streamflow estimates when assimilating into large-scale distributed hydrological models operating at a daily time step.
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Engeland, K.; Steinsland, I.; Petersen-Øverleir, A.; Johansen, S.
2012-04-01
The aim of this study is to assess the uncertainties in streamflow simulations when uncertainties in both observed inputs (precipitation and temperature) and streamflow observations used in the calibration of the hydrological model are explicitly accounted for. To achieve this goal we applied the elevation distributed HBV model operating on daily time steps to a small catchment in high elevation in Southern Norway where the seasonal snow cover is important. The uncertainties in precipitation inputs were quantified using conditional simulation. This procedure accounts for the uncertainty related to the density of the precipitation network, but neglects uncertainties related to measurement bias/errors and eventual elevation gradients in precipitation. The uncertainties in temperature inputs were quantified using a Bayesian temperature interpolation procedure where the temperature lapse rate is re-estimated every day. The uncertainty in the lapse rate was accounted for whereas the sampling uncertainty related to network density was neglected. For every day a random sample of precipitation and temperature inputs were drawn to be applied as inputs to the hydrologic model. The uncertainties in observed streamflow were assessed based on the uncertainties in the rating curve model. A Bayesian procedure was applied to estimate the probability for rating curve models with 1 to 3 segments and the uncertainties in their parameters. This method neglects uncertainties related to errors in observed water levels. Note that one rating curve was drawn to make one realisation of a whole time series of streamflow, thus the rating curve errors lead to a systematic bias in the streamflow observations. All these uncertainty sources were linked together in both calibration and evaluation of the hydrologic model using a DREAM based MCMC routine. Effects of having less information (e.g. missing one streamflow measurement for defining the rating curve or missing one precipitation station
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Saharia, M.; Wood, A.; Clark, M. P.; Bennett, A.; Nijssen, B.; Clark, E.; Newman, A. J.
2017-12-01
Most operational streamflow forecasting systems rely on a forecaster-in-the-loop approach in which some parts of the forecast workflow require an experienced human forecaster. But this approach faces challenges surrounding process reproducibility, hindcasting capability, and extension to large domains. The operational hydrologic community is increasingly moving towards `over-the-loop' (completely automated) large-domain simulations yet recent developments indicate a widespread lack of community knowledge about the strengths and weaknesses of such systems for forecasting. A realistic representation of land surface hydrologic processes is a critical element for improving forecasts, but often comes at the substantial cost of forecast system agility and efficiency. While popular grid-based models support the distributed representation of land surface processes, intermediate-scale Hydrologic Unit Code (HUC)-based modeling could provide a more efficient and process-aligned spatial discretization, reducing the need for tradeoffs between model complexity and critical forecasting requirements such as ensemble methods and comprehensive model calibration. The National Center for Atmospheric Research is collaborating with the University of Washington, the Bureau of Reclamation and the USACE to implement, assess, and demonstrate real-time, over-the-loop distributed streamflow forecasting for several large western US river basins and regions. In this presentation, we present early results from short to medium range hydrologic and streamflow forecasts for the Pacific Northwest (PNW). We employ a real-time 1/16th degree daily ensemble model forcings as well as downscaled Global Ensemble Forecasting System (GEFS) meteorological forecasts. These datasets drive an intermediate-scale configuration of the Structure for Unifying Multiple Modeling Alternatives (SUMMA) model, which represents the PNW using over 11,700 HUCs. The system produces not only streamflow forecasts (using the Mizu
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Directory of Open Access Journals (Sweden)
Ansoumana Bodian
2018-03-01
Full Text Available This research investigated the effect of climate change on the two main river basins of Senegal in West Africa: the Senegal and Gambia River Basins. We used downscaled projected future rainfall and potential evapotranspiration based on projected temperature from six General Circulation Models (CanESM2, CNRM, CSIRO, HadGEM2-CC, HadGEM2-ES, and MIROC5 and two scenarios (RCP4.5 and RCP8.5 to force the GR4J model. The GR4J model was calibrated and validated using observed daily rainfall, potential evapotranspiration from observed daily temperature, and streamflow data. For the cross-validation, two periods for each river basin were considered: 1961–1982 and 1983–2004 for the Senegal River Basin at Bafing Makana, and 1969–1985 and 1986–2000 for the Gambia River Basin at Mako. Model efficiency is evaluated using a multi-criteria function (Fagg which aggregates Nash and Sutcliffe criteria, cumulative volume error, and mean volume error. Alternating periods of simulation for calibration and validation were used. This process allows us to choose the parameters that best reflect the rainfall-runoff relationship. Once the model was calibrated and validated, we simulated streamflow at Bafing Makana and Mako stations in the near future at a daily scale. The characteristic flow rates were calculated to evaluate their possible evolution under the projected climate scenarios at the 2050 horizon. For the near future (2050 horizon, compared to the 1971–2000 reference period, results showed that for both river basins, multi-model ensemble predicted a decrease of annual streamflow from 8% (Senegal River Basin to 22% (Gambia River Basin under the RCP4.5 scenario. Under the RCP8.5 scenario, the decrease is more pronounced: 16% (Senegal River Basin and 26% (Gambia River Basin. The Gambia River Basin will be more affected by the climate change.
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Directory of Open Access Journals (Sweden)
Y. Fei
2014-09-01
Full Text Available In this study, a hydrological modelling framework was introduced to assess the climate change impacts on future river flow in the West River basin, China, especially on streamflow variability and extremes. The modelling framework includes a delta-change method with the quantile-mapping technique to construct future climate forcings on the basis of observed meteorological data and the downscaled climate model outputs. This method is able to retain the signals of extreme weather events, as projected by climate models, in the constructed future forcing scenarios. Fed with the historical and future forcing data, a large-scale hydrologic model (the Variable Infiltration Capacity model, VIC was executed for streamflow simulations and projections at daily time scales. A bootstrapping resample approach was used as an indirect alternative to test the equality of means, standard deviations and the coefficients of variation for the baseline and future streamflow time series, and to assess the future changes in flood return levels. The West River basin case study confirms that the introduced modelling framework is an efficient effective tool to quantify streamflow variability and extremes in response to future climate change.
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HYDRORECESSION: A toolbox for streamflow recession analysis
Arciniega, S.
2015-12-01
Streamflow recession curves are hydrological signatures allowing to study the relationship between groundwater storage and baseflow and/or low flows at the catchment scale. Recent studies have showed that streamflow recession analysis can be quite sensitive to the combination of different models, extraction techniques and parameter estimation methods. In order to better characterize streamflow recession curves, new methodologies combining multiple approaches have been recommended. The HYDRORECESSION toolbox, presented here, is a Matlab graphical user interface developed to analyse streamflow recession time series with the support of different tools allowing to parameterize linear and nonlinear storage-outflow relationships through four of the most useful recession models (Maillet, Boussinesq, Coutagne and Wittenberg). The toolbox includes four parameter-fitting techniques (linear regression, lower envelope, data binning and mean squared error) and three different methods to extract hydrograph recessions segments (Vogel, Brutsaert and Aksoy). In addition, the toolbox has a module that separates the baseflow component from the observed hydrograph using the inverse reservoir algorithm. Potential applications provided by HYDRORECESSION include model parameter analysis, hydrological regionalization and classification, baseflow index estimates, catchment-scale recharge and low-flows modelling, among others. HYDRORECESSION is freely available for non-commercial and academic purposes.
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Variance analysis of forecasted streamflow maxima in a wet temperate climate
Al Aamery, Nabil; Fox, James F.; Snyder, Mark; Chandramouli, Chandra V.
2018-05-01
Coupling global climate models, hydrologic models and extreme value analysis provides a method to forecast streamflow maxima, however the elusive variance structure of the results hinders confidence in application. Directly correcting the bias of forecasts using the relative change between forecast and control simulations has been shown to marginalize hydrologic uncertainty, reduce model bias, and remove systematic variance when predicting mean monthly and mean annual streamflow, prompting our investigation for maxima streamflow. We assess the variance structure of streamflow maxima using realizations of emission scenario, global climate model type and project phase, downscaling methods, bias correction, extreme value methods, and hydrologic model inputs and parameterization. Results show that the relative change of streamflow maxima was not dependent on systematic variance from the annual maxima versus peak over threshold method applied, albeit we stress that researchers strictly adhere to rules from extreme value theory when applying the peak over threshold method. Regardless of which method is applied, extreme value model fitting does add variance to the projection, and the variance is an increasing function of the return period. Unlike the relative change of mean streamflow, results show that the variance of the maxima's relative change was dependent on all climate model factors tested as well as hydrologic model inputs and calibration. Ensemble projections forecast an increase of streamflow maxima for 2050 with pronounced forecast standard error, including an increase of +30(±21), +38(±34) and +51(±85)% for 2, 20 and 100 year streamflow events for the wet temperate region studied. The variance of maxima projections was dominated by climate model factors and extreme value analyses.
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Streamflow alteration at selected sites in Kansas
Juracek, Kyle E.; Eng, Ken
2017-06-26
An understanding of streamflow alteration in response to various disturbances is necessary for the effective management of stream habitat for a variety of species in Kansas. Streamflow alteration can have negative ecological effects. Using a modeling approach, streamflow alteration was assessed for 129 selected U.S. Geological Survey streamgages in the State for which requisite streamflow and basin-characteristic information was available. The assessment involved a comparison of the observed condition from 1980 to 2015 with the predicted expected (least-disturbed) condition for 29 streamflow metrics. The metrics represent various characteristics of streamflow including average flow (annual, monthly) and low and high flow (frequency, duration, magnitude).Streamflow alteration in Kansas was indicated locally, regionally, and statewide. Given the absence of a pronounced trend in annual precipitation in Kansas, a precipitation-related explanation for streamflow alteration was not supported. Thus, the likely explanation for streamflow alteration was human activity. Locally, a flashier flow regime (typified by shorter lag times and more frequent and higher peak discharges) was indicated for three streamgages with urbanized basins that had higher percentages of impervious surfaces than other basins in the State. The combination of localized reservoir effects and regional groundwater pumping from the High Plains aquifer likely was responsible, in part, for diminished conditions indicated for multiple streamflow metrics in western and central Kansas. Statewide, the implementation of agricultural land-management practices to reduce runoff may have been responsible, in part, for a diminished duration and magnitude of high flows. In central and eastern Kansas, implemented agricultural land-management practices may have been partly responsible for an inflated magnitude of low flows at several sites.
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Directory of Open Access Journals (Sweden)
William H. Farmer
2017-10-01
New hydrological insights for the region: Several methods for estimating nonexceedance probabilities of daily mean streamflows are explored, including single-index methodologies (nearest-neighboring index and geospatial tools (kriging and topological kriging. These methods were evaluated by conducting leave-one-out cross-validations based on analyses of nearly 7 years of daily streamflow data from 79 unregulated streamgages in Ohio and neighboring states. The pooled, ordinary kriging model, with a median Nash–Sutcliffe performance of 0.87, was superior to the single-site index methods, though there was some bias in the tails of the probability distribution. Incorporating network structure through topological kriging did not improve performance. The pooled, ordinary kriging model was applied to 118 locations without systematic streamgaging across Ohio where instantaneous streamflow measurements had been made concurrent with water-quality sampling on at least 3 separate days. Spearman rank correlations between estimated nonexceedance probabilities and measured streamflows were high, with a median value of 0.76. In consideration of application, the degree of regulation in a set of sample sites helped to specify the streamgages required to implement kriging approaches successfully.
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Richey, A. S.; Richey, J. E.; Tan, A.; Liu, M.; Adam, J. C.; Sokolov, V.
2015-12-01
Central Asia presents a perfect case study to understand the dynamic, and often conflicting, linkages between food, energy, and water in natural systems. The destruction of the Aral Sea is a well-known environmental disaster, largely driven by increased irrigation demand on the rivers that feed the endorheic sea. Continued reliance on these rivers, the Amu Darya and Syr Darya, often place available water resources at odds between hydropower demands upstream and irrigation requirements downstream. A combination of tools is required to understand these linkages and how they may change in the future as a function of climate change and population growth. In addition, the region is geopolitically complex as the former Soviet basin states develop management strategies to sustainably manage shared resources. This complexity increases the importance of relying upon publically available information sources and tools. Preliminary work has shown potential for the Variable Infiltration Capacity (VIC) model to recreate the natural water balance in the Amu Darya and Syr Darya basins by comparing results to total terrestrial water storage changes observed from NASA's Gravity Recovery and Climate Experiment (GRACE) satellite mission. Modeled streamflow is well correlated to observed streamflow at upstream gauges prior to the large-scale expansion of irrigation and hydropower. However, current modeled results are unable to capture the human influence of water use on downstream flow. This study examines the utility of a crop simulation model, CropSyst, to represent irrigation demand and GRACE to improve modeled streamflow estimates in the Amu Darya and Syr Darya basins. Specifically we determine crop water demand with CropSyst utilizing available data on irrigation schemes and cropping patterns. We determine how this demand can be met either by surface water, modeled by VIC with a reservoir operation scheme, and/or by groundwater derived from GRACE. Finally, we assess how the
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Sensitivity of streamflow to climate change in California
Grantham, T.; Carlisle, D.; Wolock, D.; McCabe, G. J.; Wieczorek, M.; Howard, J.
2015-12-01
Trends of decreasing snowpack and increasing risk of drought are looming challenges for California water resource management. Increasing vulnerability of the state's natural water supplies threatens California's social-economic vitality and the health of its freshwater ecosystems. Despite growing awareness of potential climate change impacts, robust management adaptation has been hindered by substantial uncertainty in future climate predictions for the region. Down-scaled global climate model (GCM) projections uniformly suggest future warming of the region, but projections are highly variable with respect to the direction and magnitude of change in regional precipitation. Here we examine the sensitivity of California surface water supplies to climate variation independently of GCMs. We use a statistical approach to construct predictive models of monthly streamflow based on historical climate and river basin features. We then propagate an ensemble of synthetic climate simulations through the models to assess potential streamflow responses to changes in temperature and precipitation in different months and regions of the state. We also consider the range of streamflow change predicted by bias-corrected downscaled GCMs. Our results indicate that the streamflow in the xeric and coastal mountain regions of California is more sensitive to changes in precipitation than temperature, whereas streamflow in the interior mountain region responds strongly to changes in both temperature and precipitation. Mean climate projections for 2025-2075 from GCM ensembles are highly variable, indicating streamflow changes of -50% to +150% relative to baseline (1980-2010) for most months and regions. By quantifying the sensitivity of streamflow to climate change, rather than attempting to predict future hydrologic conditions based on uncertain GCM projections, these results should be more informative to water managers seeking to assess, and potentially reduce, the vulnerability of surface
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Monthly streamflow forecasting based on hidden Markov model and Gaussian Mixture Regression
Liu, Yongqi; Ye, Lei; Qin, Hui; Hong, Xiaofeng; Ye, Jiajun; Yin, Xingli
2018-06-01
Reliable streamflow forecasts can be highly valuable for water resources planning and management. In this study, we combined a hidden Markov model (HMM) and Gaussian Mixture Regression (GMR) for probabilistic monthly streamflow forecasting. The HMM is initialized using a kernelized K-medoids clustering method, and the Baum-Welch algorithm is then executed to learn the model parameters. GMR derives a conditional probability distribution for the predictand given covariate information, including the antecedent flow at a local station and two surrounding stations. The performance of HMM-GMR was verified based on the mean square error and continuous ranked probability score skill scores. The reliability of the forecasts was assessed by examining the uniformity of the probability integral transform values. The results show that HMM-GMR obtained reasonably high skill scores and the uncertainty spread was appropriate. Different HMM states were assumed to be different climate conditions, which would lead to different types of observed values. We demonstrated that the HMM-GMR approach can handle multimodal and heteroscedastic data.
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Application of ANN and fuzzy logic algorithms for streamflow ...
Indian Academy of Sciences (India)
The present study focusses on development of models using ANN and fuzzy logic (FL) algorithm for predicting the streamflow for catchment of Savitri River Basin. The input vector to these models were daily rainfall, mean daily evaporation, mean daily temperature and lag streamflow used. In the present study, 20 years ...
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Drivers influencing streamflow changes in the Upper Turia basin, Spain.
Salmoral, Gloria; Willaarts, Bárbara A; Troch, Peter A; Garrido, Alberto
2015-01-15
Many rivers across the world have experienced a significant streamflow reduction over the last decades. Drivers of the observed streamflow changes are multiple, including climate change (CC), land use and land cover changes (LULCC), water transfers and river impoundment. Many of these drivers inter-act simultaneously, making it difficult to discern the impact of each driver individually. In this study we isolate the effects of LULCC on the observed streamflow reduction in the Upper Turia basin (east Spain) during the period 1973-2008. Regression models of annual streamflow are fitted with climatic variables and also additional time variant drivers like LULCC. The ecohydrological model SWAT is used to study the magnitude and sign of streamflow change when LULCC occurs. Our results show that LULCC does play a significant role on the water balance, but it is not the main driver underpinning the observed reduction on Turia's streamflow. Increasing mean temperature is the main factor supporting increasing evapotranspiration and streamflow reduction. In fact, LULCC and CC have had an offsetting effect on the streamflow generation during the study period. While streamflow has been negatively affected by increasing temperature, ongoing LULCC have positively compensated with reduced evapotranspiration rates, thanks to mainly shrubland clearing and forest degradation processes. These findings are valuable for the management of the Turia river basin, as well as a useful approach for the determination of the weight of LULCC on the hydrological response in other regions. Copyright © 2014 Elsevier B.V. All rights reserved.
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Streamflow predictions under climate scenarios in the Boulder Creek Watershed at Orodell
Zhang, Q.; Williams, M. W.; Livneh, B.
2016-12-01
Mountainous areas have complex geological features and climatic variability, which limit our ability to simulate and predict hydrologic processes, especially in face to a changing climate. Hydrologic models can improve our understanding of land surface water and energy budgets in these regions. In this study, a distributed physically-based hydrologic model is applied to the Boulder Creek Watershed, USA to study streamflow conditions under future climatic scenarios. Model parameters were adjusted using observed streamflow data at 1/16th degree resolution, with a NSE value of 0.69. The results from CMIP5 models can give a general range of streamflow conditions under different climatic scenarios. Two scenarios are being applied, including the RCP 4.5 and 8.5 scenarios. RCP 8.5 has higher emission concentrations than RCP 4.5, but not very significant in the period of study. Using pair t-test and Mann-Whitney test at specific grid cells to compare modeled and observed climate data, four CMIP5 models were chosen to predict streamflow from 2010 to 2025. Of the four models, two models predicted increased precipitation, while the other two models predicted decreased precipitation, and the four models predicted increased minimum and maximum temperature in RCP 4.5. Average streamflow decreased by 2% 14%, while maximum SWE varies from -7% to +210% from 2010 to 2025, relative to 2006 to 2010. In RCP 8.5, three models predicted increased precipitation, while the other one model predicted decreased precipitation, and the four models predicted increased maximum and minimum temperature. Besides one model, the other three models predicted increased average streamflow by 3.5% 32%, which results from the higher increasing magnitude in precipitation. Maximum SWE varies by 6% 55% higher than that from 2006 to 2010. This study shows that average daily maximum and minimum temperature will increase toward 2025 from different climate models, while average streamflow will decrease in RCP 4
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Yan, Hongxiang; Moradkhani, Hamid; Abbaszadeh, Peyman
2017-04-01
Assimilation of satellite soil moisture and streamflow data into hydrologic models using has received increasing attention over the past few years. Currently, these observations are increasingly used to improve the model streamflow and soil moisture predictions. However, the performance of this land data assimilation (DA) system still suffers from two limitations: 1) satellite data scarcity and quality; and 2) particle weight degeneration. In order to overcome these two limitations, we propose two possible solutions in this study. First, the general Gaussian geostatistical approach is proposed to overcome the limitation in the space/time resolution of satellite soil moisture products thus improving their accuracy at uncovered/biased grid cells. Secondly, an evolutionary PF approach based on Genetic Algorithm (GA) and Markov Chain Monte Carlo (MCMC), the so-called EPF-MCMC, is developed to further reduce weight degeneration and improve the robustness of the land DA system. This study provides a detailed analysis of the joint and separate assimilation of streamflow and satellite soil moisture into a distributed Sacramento Soil Moisture Accounting (SAC-SMA) model, with the use of recently developed EPF-MCMC and the general Gaussian geostatistical approach. Performance is assessed over several basins in the USA selected from Model Parameter Estimation Experiment (MOPEX) and located in different climate regions. The results indicate that: 1) the general Gaussian approach can predict the soil moisture at uncovered grid cells within the expected satellite data quality threshold; 2) assimilation of satellite soil moisture inferred from the general Gaussian model can significantly improve the soil moisture predictions; and 3) in terms of both deterministic and probabilistic measures, the EPF-MCMC can achieve better streamflow predictions. These results recommend that the geostatistical model is a helpful tool to aid the remote sensing technique and the EPF-MCMC is a
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Jaskierniak, D.; Kuczera, G.; Benyon, R.
2016-04-01
A major challenge in surface hydrology involves predicting streamflow in ungauged catchments with heterogeneous vegetation and spatiotemporally varying evapotranspiration (ET) rates. We present a top-down approach for quantifying the influence of broad-scale changes in forest structure on ET and hence streamflow. Across three catchments between 18 and 100 km2 in size and with regenerating Eucalyptus regnans and E. delegatensis forest, we demonstrate how variation in ET can be mapped in space and over time using LiDAR data and commonly available forest inventory data. The model scales plot-level sapwood area (SA) to the catchment-level using basal area (BA) and tree stocking density (N) estimates in forest growth models. The SA estimates over a 69 year regeneration period are used in a relationship between SA and vegetation induced streamflow loss (L) to predict annual streamflow (Q) with annual rainfall (P) estimates. Without calibrating P, BA, N, SA, and L to Q data, we predict annual Q with R2 between 0.68 and 0.75 and Nash Sutcliffe efficiency (NSE) between 0.44 and 0.48. To remove bias, the model was extended to allow for runoff carry-over into the following year as well as minor correction to rainfall bias, which produced R2 values between 0.72 and 0.79, and NSE between 0.70 and 0.79. The model under-predicts streamflow during drought periods as it lacks representation of ecohydrological processes that reduce L with either reduced growth rates or rainfall interception during drought. Refining the relationship between sapwood thickness and forest inventory variables is likely to further improve results.
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Reconstructing pre-instrumental streamflow in Eastern Australia using a water balance approach
Tozer, C. R.; Kiem, A. S.; Vance, T. R.; Roberts, J. L.; Curran, M. A. J.; Moy, A. D.
2018-03-01
Streamflow reconstructions based on paleoclimate proxies provide much longer records than the short instrumental period records on which water resource management plans are currently based. In Australia there is a lack of in-situ high resolution paleoclimate proxy records, but remote proxies with teleconnections to Australian climate have utility in producing streamflow reconstructions. Here we investigate, via a case study for a catchment in eastern Australia, the novel use of an Antarctic ice-core based rainfall reconstruction within a Budyko-framework to reconstruct ∼1000 years of annual streamflow. The resulting streamflow reconstruction captures interannual to decadal variability in the instrumental streamflow, validating both the use of the ice core rainfall proxy record and the Budyko-framework method. In the preinstrumental era the streamflow reconstruction shows longer wet and dry epochs and periods of streamflow variability that are higher than observed in the instrumental era. Importantly, for both the instrumental record and preinstrumental reconstructions, the wet (dry) epochs in the rainfall record are shorter (longer) in the streamflow record and this non-linearity must be considered when inferring hydroclimatic risk or historical water availability directly from rainfall proxy records alone. These insights provide a better understanding of present infrastructure vulnerability in the context of past climate variability for eastern Australia. The streamflow reconstruction presented here also provides a better understanding of the range of hydroclimatic variability possible, and therefore represents a more realistic baseline on which to quantify the potential impacts of anthropogenic climate change on water security.
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Spatial patterns of March and September streamflow trends in Pacific Northwest Streams, 1958-2008
Chang, Heejun; Jung, Il-Won; Steele, Madeline; Gannett, Marshall
2012-01-01
Summer streamflow is a vital water resource for municipal and domestic water supplies, irrigation, salmonid habitat, recreation, and water-related ecosystem services in the Pacific Northwest (PNW) in the United States. This study detects significant negative trends in September absolute streamflow in a majority of 68 stream-gauging stations located on unregulated streams in the PNW from 1958 to 2008. The proportion of March streamflow to annual streamflow increases in most stations over 1,000 m elevation, with a baseflow index of less than 50, while absolute March streamflow does not increase in most stations. The declining trends of September absolute streamflow are strongly associated with seven-day low flow, January–March maximum temperature trends, and the size of the basin (19–7,260 km2), while the increasing trends of the fraction of March streamflow are associated with elevation, April 1 snow water equivalent, March precipitation, center timing of streamflow, and October–December minimum temperature trends. Compared with ordinary least squares (OLS) estimated regression models, spatial error regression and geographically weighted regression (GWR) models effectively remove spatial autocorrelation in residuals. The GWR model results show spatial gradients of local R 2 values with consistently higher local R 2 values in the northern Cascades. This finding illustrates that different hydrologic landscape factors, such as geology and seasonal distribution of precipitation, also influence streamflow trends in the PNW. In addition, our spatial analysis model results show that considering various geographic factors help clarify the dynamics of streamflow trends over a large geographical area, supporting a spatial analysis approach over aspatial OLS-estimated regression models for predicting streamflow trends. Results indicate that transitional rain–snow surface water-dominated basins are likely to have reduced summer streamflow under warming scenarios
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Sun, Wenchao; Ishidaira, Hiroshi; Bastola, Satish; Yu, Jingshan
2015-05-01
Lacking observation data for calibration constrains applications of hydrological models to estimate daily time series of streamflow. Recent improvements in remote sensing enable detection of river water-surface width from satellite observations, making possible the tracking of streamflow from space. In this study, a method calibrating hydrological models using river width derived from remote sensing is demonstrated through application to the ungauged Irrawaddy Basin in Myanmar. Generalized likelihood uncertainty estimation (GLUE) is selected as a tool for automatic calibration and uncertainty analysis. Of 50,000 randomly generated parameter sets, 997 are identified as behavioral, based on comparing model simulation with satellite observations. The uncertainty band of streamflow simulation can span most of 10-year average monthly observed streamflow for moderate and high flow conditions. Nash-Sutcliffe efficiency is 95.7% for the simulated streamflow at the 50% quantile. These results indicate that application to the target basin is generally successful. Beyond evaluating the method in a basin lacking streamflow data, difficulties and possible solutions for applications in the real world are addressed to promote future use of the proposed method in more ungauged basins. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
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David, McInerney; Mark, Thyer; Dmitri, Kavetski; George, Kuczera
2017-04-01
This study provides guidance to hydrological researchers which enables them to provide probabilistic predictions of daily streamflow with the best reliability and precision for different catchment types (e.g. high/low degree of ephemerality). Reliable and precise probabilistic prediction of daily catchment-scale streamflow requires statistical characterization of residual errors of hydrological models. It is commonly known that hydrological model residual errors are heteroscedastic, i.e. there is a pattern of larger errors in higher streamflow predictions. Although multiple approaches exist for representing this heteroscedasticity, few studies have undertaken a comprehensive evaluation and comparison of these approaches. This study fills this research gap by evaluating 8 common residual error schemes, including standard and weighted least squares, the Box-Cox transformation (with fixed and calibrated power parameter, lambda) and the log-sinh transformation. Case studies include 17 perennial and 6 ephemeral catchments in Australia and USA, and two lumped hydrological models. We find the choice of heteroscedastic error modelling approach significantly impacts on predictive performance, though no single scheme simultaneously optimizes all performance metrics. The set of Pareto optimal schemes, reflecting performance trade-offs, comprises Box-Cox schemes with lambda of 0.2 and 0.5, and the log scheme (lambda=0, perennial catchments only). These schemes significantly outperform even the average-performing remaining schemes (e.g., across ephemeral catchments, median precision tightens from 105% to 40% of observed streamflow, and median biases decrease from 25% to 4%). Theoretical interpretations of empirical results highlight the importance of capturing the skew/kurtosis of raw residuals and reproducing zero flows. Recommendations for researchers and practitioners seeking robust residual error schemes for practical work are provided.
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Energy Technology Data Exchange (ETDEWEB)
Takle, Eugene S.; Jha, Manoj; Lu, Er; Arritt, Raymond W.; Gutowski, William J. [Iowa State Univ. Ames, IA (United States)
2010-06-15
We use Soil and Water Assessment Tool (SWAT) when driven by observations and results of climate models to evaluate hydrological quantities, including streamflow, in the Upper Mississippi River Basin (UMRB) for 1981-2003 in comparison to observed streamflow. Daily meteorological conditions used as input to SWAT are taken from (1) observations at weather stations in the basin, (2) daily meteorological conditions simulated by a collection of regional climate models (RCMs) driven by reanalysis boundary conditions, and (3) daily meteorological conditions simulated by a collection of global climate models (GCMs). Regional models used are those whose data are archived by the North American Regional Climate Change Assessment Program (NARCCAP). Results show that regional models correctly simulate the seasonal cycle of precipitation, temperature, and streamflow within the basin. Regional models also capture interannual extremes represented by the flood of 1993 and the dry conditions of 2000. The ensemble means of both the GCM-driven and RCM-driven simulations by SWAT capture both the timing and amplitude of the seasonal cycle of streamflow with neither demonstrating significant superiority at the basin level. (orig.)
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Dudley, Robert W.
2008-01-01
The U.S. Geological Survey (USGS), in cooperation with the Maine Department of Marine Resources Bureau of Sea Run Fisheries and Habitat, began a study in 2004 to characterize the quantity, variability, and timing of streamflow in the Dennys River. The study included a synoptic summary of historical streamflow data at a long-term streamflow gage, collecting data from an additional four short-term streamflow gages, and the development and evaluation of a distributed-parameter watershed model for the Dennys River Basin. The watershed model used in this investigation was the USGS Precipitation-Runoff Modeling System (PRMS). The Geographic Information System (GIS) Weasel was used to delineate the Dennys River Basin and subbasins and derive parameters for their physical geographic features. Calibration of the models used in this investigation involved a four-step procedure in which model output was evaluated against four calibration data sets using computed objective functions for solar radiation, potential evapotranspiration, annual and seasonal water budgets, and daily streamflows. The calibration procedure involved thousands of model runs and was carried out using the USGS software application Luca (Let us calibrate). Luca uses the Shuffled Complex Evolution (SCE) global search algorithm to calibrate the model parameters. The SCE method reliably produces satisfactory solutions for large, complex optimization problems. The primary calibration effort went into the Dennys main stem watershed model. Calibrated parameter values obtained for the Dennys main stem model were transferred to the Cathance Stream model, and a similar four-step SCE calibration procedure was performed; this effort was undertaken to determine the potential to transfer modeling information to a nearby basin in the same region. The calibrated Dennys main stem watershed model performed with Nash-Sutcliffe efficiency (NSE) statistic values for the calibration period and evaluation period of 0.79 and 0
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CEREF: A hybrid data-driven model for forecasting annual streamflow from a socio-hydrological system
Zhang, Hongbo; Singh, Vijay P.; Wang, Bin; Yu, Yinghao
2016-09-01
Hydrological forecasting is complicated by flow regime alterations in a coupled socio-hydrologic system, encountering increasingly non-stationary, nonlinear and irregular changes, which make decision support difficult for future water resources management. Currently, many hybrid data-driven models, based on the decomposition-prediction-reconstruction principle, have been developed to improve the ability to make predictions of annual streamflow. However, there exist many problems that require further investigation, the chief among which is the direction of trend components decomposed from annual streamflow series and is always difficult to ascertain. In this paper, a hybrid data-driven model was proposed to capture this issue, which combined empirical mode decomposition (EMD), radial basis function neural networks (RBFNN), and external forces (EF) variable, also called the CEREF model. The hybrid model employed EMD for decomposition and RBFNN for intrinsic mode function (IMF) forecasting, and determined future trend component directions by regression with EF as basin water demand representing the social component in the socio-hydrologic system. The Wuding River basin was considered for the case study, and two standard statistical measures, root mean squared error (RMSE) and mean absolute error (MAE), were used to evaluate the performance of CEREF model and compare with other models: the autoregressive (AR), RBFNN and EMD-RBFNN. Results indicated that the CEREF model had lower RMSE and MAE statistics, 42.8% and 7.6%, respectively, than did other models, and provided a superior alternative for forecasting annual runoff in the Wuding River basin. Moreover, the CEREF model can enlarge the effective intervals of streamflow forecasting compared to the EMD-RBFNN model by introducing the water demand planned by the government department to improve long-term prediction accuracy. In addition, we considered the high-frequency component, a frequent subject of concern in EMD
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Effect of Streamflow Forecast Uncertainty on Real-Time Reservoir Operation
Zhao, T.; Cai, X.; Yang, D.
2010-12-01
Various hydrological forecast products have been applied to real-time reservoir operation, including deterministic streamflow forecast (DSF), DSF-based probabilistic streamflow forecast (DPSF), and ensemble streamflow forecast (ESF), which represent forecast uncertainty in the form of deterministic forecast error, deterministic forecast error-based uncertainty distribution, and ensemble forecast errors, respectively. Compared to previous studies that treat these forecast products as ad hoc inputs for reservoir operation models, this paper attempts to model the uncertainties involved in the various forecast products and explores their effect on real-time reservoir operation decisions. In hydrology, there are various indices reflecting the magnitude of streamflow forecast uncertainty; meanwhile, few models illustrate the forecast uncertainty evolution process. This research introduces Martingale Model of Forecast Evolution (MMFE) from supply chain management and justifies its assumptions for quantifying the evolution of uncertainty in streamflow forecast as time progresses. Based on MMFE, this research simulates the evolution of forecast uncertainty in DSF, DPSF, and ESF, and applies the reservoir operation models (dynamic programming, DP; stochastic dynamic programming, SDP; and standard operation policy, SOP) to assess the effect of different forms of forecast uncertainty on real-time reservoir operation. Through a hypothetical single-objective real-time reservoir operation model, the results illustrate that forecast uncertainty exerts significant effects. Reservoir operation efficiency, as measured by a utility function, decreases as the forecast uncertainty increases. Meanwhile, these effects also depend on the type of forecast product being used. In general, the utility of reservoir operation with ESF is nearly as high as the utility obtained with a perfect forecast; the utilities of DSF and DPSF are similar to each other but not as efficient as ESF. Moreover
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Huizinga, Richard J.
2014-01-01
Streamflow data, basin characteristics, and rainfall data from 39 streamflow-gaging stations for urban areas in and adjacent to Missouri were used by the U.S. Geological Survey in cooperation with the Metropolitan Sewer District of St. Louis to develop an initial abstraction and constant loss model (a time-distributed basin-loss model) and a gamma unit hydrograph (GUH) for urban areas in Missouri. Study-specific methods to determine peak streamflow and flood volume for a given rainfall event also were developed.
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Streamflow impacts of biofuel policy-driven landscape change.
Directory of Open Access Journals (Sweden)
Sami Khanal
Full Text Available Likely changes in precipitation (P and potential evapotranspiration (PET resulting from policy-driven expansion of bioenergy crops in the United States are shown to create significant changes in streamflow volumes and increase water stress in the High Plains. Regional climate simulations for current and biofuel cropping system scenarios are evaluated using the same atmospheric forcing data over the period 1979-2004 using the Weather Research Forecast (WRF model coupled to the NOAH land surface model. PET is projected to increase under the biofuel crop production scenario. The magnitude of the mean annual increase in PET is larger than the inter-annual variability of change in PET, indicating that PET increase is a forced response to the biofuel cropping system land use. Across the conterminous U.S., the change in mean streamflow volume under the biofuel scenario is estimated to range from negative 56% to positive 20% relative to a business-as-usual baseline scenario. In Kansas and Oklahoma, annual streamflow volume is reduced by an average of 20%, and this reduction in streamflow volume is due primarily to increased PET. Predicted increase in mean annual P under the biofuel crop production scenario is lower than its inter-annual variability, indicating that additional simulations would be necessary to determine conclusively whether predicted change in P is a response to biofuel crop production. Although estimated changes in streamflow volume include the influence of P change, sensitivity results show that PET change is the significantly dominant factor causing streamflow change. Higher PET and lower streamflow due to biofuel feedstock production are likely to increase water stress in the High Plains. When pursuing sustainable biofuels policy, decision-makers should consider the impacts of feedstock production on water scarcity.
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The effects of changing land cover on streamflow simulation in Puerto Rico
Van Beusekom, Ashley; Hay, Lauren E.; Viger, Roland; Gould, William A.; Collazo, Jaime; Henareh Khalyani, Azad
2014-01-01
This study quantitatively explores whether land cover changes have a substantive impact on simulated streamflow within the tropical island setting of Puerto Rico. The Precipitation Runoff Modeling System (PRMS) was used to compare streamflow simulations based on five static parameterizations of land cover with those based on dynamically varying parameters derived from four land cover scenes for the period 1953-2012. The PRMS simulations based on static land cover illustrated consistent differences in simulated streamflow across the island. It was determined that the scale of the analysis makes a difference: large regions with localized areas that have undergone dramatic land cover change may show negligible difference in total streamflow, but streamflow simulations using dynamic land cover parameters for a highly altered subwatershed clearly demonstrate the effects of changing land cover on simulated streamflow. Incorporating dynamic parameterization in these highly altered watersheds can reduce the predictive uncertainty in simulations of streamflow using PRMS. Hydrologic models that do not consider the projected changes in land cover may be inadequate for water resource management planning for future conditions.
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Dhakal, A. S.; Adera, S.
2017-12-01
Accurate daily streamflow prediction in ungauged watersheds with sparse information is challenging. The ability of a hydrologic model calibrated using nearby gauged watersheds to predict streamflow accurately depends on hydrologic similarities between the gauged and ungauged watersheds. This study examines daily streamflow predictions using the Precipitation-Runoff Modeling System (PRMS) for the largely ungauged San Antonio Creek watershed, a 96 km2 sub-watershed of the Alameda Creek watershed in Northern California. The process-based PRMS model is being used to improve the accuracy of recent San Antonio Creek streamflow predictions generated by two empirical methods. Although San Antonio Creek watershed is largely ungauged, daily streamflow data exists for hydrologic years (HY) 1913 - 1930. PRMS was calibrated for HY 1913 - 1930 using streamflow data, modern-day land use and PRISM precipitation distribution, and gauged precipitation and temperature data from a nearby watershed. The PRMS model was then used to generate daily streamflows for HY 1996-2013, during which the watershed was ungauged, and hydrologic responses were compared to two nearby gauged sub-watersheds of Alameda Creek. Finally, the PRMS-predicted daily flows between HY 1996-2013 were compared to the two empirically-predicted streamflow time series: (1) the reservoir mass balance method and (2) correlation of historical streamflows from 80 - 100 years ago between San Antonio Creek and a nearby sub-watershed located in Alameda Creek. While the mass balance approach using reservoir storage and transfers is helpful for estimating inflows to the reservoir, large discrepancies in daily streamflow estimation can arise. Similarly, correlation-based predicted daily flows which rely on a relationship from flows collected 80-100 years ago may not represent current watershed hydrologic conditions. This study aims to develop a method of streamflow prediction in the San Antonio Creek watershed by examining PRMS
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Downscaling of GCM forecasts to streamflow over Scandinavia
DEFF Research Database (Denmark)
Nilsson, P.; Uvo, C.B.; Landman, W.A.
2008-01-01
flows. The technique includes model output statistics (MOS) based on a non-linear Neural Network (NN) approach. Results show that streamflow forecasts from Global Circulation Model (GCM) predictions, for the Scandinavia region are viable and highest skill values were found for basins located in south......A seasonal forecasting technique to produce probabilistic and deterministic streamflow forecasts for 23 basins in Norway and northern Sweden is developed in this work. Large scale circulation and moisture fields, forecasted by the ECHAM4.5 model 4 months in advance, are used to forecast spring...
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Chegwidden, O.; Nijssen, B.; Pytlak, E.
2017-12-01
Any model simulation has errors, including errors in meteorological data, process understanding, model structure, and model parameters. These errors may express themselves as bias, timing lags, and differences in sensitivity between the model and the physical world. The evaluation and handling of these errors can greatly affect the legitimacy, validity and usefulness of the resulting scientific product. In this presentation we will discuss a case study of handling and communicating model errors during the development of a hydrologic climate change dataset for the Pacific Northwestern United States. The dataset was the result of a four-year collaboration between the University of Washington, Oregon State University, the Bonneville Power Administration, the United States Army Corps of Engineers and the Bureau of Reclamation. Along the way, the partnership facilitated the discovery of multiple systematic errors in the streamflow dataset. Through an iterative review process, some of those errors could be resolved. For the errors that remained, honest communication of the shortcomings promoted the dataset's legitimacy. Thoroughly explaining errors also improved ways in which the dataset would be used in follow-on impact studies. Finally, we will discuss the development of the "streamflow bias-correction" step often applied to climate change datasets that will be used in impact modeling contexts. We will describe the development of a series of bias-correction techniques through close collaboration among universities and stakeholders. Through that process, both universities and stakeholders learned about the others' expectations and workflows. This mutual learning process allowed for the development of methods that accommodated the stakeholders' specific engineering requirements. The iterative revision process also produced a functional and actionable dataset while preserving its scientific merit. We will describe how encountering earlier techniques' pitfalls allowed us
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Propagation of soil moisture memory to streamflow and evapotranspiration in Europe
Orth, R.; Seneviratne, S. I.
2013-10-01
As a key variable of the land-climate system soil moisture is a main driver of streamflow and evapotranspiration under certain conditions. Soil moisture furthermore exhibits outstanding memory (persistence) characteristics. Many studies also report distinct low frequency variations for streamflow, which are likely related to soil moisture memory. Using data from over 100 near-natural catchments located across Europe, we investigate in this study the connection between soil moisture memory and the respective memory of streamflow and evapotranspiration on different time scales. For this purpose we use a simple water balance model in which dependencies of runoff (normalised by precipitation) and evapotranspiration (normalised by radiation) on soil moisture are fitted using streamflow observations. The model therefore allows us to compute the memory characteristics of soil moisture, streamflow and evapotranspiration on the catchment scale. We find considerable memory in soil moisture and streamflow in many parts of the continent, and evapotranspiration also displays some memory at monthly time scale in some catchments. We show that the memory of streamflow and evapotranspiration jointly depend on soil moisture memory and on the strength of the coupling of streamflow and evapotranspiration to soil moisture. Furthermore, we find that the coupling strengths of streamflow and evapotranspiration to soil moisture depend on the shape of the fitted dependencies and on the variance of the meteorological forcing. To better interpret the magnitude of the respective memories across Europe, we finally provide a new perspective on hydrological memory by relating it to the mean duration required to recover from anomalies exceeding a certain threshold.
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Propagation of soil moisture memory to streamflow and evapotranspiration in Europe
Directory of Open Access Journals (Sweden)
R. Orth
2013-10-01
Full Text Available As a key variable of the land-climate system soil moisture is a main driver of streamflow and evapotranspiration under certain conditions. Soil moisture furthermore exhibits outstanding memory (persistence characteristics. Many studies also report distinct low frequency variations for streamflow, which are likely related to soil moisture memory. Using data from over 100 near-natural catchments located across Europe, we investigate in this study the connection between soil moisture memory and the respective memory of streamflow and evapotranspiration on different time scales. For this purpose we use a simple water balance model in which dependencies of runoff (normalised by precipitation and evapotranspiration (normalised by radiation on soil moisture are fitted using streamflow observations. The model therefore allows us to compute the memory characteristics of soil moisture, streamflow and evapotranspiration on the catchment scale. We find considerable memory in soil moisture and streamflow in many parts of the continent, and evapotranspiration also displays some memory at monthly time scale in some catchments. We show that the memory of streamflow and evapotranspiration jointly depend on soil moisture memory and on the strength of the coupling of streamflow and evapotranspiration to soil moisture. Furthermore, we find that the coupling strengths of streamflow and evapotranspiration to soil moisture depend on the shape of the fitted dependencies and on the variance of the meteorological forcing. To better interpret the magnitude of the respective memories across Europe, we finally provide a new perspective on hydrological memory by relating it to the mean duration required to recover from anomalies exceeding a certain threshold.
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McInerney, David; Thyer, Mark; Kavetski, Dmitri; Lerat, Julien; Kuczera, George
2017-03-01
Reliable and precise probabilistic prediction of daily catchment-scale streamflow requires statistical characterization of residual errors of hydrological models. This study focuses on approaches for representing error heteroscedasticity with respect to simulated streamflow, i.e., the pattern of larger errors in higher streamflow predictions. We evaluate eight common residual error schemes, including standard and weighted least squares, the Box-Cox transformation (with fixed and calibrated power parameter λ) and the log-sinh transformation. Case studies include 17 perennial and 6 ephemeral catchments in Australia and the United States, and two lumped hydrological models. Performance is quantified using predictive reliability, precision, and volumetric bias metrics. We find the choice of heteroscedastic error modeling approach significantly impacts on predictive performance, though no single scheme simultaneously optimizes all performance metrics. The set of Pareto optimal schemes, reflecting performance trade-offs, comprises Box-Cox schemes with λ of 0.2 and 0.5, and the log scheme (λ = 0, perennial catchments only). These schemes significantly outperform even the average-performing remaining schemes (e.g., across ephemeral catchments, median precision tightens from 105% to 40% of observed streamflow, and median biases decrease from 25% to 4%). Theoretical interpretations of empirical results highlight the importance of capturing the skew/kurtosis of raw residuals and reproducing zero flows. Paradoxically, calibration of λ is often counterproductive: in perennial catchments, it tends to overfit low flows at the expense of abysmal precision in high flows. The log-sinh transformation is dominated by the simpler Pareto optimal schemes listed above. Recommendations for researchers and practitioners seeking robust residual error schemes for practical work are provided.
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Nguyen, Hung T. T.; Galelli, Stefano
2018-03-01
Catchment dynamics is not often modeled in streamflow reconstruction studies; yet, the streamflow generation process depends on both catchment state and climatic inputs. To explicitly account for this interaction, we contribute a linear dynamic model, in which streamflow is a function of both catchment state (i.e., wet/dry) and paleoclimatic proxies. The model is learned using a novel variant of the Expectation-Maximization algorithm, and it is used with a paleo drought record—the Monsoon Asia Drought Atlas—to reconstruct 406 years of streamflow for the Ping River (northern Thailand). Results for the instrumental period show that the dynamic model has higher accuracy than conventional linear regression; all performance scores improve by 45-497%. Furthermore, the reconstructed trajectory of the state variable provides valuable insights about the catchment history—e.g., regime-like behavior—thereby complementing the information contained in the reconstructed streamflow time series. The proposed technique can replace linear regression, since it only requires information on streamflow and climatic proxies (e.g., tree-rings, drought indices); furthermore, it is capable of readily generating stochastic streamflow replicates. With a marginal increase in computational requirements, the dynamic model brings more desirable features and value to streamflow reconstructions.
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Piniewski, Mikołaj
2016-05-01
The objective of this study was to apply a previously developed large-scale and high-resolution SWAT model of the Vistula and the Odra basins, calibrated with the focus of natural flow simulation, in order to assess the impact of three different dam reservoirs on streamflow using the Indicators of Hydrologic Alteration (IHA). A tailored spatial calibration approach was designed, in which calibration was focused on a large set of relatively small non-nested sub-catchments with semi-natural flow regime. These were classified into calibration clusters based on the flow statistics similarity. After performing calibration and validation that gave overall positive results, the calibrated parameter values were transferred to the remaining part of the basins using an approach based on hydrological similarity of donor and target catchments. The calibrated model was applied in three case studies with the purpose of assessing the effect of dam reservoirs (Włocławek, Siemianówka and Czorsztyn Reservoirs) on streamflow alteration. Both the assessment based on gauged streamflow (Before-After design) and the one based on simulated natural streamflow showed large alterations in selected flow statistics related to magnitude, duration, high and low flow pulses and rate of change. Some benefits of using a large-scale and high-resolution hydrological model for the assessment of streamflow alteration include: (1) providing an alternative or complementary approach to the classical Before-After designs, (2) isolating the climate variability effect from the dam (or any other source of alteration) effect, (3) providing a practical tool that can be applied at a range of spatial scales over large area such as a country, in a uniform way. Thus, presented approach can be applied for designing more natural flow regimes, which is crucial for river and floodplain ecosystem restoration in the context of the European Union's policy on environmental flows.
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Directory of Open Access Journals (Sweden)
M. Piniewski
2016-05-01
Full Text Available The objective of this study was to apply a previously developed large-scale and high-resolution SWAT model of the Vistula and the Odra basins, calibrated with the focus of natural flow simulation, in order to assess the impact of three different dam reservoirs on streamflow using the Indicators of Hydrologic Alteration (IHA. A tailored spatial calibration approach was designed, in which calibration was focused on a large set of relatively small non-nested sub-catchments with semi-natural flow regime. These were classified into calibration clusters based on the flow statistics similarity. After performing calibration and validation that gave overall positive results, the calibrated parameter values were transferred to the remaining part of the basins using an approach based on hydrological similarity of donor and target catchments. The calibrated model was applied in three case studies with the purpose of assessing the effect of dam reservoirs (Włocławek, Siemianówka and Czorsztyn Reservoirs on streamflow alteration. Both the assessment based on gauged streamflow (Before-After design and the one based on simulated natural streamflow showed large alterations in selected flow statistics related to magnitude, duration, high and low flow pulses and rate of change. Some benefits of using a large-scale and high-resolution hydrological model for the assessment of streamflow alteration include: (1 providing an alternative or complementary approach to the classical Before-After designs, (2 isolating the climate variability effect from the dam (or any other source of alteration effect, (3 providing a practical tool that can be applied at a range of spatial scales over large area such as a country, in a uniform way. Thus, presented approach can be applied for designing more natural flow regimes, which is crucial for river and floodplain ecosystem restoration in the context of the European Union's policy on environmental flows.
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Santini, M.; Caporaso, L.
2017-12-01
Although the importance of water resources in the context of climate change, it is still difficult to correctly simulate the freshwater cycle over the land via General Circulation and Earth System Models (GCMs and ESMs). Existing efforts from the Climate Model Intercomparison Project 5 (CMIP5) were mainly devoted to the validation of atmospheric variables like temperature and precipitation, with low attention to discharge.Here we investigate the present-day performances of GCMs and ESMs participating to CMIP5 in simulating the discharge of the river Congo to the sea thanks to: i) the long-term availability of discharge data for the Kinshasa hydrological station representative of more than 95% of the water flowing in the whole catchment; and ii) the River's still low influence by human intervention, which enables comparison with the (mostly) natural streamflow simulated within CMIP5.Our findings suggest how most of models appear overestimating the streamflow in terms of seasonal cycle, especially in the late winter and spring, while overestimation and variability across models are lower in late summer. Weighted ensemble means are also calculated, based on simulations' performances given by several metrics, showing some improvements of results.Although simulated inter-monthly and inter-annual percent anomalies do not appear significantly different from those in observed data, when translated into well consolidated indicators of drought attributes (frequency, magnitude, timing, duration), usually adopted for more immediate communication to stakeholders and decision makers, such anomalies can be misleading.These inconsistencies produce incorrect assessments towards water management planning and infrastructures (e.g. dams or irrigated areas), especially if models are used instead of measurements, as in case of ungauged basins or for basins with insufficient data, as well as when relying on models for future estimates without a preliminary quantification of model biases.
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Directory of Open Access Journals (Sweden)
Fanping Zhang
2014-01-01
Full Text Available Streamflow forecasting has an important role in water resource management and reservoir operation. Support vector machine (SVM is an appropriate and suitable method for streamflow prediction due to its best versatility, robustness, and effectiveness. In this study, a wavelet transform particle swarm optimization support vector machine (WT-PSO-SVM model is proposed and applied for streamflow time series prediction. Firstly, the streamflow time series were decomposed into various details (Ds and an approximation (A3 at three resolution levels (21-22-23 using Daubechies (db3 discrete wavelet. Correlation coefficients between each D subtime series and original monthly streamflow time series are calculated. Ds components with high correlation coefficients (D3 are added to the approximation (A3 as the input values of the SVM model. Secondly, the PSO is employed to select the optimal parameters, C, ε, and σ, of the SVM model. Finally, the WT-PSO-SVM models are trained and tested by the monthly streamflow time series of Tangnaihai Station located in Yellow River upper stream from January 1956 to December 2008. The test results indicate that the WT-PSO-SVM approach provide a superior alternative to the single SVM model for forecasting monthly streamflow in situations without formulating models for internal structure of the watershed.
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Groundwater Pumping and Streamflow in the Yuba Basin, Sacramento Valley, California
Moss, D. R.; Fogg, G. E.; Wallender, W. W.
2011-12-01
Water transfers during drought in California's Sacramento Valley can lead to increased groundwater pumping, and as yet unknown effects on stream baseflow. Two existing groundwater models of the greater Sacramento Valley together with localized, monitoring of groundwater level fluctuations adjacent to the Bear, Feather, and Yuba Rivers, indicate cause and effect relations between the pumping and streamflow. The models are the Central Valley Hydrologic Model (CVHM) developed by the U.S. Geological Survey and C2VSIM developed by Department of Water Resources. Using two models which have similar complexity and data but differing approaches to the agricultural water boundary condition illuminates both the water budget and its uncertainty. Water budget and flux data for localized areas can be obtained from the models allowing for parameters such as precipitation, irrigation recharge, and streamflow to be compared to pumping on different temporal scales. Continuous groundwater level measurements at nested, near-stream piezometers show seasonal variations in streamflow and groundwater levels as well as the timing and magnitude of recharge and pumping. Preliminary results indicate that during years with relatively wet conditions 65 - 70% of the surface recharge for the groundwater system comes from irrigation and precipitation and 30 - 35% comes from streamflow losses. The models further indicate that during years with relatively dry conditions, 55 - 60% of the surface recharge for the groundwater system comes from irrigation and precipitation while 40 - 45% comes from streamflow losses. The models irrigation water demand, surface-water and groundwater supply, and deep percolation are integrated producing values for irrigation pumping. Groundwater extractions during the growing season, approximately between April and October, increase by almost 200%. The effects of increased pumping seasonally are not readily evident in stream stage measurements. However, during dry time
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Monthly streamflow forecasting with auto-regressive integrated moving average
Nasir, Najah; Samsudin, Ruhaidah; Shabri, Ani
2017-09-01
Forecasting of streamflow is one of the many ways that can contribute to better decision making for water resource management. The auto-regressive integrated moving average (ARIMA) model was selected in this research for monthly streamflow forecasting with enhancement made by pre-processing the data using singular spectrum analysis (SSA). This study also proposed an extension of the SSA technique to include a step where clustering was performed on the eigenvector pairs before reconstruction of the time series. The monthly streamflow data of Sungai Muda at Jeniang, Sungai Muda at Jambatan Syed Omar and Sungai Ketil at Kuala Pegang was gathered from the Department of Irrigation and Drainage Malaysia. A ratio of 9:1 was used to divide the data into training and testing sets. The ARIMA, SSA-ARIMA and Clustered SSA-ARIMA models were all developed in R software. Results from the proposed model are then compared to a conventional auto-regressive integrated moving average model using the root-mean-square error and mean absolute error values. It was found that the proposed model can outperform the conventional model.
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Understanding uncertainties in future Colorado River streamflow
Julie A. Vano,; Bradley Udall,; Cayan, Daniel; Jonathan T Overpeck,; Brekke, Levi D.; Das, Tapash; Hartmann, Holly C.; Hidalgo, Hugo G.; Hoerling, Martin P; McCabe, Gregory J.; Morino, Kiyomi; Webb, Robert S.; Werner, Kevin; Lettenmaier, Dennis P.
2014-01-01
The Colorado River is the primary water source for more than 30 million people in the United States and Mexico. Recent studies that project streamf low changes in the Colorado River all project annual declines, but the magnitude of the projected decreases range from less than 10% to 45% by the mid-twenty-first century. To understand these differences, we address the questions the management community has raised: Why is there such a wide range of projections of impacts of future climate change on Colorado River streamflow, and how should this uncertainty be interpreted? We identify four major sources of disparities among studies that arise from both methodological and model differences. In order of importance, these are differences in 1) the global climate models (GCMs) and emission scenarios used; 2) the ability of land surface and atmospheric models to simulate properly the high-elevation runoff source areas; 3) the sensitivities of land surface hydrology models to precipitation and temperature changes; and 4) the methods used to statistically downscale GCM scenarios. In accounting for these differences, there is substantial evidence across studies that future Colorado River streamflow will be reduced under the current trajectories of anthropogenic greenhouse gas emissions because of a combination of strong temperature-induced runoff curtailment and reduced annual precipitation. Reconstructions of preinstrumental streamflows provide additional insights; the greatest risk to Colorado River streamf lows is a multidecadal drought, like that observed in paleoreconstructions, exacerbated by a steady reduction in flows due to climate change. This could result in decades of sustained streamflows much lower than have been observed in the ~100 years of instrumental record.
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Lafontaine, J.; Hay, L.
2015-12-01
The United States Geological Survey (USGS) has developed a National Hydrologic Model (NHM) to support coordinated, comprehensive and consistent hydrologic model development, and facilitate the application of hydrologic simulations within the conterminous United States (CONUS). More than 1,700 gaged watersheds across the CONUS were modeled to test the feasibility of improving streamflow simulations in gaged and ungaged watersheds by linking statistically- and physically-based hydrologic models with remotely-sensed data products (i.e. - snow water equivalent) and estimates of uncertainty. Initially, the physically-based models were calibrated to measured streamflow data to provide a baseline for comparison. As many stream reaches in the CONUS are either not gaged, or are substantially impacted by water use or flow regulation, ancillary information must be used to determine reasonable parameter estimations for streamflow simulations. In addition, not all ancillary datasets are appropriate for application to all parts of the CONUS (e.g. - snow water equivalent in the southeastern U.S., where snow is a rarity). As it is not expected that any one data product or model simulation will be sufficient for representing hydrologic behavior across the entire CONUS, a systematic evaluation of which data products improve simulations of streamflow for various regions across the CONUS was performed. The resulting portfolio of calibration strategies can be used to guide selection of an appropriate combination of simulated and measured information for model development and calibration at a given location of interest. In addition, these calibration strategies have been developed to be flexible so that new data products or simulated information can be assimilated. This analysis provides a foundation to understand how well models work when streamflow data is either not available or is limited and could be used to further inform hydrologic model parameter development for ungaged areas.
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Saleh, Firas; Ramaswamy, Venkatsundar; Georgas, Nickitas; Blumberg, Alan F.; Pullen, Julie
2016-07-01
This paper investigates the uncertainties in hourly streamflow ensemble forecasts for an extreme hydrological event using a hydrological model forced with short-range ensemble weather prediction models. A state-of-the art, automated, short-term hydrologic prediction framework was implemented using GIS and a regional scale hydrological model (HEC-HMS). The hydrologic framework was applied to the Hudson River basin ( ˜ 36 000 km2) in the United States using gridded precipitation data from the National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (NARR) and was validated against streamflow observations from the United States Geologic Survey (USGS). Finally, 21 precipitation ensemble members of the latest Global Ensemble Forecast System (GEFS/R) were forced into HEC-HMS to generate a retrospective streamflow ensemble forecast for an extreme hydrological event, Hurricane Irene. The work shows that ensemble stream discharge forecasts provide improved predictions and useful information about associated uncertainties, thus improving the assessment of risks when compared with deterministic forecasts. The uncertainties in weather inputs may result in false warnings and missed river flooding events, reducing the potential to effectively mitigate flood damage. The findings demonstrate how errors in the ensemble median streamflow forecast and time of peak, as well as the ensemble spread (uncertainty) are reduced 48 h pre-event by utilizing the ensemble framework. The methodology and implications of this work benefit efforts of short-term streamflow forecasts at regional scales, notably regarding the peak timing of an extreme hydrologic event when combined with a flood threshold exceedance diagram. Although the modeling framework was implemented on the Hudson River basin, it is flexible and applicable in other parts of the world where atmospheric reanalysis products and streamflow data are available.
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In ecoregions across western USA streamflow increases during post-wildfire recovery
Wine, Michael L.; Cadol, Daniel; Makhnin, Oleg
2018-01-01
Continued growth of the human population on Earth will increase pressure on already stressed terrestrial water resources required for drinking water, agriculture, and industry. This stress demands improved understanding of critical controls on water resource availability, particularly in water-limited regions. Mechanistic predictions of future water resource availability are needed because non-stationary conditions exist in the form of changing climatic conditions, land management paradigms, and ecological disturbance regimes. While historically ecological disturbances have been small and could be neglected relative to climatic effects, evidence is accumulating that ecological disturbances, particularly wildfire, can increase regional water availability. However, wildfire hydrologic impacts are typically estimated locally and at small spatial scales, via disparate measurement methods and analysis techniques, and outside the context of climate change projections. Consequently, the relative importance of climate change driven versus wildfire driven impacts on streamflow remains unknown across the western USA. Here we show that considering wildfire in modeling streamflow significantly improves model predictions. Mixed effects modeling attributed 2%-14% of long-term annual streamflow to wildfire effects. The importance of this wildfire-linked streamflow relative to predicted climate change-induced streamflow reductions ranged from 20%-370% of the streamflow decrease predicted to occur by 2050. The rate of post-wildfire vegetation recovery and the proportion of watershed area burned controlled the wildfire effect. Our results demonstrate that in large areas of the western USA affected by wildfire, regional predictions of future water availability are subject to greater structural uncertainty than previously thought. These results suggest that future streamflows may be underestimated in areas affected by increased prevalence of hydrologically relevant ecological
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River Stream-Flow and Zayanderoud Reservoir Operation Modeling Using the Fuzzy Inference System
Directory of Open Access Journals (Sweden)
Saeed Jamali
2007-12-01
Full Text Available The Zayanderoud basin is located in the central plateau of Iran. As a result of population increase and agricultural and industrial developments, water demand on this basin has increased extensively. Given the importance of reservoir operation in water resource and management studies, the performance of fuzzy inference system (FIS for Zayanderoud reservoir operation is investigated in this paper. The model of operation consists of two parts. In the first part, the seasonal river stream-flow is forecasted using the fuzzy rule-based system. The southern oscillated index, rain, snow, and discharge are inputs of the model and the seasonal river stream-flow its output. In the second part, the operation model is constructed. The amount of releases is first optimized by a nonlinear optimization model and then the rule curves are extracted using the fuzzy inference system. This model operates on an "if-then" principle, where the "if" is a vector of fuzzy permits and "then" is the fuzzy result. The reservoir storage capacity, inflow, demand, and year condition factor are used as permits. Monthly release is taken as the consequence. The Zayanderoud basin is investigated as a case study. Different performance indices such as reliability, resiliency, and vulnerability are calculated. According to results, FIS works more effectively than the traditional reservoir operation methods such as standard operation policy (SOP or linear regression.
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Geologic and climatic controls on streamflow generation processes in a complex eogenetic karst basin
Vibhava, F.; Graham, W. D.; Maxwell, R. M.
2012-12-01
Streamflow at any given location and time is representative of surface and subsurface contributions from various sources. The ability to fully identify the factors controlling these contributions is key to successfully understanding the transport of contaminants through the system. In this study we developed a fully integrated 3D surface water-groundwater-land surface model, PARFLOW, to evaluate geologic and climatic controls on streamflow generation processes in a complex eogenetic karst basin in North Central Florida. In addition to traditional model evaluation criterion, such as comparing field observations to model simulated streamflow and groundwater elevations, we quantitatively evaluated the model's predictions of surface-groundwater interactions over space and time using a suite of binary end-member mixing models that were developed using observed specific conductivity differences among surface and groundwater sources throughout the domain. Analysis of model predictions showed that geologic heterogeneity exerts a strong control on both streamflow generation processes and land atmospheric fluxes in this watershed. In the upper basin, where the karst aquifer is overlain by a thick confining layer, approximately 92% of streamflow is "young" event flow, produced by near stream rainfall. Throughout the upper basin the confining layer produces a persistent high surficial water table which results in high evapotranspiration, low groundwater recharge and thus negligible "inter-event" streamflow. In the lower basin, where the karst aquifer is unconfined, deeper water tables result in less evapotranspiration. Thus, over 80% of the streamflow is "old" subsurface flow produced by diffuse infiltration through the epikarst throughout the lower basin, and all surface contributions to streamflow originate in the upper confined basin. Climatic variability provides a secondary control on surface-subsurface and land-atmosphere fluxes, producing significant seasonal and
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KIM, J.; Smith, M. B.; Koren, V.; Salas, F.; Cui, Z.; Johnson, D.
2017-12-01
The National Oceanic and Atmospheric Administration (NOAA)-National Weather Service (NWS) developed the Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM) framework as an initial step towards spatially distributed modeling at River Forecast Centers (RFCs). Recently, the NOAA/NWS worked with the National Center for Atmospheric Research (NCAR) to implement the National Water Model (NWM) for nationally-consistent water resources prediction. The NWM is based on the WRF-Hydro framework and is run at a 1km spatial resolution and 1-hour time step over the contiguous United States (CONUS) and contributing areas in Canada and Mexico. In this study, we compare streamflow simulations from HL-RDHM and WRF-Hydro to observations from 279 USGS stations. For streamflow simulations, HL-RDHM is run on 4km grids with the temporal resolution of 1 hour for a 5-year period (Water Years 2008-2012), using a priori parameters provided by NOAA-NWS. The WRF-Hydro streamflow simulations for the same time period are extracted from NCAR's 23 retrospective run of the NWM (version 1.0) over CONUS based on 1km grids. We choose 279 USGS stations which are relatively less affected by dams or reservoirs, in the domains of six different RFCs. We use the daily average values of simulations and observations for the convenience of comparison. The main purpose of this research is to evaluate how HL-RDHM and WRF-Hydro perform at USGS gauge stations. We compare daily time-series of observations and both simulations, and calculate the error values using a variety of error functions. Using these plots and error values, we evaluate the performances of HL-RDHM and WRF-Hydro models. Our results show a mix of model performance across geographic regions.
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Hess, Glen W.; Stonewall, Adam J.
2014-01-01
In 2013, the Upper Klamath Lake Basin, Oregon, experienced a dry spring, resulting in an executive order declaring a state of drought emergency in Klamath County. The 2013 drought limited the water supply and led to a near-total cessation of surface-water diversions for irrigation above Upper Klamath Lake once regulation was implemented. These conditions presented a unique opportunity to understand the effects of water right regulation on streamflows. The effects of regulation of diversions were evaluated by comparing measured 2013 streamflow with data from hydrologically similar years. Years with spring streamflow similar to that in 2013 measured at the Sprague River gage at Chiloquin from water years 1973 to 2012 were used to define a Composite Index Year (CIY; with diversions) for comparison to measured 2013 streamflows (no diversions). The best-fit 6 years (1977, 1981, 1990, 1991, 1994, and 2001) were used to determine the CIY. Two streams account for most of the streamflow into Upper Klamath Lake: the Williamson and Wood Rivers. Most streamflow into the lake is from the Williamson River Basin, which includes the Sprague River. Because most of the diversion regulation affecting the streamflow of the Williamson River occurred in the Sprague River Basin, and because of uncertainties about historical flows in a major diversion above the Williamson River gage, streamflow data from the Sprague River were used to estimate the change in streamflow from regulation of diversions for the Williamson River Basin. Changes in streamflow outside of the Sprague River Basin were likely minor relative to total streamflow. The effect of diversion regulation was evaluated using the “Baseflow Method,” which compared 2013 baseflow to baseflow of the CIY. The Baseflow Method reduces the potential effects of summer precipitation events on the calculations. A similar method using streamflow produced similar results, however, despite at least one summer precipitation event. The
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Multi-site Stochastic Simulation of Daily Streamflow with Markov Chain and KNN Algorithm
Mathai, J.; Mujumdar, P.
2017-12-01
A key focus of this study is to develop a method which is physically consistent with the hydrologic processes that can capture short-term characteristics of daily hydrograph as well as the correlation of streamflow in temporal and spatial domains. In complex water resource systems, flow fluctuations at small time intervals require that discretisation be done at small time scales such as daily scales. Also, simultaneous generation of synthetic flows at different sites in the same basin are required. We propose a method to equip water managers with a streamflow generator within a stochastic streamflow simulation framework. The motivation for the proposed method is to generate sequences that extend beyond the variability represented in the historical record of streamflow time series. The method has two steps: In step 1, daily flow is generated independently at each station by a two-state Markov chain, with rising limb increments randomly sampled from a Gamma distribution and the falling limb modelled as exponential recession and in step 2, the streamflow generated in step 1 is input to a nonparametric K-nearest neighbor (KNN) time series bootstrap resampler. The KNN model, being data driven, does not require assumptions on the dependence structure of the time series. A major limitation of KNN based streamflow generators is that they do not produce new values, but merely reshuffle the historical data to generate realistic streamflow sequences. However, daily flow generated using the Markov chain approach is capable of generating a rich variety of streamflow sequences. Furthermore, the rising and falling limbs of daily hydrograph represent different physical processes, and hence they need to be modelled individually. Thus, our method combines the strengths of the two approaches. We show the utility of the method and improvement over the traditional KNN by simulating daily streamflow sequences at 7 locations in the Godavari River basin in India.
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Climate change streamflow scenarios designed for critical period water resources planning studies
Hamlet, A. F.; Snover, A. K.; Lettenmaier, D. P.
2003-04-01
Long-range water planning in the United States is usually conducted by individual water management agencies using a critical period planning exercise based on a particular period of the observed streamflow record and a suite of internally-developed simulation tools representing the water system. In the context of planning for climate change, such an approach is flawed in that it assumes that the future climate will be like the historic record. Although more sophisticated planning methods will probably be required as time goes on, a short term strategy for incorporating climate uncertainty into long-range water planning as soon as possible is to create alternate inputs to existing planning methods that account for climate uncertainty as it affects both supply and demand. We describe a straight-forward technique for constructing streamflow scenarios based on the historic record that include the broad-based effects of changed regional climate simulated by several global climate models (GCMs). The streamflow scenarios are based on hydrologic simulations driven by historic climate data perturbed according to regional climate signals from four GCMs using the simple "delta" method. Further data processing then removes systematic hydrologic model bias using a quantile-based bias correction scheme, and lastly, the effects of random errors in the raw hydrologic simulations are removed. These techniques produce streamflow scenarios that are consistent in time and space with the historic streamflow record while incorporating fundamental changes in temperature and precipitation from the GCM scenarios. Planning model simulations based on these climate change streamflow scenarios can therefore be compared directly to planning model simulations based on the historic record of streamflows to help planners understand the potential impacts of climate uncertainty. The methods are currently being tested and refined in two large-scale planning exercises currently being conducted in the
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Streamflow response to increasing precipitation extremes altered by forest management
Charlene N. Kelly; Kevin J. McGuire; Chelcy Ford Miniat; James M. Vose
2016-01-01
Increases in extreme precipitation events of floods and droughts are expected to occur worldwide. The increase in extreme events will result in changes in streamflow that are expected to affect water availability for human consumption and aquatic ecosystem function. We present an analysis that may greatly improve current streamflow models by quantifying the...
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Lin, Tzu Ping; Lin, Yu Pin; Lien, Wan Yu
2015-04-01
Climate change projects have various levels of impacts on hydrological cycles around the world. The impact of climate change and uncertainty of climate projections from general circulation models (GCMs) from the Coupled Model Intercomparison Project (CMIP5) which has been just be released in Taiwan, 2014. Since the streamflow run into ocean directly due to the steep terrain and the rainfall difference between wet and dry seasons is apparent; as a result, the allocation water resource reasonable is very challenge in Taiwan, particularly under climate change. The purpose of this study was to evaluate the impacts of climate and land use changes on a small watershed in Taiwan. The AR5 General Circulation Models(GCM) output data was adopted in this study and was downscaled from the monthly to the daily weather data as the input data of hydrological model such as Soil and Water Assessment Tool (SWAT) model in this study. The spatially explicit land uses change model, the Conservation of Land Use and its Effects at Small regional extent (CLUE-s), was applied to simulate land use scenarios in 2020-2039. Combined climate and land use change scenarios were adopted as input data of the hydrological model, the SWAT model, to estimate the future streamflows. With the increasing precipitation, increasing urban area and decreasing agricultural and grass land, the annual streamflow in the most of twenty-three subbasins were also increased. Besides, due to the increasing rainfall in wet season and decreasing rainfall in dry season, the difference of streamflow between wet season and dry season are also increased. This result indicates a more stringent challenge on the water resource management in future. Therefore, impacts on water resource caused by climate change and land use change should be considered in water resource planning for the Datuan river watershed. Keywords: SWAT, GCM, CLUE-s, streamflow, climate change, land use change
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Hadi, Sinan Jasim; Tombul, Mustafa
2018-06-01
Streamflow is an essential component of the hydrologic cycle in the regional and global scale and the main source of fresh water supply. It is highly associated with natural disasters, such as droughts and floods. Therefore, accurate streamflow forecasting is essential. Forecasting streamflow in general and monthly streamflow in particular is a complex process that cannot be handled by data-driven models (DDMs) only and requires pre-processing. Wavelet transformation is a pre-processing technique; however, application of continuous wavelet transformation (CWT) produces many scales that cause deterioration in the performance of any DDM because of the high number of redundant variables. This study proposes multigene genetic programming (MGGP) as a selection tool. After the CWT analysis, it selects important scales to be imposed into the artificial neural network (ANN). A basin located in the southeast of Turkey is selected as case study to prove the forecasting ability of the proposed model. One month ahead downstream flow is used as output, and downstream flow, upstream, rainfall, temperature, and potential evapotranspiration with associated lags are used as inputs. Before modeling, wavelet coherence transformation (WCT) analysis was conducted to analyze the relationship between variables in the time-frequency domain. Several combinations were developed to investigate the effect of the variables on streamflow forecasting. The results indicated a high localized correlation between the streamflow and other variables, especially the upstream. In the models of the standalone layout where the data were entered to ANN and MGGP without CWT, the performance is found poor. In the best-scale layout, where the best scale of the CWT identified as the highest correlated scale is chosen and enters to ANN and MGGP, the performance increased slightly. Using the proposed model, the performance improved dramatically particularly in forecasting the peak values because of the inclusion
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Gudmundsson, Lukas; Do, Hong Xuan; Leonard, Michael; Westra, Seth
2018-04-01
This is Part 2 of a two-paper series presenting the Global Streamflow Indices and Metadata Archive (GSIM), which is a collection of daily streamflow observations at more than 30 000 stations around the world. While Part 1 (Do et al., 2018a) describes the data collection process as well as the generation of auxiliary catchment data (e.g. catchment boundary, land cover, mean climate), Part 2 introduces a set of quality controlled time-series indices representing (i) the water balance, (ii) the seasonal cycle, (iii) low flows and (iv) floods. To this end we first consider the quality of individual daily records using a combination of quality flags from data providers and automated screening methods. Subsequently, streamflow time-series indices are computed for yearly, seasonal and monthly resolution. The paper provides a generalized assessment of the homogeneity of all generated streamflow time-series indices, which can be used to select time series that are suitable for a specific task. The newly generated global set of streamflow time-series indices is made freely available with an digital object identifier at https://doi.pangaea.de/10.1594/PANGAEA.887470" target="_blank">https://doi.pangaea.de/10.1594/PANGAEA.887470 and is expected to foster global freshwater research, by acting as a ground truth for model validation or as a basis for assessing the role of human impacts on the terrestrial water cycle. It is hoped that a renewed interest in streamflow data at the global scale will foster efforts in the systematic assessment of data quality and provide momentum to overcome administrative barriers that lead to inconsistencies in global collections of relevant hydrological observations.
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Jeannotte, T.; Mahmood, T. H.; Matheney, R.; Hou, X.
2017-12-01
Nutrient export to streams and lakes by anthropogenic activities can lead to eutrophication and degradation of surface water quality. In Devils Lake, ND, the only terminal lake in the Northern Great Plains, the algae boom is of great concern due to the recent increase in streamflow and consequent rise in phosphorus (P) export from prairie agricultural fields. However, to date, very few studies explored the concentration (c) -streamflow (q) relationship in the headwater catchments of the Devils Lake basin. A robust watershed-scale quantitative framework would aid understanding of the c-q relationship, simulating P concentration and load. In this study, we utilize c-q relationships to develop a simple model to estimate phosphorus concentration and export from two headwater catchments of different size (Mauvais Coulee: 1032 km2 and Trib 3: 160 km2) draining to Devils Lake. Our goal is to link the phosphorus export model with a physically based hydrologic model to identify major drivers of phosphorus export. USGS provided the streamflow measurements, and we collected water samples (filtered and unfiltered) three times daily during the spring snowmelt season (March 31, 2017- April 12, 2017) at the outlets of both headwater catchments. Our results indicate that most P is dissolved and very little is particulate, suggesting little export of fine-grained sediment from agricultural fields. Our preliminary analyses in the Mauvais Coulee catchment show a chemostatic c-q relationship in the rising limb of the hydrograph, while the recession limb shows a linear and positive c-q relationship. The poor correlation in the rising limb of the hydrograph suggests intense flushing of P by spring snowmelt runoff. Flushing then continues in the recession limb of the hydrograph, but at a more constant rate. The estimated total P load for the Mauvais Coulee basin is 193 kg/km2, consistent with other catchments of similar size across the Red River of the North basin to the east. We expect
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Henn, Brian; Clark, Martyn P.; Kavetski, Dmitri; Newman, Andrew J.; Hughes, Mimi; McGurk, Bruce; Lundquist, Jessica D.
2018-01-01
Given uncertainty in precipitation gauge-based gridded datasets over complex terrain, we use multiple streamflow observations as an additional source of information about precipitation, in order to identify spatial and temporal differences between a gridded precipitation dataset and precipitation inferred from streamflow. We test whether gridded datasets capture across-crest and regional spatial patterns of variability, as well as year-to-year variability and trends in precipitation, in comparison to precipitation inferred from streamflow. We use a Bayesian model calibration routine with multiple lumped hydrologic model structures to infer the most likely basin-mean, water-year total precipitation for 56 basins with long-term (>30 year) streamflow records in the Sierra Nevada mountain range of California. We compare basin-mean precipitation derived from this approach with basin-mean precipitation from a precipitation gauge-based, 1/16° gridded dataset that has been used to simulate and evaluate trends in Western United States streamflow and snowpack over the 20th century. We find that the long-term average spatial patterns differ: in particular, there is less precipitation in the gridded dataset in higher-elevation basins whose aspect faces prevailing cool-season winds, as compared to precipitation inferred from streamflow. In a few years and basins, there is less gridded precipitation than there is observed streamflow. Lower-elevation, southern, and east-of-crest basins show better agreement between gridded and inferred precipitation. Implied actual evapotranspiration (calculated as precipitation minus streamflow) then also varies between the streamflow-based estimates and the gridded dataset. Absolute uncertainty in precipitation inferred from streamflow is substantial, but the signal of basin-to-basin and year-to-year differences are likely more robust. The findings suggest that considering streamflow when spatially distributing precipitation in complex terrain
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Directory of Open Access Journals (Sweden)
Jianzhong Zhou
2018-05-01
Full Text Available This paper introduces three artificial neural network (ANN architectures for monthly streamflow forecasting: a radial basis function network, an extreme learning machine, and the Elman network. Three ensemble techniques, a simple average ensemble, a weighted average ensemble, and an ANN-based ensemble, were used to combine the outputs of the individual ANN models. The objective was to highlight the performance of the general regression neural network-based ensemble technique (GNE through an improvement of monthly streamflow forecasting accuracy. Before the construction of an ANN model, data preanalysis techniques, such as empirical wavelet transform (EWT, were exploited to eliminate the oscillations of the streamflow series. Additionally, a theory of chaos phase space reconstruction was used to select the most relevant and important input variables for forecasting. The proposed GNE ensemble model has been applied for the mean monthly streamflow observation data from the Wudongde hydrological station in the Jinsha River Basin, China. Comparisons and analysis of this study have demonstrated that the denoised streamflow time series was less disordered and unsystematic than was suggested by the original time series according to chaos theory. Thus, EWT can be adopted as an effective data preanalysis technique for the prediction of monthly streamflow. Concurrently, the GNE performed better when compared with other ensemble techniques.
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Devendra Amatya; M. Jha; A.E. Edwards; T.M. Williams; D.R. Hitchcock
2011-01-01
SWAT is a GIS-based basin-scale model widely used for the characterization of hydrology and water quality of large, complex watersheds; however, SWAT has not been fully tested in watersheds with karst geomorphology and downstream reservoir-like embayment. In this study, SWAT was applied to test its ability to predict monthly streamflow dynamics for a 1,555 ha karst...
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Energy Technology Data Exchange (ETDEWEB)
A.G. Crook Company
1993-04-01
The development of irrigation projects since the 1830's and the construction of major dams and reservoirs since the early 1900's have altered substantially the natural streamflow regimen of the Columbia River and its tributaries. As development expanded a multipurpose approach to streamflow regulation evolved to provide flood control, irrigation, hydropower generation, navigation, recreation, water quality enhancement, fish and wildlife, and instream flow maintenance. The responsible agencies use computer programs to determine the effects of various alternative system regulations. This report describes the development of the streamflow data that these computer programs use.
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Directory of Open Access Journals (Sweden)
L. Gudmundsson
2018-04-01
Full Text Available This is Part 2 of a two-paper series presenting the Global Streamflow Indices and Metadata Archive (GSIM, which is a collection of daily streamflow observations at more than 30 000 stations around the world. While Part 1 (Do et al., 2018a describes the data collection process as well as the generation of auxiliary catchment data (e.g. catchment boundary, land cover, mean climate, Part 2 introduces a set of quality controlled time-series indices representing (i the water balance, (ii the seasonal cycle, (iii low flows and (iv floods. To this end we first consider the quality of individual daily records using a combination of quality flags from data providers and automated screening methods. Subsequently, streamflow time-series indices are computed for yearly, seasonal and monthly resolution. The paper provides a generalized assessment of the homogeneity of all generated streamflow time-series indices, which can be used to select time series that are suitable for a specific task. The newly generated global set of streamflow time-series indices is made freely available with an digital object identifier at https://doi.pangaea.de/10.1594/PANGAEA.887470 and is expected to foster global freshwater research, by acting as a ground truth for model validation or as a basis for assessing the role of human impacts on the terrestrial water cycle. It is hoped that a renewed interest in streamflow data at the global scale will foster efforts in the systematic assessment of data quality and provide momentum to overcome administrative barriers that lead to inconsistencies in global collections of relevant hydrological observations.
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Directory of Open Access Journals (Sweden)
Nkululeko Simeon Dlamini
2017-03-01
Full Text Available Potential impacts of climate change on the streamflow of the Bernam River Basin in Malaysia are assessed using ten Global Climate Models (GCMs under three Representative Concentration Pathways (RCP4.5, RCP6.0 and RCP8.5. A graphical user interface was developed that integrates all of the common procedures of assessing climate change impacts, to generate high resolution climate variables (e.g., rainfall, temperature, etc. at the local scale from large-scale climate models. These are linked in one executable module to generate future climate sequences that can be used as inputs to various models, including hydrological and crop models. The generated outputs were used as inputs to the SWAT hydrological model to simulate the hydrological processes. The evaluation results indicated that the model performed well for the watershed with a monthly R2, Nash–Sutcliffe Efficiency (NSE and Percent Bias (PBIAS values of 0.67, 0.62 and −9.4 and 0.62, 0.61 and −4.2 for the calibration and validation periods, respectively. The multi-model projections show an increase in future temperature (tmax and tmin in all respective scenarios, up to an average of 2.5 °C for under the worst-case scenario (RC8.5. Rainfall is also predicted to change with clear variations between the dry and wet season. Streamflow projections also followed rainfall pattern to a great extent with a distinct change between the dry and wet season possibly due to the increase in evapotranspiration in the watershed. In principle, the interface can be customized for the application to other watersheds by incorporating GCMs’ baseline data and their corresponding future data for those particular stations in the new watershed. Methodological limitations of the study are also discussed.
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On the probability distribution of daily streamflow in the United States
Blum, Annalise G.; Archfield, Stacey A.; Vogel, Richard M.
2017-06-01
Daily streamflows are often represented by flow duration curves (FDCs), which illustrate the frequency with which flows are equaled or exceeded. FDCs have had broad applications across both operational and research hydrology for decades; however, modeling FDCs has proven elusive. Daily streamflow is a complex time series with flow values ranging over many orders of magnitude. The identification of a probability distribution that can approximate daily streamflow would improve understanding of the behavior of daily flows and the ability to estimate FDCs at ungaged river locations. Comparisons of modeled and empirical FDCs at nearly 400 unregulated, perennial streams illustrate that the four-parameter kappa distribution provides a very good representation of daily streamflow across the majority of physiographic regions in the conterminous United States (US). Further, for some regions of the US, the three-parameter generalized Pareto and lognormal distributions also provide a good approximation to FDCs. Similar results are found for the period of record FDCs, representing the long-term hydrologic regime at a site, and median annual FDCs, representing the behavior of flows in a typical year.
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Seasonal Prediction of Taiwan's Streamflow Using Teleconnection Patterns
Chen, Chia-Jeng; Lee, Tsung-Yu
2017-04-01
Seasonal streamflow as an integrated response to complex hydro-climatic processes can be subject to activity of prevailing weather systems potentially modulated by large-scale climate oscillations (e.g., El Niño-Southern Oscillation, ENSO). To develop a seamless seasonal forecasting system in Taiwan, this study assesses how significant Taiwan's precipitation and streamflow in different seasons correlate with selected teleconnection patterns. Long-term precipitation and streamflow data in three major precipitation seasons, namely the spring rains (February to April), Mei-Yu (May and June), and typhoon (July to September) seasons, are derived at 28 upstream and 13 downstream catchments in Taiwan. The three seasons depict a complete wet period of Taiwan as well as many regions bearing similar climatic conditions in East Asia. Lagged correlation analysis is then performed to investigate how the precipitation and streamflow data correlate with predominant teleconnection indices at varied lead times. Teleconnection indices are selected only if they show certain linkage with weather systems and activity in the three seasons based on previous literature. For instance, the ENSO and Quasi-Biennial Oscillation, proven to influence East Asian climate across seasons and summer typhoon activity, respectively, are included in the list of climate indices for correlation analysis. Significant correlations found between Taiwan's precipitation and streamflow and teleconnection indices are further examined by a climate regime shift (CRS) test to identify any abrupt changes in the correlations. The understanding of existing CRS is useful for informing the forecasting system of the changes in the predictor-predictand relationship. To evaluate prediction skill in the three seasons and skill differences between precipitation and streamflow, hindcasting experiments of precipitation and streamflow are conducted using stepwise linear regression models. Discussion and suggestions for coping
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Cotterman, K. A.; Follum, M. L.; Pradhan, N. R.; Niemann, J. D.
2017-12-01
Flooding impacts numerous aspects of society, from localized flash floods to continental-scale flood events. Many numerical flood models focus solely on riverine flooding, with some capable of capturing both localized and continental-scale flood events. However, these models neglect flooding away from channels that are related to excessive ponding, typically found in areas with flat terrain and poorly draining soils. In order to obtain a holistic view of flooding, we combine flood results from the Streamflow Prediction Tool (SPT), a riverine flood model, with soil moisture downscaling techniques to determine if a better representation of flooding is obtained. This allows for a more holistic understanding of potential flood prone areas, increasing the opportunity for more accurate warnings and evacuations during flooding conditions. Thirty-five years of near-global historical streamflow is reconstructed with continental-scale flow routing of runoff from global land surface models. Elevation data was also obtained worldwide, to establish a relationship between topographic attributes and soil moisture patterns. Derived soil moisture data is validated against observed soil moisture, increasing confidence in the ability to accurately capture soil moisture patterns. Potential flooding situations can be examined worldwide, with this study focusing on the United States, Central America, and the Philippines.
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Rainier Mesa CAU Infiltration Model using INFILv3
Energy Technology Data Exchange (ETDEWEB)
Levitt, Daniel G. [Los Alamos National Laboratory; Kwicklis, Edward M. [Los Alamos National Laboratory
2012-07-13
The outline of this presentation are: (1) Model Inputs - DEM, Precipitation, Air temp, Soil props, Surface geology, Vegetation; (2) Model Pre-processing - Runoff Routing and sinks, Slope and Azimuth, Soil Ksat reduction with slope (to mitigate bathtub ring), Soil-Bedrock Interface permeabilities; (3) Model Calibration - ET using PEST, Chloride mass balance data, Streamflow using PEST; (4) Model Validation - Streamflow data not used for calibration; (5) Uncertainty Analysis; and (6) Results. Conclusions are: (1) Average annual infiltration rates =11 to 18 mm/year for RM domain; (2) Average annual infiltration rates = 7 to 11 mm/year for SM domain; (3) ET = 70% of precipitation for both domains; (4) Runoff = 8-9% for RM; and 22-24% for SM - Apparently high average runoff is caused by the truncation of the lowerelevation portions of watersheds where much of the infiltration of runoff waters would otherwise occur; (5) Model results are calibrated to measured ET, CMB data, and streamflow observations; (6) Model results are validated using streamflow observations discovered after model calibration was complete; (7) Use of soil Ksat reduction with slope to mitigate bathtub ring was successful (based on calibration results); and (8) Soil-bedrock K{_}interface is innovative approach.
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McCarthy, Peter M.
2016-04-05
Chapter E of this Scientific Investigations Report documents results from a study by the U.S. Geological Survey, in cooperation with the Montana Department of Environmental Quality and the Montana Department of Natural Resources and Conservation, to provide an update of statewide streamflow characteristics based on data through water year 2009 for streamflow-gaging stations in or near Montana. Streamflow characteristics are presented for 408 streamflow-gaging stations in Montana and adjacent areas having 10 or more years of record. Data include the magnitude and probability of annual low and high streamflow, the magnitude and probability of low streamflow for three seasons (March–June, July–October, and November–February), streamflow duration statistics for monthly and annual periods, and mean streamflows for monthly and annual periods. Streamflow is considered to be regulated at streamflow-gaging stations where dams or other large-scale human modifications affect 20 percent or more of the contributing drainage basin. Separate streamflow characteristics are presented for the unregulated and regulated periods of record for streamflow-gaging stations with sufficient data.
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Spatial and Temporal Streamflow Trends in Northern Taiwan
Directory of Open Access Journals (Sweden)
Chen-Feng Yeh
2015-02-01
Full Text Available Streamflow is an important factor in the study of water resource management, floods, and droughts. Dramatic climate change has created extreme rainfall distributions, making the study of streamflow trends and variability even more crucial. In this study, the long-term streamflow data and trends recorded at gauging stations in Northern Taiwan are analyzed using the Mann-Kendall test. The data used for trend analysis are the average annual streamflow, the average seasonal streamflow, and the high and low flows. The slope trend is calculated using the Theil-Sen estimator. Finally, change point analysis is conducted using the Mann-Whitney-Pettit test and the cumulative deviation test to gain further information about the change points and to understand the changes in streamflow before and after the change points. The average annual streamflow of the 12 gauging stations in the study area is analyzed using the Mann-Kendall test. The results show that of the 12 gauging stations, only the Ximen Bridge Station in the Lanyang River basin show a significant downward streamflow trend. Results of the monthly and seasonal average streamflow analysis show that in the spring, 72.2% of the gauging stations showed upward streamflow trends, most of which were located in the Tamsui River and the Touqian River basins. The high and low flow data analysis shows that the Ximen Bridge Station was the only gauging station to feature a significant downward streamflow trend for both high and low flows. This distribution pattern provides valuable information for regional hydrological studies and water management.
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Analytical flow duration curves for summer streamflow in Switzerland
Santos, Ana Clara; Portela, Maria Manuela; Rinaldo, Andrea; Schaefli, Bettina
2018-04-01
This paper proposes a systematic assessment of the performance of an analytical modeling framework for streamflow probability distributions for a set of 25 Swiss catchments. These catchments show a wide range of hydroclimatic regimes, including namely snow-influenced streamflows. The model parameters are calculated from a spatially averaged gridded daily precipitation data set and from observed daily discharge time series, both in a forward estimation mode (direct parameter calculation from observed data) and in an inverse estimation mode (maximum likelihood estimation). The performance of the linear and the nonlinear model versions is assessed in terms of reproducing observed flow duration curves and their natural variability. Overall, the nonlinear model version outperforms the linear model for all regimes, but the linear model shows a notable performance increase with catchment elevation. More importantly, the obtained results demonstrate that the analytical model performs well for summer discharge for all analyzed streamflow regimes, ranging from rainfall-driven regimes with summer low flow to snow and glacier regimes with summer high flow. These results suggest that the model's encoding of discharge-generating events based on stochastic soil moisture dynamics is more flexible than previously thought. As shown in this paper, the presence of snowmelt or ice melt is accommodated by a relative increase in the discharge-generating frequency, a key parameter of the model. Explicit quantification of this frequency increase as a function of mean catchment meteorological conditions is left for future research.
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Clark, E.; Wood, A.; Nijssen, B.; Clark, M. P.
2017-12-01
Short- to medium-range (1- to 7-day) streamflow forecasts are important for flood control operations and in issuing potentially life-save flood warnings. In the U.S., the National Weather Service River Forecast Centers (RFCs) issue such forecasts in real time, depending heavily on a manual data assimilation (DA) approach. Forecasters adjust model inputs, states, parameters and outputs based on experience and consideration of a range of supporting real-time information. Achieving high-quality forecasts from new automated, centralized forecast systems will depend critically on the adequacy of automated DA approaches to make analogous corrections to the forecasting system. Such approaches would further enable systematic evaluation of real-time flood forecasting methods and strategies. Toward this goal, we have implemented a real-time Sequential Importance Resampling particle filter (SIR-PF) approach to assimilate observed streamflow into simulated initial hydrologic conditions (states) for initializing ensemble flood forecasts. Assimilating streamflow alone in SIR-PF improves simulated streamflow and soil moisture during the model spin up period prior to a forecast, with consequent benefits for forecasts. Nevertheless, it only consistently limits error in simulated snow water equivalent during the snowmelt season and in basins where precipitation falls primarily as snow. We examine how the simulated initial conditions with and without SIR-PF propagate into 1- to 7-day ensemble streamflow forecasts. Forecasts are evaluated in terms of reliability and skill over a 10-year period from 2005-2015. The focus of this analysis is on how interactions between hydroclimate and SIR-PF performance impact forecast skill. To this end, we examine forecasts for 5 hydroclimatically diverse basins in the western U.S. Some of these basins receive most of their precipitation as snow, others as rain. Some freeze throughout the mid-winter while others experience significant mid-winter melt
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Arsenault, Richard; Gatien, Philippe; Renaud, Benoit; Brissette, François; Martel, Jean-Luc
2015-10-01
This study aims to test whether a weighted combination of several hydrological models can simulate flows more accurately than the models taken individually. In addition, the project attempts to identify the most efficient model averaging method and the optimal number of models to include in the weighting scheme. In order to address the first objective, streamflow was simulated using four lumped hydrological models (HSAMI, HMETS, MOHYSE and GR4J-6), each of which were calibrated with three different objective functions on 429 watersheds. The resulting 12 hydrographs (4 models × 3 metrics) were weighted and combined with the help of 9 averaging methods which are the simple arithmetic mean (SAM), Akaike information criterion (AICA), Bates-Granger (BGA), Bayes information criterion (BICA), Bayesian model averaging (BMA), Granger-Ramanathan average variant A, B and C (GRA, GRB and GRC) and the average by SCE-UA optimization (SCA). The same weights were then applied to the hydrographs in validation mode, and the Nash-Sutcliffe Efficiency metric was measured between the averaged and observed hydrographs. Statistical analyses were performed to compare the accuracy of weighted methods to that of individual models. A Kruskal-Wallis test and a multi-objective optimization algorithm were then used to identify the most efficient weighted method and the optimal number of models to integrate. Results suggest that the GRA, GRB, GRC and SCA weighted methods perform better than the individual members. Model averaging from these four methods were superior to the best of the individual members in 76% of the cases. Optimal combinations on all watersheds included at least one of each of the four hydrological models. None of the optimal combinations included all members of the ensemble of 12 hydrographs. The Granger-Ramanathan average variant C (GRC) is recommended as the best compromise between accuracy, speed of execution, and simplicity.
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Relative contributions of transient and steady state infiltration during ephemeral streamflow
Blasch, Kyle W.; Ferré, Ty P.A.; Hoffmann, John P.; Fleming, John B.
2006-01-01
Simulations of infiltration during three ephemeral streamflow events in a coarse‐grained alluvial channel overlying a less permeable basin‐fill layer were conducted to determine the relative contribution of transient infiltration at the onset of streamflow to cumulative infiltration for the event. Water content, temperature, and piezometric measurements from 2.5‐m vertical profiles within the alluvial sediments were used to constrain a variably saturated water flow and heat transport model. Simulated and measured transient infiltration rates at the onset of streamflow were about two to three orders of magnitude greater than steady state infiltration rates. The duration of simulated transient infiltration ranged from 1.8 to 20 hours, compared with steady state flow periods of 231 to 307 hours. Cumulative infiltration during the transient period represented 10 to 26% of the total cumulative infiltration, with an average contribution of approximately 18%. Cumulative infiltration error for the simulated streamflow events ranged from 9 to 25%. Cumulative infiltration error for typical streamflow events of about 8 hours in duration in is about 90%. This analysis indicates that when estimating total cumulative infiltration in coarse‐grained ephemeral stream channels, consideration of the transient infiltration at the onset of streamflow will improve predictions of the total volume of infiltration that may become groundwater recharge.
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Long-term variation analysis of a tropical river's annual streamflow regime over a 50-year period
Seyam, Mohammed; Othman, Faridah
2015-07-01
Studying the long-term changes of streamflow is an important tool for enhancing water resource and river system planning, design, and management. The aim of this work is to identify the long-term variations in annual streamflow regime over a 50-year period from 1961 to 2010 in the Selangor River, which is one of the main tropical rivers in Malaysia. Initially, the data underwent preliminary independence, normality, and homogeneity testing using the Pearson correlation coefficient and Shapiro-Wilk and Pettitt's tests, respectively. The work includes a study and analysis of the changes through nine variables describing the annual streamflow and variations in the yearly duration of high and low streamflows. The analyses were conducted via two time scales: yearly and sub-periodic. The sub-periods were obtained by segmenting the 50 years into seven sub-periods by two techniques, namely the change-point test and direct method. Even though analysis revealed nearly negligible changes in mean annual flow over the study period, the maximum annual flow generally increased while the minimum annual flow significantly decreased with respect to time. It was also observed that the variables describing the dispersion in streamflow continually increased with respect to time. An obvious increase was detected in the yearly duration of danger level of streamflow, a slight increase was noted in the yearly duration of warning and alert levels, and a slight decrease in the yearly duration of low streamflow was found. The perceived changes validate the existence of long-term changes in annual streamflow regime, which increase the probability of floods and droughts occurring in future. In light of the results, attention should be drawn to developing water resource management and flood protection plans in order to avert the harmful effects potentially resulting from the expected changes in annual streamflow regime.
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Interaction between stream temperature, streamflow, and groundwater exchanges in alpine streams
Constantz, James E.
1998-01-01
Four alpine streams were monitored to continuously collect stream temperature and streamflow for periods ranging from a week to a year. In a small stream in the Colorado Rockies, diurnal variations in both stream temperature and streamflow were significantly greater in losing reaches than in gaining reaches, with minimum streamflow losses occurring early in the day and maximum losses occurring early in the evening. Using measured stream temperature changes, diurnal streambed infiltration rates were predicted to increase as much as 35% during the day (based on a heat and water transport groundwater model), while the measured increase in streamflow loss was 40%. For two large streams in the Sierra Nevada Mountains, annual stream temperature variations ranged from 0° to 25°C. In summer months, diurnal stream temperature variations were 30–40% of annual stream temperature variations, owing to reduced streamflows and increased atmospheric heating. Previous reports document that one Sierra stream site generally gains groundwater during low flows, while the second Sierra stream site may lose water during low flows. For August the diurnal streamflow variation was 11% at the gaining stream site and 30% at the losing stream site. On the basis of measured diurnal stream temperature variations, streambed infiltration rates were predicted to vary diurnally as much as 20% at the losing stream site. Analysis of results suggests that evapotranspiration losses determined diurnal streamflow variations in the gaining reaches, while in the losing reaches, evapotranspiration losses were compounded by diurnal variations in streambed infiltration. Diurnal variations in stream temperature were reduced in the gaining reaches as a result of discharging groundwater of relatively constant temperature. For the Sierra sites, comparison of results with those from a small tributary demonstrated that stream temperature patterns were useful in delineating discharges of bank storage following
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Directory of Open Access Journals (Sweden)
Ryan R Bart
Full Text Available Higher global temperatures and increased levels of disturbance are contributing to greater tree mortality in many forest ecosystems. These same drivers can also limit forest regeneration, leading to vegetation type conversion. For the Sierra Nevada of California, little is known about how type conversion may affect streamflow, a critical source of water supply for urban, agriculture and environmental purposes. In this paper, we examined the effects of tree-to-shrub type conversion, in combination with climate change, on streamflow in two lower montane forest watersheds in the Sierra Nevada. A spatially distributed ecohydrologic model was used to simulate changes in streamflow, evaporation, and transpiration following type conversion, with an explicit focus on the role of vegetation size and aspect. Model results indicated that streamflow may show negligible change or small decreases following type conversion when the difference between tree and shrub leaf areas is small, partly due to the higher stomatal conductivity and the deep rooting depth of shrubs. In contrast, streamflow may increase when post-conversion shrubs have a small leaf area relative to trees. Model estimates also suggested that vegetation change could have a greater impact on streamflow magnitude than the direct hydrologic impacts of increased temperatures. Temperature increases, however, may have a greater impact on streamflow timing. Tree-to-shrub type conversion increased streamflow only marginally during dry years (annual precipitation < 800 mm, with most streamflow change observed during wetter years. These modeling results underscore the importance of accounting for changes in vegetation communities to accurately characterize future hydrologic regimes for the Sierra Nevada.
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Tague, Christina L.; Moritz, Max A.
2016-01-01
Higher global temperatures and increased levels of disturbance are contributing to greater tree mortality in many forest ecosystems. These same drivers can also limit forest regeneration, leading to vegetation type conversion. For the Sierra Nevada of California, little is known about how type conversion may affect streamflow, a critical source of water supply for urban, agriculture and environmental purposes. In this paper, we examined the effects of tree-to-shrub type conversion, in combination with climate change, on streamflow in two lower montane forest watersheds in the Sierra Nevada. A spatially distributed ecohydrologic model was used to simulate changes in streamflow, evaporation, and transpiration following type conversion, with an explicit focus on the role of vegetation size and aspect. Model results indicated that streamflow may show negligible change or small decreases following type conversion when the difference between tree and shrub leaf areas is small, partly due to the higher stomatal conductivity and the deep rooting depth of shrubs. In contrast, streamflow may increase when post-conversion shrubs have a small leaf area relative to trees. Model estimates also suggested that vegetation change could have a greater impact on streamflow magnitude than the direct hydrologic impacts of increased temperatures. Temperature increases, however, may have a greater impact on streamflow timing. Tree-to-shrub type conversion increased streamflow only marginally during dry years (annual precipitation < 800 mm), with most streamflow change observed during wetter years. These modeling results underscore the importance of accounting for changes in vegetation communities to accurately characterize future hydrologic regimes for the Sierra Nevada. PMID:27575592
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The importance of warm season warming to western U.S. streamflow changes
Das, T.; Pierce, D.W.; Cayan, D.R.; Vano, J.A.; Lettenmaier, D.P.
2011-01-01
Warm season climate warming will be a key driver of annual streamflow changes in four major river basins of the western U.S., as shown by hydrological model simulations using fixed precipitation and idealized seasonal temperature changes based on climate projections with SRES A2 forcing. Warm season (April-September) warming reduces streamflow throughout the year; streamflow declines both immediately and in the subsequent cool season. Cool season (October-March) warming, by contrast, increases streamflow immediately, partially compensating for streamflow reductions during the subsequent warm season. A uniform warm season warming of 3C drives a wide range of annual flow declines across the basins: 13.3%, 7.2%, 1.8%, and 3.6% in the Colorado, Columbia, Northern and Southern Sierra basins, respectively. The same warming applied during the cool season gives annual declines of only 3.5%, 1.7%, 2.1%, and 3.1%, respectively. Copyright 2011 by the American Geophysical Union.
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The effects of changing land cover on streamflow simulation in Puerto Rico
A.E. Van Beusekom; L.E. Hay; R.J. Viger; W.A. Gould; J.A. Collazo; A. Henareh Khalyani
2014-01-01
This study quantitatively explores whether land cover changes have a substantive impact on simulated streamflow within the tropical island setting of Puerto Rico. The Precipitation Runoff Modeling System (PRMS) was used to compare streamflow simulations based on five static parameterizations of land cover with those based on dynamically varying parameters derived from...
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Low Streamflow Forcasting using Minimum Relative Entropy
Cui, H.; Singh, V. P.
2013-12-01
Minimum relative entropy spectral analysis is derived in this study, and applied to forecast streamflow time series. Proposed method extends the autocorrelation in the manner that the relative entropy of underlying process is minimized so that time series data can be forecasted. Different prior estimation, such as uniform, exponential and Gaussian assumption, is taken to estimate the spectral density depending on the autocorrelation structure. Seasonal and nonseasonal low streamflow series obtained from Colorado River (Texas) under draught condition is successfully forecasted using proposed method. Minimum relative entropy determines spectral of low streamflow series with higher resolution than conventional method. Forecasted streamflow is compared to the prediction using Burg's maximum entropy spectral analysis (MESA) and Configurational entropy. The advantage and disadvantage of each method in forecasting low streamflow is discussed.
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In Brief: Online database for instantaneous streamflow data
Showstack, Randy
2007-11-01
Access to U.S. Geological Survey (USGS) historical instantaneous streamflow discharge data, dating from around 1990, is now available online through the Instantaneous Data Archive (IDA), the USGS announced on 14 November. In this new system, users can find streamflow information reported at the time intervals at which it is collected, typically 15-minute to hourly intervals. Although instantaneous data have been available for many years, they were not accessible through the Internet. Robert Hirsch, USGS Associate Director of Water, said, ``A user-friendly archive of historical instantaneous streamflow data is important to many different users for such things as floodplain mapping, flood modeling, and estimating pollutant transport.''The site currently has about 1.5 billion instantaneous data values from 5500 stream gages in 26 states. The number of states and stream gages with data will continue to increase, according to the USGS. For more information, visit the Web site: http://ida.water.usgs.gov/ida/.
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Linear genetic programming application for successive-station monthly streamflow prediction
Danandeh Mehr, Ali; Kahya, Ercan; Yerdelen, Cahit
2014-09-01
In recent decades, artificial intelligence (AI) techniques have been pronounced as a branch of computer science to model wide range of hydrological phenomena. A number of researches have been still comparing these techniques in order to find more effective approaches in terms of accuracy and applicability. In this study, we examined the ability of linear genetic programming (LGP) technique to model successive-station monthly streamflow process, as an applied alternative for streamflow prediction. A comparative efficiency study between LGP and three different artificial neural network algorithms, namely feed forward back propagation (FFBP), generalized regression neural networks (GRNN), and radial basis function (RBF), has also been presented in this study. For this aim, firstly, we put forward six different successive-station monthly streamflow prediction scenarios subjected to training by LGP and FFBP using the field data recorded at two gauging stations on Çoruh River, Turkey. Based on Nash-Sutcliffe and root mean squared error measures, we then compared the efficiency of these techniques and selected the best prediction scenario. Eventually, GRNN and RBF algorithms were utilized to restructure the selected scenario and to compare with corresponding FFBP and LGP. Our results indicated the promising role of LGP for successive-station monthly streamflow prediction providing more accurate results than those of all the ANN algorithms. We found an explicit LGP-based expression evolved by only the basic arithmetic functions as the best prediction model for the river, which uses the records of the both target and upstream stations.
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Khai Tiu, Ervin Shan; Huang, Yuk Feng; Ling, Lloyd
2018-03-01
An accurate streamflow forecasting model is important for the development of flood mitigation plan as to ensure sustainable development for a river basin. This study adopted Variational Mode Decomposition (VMD) data-preprocessing technique to process and denoise the rainfall data before putting into the Support Vector Machine (SVM) streamflow forecasting model in order to improve the performance of the selected model. Rainfall data and river water level data for the period of 1996-2016 were used for this purpose. Homogeneity tests (Standard Normal Homogeneity Test, the Buishand Range Test, the Pettitt Test and the Von Neumann Ratio Test) and normality tests (Shapiro-Wilk Test, Anderson-Darling Test, Lilliefors Test and Jarque-Bera Test) had been carried out on the rainfall series. Homogenous and non-normally distributed data were found in all the stations, respectively. From the recorded rainfall data, it was observed that Dungun River Basin possessed higher monthly rainfall from November to February, which was during the Northeast Monsoon. Thus, the monthly and seasonal rainfall series of this monsoon would be the main focus for this research as floods usually happen during the Northeast Monsoon period. The predicted water levels from SVM model were assessed with the observed water level using non-parametric statistical tests (Biased Method, Kendall's Tau B Test and Spearman's Rho Test).
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Estimation of average annual streamflows and power potentials for Alaska and Hawaii
Energy Technology Data Exchange (ETDEWEB)
Verdin, Kristine L. [Idaho National Lab. (INL), Idaho Falls, ID (United States). Idaho National Engineering and Environmental Lab. (INEEL)
2004-05-01
This paper describes the work done to develop average annual streamflow estimates and power potential for the states of Alaska and Hawaii. The Elevation Derivatives for National Applications (EDNA) database was used, along with climatic datasets, to develop flow and power estimates for every stream reach in the EDNA database. Estimates of average annual streamflows were derived using state-specific regression equations, which were functions of average annual precipitation, precipitation intensity, drainage area, and other elevation-derived parameters. Power potential was calculated through the use of the average annual streamflow and the hydraulic head of each reach, which is calculated from the EDNA digital elevation model. In all, estimates of streamflow and power potential were calculated for over 170,000 stream segments in the Alaskan and Hawaiian datasets.
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Bennett, J.; David, R. E.; Wang, Q.; Li, M.; Shrestha, D. L.
2016-12-01
Flood forecasting in Australia has historically relied on deterministic forecasting models run only when floods are imminent, with considerable forecaster input and interpretation. These now co-existed with a continually available 7-day streamflow forecasting service (also deterministic) aimed at operational water management applications such as environmental flow releases. The 7-day service is not optimised for flood prediction. We describe progress on developing a system for ensemble streamflow forecasting that is suitable for both flood prediction and water management applications. Precipitation uncertainty is handled through post-processing of Numerical Weather Prediction (NWP) output with a Bayesian rainfall post-processor (RPP). The RPP corrects biases, downscales NWP output, and produces reliable ensemble spread. Ensemble precipitation forecasts are used to force a semi-distributed conceptual rainfall-runoff model. Uncertainty in precipitation forecasts is insufficient to reliably describe streamflow forecast uncertainty, particularly at shorter lead-times. We characterise hydrological prediction uncertainty separately with a 4-stage error model. The error model relies on data transformation to ensure residuals are homoscedastic and symmetrically distributed. To ensure streamflow forecasts are accurate and reliable, the residuals are modelled using a mixture-Gaussian distribution with distinct parameters for the rising and falling limbs of the forecast hydrograph. In a case study of the Murray River in south-eastern Australia, we show ensemble predictions of floods generally have lower errors than deterministic forecasting methods. We also discuss some of the challenges in operationalising short-term ensemble streamflow forecasts in Australia, including meeting the needs for accurate predictions across all flow ranges and comparing forecasts generated by event and continuous hydrological models.
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2013-03-01
... EPA's policy to include all comments it receives in the public docket without change and to make the... Modeling To Assess the Sensitivity of Streamflow, Nutrient, and Sediment Loads to Climate Change and Urban... Loads to Climate Change and Urban Development in 20 U.S. Watersheds (EPA/600/R-12/058). EPA also is...
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Betterle, A.; Radny, D.; Schirmer, M.; Botter, G.
2017-12-01
The spatial correlation of daily streamflows represents a statistical index encapsulating the similarity between hydrographs at two arbitrary catchment outlets. In this work, a process-based analytical framework is utilized to investigate the hydrological drivers of streamflow spatial correlation through an extensive application to 78 pairs of stream gauges belonging to 13 unregulated catchments in the eastern United States. The analysis provides insight on how the observed heterogeneity of the physical processes that control flow dynamics ultimately affect streamflow correlation and spatial patterns of flow regimes. Despite the variability of recession properties across the study catchments, the impact of heterogeneous drainage rates on the streamflow spatial correlation is overwhelmed by the spatial variability of frequency and intensity of effective rainfall events. Overall, model performances are satisfactory, with root mean square errors between modeled and observed streamflow spatial correlation below 10% in most cases. We also propose a method for estimating streamflow correlation in the absence of discharge data, which proves useful to predict streamflow regimes in ungauged areas. The method consists in setting a minimum threshold on the modeled flow correlation to individuate hydrologically similar sites. Catchment outlets that are most correlated (ρ>0.9) are found to be characterized by analogous streamflow distributions across a broad range of flow regimes.
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Koltun, G.F.; Holtschlag, David J.
2010-01-01
Bootstrapping techniques employing random subsampling were used with the AFINCH (Analysis of Flows In Networks of CHannels) model to gain insights into the effects of variation in streamflow-gaging-network size and composition on the accuracy and precision of streamflow estimates at ungaged locations in the 0405 (Southeast Lake Michigan) hydrologic subregion. AFINCH uses stepwise-regression techniques to estimate monthly water yields from catchments based on geospatial-climate and land-cover data in combination with available streamflow and water-use data. Calculations are performed on a hydrologic-subregion scale for each catchment and stream reach contained in a National Hydrography Dataset Plus (NHDPlus) subregion. Water yields from contributing catchments are multiplied by catchment areas and resulting flow values are accumulated to compute streamflows in stream reaches which are referred to as flow lines. AFINCH imposes constraints on water yields to ensure that observed streamflows are conserved at gaged locations. Data from the 0405 hydrologic subregion (referred to as Southeast Lake Michigan) were used for the analyses. Daily streamflow data were measured in the subregion for 1 or more years at a total of 75 streamflow-gaging stations during the analysis period which spanned water years 1971–2003. The number of streamflow gages in operation each year during the analysis period ranged from 42 to 56 and averaged 47. Six sets (one set for each censoring level), each composed of 30 random subsets of the 75 streamflow gages, were created by censoring (removing) approximately 10, 20, 30, 40, 50, and 75 percent of the streamflow gages (the actual percentage of operating streamflow gages censored for each set varied from year to year, and within the year from subset to subset, but averaged approximately the indicated percentages).Streamflow estimates for six flow lines each were aggregated by censoring level, and results were analyzed to assess (a) how the
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Streamflow disaggregation: a nonlinear deterministic approach
Directory of Open Access Journals (Sweden)
B. Sivakumar
2004-01-01
Full Text Available This study introduces a nonlinear deterministic approach for streamflow disaggregation. According to this approach, the streamflow transformation process from one scale to another is treated as a nonlinear deterministic process, rather than a stochastic process as generally assumed. The approach follows two important steps: (1 reconstruction of the scalar (streamflow series in a multi-dimensional phase-space for representing the transformation dynamics; and (2 use of a local approximation (nearest neighbor method for disaggregation. The approach is employed for streamflow disaggregation in the Mississippi River basin, USA. Data of successively doubled resolutions between daily and 16 days (i.e. daily, 2-day, 4-day, 8-day, and 16-day are studied, and disaggregations are attempted only between successive resolutions (i.e. 2-day to daily, 4-day to 2-day, 8-day to 4-day, and 16-day to 8-day. Comparisons between the disaggregated values and the actual values reveal excellent agreements for all the cases studied, indicating the suitability of the approach for streamflow disaggregation. A further insight into the results reveals that the best results are, in general, achieved for low embedding dimensions (2 or 3 and small number of neighbors (less than 50, suggesting possible presence of nonlinear determinism in the underlying transformation process. A decrease in accuracy with increasing disaggregation scale is also observed, a possible implication of the existence of a scaling regime in streamflow.
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Nielsen, Martha G.; Locke, Daniel B.
2012-01-01
In order to evaluate water availability in the State of Maine, the U.S. Geological Survey (USGS) and the Maine Geological Survey began a cooperative investigation to provide the first rigorous evaluation of watersheds deemed "at risk" because of the combination of instream flow requirements and proportionally large water withdrawals. The study area for this investigation includes the Harvey and Merrill Brook watersheds and the Freeport aquifer in the towns of Freeport, Pownal, and Yarmouth, Maine. A numerical groundwater- flow model was used to evaluate groundwater withdrawals, groundwater-surface-water interactions, and the effect of water-management practices on streamflow. The water budget illustrates the effect that groundwater withdrawals have on streamflow and the movement of water within the system. Streamflow measurements were made following standard USGS techniques, from May through September 2009 at one site in the Merrill Brook watershed and four sites in the Harvey Brook watershed. A record-extension technique was applied to estimate long-term monthly streamflows at each of the five sites. The conceptual model of the groundwater system consists of a deep, confined aquifer (the Freeport aquifer) in a buried valley that trends through the middle of the study area, covered by a discontinuous confining unit, and topped by a thin upper saturated zone that is a mixture of sandy units, till, and weathered clay. Harvey and Merrill Brooks flow southward through the study area, and receive groundwater discharge from the upper saturated zone and from the deep aquifer through previously unknown discontinuities in the confining unit. The Freeport aquifer gets most of its recharge from local seepage around the edges of the confining unit, the remainder is received as inflow from the north within the buried valley. Groundwater withdrawals from the Freeport aquifer in the study area were obtained from the local water utility and estimated for other categories. Overall
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Bart, Ryan R; Tague, Christina L; Moritz, Max A
2016-01-01
Higher global temperatures and increased levels of disturbance are contributing to greater tree mortality in many forest ecosystems. These same drivers can also limit forest regeneration, leading to vegetation type conversion. For the Sierra Nevada of California, little is known about how type conversion may affect streamflow, a critical source of water supply for urban, agriculture and environmental purposes. In this paper, we examined the effects of tree-to-shrub type conversion, in combination with climate change, on streamflow in two lower montane forest watersheds in the Sierra Nevada. A spatially distributed ecohydrologic model was used to simulate changes in streamflow, evaporation, and transpiration following type conversion, with an explicit focus on the role of vegetation size and aspect. Model results indicated that streamflow may show negligible change or small decreases following type conversion when the difference between tree and shrub leaf areas is small, partly due to the higher stomatal conductivity and the deep rooting depth of shrubs. In contrast, streamflow may increase when post-conversion shrubs have a small leaf area relative to trees. Model estimates also suggested that vegetation change could have a greater impact on streamflow magnitude than the direct hydrologic impacts of increased temperatures. Temperature increases, however, may have a greater impact on streamflow timing. Tree-to-shrub type conversion increased streamflow only marginally during dry years (annual precipitation importance of accounting for changes in vegetation communities to accurately characterize future hydrologic regimes for the Sierra Nevada.
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Spatial Correlation Of Streamflows: An Analytical Approach
Betterle, A.; Schirmer, M.; Botter, G.
2016-12-01
The interwoven space and time variability of climate and landscape properties results in complex and non-linear hydrological response of streamflow dynamics. Understanding how meteorologic and morphological characteristics of catchments affect similarity/dissimilarity of streamflow timeseries at their outlets represents a scientific challenge with application in water resources management, ecological studies and regionalization approaches aimed to predict streamflows in ungauged areas. In this study, we establish an analytical approach to estimate the spatial correlation of daily streamflows in two arbitrary locations within a given hydrologic district or river basin at seasonal and annual time scales. The method is based on a stochastic description of the coupled streamflow dynamics at the outlet of two catchments. The framework aims to express the correlation of daily streamflows at two locations along a river network as a function of a limited number of physical parameters characterizing the main underlying hydrological drivers, that include climate conditions, precipitation regime and catchment drainage rates. The proposed method portrays how heterogeneity of climate and landscape features affect the spatial variability of flow regimes along river systems. In particular, we show that frequency and intensity of synchronous effective rainfall events in the relevant contributing catchments are the main driver of the spatial correlation of daily discharge, whereas only pronounced differences in the drainage rate of the two basins bear a significant effect on the streamflow correlation. The topological arrangement of the two outlets also influences the underlying streamflow correlation, as we show that nested catchments tend to maximize the spatial correlation of flow regimes. The application of the method to a set of catchments in the South-Eastern US suggests the potential of the proposed tool for the characterization of spatial connections of flow regimes in the
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Wei, Xiaohua; Zhang, Mingfang
2010-12-01
Climatic variability and forest disturbance are commonly recognized as two major drivers influencing streamflow change in large-scale forested watersheds. The greatest challenge in evaluating quantitative hydrological effects of forest disturbance is the removal of climatic effect on hydrology. In this paper, a method was designed to quantify respective contributions of large-scale forest disturbance and climatic variability on streamflow using the Willow River watershed (2860 km2) located in the central part of British Columbia, Canada. Long-term (>50 years) data on hydrology, climate, and timber harvesting history represented by equivalent clear-cutting area (ECA) were available to discern climatic and forestry influences on streamflow by three steps. First, effective precipitation, an integrated climatic index, was generated by subtracting evapotranspiration from precipitation. Second, modified double mass curves were developed by plotting accumulated annual streamflow against annual effective precipitation, which presented a much clearer picture of the cumulative effects of forest disturbance on streamflow following removal of climatic influence. The average annual streamflow changes that were attributed to forest disturbances and climatic variability were then estimated to be +58.7 and -72.4 mm, respectively. The positive (increasing) and negative (decreasing) values in streamflow change indicated opposite change directions, which suggest an offsetting effect between forest disturbance and climatic variability in the study watershed. Finally, a multivariate Autoregressive Integrated Moving Average (ARIMA) model was generated to establish quantitative relationships between accumulated annual streamflow deviation attributed to forest disturbances and annual ECA. The model was then used to project streamflow change under various timber harvesting scenarios. The methodology can be effectively applied to any large-scale single watershed where long-term data (>50
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Brown, M. E.; Racoviteanu, A. E.; Tarboton, D. G.; Gupta, A. Sen; Nigro, J.; Policelli, F.; Habib, S.; Tokay, M.; Shrestha, M. S.; Bajracharya, S.; Hummel, P.; Gray, M.; Duda, P.; Zaitchik, B.; Mahat, V.; Artan, G.; Tokar, S.
2014-11-01
Quantification of the contribution of the hydrologic components (snow, ice and rain) to river discharge in the Hindu Kush Himalayan (HKH) region is important for decision-making in water sensitive sectors, and for water resources management and flood risk reduction. In this area, access to and monitoring of the glaciers and their melt outflow is challenging due to difficult access, thus modeling based on remote sensing offers the potential for providing information to improve water resources management and decision making. This paper describes an integrated modeling system developed using downscaled NASA satellite based and earth system data products coupled with in-situ hydrologic data to assess the contribution of snow and glaciers to the flows of the rivers in the HKH region. Snow and glacier melt was estimated using the Utah Energy Balance (UEB) model, further enhanced to accommodate glacier ice melt over clean and debris-covered tongues, then meltwater was input into the USGS Geospatial Stream Flow Model (GeoSFM). The two model components were integrated into Better Assessment Science Integrating point and Nonpoint Sources modeling framework (BASINS) as a user-friendly open source system and was made available to countries in high Asia. Here we present a case study from the Langtang Khola watershed in the monsoon-influenced Nepal Himalaya, used to validate our energy balance approach and to test the applicability of our modeling system. The snow and glacier melt model predicts that for the eight years used for model evaluation (October 2003-September 2010), the total surface water input over the basin was 9.43 m, originating as 62% from glacier melt, 30% from snowmelt and 8% from rainfall. Measured streamflow for those years were 5.02 m, reflecting a runoff coefficient of 0.53. GeoSFM simulated streamflow was 5.31 m indicating reasonable correspondence between measured and model confirming the capability of the integrated system to provide a quantification of
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Brown, M. E.; Racoviteanu, A. E.; Tarboton, D. G.; Sen Gupta, A.; Nigro, J.; Policelli, F.; Habib, S.; Tokay, M.; Shrestha, M. S.; Bajracharya, S.
2014-01-01
Quantification of the contribution of the hydrologic components (snow, ice and rain) to river discharge in the Hindu Kush Himalayan (HKH) region is important for decision-making in water sensitive sectors, and for water resources management and flood risk reduction. In this area, access to and monitoring of the glaciers and their melt outflow is challenging due to difficult access, thus modeling based on remote sensing offers the potential for providing information to improve water resources management and decision making. This paper describes an integrated modeling system developed using downscaled NASA satellite based and earth system data products coupled with in-situ hydrologic data to assess the contribution of snow and glaciers to the flows of the rivers in the HKH region. Snow and glacier melt was estimated using the Utah Energy Balance (UEB) model, further enhanced to accommodate glacier ice melt over clean and debris-covered tongues, then meltwater was input into the USGS Geospatial Stream Flow Model (Geo- SFM). The two model components were integrated into Better Assessment Science Integrating point and Nonpoint Sources modeling framework (BASINS) as a user-friendly open source system and was made available to countries in high Asia. Here we present a case study from the Langtang Khola watershed in the monsoon-influenced Nepal Himalaya, used to validate our energy balance approach and to test the applicability of our modeling system. The snow and glacier melt model predicts that for the eight years used for model evaluation (October 2003-September 2010), the total surface water input over the basin was 9.43 m, originating as 62% from glacier melt, 30% from snowmelt and 8% from rainfall. Measured streamflow for those years were 5.02 m, reflecting a runoff coefficient of 0.53. GeoSFM simulated streamflow was 5.31 m indicating reasonable correspondence between measured and model confirming the capability of the integrated system to provide a quantification
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Drivers of annual to decadal streamflow variability in the lower Colorado River Basin
Lambeth-Beagles, R. S.; Troch, P. A.
2010-12-01
The Colorado River is the main water supply to the southwest region. As demand reaches the limit of supply in the southwest it becomes increasingly important to understand the dynamics of streamflow in the Colorado River and in particular the tributaries to the lower Colorado River. Climate change may pose an additional threat to the already-scarce water supply in the southwest. Due to the narrowing margin for error, water managers are keen on extending their ability to predict streamflow volumes on a mid-range to decadal scale. Before a predictive streamflow model can be developed, an understanding of the physical drivers of annual to decadal streamflow variability in the lower Colorado River Basin is needed. This research addresses this need by applying multiple statistical methods to identify trends, patterns and relationships present in streamflow, precipitation and temperature over the past century in four contributing watersheds to the lower Colorado River. The four watersheds selected were the Paria, Little Colorado, Virgin/Muddy, and Bill Williams. Time series data over a common period from 1906-2007 for streamflow, precipitation and temperature were used for the initial analysis. Through statistical analysis the following questions were addressed: 1) are there observable trends and patterns in these variables during the past century and 2) if there are trends or patterns, how are they related to each other? The Mann-Kendall test was used to identify trends in the three variables. Assumptions regarding autocorrelation and persistence in the data were taken into consideration. Kendall’s tau-b test was used to establish association between any found trends in the data. Initial results suggest there are two primary processes occurring. First, statistical analysis reveals significant upward trends in temperatures and downward trends in streamflow. However, there appears to be no trend in precipitation data. These trends in streamflow and temperature speak to
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Has streamflow changed in the Nordic countries?
Energy Technology Data Exchange (ETDEWEB)
Hisdal, Hege; Holmqvist, Erik; Jonsdottir, Jona Finndis; Jonsson, Pall; Kuusisto, Esko; Lindstroem, Goeran; Roald, Lars A.
2010-01-15
Climate change studies traditionally include elaboration of possible scenarios for the future and attempts to detect a climate change signal in historical data. This study focuses on the latter. A pan-Nordic dataset of more than 160 streamflow records was analysed to detect spatial and temporal changes in streamflow. The Mann-Kendall trend test was applied to study changes in annual and seasonal streamflow as well as floods and droughts for three periods: 1961-2000, 1941-2002 and 1920-2002. The period analysed and the selection of stations influenced the regional patterns found, but the overall picture was that trends towards increased streamflow were dominating for annual values and the winter and spring seasons. Trends in summer flow highly depended on the period analysed whereas no trend was found for the autumn season. A signal towards earlier snowmelt floods was clear and a tendency towards more severe summer droughts was found in southern Norway. A qualitative comparison of the findings to available streamflow scenarios for the region showed that the strongest trends found are coherent with changes expected in the scenario period, for example increased winter discharge and earlier snowmelt floods. However, there are also expected changes that are not reflected in the trends, such as the expected increase in autumn discharge in Norway. It can be concluded that the observed temperature increase has clearly affected the streamflow in the Nordic countries. These changes correspond well with the estimated consequences of a projected temperature increase. The effect of the observed and projected precipitation increase on streamflow is less clear.(Author)
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Energy Technology Data Exchange (ETDEWEB)
Wagener, Thorsten [Univ. of Bristol (United Kingdom); Mann, Michael [Pennsylvania State Univ., State College, PA (United States); Crane, Robert [Pennsylvania State Univ., State College, PA (United States)
2014-04-29
This project focuses on uncertainty in streamflow forecasting under climate change conditions. The objective is to develop easy to use methodologies that can be applied across a range of river basins to estimate changes in water availability for realistic projections of climate change. There are three major components to the project: Empirical downscaling of regional climate change projections from a range of Global Climate Models; Developing a methodology to use present day information on the climate controls on the parameterizations in streamflow models to adjust the parameterizations under future climate conditions (a trading-space-for-time approach); and Demonstrating a bottom-up approach to establishing streamflow vulnerabilities to climate change. The results reinforce the need for downscaling of climate data for regional applications, and further demonstrates the challenges of using raw GCM data to make local projections. In addition, it reinforces the need to make projections across a range of global climate models. The project demonstrates the potential for improving streamflow forecasts by using model parameters that are adjusted for future climate conditions, but suggests that even with improved streamflow models and reduced climate uncertainty through the use of downscaled data, there is still large uncertainty is the streamflow projections. The most useful output from the project is the bottom-up vulnerability driven approach to examining possible climate and land use change impacts on streamflow. Here, we demonstrate an inexpensive and easy to apply methodology that uses Classification and Regression Trees (CART) to define the climate and environmental parameters space that can produce vulnerabilities in the system, and then feeds in the downscaled projections to determine the probability top transitioning to a vulnerable sate. Vulnerabilities, in this case, are defined by the end user.
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A physical framework for evaluating net effects of wet meadow restoration on late summer streamflow
Grant, G.; Nash, C.; Selker, J. S.; Lewis, S.; Noël, P.
2017-12-01
Restoration of degraded wet meadows that develop on upland valley floors is intended to achieve a range of ecological benefits. A widely cited benefit is the potential for meadow restoration to augment late-season streamflow; however, there has been little field data demonstrating increased summer flows following restoration. Instead, the hydrologic consequences of restoration have typically been explored using coupled groundwater and surface water flow models at instrumented sites. The expected magnitude and direction of change provided by models has, however, been inconclusive. Here, we assess the streamflow benefit that can be obtained by wet meadow restoration using a parsimonious, physically-based approach. We use a one-dimensional linearized Boussinesq equation with a superimposed solution for changes in storage due to groundwater upwelling and and explicitly calculate evapotranspiration using the White Method. The model accurately predicts water table elevations from field data in the Middle Fork John Day watershed in Oregon, USA. The full solution shows that while raising channel beds can increase total water storage via increases in water table elevation in upland valley bottoms, the contributions of both lateral and longitudinal drainage from restored floodplains to late summer streamflow are undetectably small, while losses in streamflow due to greater transpiration, lower hydraulic gradients, and less drainable pore volume are substantial. Although late-summer streamflow increases should not be expected as a direct result of wet meadow restoration, these approaches offer benefits for improving the quality and health of riparian and meadow vegetation that would warrant considering such measures, even at the cost of increased water demand and reduced streamflow.
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Directory of Open Access Journals (Sweden)
Z. Dai
2010-06-01
Full Text Available Hydrological models are important tools for effective management, conservation and restoration of forested wetlands. The objective of this study was to test a distributed hydrological model, MIKE SHE, by using bi-criteria (i.e., two measurable variables, streamflow and water table depth to describe the hydrological processes in a forested watershed that is characteristic of the lower Atlantic Coastal Plain. Simulations were compared against observations of both streamflow and water table depth measured on a first-order watershed (WS80 on the Santee Experimental Forest in South Carolina, USA. Model performance was evaluated using coefficient of determination (R2 and Nash-Sutcliffe's model efficiency (E. The E and root mean squared error (RMSE were chosen as objective functions for sensitivity analysis of parameters. The model calibration and validation results demonstrated that the streamflow and water table depth were sensitive to most of the model input parameters, especially to surface detention storage, drainage depth, soil hydraulic properties, plant rooting depth, and surface roughness. Furthermore, the bi-criteria approach used for distributed model calibration and validation was shown to be better than the single-criterion in obtaining optimum model input parameters, especially for those parameters that were only sensitive to some specific conditions. Model calibration using the bi-criteria approach should be advantageous for constructing the uncertainty bounds of model inputs to simulate the hydrology for this type of forested watersheds. R2 varied from 0.60–0.99 for daily and monthly streamflow, and from 0.52–0.91 for daily water table depth. E changed from 0.53–0.96 for calibration and 0.51–0.98 for validation of daily and monthly streamflow, while E varied from 0.50–0.90 for calibration and 0.66–0.80 for validation of daily water table depth. This study showed
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Estimating ice-affected streamflow by extended Kalman filtering
Holtschlag, D.J.; Grewal, M.S.
1998-01-01
An extended Kalman filter was developed to automate the real-time estimation of ice-affected streamflow on the basis of routine measurements of stream stage and air temperature and on the relation between stage and streamflow during open-water (ice-free) conditions. The filter accommodates three dynamic modes of ice effects: sudden formation/ablation, stable ice conditions, and eventual elimination. The utility of the filter was evaluated by applying it to historical data from two long-term streamflow-gauging stations, St. John River at Dickey, Maine and Platte River at North Bend, Nebr. Results indicate that the filter was stable and that parameters converged for both stations, producing streamflow estimates that are highly correlated with published values. For the Maine station, logarithms of estimated streamflows are within 8% of the logarithms of published values 87.2% of the time during periods of ice effects and within 15% 96.6% of the time. Similarly, for the Nebraska station, logarithms of estimated streamflows are within 8% of the logarithms of published values 90.7% of the time and within 15% 97.7% of the time. In addition, the correlation between temporal updates and published streamflows on days of direct measurements at the Maine station was 0.777 and 0.998 for ice-affected and open-water periods, respectively; for the Nebraska station, corresponding correlations were 0.864 and 0.997.
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Directory of Open Access Journals (Sweden)
E. A. Rosenberg
2013-04-01
Full Text Available We assess the significance of groundwater storage for seasonal streamflow forecasts by evaluating its contribution to interannual streamflow anomalies in the 29 tributary sub-basins of the Colorado River. Monthly and annual changes in total basin storage are simulated by two implementations of the Variable Infiltration Capacity (VIC macroscale hydrology model – the standard release of the model, and an alternate version that has been modified to include the SIMple Groundwater Model (SIMGM, which represents an unconfined aquifer underlying the soil column. These estimates are compared to those resulting from basin-scale water balances derived exclusively from observational data and changes in terrestrial water storage from the Gravity Recovery and Climate Experiment (GRACE satellites. Changes in simulated groundwater storage are then compared to those derived via baseflow recession analysis for 72 reference-quality watersheds. Finally, estimates are statistically analyzed for relationships to interannual streamflow anomalies, and predictive capacities are compared across storage terms. We find that both model simulations result in similar estimates of total basin storage change, that these estimates compare favorably with those obtained from basin-scale water balances and GRACE data, and that baseflow recession analyses are consistent with simulated changes in groundwater storage. Statistical analyses reveal essentially no relationship between groundwater storage and interannual streamflow anomalies, suggesting that operational seasonal streamflow forecasts, which do not account for groundwater conditions implicitly or explicitly, are likely not detrimentally affected by this omission in the Colorado River basin.
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Directory of Open Access Journals (Sweden)
Katherine J. Chase
2016-09-01
New hydrological insights for the region: Projected changes in mean annual and mean monthly streamflow vary by the RegCM3 model selected, by watershed, and by future period. Mean annual streamflows for all future periods are projected to increase (11–21% for two of the four central Montana watersheds: Middle Musselshell River and Cottonwood Creek. Mean annual streamflows for all future periods are projected to decrease (changes of −24 to −75% for Redwater River watershed in eastern Montana. Mean annual streamflows are projected to increase slightly (2–15% for the 2030 period and decrease (changes of −16 to −44% for the 2080 period for the four remaining watersheds.
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Koltun, G.F.
2015-01-01
Between July 2013 and June 2014, the U.S. Geological Survey (USGS) made 10 streamflow measurements on the Ohio River about 1.5 miles (mi) downstream from the Hannibal Lock and Dam (near Hannibal, Ohio) and 11 streamflow measurements near the USGS Sardis gage (station number 03114306) located approximately 2.4 mi upstream from Sardis, Ohio. The measurement results were used to assess the accuracy of modeled or computed instantaneous streamflow time series created and supplied by the USGS, U.S. Army Corps of Engineers (USACE), and National Weather Service (NWS) for the Ohio River at Hannibal Lock and Dam and (or) at the USGS streamgage. Hydraulic or hydrologic models were used to create the modeled time series; index-velocity methods or gate-opening ratings coupled with hydropower operation data were used to create the computed time series. The time step of the various instantaneous streamflow time series ranged from 15 minutes to 24 hours (once-daily values at 12:00 Coordinated Universal Time [UTC]). The 15-minute time-series data, computed by the USGS for the Sardis gage, also were downsampled to 1-hour and 24-hour time steps to permit more direct comparisons with other streamflow time series.
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Past and future changes of streamflow in Poyang Lake Basin, Southeastern China
Directory of Open Access Journals (Sweden)
S. L. Sun
2012-07-01
Full Text Available To understand the causes of the past water cycle variations and the influence of climate variability on the streamflow, lake storage, and flood potential, we analyze the changes in streamflow and the underlying drivers in four typical watersheds (Gaosha, Meigang, Saitang, and Xiashan within the Poyang Lake Basin, based on the meteorological observations at 79 weather stations, and datasets of streamflow and river level at four hydrological stations for the period of 1961-2000. The contribution of different climate factors to the change in streamflow in each watershed is estimated quantitatively using the water balance equations. Results show that in each watershed, the annual streamflow exhibits an increasing trend from 1961–2000. The increases in streamflow by 4.80 m3 s−1 yr−1 and 1.29 m3 s−1 yr−1 at Meigang and Gaosha, respectively, are statistically significant at the 5% level. The increase in precipitation is the biggest contributor to the streamflow increment in Meigang (3.79 m3 s−1 yr−1, Gaosha (1.12 m3 s−1 yr−1, and Xiashan (1.34 m3 s−1 yr−1, while the decrease in evapotranspiration is the major factor controlling the streamflow increment in Saitang (0.19 m3 s−1 yr−1. In addition, radiation and wind contribute more than actual vapor pressure and mean temperature to the changes in evapotranspiration and streamflow for the four watersheds.
For revealing the possible change of streamflow due to the future climate change, we also investigate the projected precipitation and evapotranspiration from of the Coupled Model Intercomparison Project phase 3 (CMIP3 under three greenhouse gases emission scenarios (SRESA1B, SRESA2 and SRESB1 for the period of 2061–2100. When the future changes in the soil water storage -
Mississippi River streamflow measurement techniques at St. Louis, Missouri
Wastson, Chester C.; Holmes, Robert R.; Biedenham, David S.
2013-01-01
Streamflow measurement techniques of the Mississippi River at St. Louis have changed through time (1866–present). In addition to different methods used for discrete streamflow measurements, the density and range of discrete measurements used to define the rating curve (stage versus streamflow) have also changed. Several authors have utilized published water surface elevation (stage) and streamflow data to assess changes in the rating curve, which may be attributed to be caused by flood control and/or navigation structures. The purpose of this paper is to provide a thorough review of the available flow measurement data and techniques and to assess how a strict awareness of the limitations of the data may affect previous analyses. It is concluded that the pre-1930s discrete streamflow measurement data are not of sufficient accuracy to be compared with modern streamflow values in establishing long-term trends of river behavior.
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CrowdWater - Can people observe what models need?
van Meerveld, I. H. J.; Seibert, J.; Vis, M.; Etter, S.; Strobl, B.
2017-12-01
CrowdWater (www.crowdwater.ch) is a citizen science project that explores the usefulness of crowd-sourced data for hydrological model calibration and prediction. Hydrological models are usually calibrated based on observed streamflow data but it is likely easier for people to estimate relative stream water levels, such as the water level above or below a rock, than streamflow. Relative stream water levels may, therefore, be a more suitable variable for citizen science projects than streamflow. In order to test this assumption, we held surveys near seven different sized rivers in Switzerland and asked more than 450 volunteers to estimate the water level class based on a picture with a virtual staff gauge. The results show that people can generally estimate the relative water level well, although there were also a few outliers. We also asked the volunteers to estimate streamflow based on the stick method. The median estimated streamflow was close to the observed streamflow but the spread in the streamflow estimates was large and there were very large outliers, suggesting that crowd-based streamflow data is highly uncertain. In order to determine the potential value of water level class data for model calibration, we converted streamflow time series for 100 catchments in the US to stream level class time series and used these to calibrate the HBV model. The model was then validated using the streamflow data. The results of this modeling exercise show that stream level class data are useful for constraining a simple runoff model. Time series of only two stream level classes, e.g. above or below a rock in the stream, were already informative, especially when the class boundary was chosen towards the highest stream levels. There was hardly any improvement in model performance when more than five water level classes were used. This suggests that if crowd-sourced stream level observations are available for otherwise ungauged catchments, these data can be used to constrain
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Jimeno-Saez, Patricia; Pegalajar-Cuellar, Manuel; Pulido-Velazquez, David
2017-04-01
This study explores techniques of modeling water inflow series, focusing on techniques of short-term steamflow prediction. An appropriate estimation of streamflow in advance is necessary to anticipate measures to mitigate the impacts and risks related to drought conditions. This study analyzes the prediction of future streamflow of nineteen subbasins in the Alto-Genil basin in Granada (Southeast of Spain). Some of these basin streamflow have an important component of snowmelt due to part of the system is located in Sierra Nevada Mountain Range, the highest mountain of continental Spain. Streamflow prediction models have been calibrated using time series of historical natural streamflows. The available streamflow measurements have been downloaded from several public data sources. These original data have been preprocessed to turn them to the original natural regime, removing the anthropic effects. The missing values in the adopted horizon period to calibrate the prediction models have been estimated by using a Temez hydrological balance model, approaching the snowmelt processes with a hybrid degree day method. In the experimentation, ARIMA models are used as baseline method, and recurrent neural networks ELMAN and nonlinear autoregressive neural network (NAR) to test if the prediction accuracy can be improved. After performing the multiple experiments with these models, non-parametric statistical tests are applied to select the best of these techniques. In the experiments carried out with ARIMA, it is concluded that ARIMA models are not adequate in this case study due to the existence of a nonlinear component that cannot be modeled. Secondly, ELMAN and NAR neural networks with multi-start training is performed with each network structure to deal with the local optimum problem, since in neural network training there is a very strong dependence on the initial weights of the network. The obtained results suggest that both neural networks are efficient for the short
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Human influences on streamflow drought characteristics in England and Wales
Tijdeman, Erik; Hannaford, Jamie; Stahl, Kerstin
2018-02-01
Human influences can affect streamflow drought characteristics and propagation. The question is where, when and why? To answer these questions, the impact of different human influences on streamflow droughts were assessed in England and Wales, across a broad range of climate and catchments conditions. We used a dataset consisting of catchments with near-natural flow as well as catchments for which different human influences have been indicated in the metadata (Factors Affecting Runoff) of the UK National River Flow Archive (NRFA). A screening approach was applied on the streamflow records to identify human-influenced records with drought characteristics that deviated from those found for catchments with near-natural flow. Three different deviations were considered, specifically deviations in (1) the relationship between streamflow drought duration and the base flow index, BFI (specifically, BFIHOST, the BFI predicted from the hydrological properties of soils), (2) the correlation between streamflow and precipitation and (3) the temporal occurrence of streamflow droughts compared to precipitation droughts, i.e. an increase or decrease in streamflow drought months relative to precipitation drought months over the period of record. The identified deviations were then related to the indicated human influences. Results showed that the majority of catchments for which human influences were indicated did not show streamflow drought characteristics that deviated from those expected under near-natural conditions. For the catchments that did show deviating streamflow drought characteristics, prolonged streamflow drought durations were found in some of the catchments affected by groundwater abstractions. Weaker correlations between streamflow and precipitation were found for some of the catchments with reservoirs, water transfers or groundwater augmentation schemes. An increase in streamflow drought occurrence towards the end of their records was found for some of the
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Human influences on streamflow drought characteristics in England and Wales
Directory of Open Access Journals (Sweden)
E. Tijdeman
2018-02-01
Full Text Available Human influences can affect streamflow drought characteristics and propagation. The question is where, when and why? To answer these questions, the impact of different human influences on streamflow droughts were assessed in England and Wales, across a broad range of climate and catchments conditions. We used a dataset consisting of catchments with near-natural flow as well as catchments for which different human influences have been indicated in the metadata (Factors Affecting Runoff of the UK National River Flow Archive (NRFA. A screening approach was applied on the streamflow records to identify human-influenced records with drought characteristics that deviated from those found for catchments with near-natural flow. Three different deviations were considered, specifically deviations in (1 the relationship between streamflow drought duration and the base flow index, BFI (specifically, BFIHOST, the BFI predicted from the hydrological properties of soils, (2 the correlation between streamflow and precipitation and (3 the temporal occurrence of streamflow droughts compared to precipitation droughts, i.e. an increase or decrease in streamflow drought months relative to precipitation drought months over the period of record. The identified deviations were then related to the indicated human influences. Results showed that the majority of catchments for which human influences were indicated did not show streamflow drought characteristics that deviated from those expected under near-natural conditions. For the catchments that did show deviating streamflow drought characteristics, prolonged streamflow drought durations were found in some of the catchments affected by groundwater abstractions. Weaker correlations between streamflow and precipitation were found for some of the catchments with reservoirs, water transfers or groundwater augmentation schemes. An increase in streamflow drought occurrence towards the end of their records was found for
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Predictability of soil moisture and streamflow on subseasonal timescales: A case study
Orth, Rene; Seneviratne, Sonia I.
2013-10-01
Hydrological forecasts constitute an important tool in water resource management, especially in the case of impending extreme events. This study investigates the potential predictability of soil moisture and streamflow in Switzerland using a conceptual model including a simple water balance representation and a snow module. Our results show that simulated soil moisture and streamflow are more predictable (as indicated by significantly improved performance compared to climatology) until lead times of approximately 1 week and 2-3 days, respectively, when using initial soil moisture information and climatological atmospheric forcing. Using also initial snow information and seasonal weather forecasts as forcing, the predictable lead time doubles in case of soil moisture and triples for streamflow. The skill contributions of the additional information vary with altitude; at low altitudes the precipitation forecast is most important, whereas in mountainous areas the temperature forecast and the initial snow information are the most valuable contributors. We find furthermore that the soil moisture and streamflow forecast skills increase with increasing initial soil moisture anomalies. Comparing the respective value of realistic initial conditions and state-of-the-art forcing forecasts, we show that the former are generally more important for soil moisture forecasts, whereas the latter are more valuable for streamflow forecasts. To relate the derived predictabilities to respective soil moisture and streamflow memories investigated in other publications, we additionally illustrate the similarity between the concepts of memory and predictability as measures of persistence in the last part of this study.
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Streamflow characteristics at hydrologic bench-mark stations
Lawrence, C.L.
1987-01-01
The Hydrologic Bench-Mark Network was established in the 1960's. Its objectives were to document the hydrologic characteristics of representative undeveloped watersheds nationwide and to provide a comparative base for studying the effects of man on the hydrologic environment. The network, which consists of 57 streamflow gaging stations and one lake-stage station in 39 States, is planned for permanent operation. This interim report describes streamflow characteristics at each bench-mark site and identifies time trends in annual streamflow that have occurred during the data-collection period. The streamflow characteristics presented for each streamflow station are (1) flood and low-flow frequencies, (2) flow duration, (3) annual mean flow, and (4) the serial correlation coefficient for annual mean discharge. In addition, Kendall's tau is computed as an indicator of time trend in annual discharges. The period of record for most stations was 13 to 17 years, although several stations had longer periods of record. The longest period was 65 years for Merced River near Yosemite, Calif. Records of flow at 6 of 57 streamflow sites in the network showed a statistically significant change in annual mean discharge over the period of record, based on computations of Kendall's tau. The values of Kendall's tau ranged from -0.533 to 0.648. An examination of climatological records showed that changes in precipitation were most likely the cause for the change in annual mean discharge.
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Linhart, S. Mike; Nania, Jon F.; Sanders, Curtis L.; Archfield, Stacey A.
2012-01-01
linear regression method and the daily mean streamflow for the 15th day of every other month. The Flow Duration Curve Transfer method was used to estimate unregulated daily mean streamflow from the physical and climatic characteristics of gaged basins. For the Flow Duration Curve Transfer method, daily mean streamflow quantiles at the ungaged site were estimated with the parameter-based regression model, which results in a continuous daily flow-duration curve (the relation between exceedance probability and streamflow for each day of observed streamflow) at the ungaged site. By the use of a reference streamgage, the Flow Duration Curve Transfer is converted to a time series. Data used in the Flow Duration Curve Transfer method were retrieved for 113 continuous-record streamgages in Iowa and within a 50-mile buffer of Iowa. The final statewide regression equations for Iowa were computed by using a weighted-least-squares multiple linear regression method and were computed for the 0.01-, 0.05-, 0.10-, 0.15-, 0.20-, 0.30-, 0.40-, 0.50-, 0.60-, 0.70-, 0.80-, 0.85-, 0.90-, and 0.95-exceedance probability statistics determined from the daily mean streamflow with a reporting limit set at 0.1 ft3/s. The final statewide regression equation for Iowa computed by using left-censored regression techniques was computed for the 0.99-exceedance probability statistic determined from the daily mean streamflow with a low limit threshold and a reporting limit set at 0.1 ft3/s. For the Flow Anywhere method, results of the validation study conducted by using six streamgages show that differences between the root-mean-square error and the mean absolute error ranged from 1,016 to 138 ft3/s, with the larger value signifying a greater occurrence of outliers between observed and estimated streamflows. Root-mean-square-error values ranged from 1,690 to 237 ft3/s. Values of the percent root-mean-square error ranged from 115 percent to 26.2 percent. The logarithm (base 10) streamflow percent root
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Streamflow conditions along Soldier Creek, Northeast Kansas
Juracek, Kyle E.
2017-11-14
The availability of adequate water to meet the present (2017) and future needs of humans, fish, and wildlife is a fundamental issue for the Prairie Band Potawatomi Nation in northeast Kansas. Because Soldier Creek flows through the Prairie Band Potawatomi Nation Reservation, it is an important tribal resource. An understanding of historical Soldier Creek streamflow conditions is required for the effective management of tribal water resources, including drought contingency planning. Historical data for six selected U.S. Geological Survey (USGS) streamgages along Soldier Creek were used in an assessment of streamflow characteristics and trends by Juracek (2017). Streamflow data for the period of record at each streamgage were used to compute annual mean streamflow, annual mean base flow, mean monthly flow, annual peak flow, and annual minimum flow. Results of the assessment are summarized in this fact sheet.
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Department of Homeland Security — This map layer shows selected streamflow gaging stations of the United States, Puerto Rico, and the U.S. Virgin Islands, in 2013. Gaging stations, or gages, measure...
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Characteristics and changes of streamflow on the Tibetan Plateau: A review
Directory of Open Access Journals (Sweden)
Lan Cuo
2014-11-01
New hydrological insights for the region: Streamflow follows the monthly patterns of precipitation and temperature in that all peak in May–September. Streamflow changes are affected by climate change and human activities depending on the basins. Streamflow is precipitation dominated in the northern, eastern and southeastern basins. In the central and western basin either melt water or groundwater, or both contributes significantly to streamflow. Human activities have altered streamflow in the lower reaches of the eastern, northern and western basins. Long-term trends in streamflow vary with basins. Outstanding research issues include: (1 What are the linkages between streamflow and climate systems? (2 What are the basin-wide hydrological processes? And (3 What are the cryospheric change impacts on hydrological processes and water balance?
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Seasonal Patterns of Gastrointestinal Illness and Streamflow along the Ohio River
Directory of Open Access Journals (Sweden)
Elena N. Naumova
2012-05-01
Full Text Available Waterborne gastrointestinal (GI illnesses demonstrate seasonal increases associated with water quality and meteorological characteristics. However, few studies have been conducted on the association of hydrological parameters, such as streamflow, and seasonality of GI illnesses. Streamflow is correlated with biological contamination and can be used as proxy for drinking water contamination. We compare seasonal patterns of GI illnesses in the elderly (65 years and older along the Ohio River for a 14-year period (1991–2004 to seasonal patterns of streamflow. Focusing on six counties in close proximity to the river, we compiled weekly time series of hospitalizations for GI illnesses and streamflow data. Seasonal patterns were explored using Poisson annual harmonic regression with and without adjustment for streamflow. GI illnesses demonstrated significant seasonal patterns with peak timing preceding peak timing of streamflow for all six counties. Seasonal patterns of illness remain consistent after adjusting for streamflow. This study found that the time of peak GI illness precedes the peak of streamflow, suggesting either an indirect relationship or a more direct path whereby pathogens enter water supplies prior to the peak in streamflow. Such findings call for interdisciplinary research to better understand associations among streamflow, pathogen loading, and rates of gastrointestinal illnesses.
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Seasonal streamflow prediction by a combined climate-hydrologic system for river basins of Taiwan
Kuo, Chun-Chao; Gan, Thian Yew; Yu, Pao-Shan
2010-06-01
SummaryA combined, climate-hydrologic system with three components to predict the streamflow of two river basins of Taiwan at one season (3-month) lead time for the NDJ and JFM seasons was developed. The first component consists of the wavelet-based, ANN-GA model (Artificial Neural Network calibrated by Genetic Algorithm) which predicts the seasonal rainfall by using selected sea surface temperature (SST) as predictors, given that SST are generally predictable by climate models up to 6-month lead time. For the second component, three disaggregation models, Valencia and Schaake (VS), Lane, and Canonical Random Cascade Model (CRCM), were tested to compare the accuracy of seasonal rainfall disaggregated by these three models to 3-day time scale rainfall data. The third component consists of the continuous rainfall-runoff model modified from HBV (called the MHBV) and calibrated by a global optimization algorithm against the observed rainfall and streamflow data of the Shihmen and Tsengwen river basins of Taiwan. The proposed system was tested, first by disaggregating the predicted seasonal rainfall of ANN-GA to rainfall of 3-day time step using the Lane model; then the disaggregated rainfall data was used to drive the calibrated MHBV to predict the streamflow for both river basins at 3-day time step up to a season's lead time. Overall, the streamflow predicted by this combined system for the NDJ season, which is better than that of the JFM season, will be useful for the seasonal planning and management of water resources of these two river basins of Taiwan.
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Travel Times, Streamflow Velocities, and Dispersion Rates in the Yellowstone River, Montana
McCarthy, Peter M.
2009-01-01
The Yellowstone River is a vital natural resource to the residents of southeastern Montana and is a primary source of water for irrigation and recreation and the primary source of municipal water for several cities. The Yellowstone River valley is the primary east-west transportation corridor through southern Montana. This complex of infrastructure makes the Yellowstone River especially vulnerable to accidental spills from various sources such as tanker cars and trucks. In 2008, the U.S. Geological Survey (USGS), in cooperation with the Montana Department of Environmental Quality, initiated a dye-tracer study to determine instream travel times, streamflow velocities, and dispersion rates for the Yellowstone River from Lockwood to Glendive, Montana. The purpose of this report is to describe the results of this study and summarize data collected at each of the measurement sites between Lockwood and Glendive. This report also compares the results of this study to estimated travel times from a transport model developed by the USGS for a previous study. For this study, Rhodamine WT dye was injected at four locations in late September and early October 2008 during reasonably steady streamflow conditions. Streamflows ranged from 3,490 to 3,770 cubic feet per second upstream from the confluence of the Bighorn River and ranged from 6,520 to 7,570 cubic feet per second downstream from the confluence of the Bighorn River. Mean velocities were calculated for each subreach between measurement sites for the leading edge, peak concentration, centroid, and trailing edge at 10 percent of the peak concentration. Calculated velocities for the centroid of the dye plume for subreaches that were completely laterally mixed ranged from 1.83 to 3.18 ft/s within the study reach from Lockwood Bridge to Glendive Bridge. The mean of the completely mixed centroid velocity for the entire study reach, excluding the subreach between Forsyth Bridge and Cartersville Dam, was 2.80 ft/s. Longitudinal
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Vining, Kevin C.; Vecchia, Aldo V.
2014-01-01
The U.S. Geological Survey, in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, used the stochastic monthly water-balance model and existing climate data to estimate monthly streamflows for 1951–2010 for selected streamgaging stations located within the Aynak copper, cobalt, and chromium area of interest in Afghanistan. The model used physically based, nondeterministic methods to estimate the monthly volumetric water-balance components of a watershed. A comparison of estimated and recorded monthly streamflows for the streamgaging stations Kabul River at Maidan and Kabul River at Tangi-Saidan indicated that the stochastic water-balance model was able to provide satisfactory estimates of monthly streamflows for high-flow months and low-flow months even though withdrawals for irrigation likely occurred. A comparison of estimated and recorded monthly streamflows for the streamgaging stations Logar River at Shekhabad and Logar River at Sangi-Naweshta also indicated that the stochastic water-balance model was able to provide reasonable estimates of monthly streamflows for the high-flow months; however, for the upstream streamgaging station, the model overestimated monthly streamflows during periods when summer irrigation withdrawals likely occurred. Results from the stochastic water-balance model indicate that the model should be able to produce satisfactory estimates of monthly streamflows for locations along the Kabul and Logar Rivers. This information could be used by Afghanistan authorities to make decisions about surface-water resources for the Aynak copper, cobalt, and chromium area of interest.
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Can longer forest harvest intervals increase summer streamflow for salmon recovery?
The Mashel Streamflow Modeling Project in the Mashel River Basin, Washington, is using a watershed-scale ecohydrological model to assess whether longer forest harvest intervals can remediate summer low flow conditions that have contributed to sharply reduced runs of spawning Chin...
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Do, Hong Xuan; Gudmundsson, Lukas; Leonard, Michael; Westra, Seth
2018-04-01
This is the first part of a two-paper series presenting the Global Streamflow Indices and Metadata archive (GSIM), a worldwide collection of metadata and indices derived from more than 35 000 daily streamflow time series. This paper focuses on the compilation of the daily streamflow time series based on 12 free-to-access streamflow databases (seven national databases and five international collections). It also describes the development of three metadata products (freely available at https://doi.pangaea.de/10.1594/PANGAEA.887477" target="_blank">https://doi.pangaea.de/10.1594/PANGAEA.887477): (1) a GSIM catalogue collating basic metadata associated with each time series, (2) catchment boundaries for the contributing area of each gauge, and (3) catchment metadata extracted from 12 gridded global data products representing essential properties such as land cover type, soil type, and climate and topographic characteristics. The quality of the delineated catchment boundary is also made available and should be consulted in GSIM application. The second paper in the series then explores production and analysis of streamflow indices. Having collated an unprecedented number of stations and associated metadata, GSIM can be used to advance large-scale hydrological research and improve understanding of the global water cycle.
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Directory of Open Access Journals (Sweden)
H. X. Do
2018-04-01
Full Text Available This is the first part of a two-paper series presenting the Global Streamflow Indices and Metadata archive (GSIM, a worldwide collection of metadata and indices derived from more than 35 000 daily streamflow time series. This paper focuses on the compilation of the daily streamflow time series based on 12 free-to-access streamflow databases (seven national databases and five international collections. It also describes the development of three metadata products (freely available at https://doi.pangaea.de/10.1594/PANGAEA.887477: (1 a GSIM catalogue collating basic metadata associated with each time series, (2 catchment boundaries for the contributing area of each gauge, and (3 catchment metadata extracted from 12 gridded global data products representing essential properties such as land cover type, soil type, and climate and topographic characteristics. The quality of the delineated catchment boundary is also made available and should be consulted in GSIM application. The second paper in the series then explores production and analysis of streamflow indices. Having collated an unprecedented number of stations and associated metadata, GSIM can be used to advance large-scale hydrological research and improve understanding of the global water cycle.
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Tolley, D. G., III; Foglia, L.; Harter, T.
2017-12-01
Late summer and early fall streamflow decreases caused by climate change and agricultural pumping contribute to increased water temperatures and result in large disconnected sections during dry years in many semi-arid regions with Mediterranean climate. This negatively impacts aquatic habitat of fish species such as coho and fall-run Chinook salmon. In collaboration with local stakeholders, the Scott Valley Integrated Hydrologic Model (SVIHMv3) was developed to assess future water management scenarios with the goal of improving aquatic species habitat while maintaining agricultural production in the valley. The Null Space Monte Carlo (NSMC) method available in PEST was used to quantify the range of predicted streamflow changes for three conjunctive use scenarios: 1) managed aquifer recharge (MAR), 2) in lieu recharge (ILR, substituting surface-water irrigation for irrigation with groundwater while flows are available), and 3) MAR + ILR. Random parameter sets were generated using the calibrated covariance matrix of the model, which were then recalibrated if the sum of squared residuals was greater than 10% of the original sum of squared weighted residuals. These calibration-constrained stochastic parameter sets were then used to obtain a distribution of streamflow changes resulting from implementing the conjunctive use scenarios. Preliminary results show that while the range of streamflow increases using managed aquifer recharge is much narrower (i.e., greater degree of certainty) than in lieu recharge, there are potentially much greater benefits to streamflow by implementing in lieu recharge (although also greater costs). Combining the two scenarios provides the greatest benefit for increasing late summer and early fall streamflow, as most of the MAR streamflow increases are during the spring and early summer which ILR is able to take advantage of. Incorporation of uncertainty into model predictions is critical for establishing and maintaining stakeholder trust
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Macroinvertebrate community change associated with the severity of streamflow alteration
Carlisle, Daren M.; Eng, Kenny; Nelson, S.M.
2014-01-01
Natural streamflows play a critical role in stream ecosystems, yet quantitative relations between streamflow alteration and stream health have been elusive. One reason for this difficulty is that neither streamflow alteration nor ecological responses are measured relative to their natural expectations. We assessed macroinvertebrate community condition in 25 mountain streams representing a large gradient of streamflow alteration, which we quantified as the departure of observed flows from natural expectations. Observed flows were obtained from US Geological Survey streamgaging stations and discharge records from dams and diversion structures. During low-flow conditions in September, samples of macroinvertebrate communities were collected at each site, in addition to measures of physical habitat, water chemistry and organic matter. In general, streamflows were artificially high during summer and artificially low throughout the rest of the year. Biological condition, as measured by richness of sensitive taxa (Ephemeroptera, Plecoptera and Trichoptera) and taxonomic completeness (O/E), was strongly and negatively related to the severity of depleted flows in winter. Analyses of macroinvertebrate traits suggest that taxa losses may have been caused by thermal modification associated with streamflow alteration. Our study yielded quantitative relations between the severity of streamflow alteration and the degree of biological impairment and suggests that water management that reduces streamflows during winter months is likely to have negative effects on downstream benthic communities in Utah mountain streams.
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Van Tiel, Marit; Teuling, Adriaan J.; Wanders, Niko; Vis, Marc J. P.; Stahl, Kerstin; Van Loon, Anne F.
2018-01-01
Glaciers are essential hydrological reservoirs, storing and releasing water at various timescales. Short-term variability in glacier melt is one of the causes of streamflow droughts, here defined as deficiencies from the flow regime. Streamflow droughts in glacierised catchments have a wide range of interlinked causing factors related to precipitation and temperature on short and long timescales. Climate change affects glacier storage capacity, with resulting consequences for discharge regimes and streamflow drought. Future projections of streamflow drought in glacierised basins can, however, strongly depend on the modelling strategies and analysis approaches applied. Here, we examine the effect of different approaches, concerning the glacier modelling and the drought threshold, on the characterisation of streamflow droughts in glacierised catchments. Streamflow is simulated with the Hydrologiska Byråns Vattenbalansavdelning (HBV-light) model for two case study catchments, the Nigardsbreen catchment in Norway and the Wolverine catchment in Alaska, and two future climate change scenarios (RCP4.5 and RCP8.5). Two types of glacier modelling are applied, a constant and dynamic glacier area conceptualisation. Streamflow droughts are identified with the variable threshold level method and their characteristics are compared between two periods, a historical (1975-2004) and future (2071-2100) period. Two existing threshold approaches to define future droughts are employed: (1) the threshold from the historical period; (2) a transient threshold approach, whereby the threshold adapts every year in the future to the changing regimes. Results show that drought characteristics differ among the combinations of glacier area modelling and thresholds. The historical threshold combined with a dynamic glacier area projects extreme increases in drought severity in the future, caused by the regime shift due to a reduction in glacier area. The historical threshold combined with a
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Granato, Gregory E.; Ries, Kernell G.; Steeves, Peter A.
2017-10-16
Streamflow statistics are needed by decision makers for many planning, management, and design activities. The U.S. Geological Survey (USGS) StreamStats Web application provides convenient access to streamflow statistics for many streamgages by accessing the underlying StreamStatsDB database. In 2016, non-interpretive streamflow statistics were compiled for streamgages located throughout the Nation and stored in StreamStatsDB for use with StreamStats and other applications. Two previously published USGS computer programs that were designed to help calculate streamflow statistics were updated to better support StreamStats as part of this effort. These programs are named “GNWISQ” (Get National Water Information System Streamflow (Q) files), updated to version 1.1.1, and “QSTATS” (Streamflow (Q) Statistics), updated to version 1.1.2.Statistics for 20,438 streamgages that had 1 or more complete years of record during water years 1901 through 2015 were calculated from daily mean streamflow data; 19,415 of these streamgages were within the conterminous United States. About 89 percent of the 20,438 streamgages had 3 or more years of record, and about 65 percent had 10 or more years of record. Drainage areas of the 20,438 streamgages ranged from 0.01 to 1,144,500 square miles. The magnitude of annual average streamflow yields (streamflow per square mile) for these streamgages varied by almost six orders of magnitude, from 0.000029 to 34 cubic feet per second per square mile. About 64 percent of these streamgages did not have any zero-flow days during their available period of record. The 18,122 streamgages with 3 or more years of record were included in the StreamStatsDB compilation so they would be available via the StreamStats interface for user-selected streamgages. All the statistics are available in a USGS ScienceBase data release.
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On the sensitivity of annual streamflow to air temperature
Milly, Paul C.D.; Kam, Jonghun; Dunne, Krista A.
2018-01-01
Although interannual streamflow variability is primarily a result of precipitation variability, temperature also plays a role. The relative weakness of the temperature effect at the annual time scale hinders understanding, but may belie substantial importance on climatic time scales. Here we develop and evaluate a simple theory relating variations of streamflow and evapotranspiration (E) to those of precipitation (P) and temperature. The theory is based on extensions of the Budyko water‐balance hypothesis, the Priestley‐Taylor theory for potential evapotranspiration ( ), and a linear model of interannual basin storage. The theory implies that the temperature affects streamflow by modifying evapotranspiration through a Clausius‐Clapeyron‐like relation and through the sensitivity of net radiation to temperature. We apply and test (1) a previously introduced “strong” extension of the Budyko hypothesis, which requires that the function linking temporal variations of the evapotranspiration ratio (E/P) and the index of dryness ( /P) at an annual time scale is identical to that linking interbasin variations of the corresponding long‐term means, and (2) a “weak” extension, which requires only that the annual evapotranspiration ratio depends uniquely on the annual index of dryness, and that the form of that dependence need not be known a priori nor be identical across basins. In application of the weak extension, the readily observed sensitivity of streamflow to precipitation contains crucial information about the sensitivity to potential evapotranspiration and, thence, to temperature. Implementation of the strong extension is problematic, whereas the weak extension appears to capture essential controls of the temperature effect efficiently.
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Lara, Antonio; Bahamondez, Alejandra; González-Reyes, Alvaro; Muñoz, Ariel A.; Cuq, Emilio; Ruiz-Gómez, Carolina
2015-10-01
The understanding of the long-term variation of large rivers streamflow with a high economic and social relevance is necessary in order to improve the planning and management of water resources in different regions of the world. The Baker River has the highest mean discharge of those draining both slopes of the Andes South of 20°S and it is among the six rivers with the highest mean streamflow in the Pacific domain of South America (1100 m3 s-1 at its outlet). It drains an international basin of 29,000 km2 shared by Chile and Argentina and has a high ecologic and economic value including conservation, tourism, recreational fishing, and projected hydropower. This study reconstructs the austral summer - early fall (January-April) streamflow for the Baker River from Nothofagus pumilio tree-rings for the period 1765-2004. Summer streamflow represents 45.2% of the annual discharge. The regression model for the period (1961-2004) explains 54% of the variance of the Baker River streamflow (R2adj = 0.54). The most significant temporal pattern in the record is the sustained decline since the 1980s (τ = -0.633, p = 1.0144 ∗ 10-5 for the 1985-2004 period), which is unprecedented since 1765. The Correlation of the Baker streamflow with the November-April observed Southern Annular Mode (SAM) is significant (1961-2004, r = -0.55, p < 0.001). The Baker record is also correlated with the available SAM tree-ring reconstruction based on other species when both series are filtered with a 25-year spline and detrended (1765-2004, r = -0.41, p < 0.01), emphasizing SAM as the main climatic forcing of the Baker streamflow. Three of the five summers with the highest streamflow in the entire reconstructed record occurred after the 1950s (1977, 1958 and 1959). The causes of this high streamflow events are not yet clear and cannot be associated with the reported recent increase in the frequency of glacial-lake outburst floods (GLOFs). The decreasing trend in the observed and reconstructed
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Lehner, F.; Wood, A.; Llewellyn, D.; Blatchford, D. B.; Goodbody, A. G.; Pappenberger, F.
2017-12-01
Recent studies have documented the influence of increasing temperature on streamflow across the American West, including snow-melt driven rivers such as the Colorado or Rio Grande. At the same time, some basins are reporting decreasing skill in seasonal streamflow forecasts, termed water supply forecasts (WSFs), over the recent decade. While the skill in seasonal precipitation forecasts from dynamical models remains low, their skill in predicting seasonal temperature variations could potentially be harvested for WSFs to account for non-stationarity in regional temperatures. Here, we investigate whether WSF skill can be improved by incorporating seasonal temperature forecasts from dynamical forecasting models (from the North American Multi Model Ensemble and the European Centre for Medium-Range Weather Forecast System 4) into traditional statistical forecast models. We find improved streamflow forecast skill relative to traditional WSF approaches in a majority of headwater locations in the Colorado and Rio Grande basins. Incorporation of temperature into WSFs thus provides a promising avenue to increase the robustness of current forecasting techniques in the face of continued regional warming.
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Directory of Open Access Journals (Sweden)
Ying Zhang
2017-09-01
Full Text Available Streamflow estimates are substantially important as fresh water shortages increase in arid and semi-arid regions where evapotranspiration (ET is a significant contribution to the water balance. In this regard, evapotranspiration data can be assimilated into a distributed hydrological model (SWAT, Soil and Water Assessment Tool for improving streamflow estimates. The SWAT model has been widely used for streamflow estimations, but the applications combining SWAT and ET products were rare. Thus, this study aims to develop a SWAT-based evapotranspiration data assimilation system. In particular, SWAT is gridded at Hydrologic Response Unit (HRU level to incorporate gridded ET products acquired from the remote sensing-based ETMonitor model. In the modeling case, Gridded SWAT (GSWAT shows a good agreement of streamflow modeling with the original SWAT. Such a scant margin between them is due to the modeling domain mismatch caused by different HRU delineations. In the ET assimilation case, we carry out a synthetic data experiment to illustrate the state augmentation Direct Insertion (DI method and a real data experiment for the upper Heihe River Basin. The results demonstrate the benefits of the ET assimilation for improving hydrologic processes representations. In the future, more remotely sensed data can be assimilated into the data assimilation system to provide more reliable hydrological predictions.
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Shoaib, Syed Abu; Marshall, Lucy; Sharma, Ashish
2018-06-01
Every model to characterise a real world process is affected by uncertainty. Selecting a suitable model is a vital aspect of engineering planning and design. Observation or input errors make the prediction of modelled responses more uncertain. By way of a recently developed attribution metric, this study is aimed at developing a method for analysing variability in model inputs together with model structure variability to quantify their relative contributions in typical hydrological modelling applications. The Quantile Flow Deviation (QFD) metric is used to assess these alternate sources of uncertainty. The Australian Water Availability Project (AWAP) precipitation data for four different Australian catchments is used to analyse the impact of spatial rainfall variability on simulated streamflow variability via the QFD. The QFD metric attributes the variability in flow ensembles to uncertainty associated with the selection of a model structure and input time series. For the case study catchments, the relative contribution of input uncertainty due to rainfall is higher than that due to potential evapotranspiration, and overall input uncertainty is significant compared to model structure and parameter uncertainty. Overall, this study investigates the propagation of input uncertainty in a daily streamflow modelling scenario and demonstrates how input errors manifest across different streamflow magnitudes.
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Tanguy, M.; Prudhomme, C.; Harrigan, S.; Smith, K. A.; Parry, S.
2017-12-01
Forecasting hydrological extremes is challenging, especially at lead times over 1 month for catchments with limited hydrological memory and variable climates. One simple way to derive monthly or seasonal hydrological forecasts is to use historical climate data to drive hydrological models using the Ensemble Streamflow Prediction (ESP) method. This gives a range of possible future streamflow given known initial hydrologic conditions alone. The degree of skill of ESP depends highly on the forecast initialisation month and catchment type. Using dynamic rainfall forecasts as driving data instead of historical data could potentially improve streamflow predictions. A lot of effort is being invested within the meteorological community to improve these forecasts. However, while recent progress shows promise (e.g. NAO in winter), the skill of these forecasts at monthly to seasonal timescales is generally still limited, and the extent to which they might lead to improved hydrological forecasts is an area of active research. Additionally, these meteorological forecasts are currently being produced at 1 month or seasonal time-steps in the UK, whereas hydrological models require forcings at daily or sub-daily time-steps. Keeping in mind these limitations of available rainfall forecasts, the objectives of this study are to find out (i) how accurate monthly dynamical rainfall forecasts need to be to outperform ESP, and (ii) how the method used to disaggregate monthly rainfall forecasts into daily rainfall time series affects results. For the first objective, synthetic rainfall time series were created by increasingly degrading observed data (proxy for a `perfect forecast') from 0 % to +/-50 % error. For the second objective, three different methods were used to disaggregate monthly rainfall data into daily time series. These were used to force a simple lumped hydrological model (GR4J) to generate streamflow predictions at a one-month lead time for over 300 catchments
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Liu, Jianyu; Zhang, Qiang; Zhang, Yongqiang; Chen, Xi; Li, Jianfeng; Aryal, Santosh K.
2017-10-01
Climatic elasticity has been widely applied to assess streamflow responses to climate changes. To fully assess impacts of climate under global warming on streamflow and reduce the error and uncertainty from various control variables, we develop a four-parameter (precipitation, catchment characteristics n, and maximum and minimum temperatures) climatic elasticity method named PnT, based on the widely used Budyko framework and simplified Makkink equation. We use this method to carry out the first comprehensive evaluation of the streamflow response to potential climate change for 372 widely spread catchments in China. The PnT climatic elasticity was first evaluated for a period 1980-2000, and then used to evaluate streamflow change response to climate change based on 12 global climate models under Representative Concentration Pathway 2.6 (RCP2.6) and RCP 8.5 emission scenarios. The results show that (1) the PnT climatic elasticity method is reliable; (2) projected increasing streamflow takes place in more than 60% of the selected catchments, with mean increments of 9% and 15.4% under RCP2.6 and RCP8.5 respectively; and (3) uncertainties in the projected streamflow are considerable in several regions, such as the Pearl River and Yellow River, with more than 40% of the selected catchments showing inconsistent change directions. Our results can help Chinese policy makers to manage and plan water resources more effectively, and the PnT climatic elasticity should be applied to other parts of the world.
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Directory of Open Access Journals (Sweden)
C. L. Tague
2013-01-01
Full Text Available Hydrologic models are one of the core tools used to project how water resources may change under a warming climate. These models are typically applied over a range of scales, from headwater streams to higher order rivers, and for a variety of purposes, such as evaluating changes to aquatic habitat or reservoir operation. Most hydrologic models require streamflow data to calibrate subsurface drainage parameters. In many cases, long-term gage records may not be available for calibration, particularly when assessments are focused on low-order stream reaches. Consequently, hydrologic modeling of climate change impacts is often performed in the absence of sufficient data to fully parameterize these hydrologic models. In this paper, we assess a geologic-based strategy for assigning drainage parameters. We examine the performance of this modeling strategy for the McKenzie River watershed in the US Oregon Cascades, a region where previous work has demonstrated sharp contrasts in hydrology based primarily on geological differences between the High and Western Cascades. Based on calibration and verification using existing streamflow data, we demonstrate that: (1 a set of streams ranging from 1st to 3rd order within the Western Cascade geologic region can share the same drainage parameter set, while (2 streams from the High Cascade geologic region require a different parameter set. Further, we show that a watershed comprised of a mixture of High and Western Cascade geologies can be modeled without additional calibration by transferring parameters from these distinctive High and Western Cascade end-member parameter sets. More generally, we show that by defining a set of end-member parameters that reflect different geologic classes, we can more efficiently apply a hydrologic model over a geologically complex landscape and resolve geo-climatic differences in how different watersheds are likely to respond to simple warming scenarios.
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Paul, M.; Negahban-Azar, M.
2017-12-01
The hydrologic models usually need to be calibrated against observed streamflow at the outlet of a particular drainage area through a careful model calibration. However, a large number of parameters are required to fit in the model due to their unavailability of the field measurement. Therefore, it is difficult to calibrate the model for a large number of potential uncertain model parameters. This even becomes more challenging if the model is for a large watershed with multiple land uses and various geophysical characteristics. Sensitivity analysis (SA) can be used as a tool to identify most sensitive model parameters which affect the calibrated model performance. There are many different calibration and uncertainty analysis algorithms which can be performed with different objective functions. By incorporating sensitive parameters in streamflow simulation, effects of the suitable algorithm in improving model performance can be demonstrated by the Soil and Water Assessment Tool (SWAT) modeling. In this study, the SWAT was applied in the San Joaquin Watershed in California covering 19704 km2 to calibrate the daily streamflow. Recently, sever water stress escalating due to intensified climate variability, prolonged drought and depleting groundwater for agricultural irrigation in this watershed. Therefore it is important to perform a proper uncertainty analysis given the uncertainties inherent in hydrologic modeling to predict the spatial and temporal variation of the hydrologic process to evaluate the impacts of different hydrologic variables. The purpose of this study was to evaluate the sensitivity and uncertainty of the calibrated parameters for predicting streamflow. To evaluate the sensitivity of the calibrated parameters three different optimization algorithms (Sequential Uncertainty Fitting- SUFI-2, Generalized Likelihood Uncertainty Estimation- GLUE and Parameter Solution- ParaSol) were used with four different objective functions (coefficient of determination
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Rasmussen, Patrick P.; Gray, John R.; Glysson, G. Douglas; Ziegler, Andrew C.
2009-01-01
In-stream continuous turbidity and streamflow data, calibrated with measured suspended-sediment concentration data, can be used to compute a time series of suspended-sediment concentration and load at a stream site. Development of a simple linear (ordinary least squares) regression model for computing suspended-sediment concentrations from instantaneous turbidity data is the first step in the computation process. If the model standard percentage error (MSPE) of the simple linear regression model meets a minimum criterion, this model should be used to compute a time series of suspended-sediment concentrations. Otherwise, a multiple linear regression model using paired instantaneous turbidity and streamflow data is developed and compared to the simple regression model. If the inclusion of the streamflow variable proves to be statistically significant and the uncertainty associated with the multiple regression model results in an improvement over that for the simple linear model, the turbidity-streamflow multiple linear regression model should be used to compute a suspended-sediment concentration time series. The computed concentration time series is subsequently used with its paired streamflow time series to compute suspended-sediment loads by standard U.S. Geological Survey techniques. Once an acceptable regression model is developed, it can be used to compute suspended-sediment concentration beyond the period of record used in model development with proper ongoing collection and analysis of calibration samples. Regression models to compute suspended-sediment concentrations are generally site specific and should never be considered static, but they represent a set period in a continually dynamic system in which additional data will help verify any change in sediment load, type, and source.
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Streamflow responses in Chile to megathrust earthquakes in the 20th and 21st centuries
Mohr, Christian; Manga, Michael; Wang, Chi-yuen; Korup, Oliver
2016-04-01
Both coseismic static stress and dynamic stresses associated with seismic waves may cause responses in hydrological systems. Such responses include changes in the water level, hydrochemistry and streamflow discharge. Earthquake effects on hydrological systems provide a means to study the interaction between stress changes and regional hydrology, which is otherwise rarely possible. Chile is a country of frequent and large earthquakes and thus provides abundant opportunities to study such interactions and processes. We analyze streamflow responses in Chile to several megathrust earthquakes, including the 1943 Mw 8.1 Coquimbo, 1950 Mw 8.2 Antofagasta, 1960 Mw 9.5 Valdivia, 1985 Mw 8.0 Valparaiso, 1995 Mw 8.0 Antofagasta, 2010 Mw 8.8 Maule, and the 2014 Mw 8.2 Iquique earthquakes. We use data from 716 stream gauges distributed from the Altiplano in the North to Tierra del Fuego in the South. This network covers the Andes mountain ranges, the central valley, the Coastal Mountain ranges and (mainly in the more southern parts) the Coastal flats. We combine empirical magnitude-distance relationships, machine learning tools, and process-based modeling to characterize responses. We first assess the streamflow anomalies and relate these to topographical, hydro-climatic, geological and earthquake-related (volumetric and dynamic strain) factors using various classifiers. We then apply 1D-groundwater flow modeling to selected catchments in order to test competing hypotheses for the origin of streamflow changes. We show that the co-seismic responses of streamflow mostly involved increasing discharges. We conclude that enhanced vertical permeability can explain most streamflow responses at the regional scale. The total excess water released by a single earthquake, i.e. the Maule earthquake, yielded up to 1 km3. Against the background of megathrust earthquakes frequently hitting Chile, the amount of water released by earthquakes is substantial, particularly for the arid northern
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Directory of Open Access Journals (Sweden)
M. Van Tiel
2018-01-01
Full Text Available Glaciers are essential hydrological reservoirs, storing and releasing water at various timescales. Short-term variability in glacier melt is one of the causes of streamflow droughts, here defined as deficiencies from the flow regime. Streamflow droughts in glacierised catchments have a wide range of interlinked causing factors related to precipitation and temperature on short and long timescales. Climate change affects glacier storage capacity, with resulting consequences for discharge regimes and streamflow drought. Future projections of streamflow drought in glacierised basins can, however, strongly depend on the modelling strategies and analysis approaches applied. Here, we examine the effect of different approaches, concerning the glacier modelling and the drought threshold, on the characterisation of streamflow droughts in glacierised catchments. Streamflow is simulated with the Hydrologiska Byråns Vattenbalansavdelning (HBV-light model for two case study catchments, the Nigardsbreen catchment in Norway and the Wolverine catchment in Alaska, and two future climate change scenarios (RCP4.5 and RCP8.5. Two types of glacier modelling are applied, a constant and dynamic glacier area conceptualisation. Streamflow droughts are identified with the variable threshold level method and their characteristics are compared between two periods, a historical (1975–2004 and future (2071–2100 period. Two existing threshold approaches to define future droughts are employed: (1 the threshold from the historical period; (2 a transient threshold approach, whereby the threshold adapts every year in the future to the changing regimes. Results show that drought characteristics differ among the combinations of glacier area modelling and thresholds. The historical threshold combined with a dynamic glacier area projects extreme increases in drought severity in the future, caused by the regime shift due to a reduction in glacier area. The historical
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Streamflow of 2016—Water year summary
Jian, Xiaodong; Wolock, David M.; Lins, Harry F.; Brady, Steven J.
2017-09-26
The maps and graphs in this summary describe national streamflow conditions for water year 2016 (October 1, 2015, to September 30, 2016) in the context of streamflow ranks relative to the 87-year period of 1930–2016, unless otherwise noted. The illustrations are based on observed data from the U.S. Geological Survey’s (USGS) National Streamflow Network. The period of 1930–2016 was used because the number of streamgages before 1930 was too small to provide representative data for computing statistics for most regions of the country.In the summary, reference is made to the term “runoff,” which is the depth to which a river basin, State, or other geographic area would be covered with water if all the streamflow within the area during a specified period was uniformly distributed on it. Runoff quantifies the magnitude of water flowing through the Nation’s rivers and streams in measurement units that can be compared from one area to another.In all the graphics, a rank of 1 indicates the highest flow of all years analyzed and 87 indicates the lowest flow of all years. Rankings of streamflow are grouped into much below normal, below normal, normal, above normal, and much above normal based on percentiles of flow (less than 10 percent, 10–24 percent, 25–75 percent, 76–90 percent, and greater than 90 percent, respectively). Some of the data used to produce the maps and graphs are provisional and subject to change.
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Response of streamflow to projected climate change scenarios in an ...
Indian Academy of Sciences (India)
Snowmelt run-off model (SRM) based on degree-day approach has been employed to evaluate the change in snow-cover depletion and corresponding streamflow under different projected climatic scenarios foran eastern Himalayan catchment in India. Nuranang catchment located at Tawang district of ArunachalPradesh ...
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Substantial proportion of global streamflow less than three months old
Jasechko, Scott; Kirchner, James W.; Welker, Jeffrey M.; McDonnell, Jeffrey J.
2016-02-01
Biogeochemical cycles, contaminant transport and chemical weathering are regulated by the speed at which precipitation travels through landscapes and reaches streams. Streamflow is a mixture of young and old precipitation, but the global proportions of these young and old components are not known. Here we analyse seasonal cycles of oxygen isotope ratios in rain, snow and streamflow compiled from 254 watersheds around the world, and calculate the fraction of streamflow that is derived from precipitation that fell within the past two or three months. This young streamflow accounts for about a third of global river discharge, and comprises at least 5% of discharge in about 90% of the catchments we investigated. We conclude that, although typical catchments have mean transit times of years or even decades, they nonetheless can rapidly transmit substantial fractions of soluble contaminant inputs to streams. Young streamflow is less prevalent in steeper landscapes, which suggests they are characterized by deeper vertical infiltration. Because young streamflow is derived from less than 0.1% of global groundwater storage, we conclude that this thin veneer of aquifer storage will have a disproportionate influence on stream water quality.
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Evaluation of bias-correction methods for ensemble streamflow volume forecasts
Directory of Open Access Journals (Sweden)
T. Hashino
2007-01-01
Full Text Available Ensemble prediction systems are used operationally to make probabilistic streamflow forecasts for seasonal time scales. However, hydrological models used for ensemble streamflow prediction often have simulation biases that degrade forecast quality and limit the operational usefulness of the forecasts. This study evaluates three bias-correction methods for ensemble streamflow volume forecasts. All three adjust the ensemble traces using a transformation derived with simulated and observed flows from a historical simulation. The quality of probabilistic forecasts issued when using the three bias-correction methods is evaluated using a distributions-oriented verification approach. Comparisons are made of retrospective forecasts of monthly flow volumes for a north-central United States basin (Des Moines River, Iowa, issued sequentially for each month over a 48-year record. The results show that all three bias-correction methods significantly improve forecast quality by eliminating unconditional biases and enhancing the potential skill. Still, subtle differences in the attributes of the bias-corrected forecasts have important implications for their use in operational decision-making. Diagnostic verification distinguishes these attributes in a context meaningful for decision-making, providing criteria to choose among bias-correction methods with comparable skill.
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Directory of Open Access Journals (Sweden)
Jaewon Kwak
2016-03-01
Full Text Available Long-term streamflow data are vital for analysis of hydrological droughts. Using an artificial neural network (ANN model and nine tree-ring indices, this study reconstructed the annual streamflow of the Sacramento River for the period from 1560 to 1871. Using the reconstructed streamflow data, the copula method was used for bivariate drought analysis, deriving a hydrological drought return period plot for the Sacramento River basin. Results showed strong correlation among drought characteristics, and the drought with a 20-year return period (17.2 million acre-feet (MAF per year in the Sacramento River basin could be considered a critical level of drought for water shortages.
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Technical note: Combining quantile forecasts and predictive distributions of streamflows
Bogner, Konrad; Liechti, Katharina; Zappa, Massimiliano
2017-11-01
The enhanced availability of many different hydro-meteorological modelling and forecasting systems raises the issue of how to optimally combine this great deal of information. Especially the usage of deterministic and probabilistic forecasts with sometimes widely divergent predicted future streamflow values makes it even more complicated for decision makers to sift out the relevant information. In this study multiple streamflow forecast information will be aggregated based on several different predictive distributions, and quantile forecasts. For this combination the Bayesian model averaging (BMA) approach, the non-homogeneous Gaussian regression (NGR), also known as the ensemble model output statistic (EMOS) techniques, and a novel method called Beta-transformed linear pooling (BLP) will be applied. By the help of the quantile score (QS) and the continuous ranked probability score (CRPS), the combination results for the Sihl River in Switzerland with about 5 years of forecast data will be compared and the differences between the raw and optimally combined forecasts will be highlighted. The results demonstrate the importance of applying proper forecast combination methods for decision makers in the field of flood and water resource management.
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Farmer, William H.; Archfield, Stacey A.; Over, Thomas M.; Hay, Lauren E.; LaFontaine, Jacob H.; Kiang, Julie E.
2015-01-01
Effective and responsible management of water resources relies on a thorough understanding of the quantity and quality of available water. Streamgages cannot be installed at every location where streamflow information is needed. As part of its National Water Census, the U.S. Geological Survey is planning to provide streamflow predictions for ungaged locations. In order to predict streamflow at a useful spatial and temporal resolution throughout the Nation, efficient methods need to be selected. This report examines several methods used for streamflow prediction in ungaged basins to determine the best methods for regional and national implementation. A pilot area in the southeastern United States was selected to apply 19 different streamflow prediction methods and evaluate each method by a wide set of performance metrics. Through these comparisons, two methods emerged as the most generally accurate streamflow prediction methods: the nearest-neighbor implementations of nonlinear spatial interpolation using flow duration curves (NN-QPPQ) and standardizing logarithms of streamflow by monthly means and standard deviations (NN-SMS12L). It was nearly impossible to distinguish between these two methods in terms of performance. Furthermore, neither of these methods requires significantly more parameterization in order to be applied: NN-SMS12L requires 24 regional regressions—12 for monthly means and 12 for monthly standard deviations. NN-QPPQ, in the application described in this study, required 27 regressions of particular quantiles along the flow duration curve. Despite this finding, the results suggest that an optimal streamflow prediction method depends on the intended application. Some methods are stronger overall, while some methods may be better at predicting particular statistics. The methods of analysis presented here reflect a possible framework for continued analysis and comprehensive multiple comparisons of methods of prediction in ungaged basins (PUB
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Prediction of Missing Streamflow Data using Principle of Information Entropy
Directory of Open Access Journals (Sweden)
Santosa, B.
2014-01-01
Full Text Available Incomplete (missing of streamflow data often occurs. This can be caused by a not continous data recording or poor storage. In this study, missing consecutive streamflow data are predicted using the principle of information entropy. Predictions are performed using the complete monthly streamflow information from the nearby river. Data on average monthly streamflow used as a simulation sample are taken from observation stations Katulampa, Batubeulah, and Genteng, which are the Ciliwung Cisadane river areas upstream. The simulated prediction of missing streamflow data in 2002 and 2003 at Katulampa Station are based on information from Genteng Station, and Batubeulah Station. The mean absolute error (MAE average obtained was 0,20 and 0,21 in 2002 and the MAE average in 2003 was 0,12 and 0,16. Based on the value of the error and pattern of filled gaps, this method has the potential to be developed further.
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Hassaballah, Khalid; Mohamed, Yasir; Uhlenbrook, Stefan; Biro, Khalid
2017-10-01
Understanding the land use and land cover changes (LULCCs) and their implication on surface hydrology of the Dinder and Rahad basins (D&R, approximately 77 504 km2) is vital for the management and utilization of water resources in the basins. Although there are many studies on LULCC in the Blue Nile Basin, specific studies on LULCC in the D&R are still missing. Hence, its impact on streamflow is unknown. The objective of this paper is to understand the LULCC in the Dinder and Rahad and its implications on streamflow response using satellite data and hydrological modelling. The hydrological model has been derived by different sets of land use and land cover maps from 1972, 1986, 1998 and 2011. Catchment topography, land cover and soil maps are derived from satellite images and serve to estimate model parameters. Results of LULCC detection between 1972 and 2011 indicate a significant decrease in woodland and an increase in cropland. Woodland decreased from 42 to 14 % and from 35 to 14 % for Dinder and Rahad, respectively. Cropland increased from 14 to 47 % and from 18 to 68 % in Dinder and Rahad, respectively. The model results indicate that streamflow is affected by LULCC in both the Dinder and the Rahad rivers. The effect of LULCC on streamflow is significant during 1986 and 2011. This could be attributed to the severe drought during the mid-1980s and the recent large expansion in cropland.
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Diverse multi-decadal changes in streamflow within a rapidly urbanizing region
Diem, Jeremy E.; Hill, T. Chee; Milligan, Richard A.
2018-01-01
The impact of urbanization on streamflow depends on a variety of factors (e.g., climate, initial land cover, inter-basin transfers, water withdrawals, wastewater effluent, etc.). The purpose of this study is to examine trends in streamflow from 1986 to 2015 in a range of watersheds within the rapidly urbanizing Atlanta, GA metropolitan area. This study compares eight watersheds over three decades, while minimizing the influence of inter-annual precipitation variability. Population and land-cover data were used to analyze changes over approximately twenty years within the watersheds. Precipitation totals for the watersheds were estimated using precipitation totals at nearby weather stations. Multiple streamflow variables, such as annual streamflow, frequencies of high-flow days (HFDs), flashiness, and precipitation-adjusted streamflow, for the eight streams were calculated using daily streamflow data. Variables were tested for significant trends from 1986 to 2015 and significant differences between 1986-2000 and 2001-2015. Flashiness increased for all streams without municipal water withdrawals, and the four watersheds with the largest increase in developed land had significant increases in flashiness. Significant positive trends in precipitation-adjusted mean annual streamflow and HFDs occurred for the two watersheds (Big Creek and Suwanee Creek) that experienced the largest increases in development, and these were the only watersheds that went from majority forest land in 1986 to majority developed land in 2015. With a disproportionate increase in HFD occurrence during summer, Big Creek and Suwannee Creek also had a reduction in intra-annual variability of HFD occurrence. Watersheds that were already substantially developed at the beginning of the period and did not have wastewater discharge had declining streamflow. The most urbanized watershed (Peachtree Creek) had a significant decrease in streamflow, and a possible cause of the decrease was increasing
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International Nuclear Information System (INIS)
Fatichi, S.; Rimkus, S.; Burlando, P.; Bordoy, R.
2014-01-01
Projections of climate change effects in streamflow are increasingly required to plan water management strategies. These projections are however largely uncertain due to the spread among climate model realizations, internal climate variability, and difficulties in transferring climate model results at the spatial and temporal scales required by catchment hydrology. A combination of a stochastic downscaling methodology and distributed hydrological modeling was used in the ACQWA project to provide projections of future streamflow (up to year 2050) for the upper Po and Rhone basins, respectively located in northern Italy and south-western Switzerland. Results suggest that internal (stochastic) climate variability is a fundamental source of uncertainty, typically comparable or larger than the projected climate change signal. Therefore, climate change effects in streamflow mean, frequency, and seasonality can be masked by natural climatic fluctuations in large parts of the analyzed regions. An exception to the overwhelming role of stochastic variability is represented by high elevation catchments fed by glaciers where streamflow is expected to be considerably reduced due to glacier retreat, with consequences appreciable in the main downstream rivers in August and September. Simulations also identify regions (west upper Rhone and Toce, Ticino river basins) where a strong precipitation increase in the February to April period projects streamflow beyond the range of natural climate variability during the melting season. This study emphasizes the importance of including internal climate variability in climate change analyses, especially when compared to the limited uncertainty that would be accounted for by few deterministic projections. The presented results could be useful in guiding more specific impact studies, although design or management decisions should be better based on reliability and vulnerability criteria as suggested by recent literature. - Highlights:
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Energy Technology Data Exchange (ETDEWEB)
Fatichi, S., E-mail: simone.fatichi@ifu.baug.ethz.ch; Rimkus, S.; Burlando, P.; Bordoy, R.
2014-09-15
Projections of climate change effects in streamflow are increasingly required to plan water management strategies. These projections are however largely uncertain due to the spread among climate model realizations, internal climate variability, and difficulties in transferring climate model results at the spatial and temporal scales required by catchment hydrology. A combination of a stochastic downscaling methodology and distributed hydrological modeling was used in the ACQWA project to provide projections of future streamflow (up to year 2050) for the upper Po and Rhone basins, respectively located in northern Italy and south-western Switzerland. Results suggest that internal (stochastic) climate variability is a fundamental source of uncertainty, typically comparable or larger than the projected climate change signal. Therefore, climate change effects in streamflow mean, frequency, and seasonality can be masked by natural climatic fluctuations in large parts of the analyzed regions. An exception to the overwhelming role of stochastic variability is represented by high elevation catchments fed by glaciers where streamflow is expected to be considerably reduced due to glacier retreat, with consequences appreciable in the main downstream rivers in August and September. Simulations also identify regions (west upper Rhone and Toce, Ticino river basins) where a strong precipitation increase in the February to April period projects streamflow beyond the range of natural climate variability during the melting season. This study emphasizes the importance of including internal climate variability in climate change analyses, especially when compared to the limited uncertainty that would be accounted for by few deterministic projections. The presented results could be useful in guiding more specific impact studies, although design or management decisions should be better based on reliability and vulnerability criteria as suggested by recent literature. - Highlights:
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Streamflow prediction using multi-site rainfall obtained from hydroclimatic teleconnection
Kashid, S. S.; Ghosh, Subimal; Maity, Rajib
2010-12-01
SummarySimultaneous variations in weather and climate over widely separated regions are commonly known as "hydroclimatic teleconnections". Rainfall and runoff patterns, over continents, are found to be significantly teleconnected, with large-scale circulation patterns, through such hydroclimatic teleconnections. Though such teleconnections exist in nature, it is very difficult to model them, due to their inherent complexity. Statistical techniques and Artificial Intelligence (AI) tools gain popularity in modeling hydroclimatic teleconnection, based on their ability, in capturing the complicated relationship between the predictors (e.g. sea surface temperatures) and predictand (e.g., rainfall). Genetic Programming is such an AI tool, which is capable of capturing nonlinear relationship, between predictor and predictand, due to its flexible functional structure. In the present study, gridded multi-site weekly rainfall is predicted from El Niño Southern Oscillation (ENSO) indices, Equatorial Indian Ocean Oscillation (EQUINOO) indices, Outgoing Longwave Radiation (OLR) and lag rainfall at grid points, over the catchment, using Genetic Programming. The predicted rainfall is further used in a Genetic Programming model to predict streamflows. The model is applied for weekly forecasting of streamflow in Mahanadi River, India, and satisfactory performance is observed.
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Carlisle, Daren M.; Wolock, David M.; Meador, Michael R.
2011-01-01
Human impacts on watershed hydrology are widespread in the US, but the prevalence and severity of stream-flow alteration and its potential ecological consequences have not been quantified on a national scale. We assessed streamflow alteration at 2888 streamflow monitoring sites throughout the conterminous US. The magnitudes of mean annual (1980–2007) minimum and maximum streamflows were found to have been altered in 86% of assessed streams. The occurrence, type, and severity of streamflow alteration differed markedly between arid and wet climates. Biological assessments conducted on a subset of these streams showed that, relative to eight chemical and physical covariates, diminished flow magnitudes were the primary predictors of biological integrity for fish and macroinvertebrate communities. In addition, the likelihood of biological impairment doubled with increasing severity of diminished streamflows. Among streams with diminished flow magnitudes, increasingly common fish and macroinvertebrate taxa possessed traits characteristic of lake or pond habitats, including a preference for fine-grained substrates and slow-moving currents, as well as the ability to temporarily leave the aquatic environment.
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Simulation of streamflow in the McTier Creek watershed, South Carolina
Feaster, Toby D.; Golden, Heather E.; Odom, Kenneth R.; Lowery, Mark A.; Conrads, Paul; Bradley, Paul M.
2010-01-01
The McTier Creek watershed is located in the Sand Hills ecoregion of South Carolina and is a small catchment within the Edisto River Basin. Two watershed hydrology models were applied to the McTier Creek watershed as part of a larger scientific investigation to expand the understanding of relations among hydrologic, geochemical, and ecological processes that affect fish-tissue mercury concentrations within the Edisto River Basin. The two models are the topography-based hydrological model (TOPMODEL) and the grid-based mercury model (GBMM). TOPMODEL uses the variable-source area concept for simulating streamflow, and GBMM uses a spatially explicit modified curve-number approach for simulating streamflow. The hydrologic output from TOPMODEL can be used explicitly to simulate the transport of mercury in separate applications, whereas the hydrology output from GBMM is used implicitly in the simulation of mercury fate and transport in GBMM. The modeling efforts were a collaboration between the U.S. Geological Survey and the U.S. Environmental Protection Agency, National Exposure Research Laboratory. Calibrations of TOPMODEL and GBMM were done independently while using the same meteorological data and the same period of record of observed data. Two U.S. Geological Survey streamflow-gaging stations were available for comparison of observed daily mean flow with simulated daily mean flow-station 02172300, McTier Creek near Monetta, South Carolina, and station 02172305, McTier Creek near New Holland, South Carolina. The period of record at the Monetta gage covers a broad range of hydrologic conditions, including a drought and a significant wet period. Calibrating the models under these extreme conditions along with the normal flow conditions included in the record enhances the robustness of the two models. Several quantitative assessments of the goodness of fit between model simulations and the observed daily mean flows were done. These included the Nash-Sutcliffe coefficient
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Van Hoy, D.; Mahmood, T. H.; Jeannotte, T.; Todhunter, P. E.
2017-12-01
The recent shift in hydroclimatic conditions in the Northern Great Plains (NGP) has led to an increase in precipitation, rainfall rate, and wetland connectivity over the last few decades. These changes yield an integrated response resulting in high mean annual streamflow and subsequent flooding in many NGP basins such as the terminal Devils Lake Basin (DLB). In this study, we investigate the impacts of recent climatic wetting on distributed hydrologic responses such as snow processes and streamflow using a field-tested and physically-based cold region hydrologic model (CRHM). CHRM is designed for cold prairie regions and has modules to simulate major processes such as blowing snow transport, sublimation, interception, frozen soil infiltration, snowmelt and subsequent streamflow generation. Our modeling focuses on a tributary basin of the DLB known as the Mauvais Coulee Basin (MCB). Since there were no snow observations in the MCB, we conducted a detailed snow survey at distributed locations estimating snow depth, density, and snow water equivalent (SWE) using a prairie snow tube four times during winter of 2016-17. The MCB model was evaluated against distributed snow observations and streamflow measured at the basin outlet (USGS) for the year 2016-2017. Preliminary results indicate that the simulated SWEs at distributed locations and streamflow (NSE ≈ 0.70) are in good agreement with observations. The simulated SWE maps exhibit large spatiotemporal variation during 2016-17 winter due to spatial variability in precipitation, snow redistribution from stubble field to wooded areas, and snow accumulations in small depressions across the subbasins. The main source of snow appears to be the hills and ridges of the eastern and western edges of the basin, while the main sink is the large flat central valleys. The model will be used to examine the effect of recent changes to precipitation and temperature on snow processes and subsequent streamflow for 2004-2017 season. We
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Energy Technology Data Exchange (ETDEWEB)
Ahmed E. Hassan
2006-01-24
Models have an inherent uncertainty. The difficulty in fully characterizing the subsurface environment makes uncertainty an integral component of groundwater flow and transport models, which dictates the need for continuous monitoring and improvement. Building and sustaining confidence in closure decisions and monitoring networks based on models of subsurface conditions require developing confidence in the models through an iterative process. The definition of model validation is postulated as a confidence building and long-term iterative process (Hassan, 2004a). Model validation should be viewed as a process not an end result. Following Hassan (2004b), an approach is proposed for the validation process of stochastic groundwater models. The approach is briefly summarized herein and detailed analyses of acceptance criteria for stochastic realizations and of using validation data to reduce input parameter uncertainty are presented and applied to two case studies. During the validation process for stochastic models, a question arises as to the sufficiency of the number of acceptable model realizations (in terms of conformity with validation data). Using a hierarchical approach to make this determination is proposed. This approach is based on computing five measures or metrics and following a decision tree to determine if a sufficient number of realizations attain satisfactory scores regarding how they represent the field data used for calibration (old) and used for validation (new). The first two of these measures are applied to hypothetical scenarios using the first case study and assuming field data consistent with the model or significantly different from the model results. In both cases it is shown how the two measures would lead to the appropriate decision about the model performance. Standard statistical tests are used to evaluate these measures with the results indicating they are appropriate measures for evaluating model realizations. The use of validation
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Applications of the PyTOPKAPI model to ungauged catchments
African Journals Online (AJOL)
Many catchments in developing countries are poorly gauged/totally ungauged which hinders water resource ... INTRODUCTION ... focusing on the output of model calibration and validation. The last .... The improved PyTOPKAPI model is coded in Python ...... computer program for estimating streamflow statistics for ungaged.
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Poole, Sandra; Vis, Marc; Knight, Rodney; Seibert, Jan
2017-01-01
Ecologically relevant streamflow characteristics (SFCs) of ungauged catchments are often estimated from simulated runoff of hydrologic models that were originally calibrated on gauged catchments. However, SFC estimates of the gauged donor catchments and subsequently the ungauged catchments can be substantially uncertain when models are calibrated using traditional approaches based on optimization of statistical performance metrics (e.g., Nash–Sutcliffe model efficiency). An improved calibration strategy for gauged catchments is therefore crucial to help reduce the uncertainties of estimated SFCs for ungauged catchments. The aim of this study was to improve SFC estimates from modeled runoff time series in gauged catchments by explicitly including one or several SFCs in the calibration process. Different types of objective functions were defined consisting of the Nash–Sutcliffe model efficiency, single SFCs, or combinations thereof. We calibrated a bucket-type runoff model (HBV – Hydrologiska Byråns Vattenavdelning – model) for 25 catchments in the Tennessee River basin and evaluated the proposed calibration approach on 13 ecologically relevant SFCs representing major flow regime components and different flow conditions. While the model generally tended to underestimate the tested SFCs related to mean and high-flow conditions, SFCs related to low flow were generally overestimated. The highest estimation accuracies were achieved by a SFC-specific model calibration. Estimates of SFCs not included in the calibration process were of similar quality when comparing a multi-SFC calibration approach to a traditional model efficiency calibration. For practical applications, this implies that SFCs should preferably be estimated from targeted runoff model calibration, and modeled estimates need to be carefully interpreted.
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Arumugam, S.; Mazrooei, A.; Lakshmi, V.; Wood, A.
2017-12-01
Subseasonal-to-seasonal (S2S) forecasts of soil moisture and streamflow provides critical information for water and agricultural systems to support short-term planning and mangement. This study evaluates the role of observed streamflow and remotely-sensed soil moisture from SMAP (Soil Moisture Active Passive) mission in improving S2S streamflow and soil moisture forecasting using data assimilation (DA). We first show the ability to forecast soil moisture at monthly-to-seaasonal time scale by forcing climate forecasts with NASA's Land Information System and then compares the developed soil moisture forecast with the SMAP data over the Southeast US. Our analyses show significant skill in forecasting real-time soil moisture over 1-3 months using climate information. We also show that the developed soil moisture forecasts capture the observed severe drought conditions (2007-2008) over the Southeast US. Following that, we consider both SMAP data and observed streamflow for improving S2S streamflow and soil moisture forecasts for a pilot study area, Tar River basin, in NC. Towards this, we consider variational assimilation (VAR) of gauge-measured daily streamflow data in improving initial hydrologic conditions of Variable Infiltration Capacity (VIC) model. The utility of data assimilation is then assessed in improving S2S forecasts of streamflow and soil moisture through a retrospective analyses. Furthermore, the optimal frequency of data assimilation and optimal analysis window (number of past observations to use) are also assessed in order to achieve the maximum improvement in S2S forecasts of streamflow and soil moisture. Potential utility of updating initial conditions using DA and providing skillful forcings are also discussed.
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Streamflow timing of mountain rivers in Spain: Recent changes and future projections
Morán-Tejeda, Enrique; Lorenzo-Lacruz, Jorge; López-Moreno, Juan Ignacio; Rahman, Kazi; Beniston, Martin
2014-09-01
Changes in streamflow timing are studied in 27 mountain rivers in Spain, in the context of climate warming. The studied rivers are characterized by a highflows period in spring due to snowmelt, although differences in the role of snow and consequently in the timing of flows are observed amongst cases. We calculated for every year of the studied period (1976-2008) various hydrological indices that enable locating the timing of spring flows within the annual hydrologic regime, including the day of 75% of mass, and the day of spring maximum. The evolution of these indices was compared with that of seasonal precipitation and temperature, and trends in time were calculated. Results show a general negative trend in the studied indices which indicates that spring peaks due to snowmelt are shifting earlier within the hydrological year. Spring temperatures, which show a significant increasing trend, are the main co-variable responsible for the observed changes in the streamflow timing. In a second set of analyses we performed hydrological simulations with the SWAT model, in order to estimate changes in streamflow timing under projected warming temperatures. Projections show further shifting of spring peak flows along with a more pronounced low water level period in the summer. The simulations also allowed quantifying the role of snowfall-snowmelt on the observed changes in streamflow.
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Ye, Xuchun; Xu, Chong-Yu; Li, Xianghu; Zhang, Qi
2018-05-01
The occurrence of flood and drought frequency is highly correlated with the temporal fluctuations of streamflow series; understanding of these fluctuations is essential for the improved modeling and statistical prediction of extreme changes in river basins. In this study, the complexity of daily streamflow fluctuations was investigated by using multifractal detrended fluctuation analysis (MF-DFA) in a large heterogeneous lake basin, the Poyang Lake basin in China, and the potential impacts of human activities were also explored. Major results indicate that the multifractality of streamflow fluctuations shows significant regional characteristics. In the study catchment, all the daily streamflow series present a strong long-range correlation with Hurst exponents bigger than 0.8. The q-order Hurst exponent h( q) of all the hydrostations can be characterized well by only two parameters: a (0.354 ≤ a ≤ 0.384) and b (0.627 ≤ b ≤ 0.677), with no pronounced differences. Singularity spectrum analysis pointed out that small fluctuations play a dominant role in all daily streamflow series. Our research also revealed that both the correlation properties and the broad probability density function (PDF) of hydrological series can be responsible for the multifractality of streamflow series that depends on watershed areas. In addition, we emphasized the relationship between watershed area and the estimated multifractal parameters, such as the Hurst exponent and fitted parameters a and b from the q-order Hurst exponent h( q). However, the relationship between the width of the singularity spectrum (Δ α) and watershed area is not clear. Further investigation revealed that increasing forest coverage and reservoir storage can effectively enhance the persistence of daily streamflow, decrease the hydrological complexity of large fluctuations, and increase the small fluctuations.
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Directory of Open Access Journals (Sweden)
Kang Liang
2017-06-01
Full Text Available Hydrological predictions in ungauged lakes are one of the most important issues in hydrological sciences. The habitat of the Relict Gull (Larus relictus in the Erdos Larus relictus National Nature Reserve (ELRNNR has been seriously endangered by lake shrinkage, yet the hydrological processes in the catchment are poorly understood due to the lack of in-situ observations. Therefore, it is necessary to assess the variation in lake streamflow and its drivers. In this study, we employed the remote sensing technique and empirical equation to quantify the time series of lake water budgets, and integrated a water balance model and climate elasticity method to further examine ELRNNR basin streamflow variations from1974 to 2013. The results show that lake variations went through three phases with significant differences: The rapidly expanding sub-period (1974–1979, the relatively stable sub-period (1980–1999, and the dramatically shrinking sub-period (2000–2013. Both climate variation (expressed by precipitation and evapotranspiration and human activities were quantified as drivers of streamflow variation, and the driving forces in the three phases had different contributions. As human activities gradually intensified, the contributions of human disturbances on streamflow variation obviously increased, accounting for 22.3% during 1980–1999 and up to 59.2% during 2000–2013. Intensified human interferences and climate warming have jointly led to the lake shrinkage since 1999. This study provides a useful reference to quantify lake streamflow and its drivers in ungauged basins.
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Stamey, Timothy C.
2001-01-01
In 1999, the U.S. Geological Survey, in cooperation with the U.S. Army Signal Center and Fort Gordon, began collection of periodic streamflow data at four streams on the military base to assess and estimate streamflow characteristics of those streams for potential water-supply sources. Simple and reliable methods of determining streamflow characteristics of selected streams on the military base are needed for the initial implementation of the Fort Gordon Integrated Natural Resources Management Plan. Long-term streamflow data from the Butler Creek streamflow gaging station were used along with several concurrent discharge measurements made at three selected partial-record streamflow stations on Fort Gordon to determine selected low-flow streamflow characteristics. Streamflow data were collected and analyzed using standard U.S. Geological Survey methods and computer application programs to verify the use of simple drainage area to discharge ratios, which were used to estimate the low-flow characteristics for the selected streams. Low-flow data computed based on daily mean streamflow include: mean discharges for consecutive 1-, 3-, 7-, 14-, and 30-day period and low-flow estimates of 7Q10, 30Q2, 60Q2, and 90Q2 recurrence intervals. Flow-duration data also were determined for the 10-, 30-, 50-, 70-, and 90-percent exceedence flows. Preliminary analyses of the streamflow indicate that the flow duration and selected low-flow statistics for the selected streams averages from about 0.15 to 2.27 cubic feet per square mile. The long-term gaged streamflow data indicate that the streamflow conditions for the period analyzed were in the 50- to 90-percent flow range, or in which streamflow would be exceeded about 50 to 90 percent of the time.
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Ravindranath, A.; Devineni, N.
2017-12-01
Studies have shown that streamflow behavior and dynamics have a significant link with climate and climate variability. Patterns of persistent regime behavior from extended streamflow records in many watersheds justify investigating large-scale climate mechanisms as potential drivers of hydrologic regime behavior and streamflow variability. Understanding such streamflow-climate relationships is crucial to forecasting/simulation systems and the planning and management of water resources. In this study, hidden Markov models are used with reconstructed streamflow to detect regime-like behaviors - the hidden states - and state transition phenomena. Individual extreme events and their spatial variability across the basin are then verified with the identified states. Wavelet analysis is performed to examine the signals over time in the streamflow records. Joint analyses of the climatic data in the 20th century and the identified states are undertaken to better understand the hydroclimatic connections within the basin as well as important teleconnections that influence water supply. Compositing techniques are used to identify atmospheric circulation patterns associated with identified states of streamflow. The grouping of such synoptic patterns and their frequency are then examined. Sliding time-window correlation analysis and cross-wavelet spectral analysis are performed to establish the synchronicity of basin flows to the identified synoptic and teleconnection patterns. The Missouri River Basin (MRB) is examined in this study, both as a means of better understanding the synoptic climate controls in this important watershed and as a case study for the techniques developed here. Initial wavelet analyses of reconstructed streamflow at major gauges in the MRB show multidecadal cycles in regime behavior.
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Contribution of human and climate change impacts to changes in streamflow of Canada.
Tan, Xuezhi; Gan, Thian Yew
2015-12-04
Climate change exerts great influence on streamflow by changing precipitation, temperature, snowpack and potential evapotranspiration (PET), while human activities in a watershed can directly alter the runoff production and indirectly through affecting climatic variables. However, to separate contribution of anthropogenic and natural drivers to observed changes in streamflow is non-trivial. Here we estimated the direct influence of human activities and climate change effect to changes of the mean annual streamflow (MAS) of 96 Canadian watersheds based on the elasticity of streamflow in relation to precipitation, PET and human impacts such as land use and cover change. Elasticities of streamflow for each watershed are analytically derived using the Budyko Framework. We found that climate change generally caused an increase in MAS, while human impacts generally a decrease in MAS and such impact tends to become more severe with time, even though there are exceptions. Higher proportions of human contribution, compared to that of climate change contribution, resulted in generally decreased streamflow of Canada observed in recent decades. Furthermore, if without contributions from retreating glaciers to streamflow, human impact would have resulted in a more severe decrease in Canadian streamflow.
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Model Validation Status Review
International Nuclear Information System (INIS)
E.L. Hardin
2001-01-01
The primary objective for the Model Validation Status Review was to perform a one-time evaluation of model validation associated with the analysis/model reports (AMRs) containing model input to total-system performance assessment (TSPA) for the Yucca Mountain site recommendation (SR). This review was performed in response to Corrective Action Request BSC-01-C-01 (Clark 2001, Krisha 2001) pursuant to Quality Assurance review findings of an adverse trend in model validation deficiency. The review findings in this report provide the following information which defines the extent of model validation deficiency and the corrective action needed: (1) AMRs that contain or support models are identified, and conversely, for each model the supporting documentation is identified. (2) The use for each model is determined based on whether the output is used directly for TSPA-SR, or for screening (exclusion) of features, events, and processes (FEPs), and the nature of the model output. (3) Two approaches are used to evaluate the extent to which the validation for each model is compliant with AP-3.10Q (Analyses and Models). The approaches differ in regard to whether model validation is achieved within individual AMRs as originally intended, or whether model validation could be readily achieved by incorporating information from other sources. (4) Recommendations are presented for changes to the AMRs, and additional model development activities or data collection, that will remedy model validation review findings, in support of licensing activities. The Model Validation Status Review emphasized those AMRs that support TSPA-SR (CRWMS M and O 2000bl and 2000bm). A series of workshops and teleconferences was held to discuss and integrate the review findings. The review encompassed 125 AMRs (Table 1) plus certain other supporting documents and data needed to assess model validity. The AMRs were grouped in 21 model areas representing the modeling of processes affecting the natural and
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Model Validation Status Review
Energy Technology Data Exchange (ETDEWEB)
E.L. Hardin
2001-11-28
The primary objective for the Model Validation Status Review was to perform a one-time evaluation of model validation associated with the analysis/model reports (AMRs) containing model input to total-system performance assessment (TSPA) for the Yucca Mountain site recommendation (SR). This review was performed in response to Corrective Action Request BSC-01-C-01 (Clark 2001, Krisha 2001) pursuant to Quality Assurance review findings of an adverse trend in model validation deficiency. The review findings in this report provide the following information which defines the extent of model validation deficiency and the corrective action needed: (1) AMRs that contain or support models are identified, and conversely, for each model the supporting documentation is identified. (2) The use for each model is determined based on whether the output is used directly for TSPA-SR, or for screening (exclusion) of features, events, and processes (FEPs), and the nature of the model output. (3) Two approaches are used to evaluate the extent to which the validation for each model is compliant with AP-3.10Q (Analyses and Models). The approaches differ in regard to whether model validation is achieved within individual AMRs as originally intended, or whether model validation could be readily achieved by incorporating information from other sources. (4) Recommendations are presented for changes to the AMRs, and additional model development activities or data collection, that will remedy model validation review findings, in support of licensing activities. The Model Validation Status Review emphasized those AMRs that support TSPA-SR (CRWMS M&O 2000bl and 2000bm). A series of workshops and teleconferences was held to discuss and integrate the review findings. The review encompassed 125 AMRs (Table 1) plus certain other supporting documents and data needed to assess model validity. The AMRs were grouped in 21 model areas representing the modeling of processes affecting the natural and
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Assessing the predictive capability of randomized tree-based ensembles in streamflow modelling
Galelli, S.; Castelletti, A.
2013-07-01
Combining randomization methods with ensemble prediction is emerging as an effective option to balance accuracy and computational efficiency in data-driven modelling. In this paper, we investigate the prediction capability of extremely randomized trees (Extra-Trees), in terms of accuracy, explanation ability and computational efficiency, in a streamflow modelling exercise. Extra-Trees are a totally randomized tree-based ensemble method that (i) alleviates the poor generalisation property and tendency to overfitting of traditional standalone decision trees (e.g. CART); (ii) is computationally efficient; and, (iii) allows to infer the relative importance of the input variables, which might help in the ex-post physical interpretation of the model. The Extra-Trees potential is analysed on two real-world case studies - Marina catchment (Singapore) and Canning River (Western Australia) - representing two different morphoclimatic contexts. The evaluation is performed against other tree-based methods (CART and M5) and parametric data-driven approaches (ANNs and multiple linear regression). Results show that Extra-Trees perform comparatively well to the best of the benchmarks (i.e. M5) in both the watersheds, while outperforming the other approaches in terms of computational requirement when adopted on large datasets. In addition, the ranking of the input variable provided can be given a physically meaningful interpretation.
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Dugger, A. L.; Zhang, Y.; Gochis, D.; Yu, W.; McCreight, J. L.; Karsten, L.; Rafieeinasab, A.; Sampson, K. M.; Salas, F.; Read, L.; Pan, L.; Yates, D. N.; Cosgrove, B.; Clark, E. P.
2017-12-01
Streamflow extremes (lows and peaks) tend to have disproportionately higher impacts on the human and natural systems compared to mean streamflow. Examining and understanding the spatiotemporal distributions of streamflow extremes is of significant interests to both the research community and the water resources management. In this work, the output from the 24-year (1993 through 2016) retrospective runs of the National Water Model (NWM) version of WRF-Hydro will be analyzed for streamflow extremes over the CONUS domain. The CONUS domain was configured at 1-km resolution for land surface grid and 250-m resolution for terrain routing. The WRF-Hydro runs were forced by the regridded and downscaled NLDAS2 data. The analyses focus on daily mean streamflow values over the full water year and within the summer and winter seasons. Connections between NWM streamflow and other hydrologic variables (e.g. snowpack, soil moisture/saturation and ET) with variations in large-scale climate phenomena, e.g., El Niño - Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), and North American monsoon are examined. The CONUS domain has a diverse environment and is characterized by complex terrain, heterogeneous land surfaces and ecosystems, and numerous hydrological basins. The potential dependence of streamflow extremes on regional terrain character, climatic conditions, and ecologic zones will also be investigated.
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Effects of water-supply reservoirs on streamflow in Massachusetts
Levin, Sara B.
2016-10-06
State and local water-resource managers need modeling tools to help them manage and protect water-supply resources for both human consumption and ecological needs. The U.S. Geological Survey, in cooperation with the Massachusetts Department of Environmental Protection, has developed a decision-support tool to estimate the effects of reservoirs on natural streamflow. The Massachusetts Reservoir Simulation Tool is a model that simulates the daily water balance of a reservoir. The reservoir simulation tool provides estimates of daily outflows from reservoirs and compares the frequency, duration, and magnitude of the volume of outflows from reservoirs with estimates of the unaltered streamflow that would occur if no dam were present. This tool will help environmental managers understand the complex interactions and tradeoffs between water withdrawals, reservoir operational practices, and reservoir outflows needed for aquatic habitats.A sensitivity analysis of the daily water balance equation was performed to identify physical and operational features of reservoirs that could have the greatest effect on reservoir outflows. For the purpose of this report, uncontrolled releases of water (spills or spillage) over the reservoir spillway were considered to be a proxy for reservoir outflows directly below the dam. The ratio of average withdrawals to the average inflows had the largest effect on spillage patterns, with the highest withdrawals leading to the lowest spillage. The size of the surface area relative to the drainage area of the reservoir also had an effect on spillage; reservoirs with large surface areas have high evaporation rates during the summer, which can contribute to frequent and long periods without spillage, even in the absence of water withdrawals. Other reservoir characteristics, such as variability of inflows, groundwater interactions, and seasonal demand patterns, had low to moderate effects on the frequency, duration, and magnitude of spillage. The
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International Nuclear Information System (INIS)
Napier, B.A.; Simpson, J.C.; Eslinger, P.W.; Ramsdell, J.V. Jr.; Thiede, M.E.; Walters, W.H.
1994-05-01
The Hanford Environmental Dose Reconstruction (HEDR) Project has developed a set of computer models for estimating the possible radiation doses that individuals may have received from past Hanford Site operations. This document describes the validation of these models. In the HEDR Project, the model validation exercise consisted of comparing computational model estimates with limited historical field measurements and experimental measurements that are independent of those used to develop the models. The results of any one test do not mean that a model is valid. Rather, the collection of tests together provide a level of confidence that the HEDR models are valid
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Thakur, B.; Pathak, P.; Kalra, A.; Ahmad, S.
2016-12-01
The identification of primary drivers of streamflow may prove beneficial in forecasting streamflow in the Midwestern U.S. In the past researches, streamflow in the region have been strongly correlated with El Niño-Southern Oscillation (ENSO), Atlantic Multidecadal Oscillation (AMO) and Pacific Decadal Oscillation (PDO). The present study takes in to account the pre-defined Pacific and Atlantic Ocean regions (e.g., ENSO, PDO, AMO) along with new regions with an intent to identify new significantly correlated regions. This study assesses the interrelationship between sea surface temperatures (SST) anomalies in the Pacific and Atlantic Ocean and seasonal streamflow in the Midwestern U.S. Average Pacific and Atlantic Ocean SST anomalies, were calculated for 2 different 3 month series: September-November and December-February so as to create a lead time varying from 3 to 9 months. Streamflow were averaged for three seasons: spring (April-June), spring-summer (April-August) and summer (June-August). The correlation between streamflow and SST is analyzed using singular value decomposition for a period of 1960-2013. The result of the study showed several regions-other than the known Pacific and Atlantic Ocean regions- that were significantly correlated with streamflow stations. Higher correlation between the climate indices and streamflow were observed as the lead time decreased. The identification of the associations between SST and streamflow and significant SST regions in the Pacific and Atlantic Ocean may enhance the skill of streamflow predictability and water management in the region.
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Trends and variability in streamflow and snowmelt runoff timing in the southern Tianshan Mountains
Shen, Yan-Jun; Shen, Yanjun; Fink, Manfred; Kralisch, Sven; Chen, Yaning; Brenning, Alexander
2018-02-01
Streamflow and snowmelt runoff timing of mountain rivers are susceptible to climate change. Trends and variability in streamflow and snowmelt runoff timing in four mountain basins in the southern Tianshan were analyzed in this study. Streamflow trends were detected by Mann-Kendall tests and changes in snowmelt runoff timing were analyzed based on the winter/spring snowmelt runoff center time (WSCT). Pearson's correlation coefficient was further calculated to analyze the relationships between climate variables, streamflow and WSCT. Annual streamflow increased significantly in past decades in the southern Tianshan, especially in spring and winter months. However, the relations between streamflow and temperature/precipitation depend on the different streamflow generation processes. Annual precipitation plays a vital role in controlling recharge in the Toxkon basin, while the Kaidu and Huangshuigou basins are governed by both precipitation and temperature. Seasonally, temperature has a strong effect on streamflow in autumn and winter, while summer streamflow appears more sensitive to changes in precipitation. However, temperature is the dominant factor for streamflow in the glacierized Kunmalik basin at annual and seasonal scales. An uptrend in streamflow begins in the 1990s at both annual and seasonal scales, which is generally consistent with temperature and precipitation fluctuations. Average WSCT dates in the Kaidu and Huangshuigou basins are earlier than in the Toxkon and Kunmalik basins, and shifted towards earlier dates since the mid-1980s in all the basins. It is plausible that WSCT dates are more sensitive to warmer temperature in spring period compared to precipitation, except for the Huangshuigou basin. Taken together, these findings are useful for applications in flood risk regulation, future hydropower projects and integrated water resources management.
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Monthly streamflow forecasting at varying spatial scales in the Rhine basin
Schick, Simon; Rössler, Ole; Weingartner, Rolf
2018-02-01
Model output statistics (MOS) methods can be used to empirically relate an environmental variable of interest to predictions from earth system models (ESMs). This variable often belongs to a spatial scale not resolved by the ESM. Here, using the linear model fitted by least squares, we regress monthly mean streamflow of the Rhine River at Lobith and Basel against seasonal predictions of precipitation, surface air temperature, and runoff from the European Centre for Medium-Range Weather Forecasts. To address potential effects of a scale mismatch between the ESM's horizontal grid resolution and the hydrological application, the MOS method is further tested with an experiment conducted at the subcatchment scale. This experiment applies the MOS method to 133 additional gauging stations located within the Rhine basin and combines the forecasts from the subcatchments to predict streamflow at Lobith and Basel. In doing so, the MOS method is tested for catchments areas covering 4 orders of magnitude. Using data from the period 1981-2011, the results show that skill, with respect to climatology, is restricted on average to the first month ahead. This result holds for both the predictor combination that mimics the initial conditions and the predictor combinations that additionally include the dynamical seasonal predictions. The latter, however, reduce the mean absolute error of the former in the range of 5 to 12 %, which is consistently reproduced at the subcatchment scale. An additional experiment conducted for 5-day mean streamflow indicates that the dynamical predictions help to reduce uncertainties up to about 20 days ahead, but it also reveals some shortcomings of the present MOS method.
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Li, Zhi; Jin, Jiming
2017-11-01
Projected hydrological variability is important for future resource and hazard management of water supplies because changes in hydrological variability can cause more disasters than changes in the mean state. However, climate change scenarios downscaled from Earth System Models (ESMs) at single sites cannot meet the requirements of distributed hydrologic models for simulating hydrological variability. This study developed multisite multivariate climate change scenarios via three steps: (i) spatial downscaling of ESMs using a transfer function method, (ii) temporal downscaling of ESMs using a single-site weather generator, and (iii) reconstruction of spatiotemporal correlations using a distribution-free shuffle procedure. Multisite precipitation and temperature change scenarios for 2011-2040 were generated from five ESMs under four representative concentration pathways to project changes in streamflow variability using the Soil and Water Assessment Tool (SWAT) for the Jing River, China. The correlation reconstruction method performed realistically for intersite and intervariable correlation reproduction and hydrological modeling. The SWAT model was found to be well calibrated with monthly streamflow with a model efficiency coefficient of 0.78. It was projected that the annual mean precipitation would not change, while the mean maximum and minimum temperatures would increase significantly by 1.6 ± 0.3 and 1.3 ± 0.2 °C; the variance ratios of 2011-2040 to 1961-2005 were 1.15 ± 0.13 for precipitation, 1.15 ± 0.14 for mean maximum temperature, and 1.04 ± 0.10 for mean minimum temperature. A warmer climate was predicted for the flood season, while the dry season was projected to become wetter and warmer; the findings indicated that the intra-annual and interannual variations in the future climate would be greater than in the current climate. The total annual streamflow was found to change insignificantly but its variance ratios of 2011-2040 to 1961-2005 increased
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Ho, M. W.; Lall, U.; Cook, E. R.
2015-12-01
Advances in paleoclimatology in the past few decades have provided opportunities to expand the temporal perspective of the hydrological and climatological variability across the world. The North American region is particularly fortunate in this respect where a relatively dense network of high resolution paleoclimate proxy records have been assembled. One such network is the annually-resolved Living Blended Drought Atlas (LBDA): a paleoclimate reconstruction of the Palmer Drought Severity Index (PDSI) that covers North America on a 0.5° × 0.5° grid based on tree-ring chronologies. However, the use of the LBDA to assess North American streamflow variability requires a model by which streamflow may be reconstructed. Paleoclimate reconstructions have typically used models that first seek to quantify the relationship between the paleoclimate variable and the environmental variable of interest before extrapolating the relationship back in time. In contrast, the pre-instrumental streamflow is here considered as "missing" data. A method of imputing the "missing" streamflow data, prior to the instrumental record, is applied through multiple imputation using chained equations for streamflow in the Missouri River Basin. In this method, the distribution of the instrumental streamflow and LBDA is used to estimate sets of plausible values for the "missing" streamflow data resulting in a ~600 year-long streamflow reconstruction. Past research into external climate forcings, oceanic-atmospheric variability and its teleconnections, and assessments of rare multi-centennial instrumental records demonstrate that large temporal oscillations in hydrological conditions are unlikely to be captured in most instrumental records. The reconstruction of multi-centennial records of streamflow will enable comprehensive assessments of current and future water resource infrastructure and operations under the existing scope of natural climate variability.
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Gibbs, Matthew S.; McInerney, David; Humphrey, Greer; Thyer, Mark A.; Maier, Holger R.; Dandy, Graeme C.; Kavetski, Dmitri
2018-02-01
Monthly to seasonal streamflow forecasts provide useful information for a range of water resource management and planning applications. This work focuses on improving such forecasts by considering the following two aspects: (1) state updating to force the models to match observations from the start of the forecast period, and (2) selection of a shorter calibration period that is more representative of the forecast period, compared to a longer calibration period traditionally used. The analysis is undertaken in the context of using streamflow forecasts for environmental flow water management of an open channel drainage network in southern Australia. Forecasts of monthly streamflow are obtained using a conceptual rainfall-runoff model combined with a post-processor error model for uncertainty analysis. This model set-up is applied to two catchments, one with stronger evidence of non-stationarity than the other. A range of metrics are used to assess different aspects of predictive performance, including reliability, sharpness, bias and accuracy. The results indicate that, for most scenarios and metrics, state updating improves predictive performance for both observed rainfall and forecast rainfall sources. Using the shorter calibration period also improves predictive performance, particularly for the catchment with stronger evidence of non-stationarity. The results highlight that a traditional approach of using a long calibration period can degrade predictive performance when there is evidence of non-stationarity. The techniques presented can form the basis for operational monthly streamflow forecasting systems and provide support for environmental decision-making.
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Feng, D.; Zhao, Y.; Raoufi, R.; Beighley, E.; Melack, J.
2017-12-01
The Santa Barbara Coastal - Long Term Ecological Research Project is focused on investigating the relative importance of land and ocean processes in structuring giant kelp forest ecosystems. Understanding how current and future climate conditions influence terrestrial export of water is a central theme for the project. In this study, the Hillslope River Routing (HRR) model is forced with past measurement-based (1950 to 2005) and future model-based (2006 to 2100) precipitation and temperature to estimate daily streamflow dynamics. The study region is roughly 800 km2 with 179 watersheds ranging from 0.1 to 123 km2. The model-based forcings are downscaled to a spatial resolution of 6 km by 6 km. The Priestley and Taylor method is used to estimate potential evapotranspiration based on the Food and Agriculture Organization of the United Nations limited climate data approximations and land surface conditions (albedo, leaf area index, land cover) measured from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites. The HRR model is calibrated for the period 1984 to 2013 using USGS streamflow. Median changes in downscaled precipitation projections from 10 models and two emission scenarios (RCP 4.5 and 8.5) combined with significance testing, suggest that the distribution of precipitation throughout the rainy season will change: decrease at the beginning of the rainy season (Oct-Dec), increase during peak season (Jan-Mar) and decrease at the end (Apr-Jun). Annually, results suggest a slight increase in precipitation. The decrease of rainfall in spring and fall and increase in winter will lead to a shorter (10-15 days, 8-14%), more intense wet season. Both the magnitude and frequency of large storms (>36 mm/day) are likely to increase. Following the precipitation patterns, streamflow in spring and fall is likely to decrease while winter streamflow and annual peak flows are likely to increase due to increased winter precipitation and
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IOD and ENSO impacts on the extreme stream-flows of Citarum river in Indonesia
Energy Technology Data Exchange (ETDEWEB)
Sahu, Netrananda; Yamashiki, Yosuke; Takara, Kaoru [Kyoto University, Disaster Prevention Research Institute, Innovative Disaster Prevention Technology and Policy Research Laboratory, Gokasho, Uji City, Kyoto (Japan); Behera, Swadhin K. [JAMSTEC, Research Institute for Global Change, Yokohama, Kanagawa (Japan); JAMSTEC, Application Laboratory, Yokohama (Japan); Yamagata, Toshio [University of Tokyo, School of Science, Bunkyo-ku, Tokyo (Japan); JAMSTEC, Application Laboratory, Yokohama (Japan)
2012-10-15
Extreme stream-flow events of Citarum River are derived from the daily stream-flows at the Nanjung gauge station. Those events are identified based on their persistently extreme flows for 6 or more days during boreal fall when the seasonal mean stream-flow starts peaking-up from the lowest seasonal flows of June-August. Most of the extreme events of high-streamflows were related to La Nina conditions of tropical Pacific. A few of them were also associated with the negative phases of IOD and the newly identified El Nino Modoki. Unlike the cases of extreme high streamflows, extreme low streamflow events are seen to be associated with the positive IODs. Nevertheless, it was also found that the low-stream-flow events related to positive IOD events were also associated with El Nino events except for one independent event of 1977. Because the occurrence season coincides the peak season of IOD, not only the picked extreme events are seen to fall under the IOD seasons but also there exists a statistically significant correlation of 0.51 between the seasonal IOD index and the seasonal streamflows. There also exists a significant lag correlation when IOD of June-August season leads the streamflows of September-November. A significant but lower correlation coefficient (0.39) is also found between the seasonal streamflow and El Nino for September-November season only. (orig.)
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Directory of Open Access Journals (Sweden)
S. Wang
2012-12-01
Full Text Available Model calibration is essential for hydrologic modeling of large watersheds in a heterogeneous mountain environment. Little guidance is available for model calibration protocols for distributed models that aim at capturing the spatial variability of hydrologic processes. This study used the physically-based distributed hydrologic model, MIKE SHE, to contrast a lumped calibration protocol that used streamflow measured at one single watershed outlet to a multi-site calibration method which employed streamflow measurements at three stations within the large Chaohe River basin in northern China. Simulation results showed that the single-site calibrated model was able to sufficiently simulate the hydrographs for two of the three stations (Nash-Sutcliffe coefficient of 0.65–0.75, and correlation coefficient 0.81–0.87 during the testing period, but the model performed poorly for the third station (Nash-Sutcliffe coefficient only 0.44. Sensitivity analysis suggested that streamflow of upstream area of the watershed was dominated by slow groundwater, whilst streamflow of middle- and down- stream areas by relatively quick interflow. Therefore, a multi-site calibration protocol was deemed necessary. Due to the potential errors and uncertainties with respect to the representation of spatial variability, performance measures from the multi-site calibration protocol slightly decreased for two of the three stations, whereas it was improved greatly for the third station. We concluded that multi-site calibration protocol reached a compromise in term of model performance for the three stations, reasonably representing the hydrographs of all three stations with Nash-Sutcliffe coefficient ranging from 0.59–072. The multi-site calibration protocol applied in the analysis generally has advantages to the single site calibration protocol.
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Methods to estimate historical daily streamflow for ungaged stream locations in Minnesota
Lorenz, David L.; Ziegeweid, Jeffrey R.
2016-03-14
Effective and responsible management of water resources relies on a thorough understanding of the quantity and quality of available water; however, streamgages cannot be installed at every location where streamflow information is needed. Therefore, methods for estimating streamflow at ungaged stream locations need to be developed. This report presents a statewide study to develop methods to estimate the structure of historical daily streamflow at ungaged stream locations in Minnesota. Historical daily mean streamflow at ungaged locations in Minnesota can be estimated by transferring streamflow data at streamgages to the ungaged location using the QPPQ method. The QPPQ method uses flow-duration curves at an index streamgage, relying on the assumption that exceedance probabilities are equivalent between the index streamgage and the ungaged location, and estimates the flow at the ungaged location using the estimated flow-duration curve. Flow-duration curves at ungaged locations can be estimated using recently developed regression equations that have been incorporated into StreamStats (http://streamstats.usgs.gov/), which is a U.S. Geological Survey Web-based interactive mapping tool that can be used to obtain streamflow statistics, drainage-basin characteristics, and other information for user-selected locations on streams.
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Modifying WEPP to improve streamflow simulation in a Pacific Northwest watershed
A. Srivastava; M. Dobre; J. Q. Wu; W. J. Elliot; E. A. Bruner; S. Dun; E. S. Brooks; I. S. Miller
2013-01-01
The assessment of water yield from hillslopes into streams is critical in managing water supply and aquatic habitat. Streamflow is typically composed of surface runoff, subsurface lateral flow, and groundwater baseflow; baseflow sustains the stream during the dry season. The Water Erosion Prediction Project (WEPP) model simulates surface runoff, subsurface lateral flow...
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Koskela, J. J.; Croke, B. W. F.; Koivusalo, H.; Jakeman, A. J.; Kokkonen, T.
2012-11-01
Bayesian inference is used to study the effect of precipitation and model structural uncertainty on estimates of model parameters and confidence limits of predictive variables in a conceptual rainfall-runoff model in the snow-fed Rudbäck catchment (142 ha) in southern Finland. The IHACRES model is coupled with a simple degree day model to account for snow accumulation and melt. The posterior probability distribution of the model parameters is sampled by using the Differential Evolution Adaptive Metropolis (DREAM(ZS)) algorithm and the generalized likelihood function. Precipitation uncertainty is taken into account by introducing additional latent variables that were used as multipliers for individual storm events. Results suggest that occasional snow water equivalent (SWE) observations together with daily streamflow observations do not contain enough information to simultaneously identify model parameters, precipitation uncertainty and model structural uncertainty in the Rudbäck catchment. The addition of an autoregressive component to account for model structure error and latent variables having uniform priors to account for input uncertainty lead to dubious posterior distributions of model parameters. Thus our hypothesis that informative priors for latent variables could be replaced by additional SWE data could not be confirmed. The model was found to work adequately in 1-day-ahead simulation mode, but the results were poor in the simulation batch mode. This was caused by the interaction of parameters that were used to describe different sources of uncertainty. The findings may have lessons for other cases where parameterizations are similarly high in relation to available prior information.
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Directory of Open Access Journals (Sweden)
Hong Hanh Nguyen
2017-01-01
Full Text Available To assist water resource managers with future land use planning efforts, the eco-hydrological model Soil and Water Assessment Tool (SWAT was applied to three catchments in South Australia that experience extreme low flow conditions. Particular land uses and management issues of interest included forest covers, known to affect water yields, and farm dams, known to intercept and change the hydrological dynamics in a catchment. The study achieved a satisfactory daily calibration when irrigation farm dams were incorporated in the model. For the catchment dominated by extreme low flows, a better daily simulation across a range of qualitative and quantitative metrics was gained using the base-flow static threshold optimization technique. Scenario analysis on effects of forest cover indicated an increase of surface flow and a reduction of base-flow when native eucalyptus lands were replaced by pastures and vice versa. A decreasing trend was observed for the overall water yield of catchments with more forest plantation due to the higher evapotranspiration (ET rate and the decline in surface flow. With regards to effects of irrigation farm dams, assessment on a daily time step suggested that a significant volume of water is stored in these systems with the water loss rate highest in June and July. On an annual basis, the model indicated that approximately 13.1% to 22.0% of water has been captured by farm dams for irrigation. However, the scenario analysis revealed that the purposes of use of farm dams rather than their volumetric capacities in the catchment determined the magnitude of effects on streamflows. Water extracted from farm dams for irrigation of orchards and vineyards are more likely to diminish streamflows than other land uses. Outputs from this study suggest that the water use restrictions from farm dams during recent drought periods were an effective tool to minimize impacts on streamflows.
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Streamflow Trends and Responses to Climate Variability and Land Cover Change in South Dakota
Directory of Open Access Journals (Sweden)
Karishma Niloy Kibria
2016-01-01
Full Text Available Trends in high, moderate, and low streamflow conditions from United States Geological Survey (USGS gauging stations were evaluated for a period of 1951–2013 for 18 selected watersheds in South Dakota (SD using a modified Mann-Kendall test. Rainfall trends from 21 rainfall observation stations located within 20-km of the streamflow gauging stations were also evaluated for the same study period. The concept of elasticity was used to examine sensitivity of streamflow to variation in rainfall and land cover (i.e., grassland in the study watersheds. Results indicated significant increasing trends in seven of the studied streams (of which five are in the east and two are located in the west, nine with slight increasing trends, and two with decreasing trends for annual streamflow. About half of the streams exhibited significant increasing trends in low and moderate flow conditions compared to high flow conditions. Ten rainfall stations showed slight increasing trends and seven showed decreasing trends for annual rainfall. Streamflow elasticity analysis revealed that streamflow was highly influenced by rainfall across the state (five of eastern streams and seven of western streams. Based on this analysis, a 10% increase in annual rainfall would result in 11%–30% increase in annual streamflow in more than 60% of SD streams. While streamflow appears to be more sensitive to rainfall across the state, high sensitivity of streamflow to rapid decrease in grassland area was detected in two western watersheds. This study provides valuable insight into of the relationship between streamflow, climate, and grassland cover in SD and would support further research and stakeholder decision making about water resources.
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IOD and ENSO impacts on the extreme stream-flows of Citarum river in Indonesia
Sahu, Netrananda; Behera, Swadhin K.; Yamashiki, Yosuke; Takara, Kaoru; Yamagata, Toshio
2012-10-01
Extreme stream-flow events of Citarum River are derived from the daily stream-flows at the Nanjung gauge station. Those events are identified based on their persistently extreme flows for 6 or more days during boreal fall when the seasonal mean stream-flow starts peaking-up from the lowest seasonal flows of June-August. Most of the extreme events of high-streamflows were related to La Niña conditions of tropical Pacific. A few of them were also associated with the negative phases of IOD and the newly identified El Niño Modoki. Unlike the cases of extreme high streamflows, extreme low streamflow events are seen to be associated with the positive IODs. Nevertheless, it was also found that the low-stream-flow events related to positive IOD events were also associated with El Niño events except for one independent event of 1977. Because the occurrence season coincides the peak season of IOD, not only the picked extreme events are seen to fall under the IOD seasons but also there exists a statistically significant correlation of 0.51 between the seasonal IOD index and the seasonal streamflows. There also exists a significant lag correlation when IOD of June-August season leads the streamflows of September-November. A significant but lower correlation coefficient (0.39) is also found between the seasonal streamflow and El Niño for September-November season only.
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Causes of interannual to decadal variability of Gila River streamflow over the past century
Directory of Open Access Journals (Sweden)
M.A. Pascolini-Campbell
2015-03-01
Full Text Available Study region: The Gila River, New Mexico, is characterized by two peaks in streamflow: one in the winter–spring (December–May, and summer (August–September. The region is influenced both by Pacific SST variability as well as the North American Monsoon. Study focus: The mechanisms responsible for the variability of the winter–spring and summer streamflow peaks are investigated by correlation of streamflow with precipitation and sea surface temperature for 1928–2012. Decadal variability in the flow record is examined for a longer term perspective on Gila River streamflow using tree ring-based reconstructions of the Palmer Drought Severity Index (PDSI and the Standardized Precipitation Index (SPI. New hydrological insights for the region: Results indicate a strong influence of winter–spring precipitation and Pacific SST anomalies on the winter–spring streamflow, with El Niño conditions in the Pacific causing increased precipitation and streamflow. Decadal Pacific variability helps explain the transition from high winter flow in the late 20th century to lower flows in the most recent decade. The summer streamflow has a somewhat weaker correlation with precipitation and Pacific SST than the winter–spring streamflow. Its variability is more likely influenced by local North American Monsoon precipitation variability. PDSI and SPI reconstructions indicate much more severe and extended periods of droughts and pluvials in past centuries as well as periods of concurrent winter and summer drought. Keywords: Streamflow decadal variability, Drought, Pluvials, Treering, Teleconnections, North American Monsoon
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Yang, Xiaoli; Zheng, Weifei; Ren, Liliang; Zhang, Mengru; Wang, Yuqian; Liu, Yi; Yuan, Fei; Jiang, Shanhu
2018-02-01
The Yellow River Basin (YRB) is the largest river basin in northern China, which has suffering water scarcity and drought hazard for many years. Therefore, assessments the potential impacts of climate change on the future streamflow in this basin is very important for local policy and planning on food security. In this study, based on the observations of 101 meteorological stations in YRB, equidistant CDF matching (EDCDFm) statistical downscaling approach was applied to eight climate models under two emissions scenarios (RCP4.5 and RCP8.5) from phase five of the Coupled Model Intercomparison Project (CMIP5). Variable infiltration capacity (VIC) model with 0.25° × 0.25° spatial resolution was developed based on downscaled fields for simulating streamflow in the future period over YRB. The results show that with the global warming trend, the annual streamflow will reduced about 10 % during the period of 2021-2050, compared to the base period of 1961-1990 in YRB. There should be suitable water resources planning to meet the demands of growing populations and future climate changing in this region.
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An environmental streamflow assessment for the Santiam River basin, Oregon
Risley, John C.; Wallick, J. Rose; Mangano, Joseph F.; Jones, Krista L.
2012-01-01
The Santiam River is a tributary of the Willamette River in northwestern Oregon and drains an area of 1,810 square miles. The U.S. Army Corps of Engineers (USACE) operates four dams in the basin, which are used primarily for flood control, hydropower production, recreation, and water-quality improvement. The Detroit and Big Cliff Dams were constructed in 1953 on the North Santiam River. The Green Peter and Foster Dams were completed in 1967 on the South Santiam River. The impacts of the structures have included a decrease in the frequency and magnitude of floods and an increase in low flows. For three North Santiam River reaches, the median of annual 1-day maximum streamflows decreased 42–50 percent because of regulated streamflow conditions. Likewise, for three reaches in the South Santiam River basin, the median of annual 1-day maximum streamflows decreased 39–52 percent because of regulation. In contrast to their effect on high flows, the dams increased low flows. The median of annual 7-day minimum flows in six of the seven study reaches increased under regulated streamflow conditions between 60 and 334 percent. On a seasonal basis, median monthly streamflows decreased from February to May and increased from September to January in all the reaches. However, the magnitude of these impacts usually decreased farther downstream from dams because of cumulative inflow from unregulated tributaries and groundwater entering the North, South, and main-stem Santiam Rivers below the dams. A Wilcox rank-sum test of monthly precipitation data from Salem, Oregon, and Waterloo, Oregon, found no significant difference between the pre-and post-dam periods, which suggests that the construction and operation of the dams since the 1950s and 1960s are a primary cause of alterations to the Santiam River basin streamflow regime. In addition to the streamflow analysis, this report provides a geomorphic characterization of the Santiam River basin and the associated conceptual
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Streamflow characteristics and trends along Soldier Creek, Northeast Kansas
Juracek, Kyle E.
2017-08-16
Historical data for six selected U.S. Geological Survey streamgages along Soldier Creek in northeast Kansas were used in an assessment of streamflow characteristics and trends. This information is required by the Prairie Band Potawatomi Nation for the effective management of tribal water resources, including drought contingency planning. Streamflow data for the period of record at each streamgage were used to assess annual mean streamflow, annual mean base flow, mean monthly flow, annual peak flow, and annual minimum flow.Annual mean streamflows along Soldier Creek were characterized by substantial year-to-year variability with no pronounced long-term trends. On average, annual mean base flow accounted for about 20 percent of annual mean streamflow. Mean monthly flows followed a general seasonal pattern that included peak values in spring and low values in winter. Annual peak flows, which were characterized by considerable year-to-year variability, were most likely to occur in May and June and least likely to occur during November through February. With the exception of a weak yet statistically significant increasing trend at the Soldier Creek near Topeka, Kansas, streamgage, there were no pronounced long-term trends in annual peak flows. Annual 1-day, 30-day, and 90-day mean minimum flows were characterized by considerable year-to-year variability with no pronounced long-term trend. During an extreme drought, as was the case in the mid-1950s, there may be zero flow in Soldier Creek continuously for a period of one to several months.
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Identification of symmetric and asymmetric responses in seasonal streamflow globally to ENSO phase
Lee, Donghoon; Ward, Philip J.; Block, Paul
2018-04-01
The phase of the El Niño Southern Oscillation (ENSO) has large-ranging effects on streamflow and hydrologic conditions globally. While many studies have evaluated this relationship through correlation analysis between annual streamflow and ENSO indices, an assessment of potential asymmetric relationships between ENSO and streamflow is lacking. Here, we evaluate seasonal variations in streamflow by ENSO phase to identify asymmetric (AR) and symmetric (SR) spatial pattern responses globally and further corroborate with local precipitation and hydrological condition. The AR and SR patterns between seasonal precipitation and streamflow are identified at many locations for the first time. Our results identify strong SR patterns in particular regions including northwestern and southern US, northeastern and southeastern South America, northeastern and southern Africa, southwestern Europe, and central-south Russia. The seasonally lagged anomalous streamflow patterns are also identified and attributed to snowmelt, soil moisture, and/or cumulative hydrological processes across river basins. These findings may be useful in water resources management and natural hazards planning by better characterizing the propensity of flood or drought conditions by ENSO phase.
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Fatichi, S; Rimkus, S; Burlando, P; Bordoy, R
2014-09-15
Projections of climate change effects in streamflow are increasingly required to plan water management strategies. These projections are however largely uncertain due to the spread among climate model realizations, internal climate variability, and difficulties in transferring climate model results at the spatial and temporal scales required by catchment hydrology. A combination of a stochastic downscaling methodology and distributed hydrological modeling was used in the ACQWA project to provide projections of future streamflow (up to year 2050) for the upper Po and Rhone basins, respectively located in northern Italy and south-western Switzerland. Results suggest that internal (stochastic) climate variability is a fundamental source of uncertainty, typically comparable or larger than the projected climate change signal. Therefore, climate change effects in streamflow mean, frequency, and seasonality can be masked by natural climatic fluctuations in large parts of the analyzed regions. An exception to the overwhelming role of stochastic variability is represented by high elevation catchments fed by glaciers where streamflow is expected to be considerably reduced due to glacier retreat, with consequences appreciable in the main downstream rivers in August and September. Simulations also identify regions (west upper Rhone and Toce, Ticino river basins) where a strong precipitation increase in the February to April period projects streamflow beyond the range of natural climate variability during the melting season. This study emphasizes the importance of including internal climate variability in climate change analyses, especially when compared to the limited uncertainty that would be accounted for by few deterministic projections. The presented results could be useful in guiding more specific impact studies, although design or management decisions should be better based on reliability and vulnerability criteria as suggested by recent literature. Copyright © 2013
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Directory of Open Access Journals (Sweden)
Z. Li
2017-11-01
Full Text Available Projected hydrological variability is important for future resource and hazard management of water supplies because changes in hydrological variability can cause more disasters than changes in the mean state. However, climate change scenarios downscaled from Earth System Models (ESMs at single sites cannot meet the requirements of distributed hydrologic models for simulating hydrological variability. This study developed multisite multivariate climate change scenarios via three steps: (i spatial downscaling of ESMs using a transfer function method, (ii temporal downscaling of ESMs using a single-site weather generator, and (iii reconstruction of spatiotemporal correlations using a distribution-free shuffle procedure. Multisite precipitation and temperature change scenarios for 2011–2040 were generated from five ESMs under four representative concentration pathways to project changes in streamflow variability using the Soil and Water Assessment Tool (SWAT for the Jing River, China. The correlation reconstruction method performed realistically for intersite and intervariable correlation reproduction and hydrological modeling. The SWAT model was found to be well calibrated with monthly streamflow with a model efficiency coefficient of 0.78. It was projected that the annual mean precipitation would not change, while the mean maximum and minimum temperatures would increase significantly by 1.6 ± 0.3 and 1.3 ± 0.2 °C; the variance ratios of 2011–2040 to 1961–2005 were 1.15 ± 0.13 for precipitation, 1.15 ± 0.14 for mean maximum temperature, and 1.04 ± 0.10 for mean minimum temperature. A warmer climate was predicted for the flood season, while the dry season was projected to become wetter and warmer; the findings indicated that the intra-annual and interannual variations in the future climate would be greater than in the current climate. The total annual streamflow was found to change insignificantly but its
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The Impacts of Climate Variability and Land Use Change on Streamflow in the Hailiutu River Basin
Directory of Open Access Journals (Sweden)
Guangwen Shao
2018-06-01
Full Text Available The Hailiutu River basin is a typical semi-arid wind sandy grass shoal watershed in northwest China. Climate and land use have changed significantly during the period 1970–2014. These changes are expected to impact hydrological processes in the basin. The Mann–Kendall (MK test and sequential t-test analysis of the regime shift method were used to detect the trend and shifts of the hydrometeorological time series. Based on the analyzed results, seven scenarios were developed by combining different land use and/or climate situations. The Soil Water Assessment Tool (SWAT model was applied to analyze the impacts of climate variability and land use change on the values of the hydrological components. The China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS was applied to enhance the spatial expressiveness of precipitation data in the study area during the period 2008–2014. Rather than solely using observed precipitation or CMADS precipitation, the precipitation values of CMADS and the observed precipitation values were combined to drive the SWAT model for better simulation results. From the trend analysis, the annual streamflow and wind speed showed a significant downward trend. No significant trend was found for the annual precipitation series; however, the temperature series showed upward trends. With the change point analysis, the whole study period was divided into three sub-periods (1970–1985, 1986–2000, and 2001–2014. The annual precipitation, mean wind speed, and average temperature values were 316 mm, 2.62 m/s, and 7.9 °C, respectively, for the sub-period 1970–1985, 272 mm, 2.58 m/s, and 8.4 °C, respectively, for the sub-period 1986–2000, and 391 mm, 2.2 m/s, and 9.35 °C, respectively, for the sub-period 2001–2014. The simulated mean annual streamflow was 35.09 mm/year during the period 1970–1985. Considering the impact of the climate variability, the simulated mean annual streamflow values were
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Restrepo-Estrada, Camilo; de Andrade, Sidgley Camargo; Abe, Narumi; Fava, Maria Clara; Mendiondo, Eduardo Mario; de Albuquerque, João Porto
2018-02-01
Floods are one of the most devastating types of worldwide disasters in terms of human, economic, and social losses. If authoritative data is scarce, or unavailable for some periods, other sources of information are required to improve streamflow estimation and early flood warnings. Georeferenced social media messages are increasingly being regarded as an alternative source of information for coping with flood risks. However, existing studies have mostly concentrated on the links between geo-social media activity and flooded areas. Thus, there is still a gap in research with regard to the use of social media as a proxy for rainfall-runoff estimations and flood forecasting. To address this, we propose using a transformation function that creates a proxy variable for rainfall by analysing geo-social media messages and rainfall measurements from authoritative sources, which are later incorporated within a hydrological model for streamflow estimation. We found that the combined use of official rainfall values with the social media proxy variable as input for the Probability Distributed Model (PDM), improved streamflow simulations for flood monitoring. The combination of authoritative sources and transformed geo-social media data during flood events achieved a 71% degree of accuracy and a 29% underestimation rate in a comparison made with real streamflow measurements. This is a significant improvement on the respective values of 39% and 58%, achieved when only authoritative data were used for the modelling. This result is clear evidence of the potential use of derived geo-social media data as a proxy for environmental variables for improving flood early-warning systems.
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SWAT application in intensive irrigation systems: Model modification, calibration and validation
Dechmi, Farida; Burguete, Javier; Skhiri, Ahmed
2012-01-01
The Soil and Water Assessment Tool (SWAT) is a well established, distributed, eco-hydrologic model. However, using the study case of an agricultural intensive irrigated watershed, it was shown that all the model versions are not able to appropriately reproduce the total streamflow in such system when the irrigation source is outside the watershed. The objective of this study was to modify the SWAT2005 version for correctly simulating the main hydrological processes. Crop yield, total streamfl...
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Arsenault, R.; Mai, J.; Latraverse, M.; Tolson, B.
2017-12-01
Probabilistic ensemble forecasts generated by the ensemble streamflow prediction (ESP) methodology are subject to biases due to errors in the hydrological model's initial states. In day-to-day operations, hydrologists must compensate for discrepancies between observed and simulated states such as streamflow. However, in data-scarce regions, little to no information is available to guide the streamflow assimilation process. The manual assimilation process can then lead to more uncertainty due to the numerous options available to the forecaster. Furthermore, the model's mass balance may be compromised and could affect future forecasts. In this study we propose a data-driven approach in which specific variables that may be adjusted during assimilation are defined. The underlying principle was to identify key variables that would be the most appropriate to modify during streamflow assimilation depending on the initial conditions such as the time period of the assimilation, the snow water equivalent of the snowpack and meteorological conditions. The variables to adjust were determined by performing an automatic variational data assimilation on individual (or combinations of) model state variables and meteorological forcing. The assimilation aimed to simultaneously optimize: (1) the error between the observed and simulated streamflow at the timepoint where the forecasts starts and (2) the bias between medium to long-term observed and simulated flows, which were simulated by running the model with the observed meteorological data on a hindcast period. The optimal variables were then classified according to the initial conditions at the time period where the forecast is initiated. The proposed method was evaluated by measuring the average electricity generation of a hydropower complex in Québec, Canada driven by this method. A test-bed which simulates the real-world assimilation, forecasting, water release optimization and decision-making of a hydropower cascade was
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Painter, Colin C.; Heimann, David C.; Lanning-Rush, Jennifer L.
2017-08-14
A study was done by the U.S. Geological Survey in cooperation with the Kansas Department of Transportation and the Federal Emergency Management Agency to develop regression models to estimate peak streamflows of annual exceedance probabilities of 50, 20, 10, 4, 2, 1, 0.5, and 0.2 percent at ungaged locations in Kansas. Peak streamflow frequency statistics from selected streamgages were related to contributing drainage area and average precipitation using generalized least-squares regression analysis. The peak streamflow statistics were derived from 151 streamgages with at least 25 years of streamflow data through 2015. The developed equations can be used to predict peak streamflow magnitude and frequency within two hydrologic regions that were defined based on the effects of irrigation. The equations developed in this report are applicable to streams in Kansas that are not substantially affected by regulation, surface-water diversions, or urbanization. The equations are intended for use for streams with contributing drainage areas ranging from 0.17 to 14,901 square miles in the nonirrigation effects region and, 1.02 to 3,555 square miles in the irrigation-affected region, corresponding to the range of drainage areas of the streamgages used in the development of the regional equations.
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Modeling streamflow from coupled airborne laser scanning and acoustic Doppler current profiler data
Norris, Lam; Kean, Jason W.; Lyon, Steve
2016-01-01
The rating curve enables the translation of water depth into stream discharge through a reference cross-section. This study investigates coupling national scale airborne laser scanning (ALS) and acoustic Doppler current profiler (ADCP) bathymetric survey data for generating stream rating curves. A digital terrain model was defined from these data and applied in a physically based 1-D hydraulic model to generate rating curves for a regularly monitored location in northern Sweden. Analysis of the ALS data showed that overestimation of the streambank elevation could be adjusted with a root mean square error (RMSE) block adjustment using a higher accuracy manual topographic survey. The results of our study demonstrate that the rating curve generated from the vertically corrected ALS data combined with ADCP data had lower errors (RMSE = 0.79 m3/s) than the empirical rating curve (RMSE = 1.13 m3/s) when compared to streamflow measurements. We consider these findings encouraging as hydrometric agencies can potentially leverage national-scale ALS and ADCP instrumentation to reduce the cost and effort required for maintaining and establishing rating curves at gauging station sites similar to the Röån River.
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Liu, Z.; Rajib, M. A.; Jafarzadegan, K.; Merwade, V.
2015-12-01
Application of land surface/hydrologic models within an operational flood forecasting system can provide probable time of occurrence and magnitude of streamflow at specific locations along a stream. Creating time-varying spatial extent of flood inundation and depth requires the use of a hydraulic or hydrodynamic model. Models differ in representing river geometry and surface roughness which can lead to different output depending on the particular model being used. The result from a single hydraulic model provides just one possible realization of the flood extent without capturing the uncertainty associated with the input or the model parameters. The objective of this study is to compare multiple hydraulic models toward generating ensemble flood inundation extents. Specifically, relative performances of four hydraulic models, including AutoRoute, HEC-RAS, HEC-RAS 2D, and LISFLOOD are evaluated under different geophysical conditions in several locations across the United States. By using streamflow output from the same hydrologic model (SWAT in this case), hydraulic simulations are conducted for three configurations: (i) hindcasting mode by using past observed weather data at daily time scale in which models are being calibrated against USGS streamflow observations, (ii) validation mode using near real-time weather data at sub-daily time scale, and (iii) design mode with extreme streamflow data having specific return periods. Model generated inundation maps for observed flood events both from hindcasting and validation modes are compared with remotely sensed images, whereas the design mode outcomes are compared with corresponding FEMA generated flood hazard maps. The comparisons presented here will give insights on probable model-specific nature of biases and their relative advantages/disadvantages as components of an operational flood forecasting system.
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Shallow and Deep Groundwater Contributions to Ephemeral Streamflow Generation
Zimmer, M. A.; McGlynn, B. L.
2016-12-01
Our understanding of streamflow generation processes in low relief, humid landscapes is limited. To address this, we utilized an ephemeral-to-intermittent drainage network in the Piedmont region of the United States to gain new understanding about the drivers of ephemeral streamflow generation, stream-groundwater interactions, and longitudinal expansion and contraction of the stream network. We used hydrometric and chemical data collected within zero through second order catchments to characterize streamflow and overland, shallow soil, and deep subsurface flow across landscape positions. Results showed bi-directionality in stream-groundwater gradients that were dependent on catchment storage state. This led to annual groundwater recharge magnitudes that were similar to annual streamflow. Perched shallow and deep water table contributions shifted dominance with changes in catchment storage state, producing distinct stream hydrograph recession constants. Active channel length versus runoff followed a consistent relationship independent of storage state, but exhibited varying discharge-solute hysteresis directions. Together, our results suggest that temporary streams can act as both important groundwater recharge and discharge locations across the landscape, especially in this region where ephemeral drainage densities are among the highest recorded. Our results also highlight that the internal catchment dynamics that generate temporary streams play an important role in dictating biogeochemical fluxes at the landscape scale.
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Teutschbein, Claudia; Grabs, Thomas; Laudon, Hjalmar; Karlsen, Reinert H.; Bishop, Kevin
2018-06-01
In this paper we explored how landscape characteristics such as topography, geology, soils and land cover influence the way catchments respond to changing climate conditions. Based on an ensemble of 15 regional climate models bias-corrected with a distribution-mapping approach, present and future streamflow in 14 neighboring and rather similar catchments in Northern Sweden was simulated with the HBV model. We established functional relationships between a range of landscape characteristics and projected changes in streamflow signatures. These were then used to analyze hydrological consequences of physical perturbations in a hypothetically ungauged basin in a climate change context. Our analysis showed a strong connection between the forest cover extent and the sensitivity of different components of a catchment's hydrological regime to changing climate conditions. This emphasizes the need to redefine forestry goals and practices in advance of climate change-related risks and uncertainties.
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An analytical approach to separate climate and human contributions to basin streamflow variability
Li, Changbin; Wang, Liuming; Wanrui, Wang; Qi, Jiaguo; Linshan, Yang; Zhang, Yuan; Lei, Wu; Cui, Xia; Wang, Peng
2018-04-01
Climate variability and anthropogenic regulations are two interwoven factors in the ecohydrologic system across large basins. Understanding the roles that these two factors play under various hydrologic conditions is of great significance for basin hydrology and sustainable water utilization. In this study, we present an analytical approach based on coupling water balance method and Budyko hypothesis to derive effectiveness coefficients (ECs) of climate change, as a way to disentangle contributions of it and human activities to the variability of river discharges under different hydro-transitional situations. The climate dominated streamflow change (ΔQc) by EC approach was compared with those deduced by the elasticity method and sensitivity index. The results suggest that the EC approach is valid and applicable for hydrologic study at large basin scale. Analyses of various scenarios revealed that contributions of climate change and human activities to river discharge variation differed among the regions of the study area. Over the past several decades, climate change dominated hydro-transitions from dry to wet, while human activities played key roles in the reduction of streamflow during wet to dry periods. Remarkable decline of discharge in upstream was mainly due to human interventions, although climate contributed more to runoff increasing during dry periods in the semi-arid downstream. Induced effectiveness on streamflow changes indicated a contribution ratio of 49% for climate and 51% for human activities at the basin scale from 1956 to 2015. The mathematic derivation based simple approach, together with the case example of temporal segmentation and spatial zoning, could help people understand variation of river discharge with more details at a large basin scale under the background of climate change and human regulations.
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Lee, T.M.; Sacks, L.A.; Hughes, J.D.
2010-01-01
The Charlie Creek basin was studied from April 2004 to December 2005 to better understand how groundwater levels in the underlying aquifers and storage and overflow of water from headwater wetlands preserve the streamflows exiting this least-developed tributary basin of the Peace River watershed. The hydrogeologic framework, physical characteristics, and streamflow were described and quantified for five subbasins of the 330-square mile Charlie Creek basin, allowing the contribution of its headwaters area and tributary subbasins to be separately quantified. A MIKE SHE model simulation of the integrated surface-water and groundwater flow processes in the basin was used to simulate daily streamflow observed over 21 months in 2004 and 2005 at five streamflow stations, and to quantify the monthly and annual water budgets for the five subbasins including the changing amount of water stored in wetlands. Groundwater heads were mapped in Zone 2 of the intermediate aquifer system and in the Upper Floridan aquifer, and were used to interpret the location of artesian head conditions in the Charlie Creek basin and its relation to streamflow. Artesian conditions in the intermediate aquifer system induce upward groundwater flow into the surficial aquifer and help sustain base flow which supplies about two-thirds of the streamflow from the Charlie Creek basin. Seepage measurements confirmed seepage inflow to Charlie Creek during the study period. The upper half of the basin, comprised largely of the Upper Charlie Creek subbasin, has lower runoff potential than the lower basin, more storage of runoff in wetlands, and periodically generates no streamflow. Artesian head conditions in the intermediate aquifer system were widespread in the upper half of the Charlie Creek basin, preventing downward leakage from expansive areas of wetlands and enabling them to act as headwaters to Charlie Creek once their storage requirements were met. Currently, the dynamic balance between wetland
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Statistical summaries of selected Iowa streamflow data through September 2013
Eash, David A.; O'Shea, Padraic S.; Weber, Jared R.; Nguyen, Kevin T.; Montgomery, Nicholas L.; Simonson, Adrian J.
2016-01-04
Statistical summaries of streamflow data collected at 184 streamgages in Iowa are presented in this report. All streamgages included for analysis have at least 10 years of continuous record collected before or through September 2013. This report is an update to two previously published reports that presented statistical summaries of selected Iowa streamflow data through September 1988 and September 1996. The statistical summaries include (1) monthly and annual flow durations, (2) annual exceedance probabilities of instantaneous peak discharges (flood frequencies), (3) annual exceedance probabilities of high discharges, and (4) annual nonexceedance probabilities of low discharges and seasonal low discharges. Also presented for each streamgage are graphs of the annual mean discharges, mean annual mean discharges, 50-percent annual flow-duration discharges (median flows), harmonic mean flows, mean daily mean discharges, and flow-duration curves. Two sets of statistical summaries are presented for each streamgage, which include (1) long-term statistics for the entire period of streamflow record and (2) recent-term statistics for or during the 30-year period of record from 1984 to 2013. The recent-term statistics are only calculated for streamgages with streamflow records pre-dating the 1984 water year and with at least 10 years of record during 1984–2013. The streamflow statistics in this report are not adjusted for the effects of water use; although some of this water is used consumptively, most of it is returned to the streams.
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International Nuclear Information System (INIS)
Xie, Mengfei; Zhou, Jianzhong; Li, Chunlong; Zhu, Shuang
2015-01-01
Highlights: • Monthly streamflow forecasting error is considered. • An improved parallel progressive optimality algorithm is proposed. • Forecasting dispatching chart is manufactured accompanying with a set of rules. • Applications in Xiluodu and Xiangjiaba cascade hydro plants. - Abstract: Reliable streamflow forecasts are very significant for reservoir operation and hydropower generation. But for monthly streamflow forecasting, the forecasting result is unreliable and it is hard to be utilized, although it has a certain reference value for long-term hydro generation scheduling. Current researches mainly focus on deterministic scheduling, and few of them consider the uncertainties. So this paper considers the forecasting error which exists in monthly streamflow forecasting and proposes a new long-term hydro generation scheduling method called forecasting dispatching chart for Xiluodu and Xiangjiaba cascade hydro plants. First, in order to consider the uncertainties of inflow, Monte Carlo simulation is employed to generate streamflow data according to the forecasting value and error distribution curves. Then the large amount of data obtained by Monte Carlo simulation is used as inputs for long-term hydro generation scheduling model. Because of the large amount of streamflow data, the computation speed of conventional algorithm cannot meet the demand. So an improved parallel progressive optimality algorithm is proposed to solve the long-term hydro generation scheduling problem and a series of solutions are obtained. These solutions constitute an interval set, unlike the unique solution in the traditional deterministic long-term hydro generation scheduling. At last, the confidence intervals of the solutions are calculated and forecasting dispatching chart is proposed as a new method for long-term hydro generation scheduling. A set of rules are proposed corresponding to forecasting dispatching chart. The chart is tested for practical operations and achieves
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An intercomparison of approaches for improving operational seasonal streamflow forecasts
Mendoza, Pablo A.; Wood, Andrew W.; Clark, Elizabeth; Rothwell, Eric; Clark, Martyn P.; Nijssen, Bart; Brekke, Levi D.; Arnold, Jeffrey R.
2017-07-01
For much of the last century, forecasting centers around the world have offered seasonal streamflow predictions to support water management. Recent work suggests that the two major avenues to advance seasonal predictability are improvements in the estimation of initial hydrologic conditions (IHCs) and the incorporation of climate information. This study investigates the marginal benefits of a variety of methods using IHCs and/or climate information, focusing on seasonal water supply forecasts (WSFs) in five case study watersheds located in the US Pacific Northwest region. We specify two benchmark methods that mimic standard operational approaches - statistical regression against IHCs and model-based ensemble streamflow prediction (ESP) - and then systematically intercompare WSFs across a range of lead times. Additional methods include (i) statistical techniques using climate information either from standard indices or from climate reanalysis variables and (ii) several hybrid/hierarchical approaches harnessing both land surface and climate predictability. In basins where atmospheric teleconnection signals are strong, and when watershed predictability is low, climate information alone provides considerable improvements. For those basins showing weak teleconnections, custom predictors from reanalysis fields were more effective in forecast skill than standard climate indices. ESP predictions tended to have high correlation skill but greater bias compared to other methods, and climate predictors failed to substantially improve these deficiencies within a trace weighting framework. Lower complexity techniques were competitive with more complex methods, and the hierarchical expert regression approach introduced here (hierarchical ensemble streamflow prediction - HESP) provided a robust alternative for skillful and reliable water supply forecasts at all initialization times. Three key findings from this effort are (1) objective approaches supporting methodologically
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Multivariate Bias Correction Procedures for Improving Water Quality Predictions from the SWAT Model
Arumugam, S.; Libera, D.
2017-12-01
Water quality observations are usually not available on a continuous basis for longer than 1-2 years at a time over a decadal period given the labor requirements making calibrating and validating mechanistic models difficult. Further, any physical model predictions inherently have bias (i.e., under/over estimation) and require post-simulation techniques to preserve the long-term mean monthly attributes. This study suggests a multivariate bias-correction technique and compares to a common technique in improving the performance of the SWAT model in predicting daily streamflow and TN loads across the southeast based on split-sample validation. The approach is a dimension reduction technique, canonical correlation analysis (CCA) that regresses the observed multivariate attributes with the SWAT model simulated values. The common approach is a regression based technique that uses an ordinary least squares regression to adjust model values. The observed cross-correlation between loadings and streamflow is better preserved when using canonical correlation while simultaneously reducing individual biases. Additionally, canonical correlation analysis does a better job in preserving the observed joint likelihood of observed streamflow and loadings. These procedures were applied to 3 watersheds chosen from the Water Quality Network in the Southeast Region; specifically, watersheds with sufficiently large drainage areas and number of observed data points. The performance of these two approaches are compared for the observed period and over a multi-decadal period using loading estimates from the USGS LOADEST model. Lastly, the CCA technique is applied in a forecasting sense by using 1-month ahead forecasts of P & T from ECHAM4.5 as forcings in the SWAT model. Skill in using the SWAT model for forecasting loadings and streamflow at the monthly and seasonal timescale is also discussed.
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Guay, Joel R.
2002-01-01
To better understand the rainfall-runoff characteristics of the eastern part of the San Jacinto River Basin and to estimate the effects of increased urbanization on streamflow, channel infiltration, and land-surface infiltration, a long-term (1950?98) time series of monthly flows in and out of the channels and land surfaces were simulated using the Hydrologic Simulation Program- FORTRAN (HSPF) rainfall-runoff model. Channel and land-surface infiltration includes rainfall or runoff that infiltrates past the zone of evapotranspiration and may become ground-water recharge. The study area encompasses about 256 square miles of the San Jacinto River drainage basin in Riverside County, California. Daily streamflow (for periods with available data between 1950 and 1998), and daily rainfall and evaporation (1950?98) data; monthly reservoir storage data (1961?98); and estimated mean annual reservoir inflow data (for 1974 conditions) were used to calibrate the rainfall-runoff model. Measured and simulated mean annual streamflows for the San Jacinto River near San Jacinto streamflow-gaging station (North-South Fork subbasin) for 1950?91 and 1997?98 were 14,000 and 14,200 acre-feet, respectively, a difference of 1.4 percent. The standard error of the mean for measured and simulated annual streamflow in the North-South Fork subbasin was 3,520 and 3,160 acre-feet, respectively. Measured and simulated mean annual streamflows for the Bautista Creek streamflow-gaging station (Bautista Creek subbasin) for 1950?98 were 980 acre-feet and 991 acre-feet, respectively, a difference of 1.1 percent. The standard error of the mean for measured and simulated annual streamflow in the Bautista Creek subbasin was 299 and 217 acre-feet, respectively. Measured and simulated annual streamflows for the San Jacinto River above State Street near San Jacinto streamflow-gaging station (Poppet subbasin) for 1998 were 23,400 and 23,500 acre-feet, respectively, a difference of 0.4 percent. The simulated
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Modelling the effects of climate change on streamflow in a sub-basin of the lower Churchill River
International Nuclear Information System (INIS)
Pryse-Phillips, Amy; Snelgrove, Ken
2010-01-01
Climate change is likely to affect extreme flows as well as average flows. This is an important consideration for hydroelectric power producers. This paper presented the development of an approach to assess the impact of climate changes on seasonal and average annual river flows. The main goal was to investigate how climate change will affect the hydroelectric potential of the Lower Churchill Project using different combinations of emissions scenarios, climate model output and downscaling techniques. The setup and calibration of the numerical hydrological model, WATFLOOD, were performed as preliminary work for the Pinus River basin selected as study basin. Downscaled climate data from the North America change assessment program for both current and future climate periods were analysed. The calibrated model was used to simulate the current and future period streamflow scenarios. The results showed a 13 percent increase in mean annual flows concentrated in the winter and spring seasons.
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Modelling the effects of climate change on streamflow in a sub-basin of the lower Churchill River
Energy Technology Data Exchange (ETDEWEB)
Pryse-Phillips, Amy [Hatch Ltd., St John' s, (Canada); Snelgrove, Ken [Memorial University of Newfoundland, St John' s, (Canada)
2010-07-01
Climate change is likely to affect extreme flows as well as average flows. This is an important consideration for hydroelectric power producers. This paper presented the development of an approach to assess the impact of climate changes on seasonal and average annual river flows. The main goal was to investigate how climate change will affect the hydroelectric potential of the Lower Churchill Project using different combinations of emissions scenarios, climate model output and downscaling techniques. The setup and calibration of the numerical hydrological model, WATFLOOD, were performed as preliminary work for the Pinus River basin selected as study basin. Downscaled climate data from the North America change assessment program for both current and future climate periods were analysed. The calibrated model was used to simulate the current and future period streamflow scenarios. The results showed a 13 percent increase in mean annual flows concentrated in the winter and spring seasons.
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Smith, Erik A.; Sanocki, Chris A.; Lorenz, David L.; Jacobsen, Katrin E.
2017-12-27
Streamflow distribution maps for the Cannon River and St. Louis River drainage basins were developed by the U.S. Geological Survey, in cooperation with the Legislative-Citizen Commission on Minnesota Resources, to illustrate relative and cumulative streamflow distributions. The Cannon River was selected to provide baseline data to assess the effects of potential surficial sand mining, and the St. Louis River was selected to determine the effects of ongoing Mesabi Iron Range mining. Each drainage basin (Cannon, St. Louis) was subdivided into nested drainage basins: the Cannon River was subdivided into 152 nested drainage basins, and the St. Louis River was subdivided into 353 nested drainage basins. For each smaller drainage basin, the estimated volumes of groundwater discharge (as base flow) and surface runoff flowing into all surface-water features were displayed under the following conditions: (1) extreme low-flow conditions, comparable to an exceedance-probability quantile of 0.95; (2) low-flow conditions, comparable to an exceedance-probability quantile of 0.90; (3) a median condition, comparable to an exceedance-probability quantile of 0.50; and (4) a high-flow condition, comparable to an exceedance-probability quantile of 0.02.Streamflow distribution maps were developed using flow-duration curve exceedance-probability quantiles in conjunction with Soil-Water-Balance model outputs; both the flow-duration curve and Soil-Water-Balance models were built upon previously published U.S. Geological Survey reports. The selected streamflow distribution maps provide a proactive water management tool for State cooperators by illustrating flow rates during a range of hydraulic conditions. Furthermore, after the nested drainage basins are highlighted in terms of surface-water flows, the streamflows can be evaluated in the context of meeting specific ecological flows under different flow regimes and potentially assist with decisions regarding groundwater and surface
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CSIR Research Space (South Africa)
Malherbe, J
2014-07-01
Full Text Available -1 Meteorological Applications Vol. 21(3) Seasonal forecasts of the SINTEX-F coupled model applied to maize yield and streamflow estimates over north-eastern South Africa J. Malherbe,a* W. A. Landman,b,c C. Olivier,d H. Sakumae and J- J. Luof a Institute... for Soil, Climate and Water, Agricultural Research Council, Pretoria, South Africa b Council for Scientific and Industrial Research, Natural Resources and the Environment, Pretoria, South Africa c Department of Geography, Geoinformatics and Meteorology...
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Estimated ground-water recharge from streamflow in Fortymile Wash near Yucca Mountain, Nevada
International Nuclear Information System (INIS)
Savard, C.S.
1998-01-01
The two purposes of this report are to qualitatively document ground-water recharge from stream-flow in Fortymile Wash during the period 1969--95 from previously unpublished ground-water levels in boreholes in Fortymile Canyon during 1982--91 and 1995, and to quantitatively estimate the long-term ground-water recharge rate from streamflow in Fortymile Wash for four reaches of Fortymile Wash (Fortymile Canyon, upper Jackass Flats, lower Jackass Flats, and Amargosa Desert). The long-term groundwater recharge rate was estimated from estimates of the volume of water available for infiltration, the volume of infiltration losses from streamflow, the ground-water recharge volume from infiltration losses, and an analysis of the different periods of data availability. The volume of water available for infiltration and ground-water recharge in the four reaches was estimated from known streamflow in ephemeral Fortymile Wash, which was measured at several gaging station locations. The volume of infiltration losses from streamflow for the four reaches was estimated from a streamflow volume loss factor applied to the estimated streamflows. the ground-water recharge volume was estimated from a linear relation between infiltration loss volume and ground-water recharge volume for each of the four reaches. Ground-water recharge rates were estimated for three different periods of data availability (1969--95, 1983--95, and 1992--95) and a long-term ground-water recharge rate estimated for each of the four reaches
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Estimated ground-water recharge from streamflow in Fortymile Wash near Yucca Mountain, Nevada
Energy Technology Data Exchange (ETDEWEB)
Savard, C.S.
1998-10-01
The two purposes of this report are to qualitatively document ground-water recharge from stream-flow in Fortymile Wash during the period 1969--95 from previously unpublished ground-water levels in boreholes in Fortymile Canyon during 1982--91 and 1995, and to quantitatively estimate the long-term ground-water recharge rate from streamflow in Fortymile Wash for four reaches of Fortymile Wash (Fortymile Canyon, upper Jackass Flats, lower Jackass Flats, and Amargosa Desert). The long-term groundwater recharge rate was estimated from estimates of the volume of water available for infiltration, the volume of infiltration losses from streamflow, the ground-water recharge volume from infiltration losses, and an analysis of the different periods of data availability. The volume of water available for infiltration and ground-water recharge in the four reaches was estimated from known streamflow in ephemeral Fortymile Wash, which was measured at several gaging station locations. The volume of infiltration losses from streamflow for the four reaches was estimated from a streamflow volume loss factor applied to the estimated streamflows. the ground-water recharge volume was estimated from a linear relation between infiltration loss volume and ground-water recharge volume for each of the four reaches. Ground-water recharge rates were estimated for three different periods of data availability (1969--95, 1983--95, and 1992--95) and a long-term ground-water recharge rate estimated for each of the four reaches.
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Obtaining Streamflow Statistics for Massachusetts Streams on the World Wide Web
Ries, Kernell G.; Steeves, Peter A.; Freeman, Aleda; Singh, Raj
2000-01-01
A World Wide Web application has been developed to make it easy to obtain streamflow statistics for user-selected locations on Massachusetts streams. The Web application, named STREAMSTATS (available at http://water.usgs.gov/osw/streamstats/massachusetts.html ), can provide peak-flow frequency, low-flow frequency, and flow-duration statistics for most streams in Massachusetts. These statistics describe the magnitude (how much), frequency (how often), and duration (how long) of flow in a stream. The U.S. Geological Survey (USGS) has published streamflow statistics, such as the 100-year peak flow, the 7-day, 10-year low flow, and flow-duration statistics, for its data-collection stations in numerous reports. Federal, State, and local agencies need these statistics to plan and manage use of water resources and to regulate activities in and around streams. Engineering and environmental consulting firms, utilities, industry, and others use the statistics to design and operate water-supply systems, hydropower facilities, industrial facilities, wastewater treatment facilities, and roads, bridges, and other structures. Until now, streamflow statistics for data-collection stations have often been difficult to obtain because they are scattered among many reports, some of which are not readily available to the public. In addition, streamflow statistics are often needed for locations where no data are available. STREAMSTATS helps solve these problems. STREAMSTATS was developed jointly by the USGS and MassGIS, the State Geographic Information Systems (GIS) agency, in cooperation with the Massachusetts Departments of Environmental Management and Environmental Protection. The application consists of three major components: (1) a user interface that displays maps and allows users to select stream locations for which they want streamflow statistics (fig. 1), (2) a data base of previously published streamflow statistics and descriptive information for 725 USGS data
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The forest-streamflow relationship in China: a 40-year retrospect
Xiaohua Wei; Ge Sun; Shirong Liu; Hong Jiang; Guoyi Zhou; Limin Dai
2008-01-01
The relationship between forests and streamflows has long been an important research interest in China. The purpose of this paper is to summarize progress and lessons learned from the forest-streamflow studies over the past four decades in China. To better measure the research gaps between China and other parts of the world, a brief global review on the findings from...
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Dauwalter, D.C.; Fisher, W.L.
2007-01-01
We documented the nesting chronology, nest site selection and nest success of smallmouth bass Micropterus dolomieu in an upstream (4th order) and downstream (5th order) reach of Baron Fork Creek, Oklahoma. Males started nesting in mid-Apr. when water temperatures increased to 16.9 C upstream, and in late-Apr. when temperatures increased to 16.2 C downstream. Streamflows were low (77% upstream to 82% downstream of mean Apr. streamflow, and 12 and 18% of meanjun. streamflow; 47 and 55 y of record), and decreased throughout the spawning period. Larger males nested first upstream, as has been observed in other populations, but not downstream. Upstream, progeny in 62 of 153 nests developed to swim-up stage. Downstream, progeny in 31 of 73 nests developed to swim-up. Nesting densities upstream (147/km) and downstream (100/km) were both higher than any densities previously reported. Males selected nest sites with intermediate water depths, low water velocity and near cover, behavior that is typical of smallmouth bass. Documented nest failures resulted from human disturbance, angling, and longear sunfish predation. Logistic exposure models showed that water velocity at the nest was negatively related and length of the guarding male was positively related to nest success upstream. Male length and number of degree days were both positively related to nest success downstream. Our results, and those of other studies, suggest that biological factors account for most nest failures during benign (stable, low flow) streamflow conditions, whereas nest failures attributed to substrate mobility or nest abandonment dominate when harsh streamflow conditions (spring floods) coincide with the spawning season.
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Streamflow characteristics of the Colorado River Basin in Utah through September 1981
Christensen, R.C.; Johnson, E.B.; Plantz, G.G.
1987-01-01
This report summarizes discharge data and other streamflow characteristics developed from gag ing-station records collected through September 1981 at 337 stations in the Colorado River Basin in Utah. Data also are included for 14 stations in adjacent areas of the bordering states of Arizona, Colorado, and Wyoming (fig. 1). The study leading to this report was done in cooperation with the U.S. Bureau of Land Management, which needs the streamflow data in order to evaluate impacts of mining on the hydrologic system. The report also will be beneficial to other Federal, State, and county agencies and to individuals concerned with water supply and water problems in the Colorado River Basin.The streamflow characteristics in the report could be useful in many water-related studies that involve the following:Definition of baseline-hydrologic conditions; studies of the effects of man's activities on streamflow; frequency analyses of low and high flows; regional analyses of streamflow characteristics; design of water-supply systems; water-power studies; forecasting of stream discharge; time-series analyses of streamflow; design of flood-control structures; stream-pollution studies; and water-chemistry transport studies.The basic data used to develop the summaries in this report are records of daily and peak discharge collected by the U.S. Geological Survey and other Federal agencies. Much of the work of the Geological Survey was done in cooperation with Federal, State, and county agencies. Discharge recordsincluded in the report generally were for stations with at least 1 complete water year of record and nearby stations that were on the same stream and had different streamflow characteristics. A water year is a 12-month period ending September 30, and it is designated by the calendar year in which it ends. For streams that have had significant changes in regulation by reservoirs or diversions, the records before and after those changes were used separately to provide
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United States streamflow probabilities based on forecasted La Nina, winter-spring 2000
Dettinger, M.D.; Cayan, D.R.; Redmond, K.T.
1999-01-01
Although for the last 5 months the TahitiDarwin Southern Oscillation Index (SOI) has hovered close to normal, the “equatorial” SOI has remained in the La Niña category and predictions are calling for La Niña conditions this winter. In view of these predictions of continuing La Niña and as a direct extension of previous studies of the relations between El NiñoSouthern Oscil-lation (ENSO) conditions and streamflow in the United States (e.g., Redmond and Koch, 1991; Cayan and Webb, 1992; Redmond and Cayan, 1994; Dettinger et al., 1998; Garen, 1998; Cayan et al., 1999; Dettinger et al., in press), the probabilities that United States streamflows from December 1999 through July 2000 will be in upper and lower thirds (terciles) of the historical records are estimated here. The processes that link ENSO to North American streamflow are discussed in detail in these diagnostics studies. Our justification for generating this forecast is threefold: (1) Cayan et al. (1999) recently have shown that ENSO influences on streamflow variations and extremes are proportionately larger than the corresponding precipitation teleconnections. (2) Redmond and Cayan (1994) and Dettinger et al. (in press) also have shown that the low-frequency evolution of ENSO conditions support long-lead correlations between ENSO and streamflow in many rivers of the conterminous United States. (3) In many rivers, significant (weeks-to-months) delays between precipitation and the release to streams of snowmelt or ground-water discharge can support even longer term forecasts of streamflow than is possible for precipitation. The relatively slow, orderly evolution of El Niño-Southern Oscillation episodes, the accentuated dependence of streamflow upon ENSO, and the long lags between precipitation and flow encourage us to provide the following analysis as a simple prediction of this year’s river flows.
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STATIONARITY OF ANNUAL MAXIMUM DAILY STREAMFLOW TIME SERIES IN SOUTH-EAST BRAZILIAN RIVERS
Directory of Open Access Journals (Sweden)
Jorge Machado Damázio
2015-08-01
Full Text Available DOI: 10.12957/cadest.2014.18302The paper presents a statistical analysis of annual maxima daily streamflow between 1931 and 2013 in South-East Brazil focused in detecting and modelling non-stationarity aspects. Flood protection for the large valleys in South-East Brazil is provided by multiple purpose reservoir systems built during 20th century, which design and operation plans has been done assuming stationarity of historical flood time series. Land cover changes and rapidly-increasing level of atmosphere greenhouse gases of the last century may be affecting flood regimes in these valleys so that it can be that nonstationary modelling should be applied to re-asses dam safety and flood control operation rules at the existent reservoir system. Six annual maximum daily streamflow time series are analysed. The time series were plotted together with fitted smooth loess functions and non-parametric statistical tests are performed to check the significance of apparent trends shown by the plots. Non-stationarity is modelled by fitting univariate extreme value distribution functions which location varies linearly with time. Stationarity and non-stationarity modelling are compared with the likelihood ratio statistic. In four of the six analyzed time series non-stationarity modelling outperformed stationarity modelling.Keywords: Stationarity; Extreme Value Distributions; Flood Frequency Analysis; Maximum Likelihood Method.
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An unusual kind of diurnal streamflow variation
Directory of Open Access Journals (Sweden)
Cuevas Jaime G.
2018-03-01
Full Text Available During hydrological research in a Chilean swamp forest, we noted a pattern of higher streamflows close to midday and lower ones close to midnight, the opposite of an evapotranspiration (Et-driven cycle. We analyzed this diurnal streamflow signal (DSS, which appeared mid-spring (in the growing season. The end of this DSS coincided with a sustained rain event in autumn, which deeply affected stream and meteorological variables. A survey along the stream revealed that the DSS maximum and minimum values appeared 6 and 4 hours earlier, respectively, at headwaters located in the mountain forests/ plantations than at the control point in the swamp forest. Et in the swamp forest was higher in the morning and in the late afternoon, but this process could not influence the groundwater stage. Trees in the mountain headwaters reached their maximum Ets in the early morning and/or close to midday. Our results suggest that the DSS is a wave that moves from forests high in the mountains towards lowland areas, where Et is decoupled from the DSS. This signal delay seems to convert the link between streamflow and Et in an apparent, but spurious positive relationship. It also highlights the role of landscape heterogeneity in shaping hydrological processes.
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Consistent and efficient processing of ADCP streamflow measurements
Mueller, David S.; Constantinescu, George; Garcia, Marcelo H.; Hanes, Dan
2016-01-01
The use of Acoustic Doppler Current Profilers (ADCPs) from a moving boat is a commonly used method for measuring streamflow. Currently, the algorithms used to compute the average depth, compute edge discharge, identify invalid data, and estimate velocity and discharge for invalid data vary among manufacturers. These differences could result in different discharges being computed from identical data. Consistent computational algorithm, automated filtering, and quality assessment of ADCP streamflow measurements that are independent of the ADCP manufacturer are being developed in a software program that can process ADCP moving-boat discharge measurements independent of the ADCP used to collect the data.
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María Santiago, José; Muñoz-Mas, Rafael; Solana-Gutiérrez, Joaquín; García de Jalón, Diego; Alonso, Carlos; Martínez-Capel, Francisco; Pórtoles, Javier; Monjo, Robert; Ribalaygua, Jaime
2017-08-01
Climate changes affect aquatic ecosystems by altering temperatures and precipitation patterns, and the rear edges of the distributions of cold-water species are especially sensitive to these effects. The main goal of this study was to predict in detail how changes in air temperature and precipitation will affect streamflow, the thermal habitat of a cold-water fish (the brown trout, Salmo trutta), and the synergistic relationships among these variables at the rear edge of the natural distribution of brown trout. Thirty-one sites in 14 mountain rivers and streams were studied in central Spain. Models of streamflow were built for several of these sites using M5 model trees, and a non-linear regression method was used to estimate stream temperatures. Nine global climate models simulations for Representative Concentration Pathways RCP4.5 and RCP8.5 scenarios were downscaled to the local level. Significant reductions in streamflow were predicted to occur in all of the basins (max. -49 %) by the year 2099, and seasonal differences were noted between the basins. The stream temperature models showed relationships between the model parameters, geology and hydrologic responses. Temperature was sensitive to streamflow in one set of streams, and summer reductions in streamflow contributed to additional stream temperature increases (max. 3.6 °C), although the sites that are most dependent on deep aquifers will likely resist warming to a greater degree. The predicted increases in water temperatures were as high as 4.0 °C. Temperature and streamflow changes will cause a shift in the rear edge of the distribution of this species. However, geology will affect the extent of this shift. Approaches like the one used herein have proven to be useful in planning the prevention and mitigation of the negative effects of climate change by differentiating areas based on the risk level and viability of fish populations.
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Ren, Weiwei; Yang, Tao; Shi, Pengfei; Xu, Chong-yu; Zhang, Ke; Zhou, Xudong; Shao, Quanxi; Ciais, Philippe
2018-06-01
Climate change imposes profound influence on regional hydrological cycle and water security in many alpine regions worldwide. Investigating regional climate impacts using watershed scale hydrological models requires a large number of input data such as topography, meteorological and hydrological data. However, data scarcity in alpine regions seriously restricts evaluation of climate change impacts on water cycle using conventional approaches based on global or regional climate models, statistical downscaling methods and hydrological models. Therefore, this study is dedicated to development of a probabilistic model to replace the conventional approaches for streamflow projection. The probabilistic model was built upon an advanced Bayesian Neural Network (BNN) approach directly fed by the large-scale climate predictor variables and tested in a typical data sparse alpine region, the Kaidu River basin in Central Asia. Results show that BNN model performs better than the general methods across a number of statistical measures. The BNN method with flexible model structures by active indicator functions, which reduce the dependence on the initial specification for the input variables and the number of hidden units, can work well in a data limited region. Moreover, it can provide more reliable streamflow projections with a robust generalization ability. Forced by the latest bias-corrected GCM scenarios, streamflow projections for the 21st century under three RCP emission pathways were constructed and analyzed. Briefly, the proposed probabilistic projection approach could improve runoff predictive ability over conventional methods and provide better support to water resources planning and management under data limited conditions as well as enable a facilitated climate change impact analysis on runoff and water resources in alpine regions worldwide.
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Dwivedi, R.; Meixner, T.; McIntosh, J. C.; Ferre, T. P. A.; Eastoe, C. J.; Minor, R. L.; Barron-Gafford, G.; Chorover, J.
2017-12-01
The composition of natural mountainous waters maintains important control over the water quality available to downstream users. Furthermore, the geochemical constituents of stream water in the mountainous catchments represent the result of the spatial and temporal evolution of critical zone structure and processes. A key problem is that high elevation catchments involve rugged terrain and are subject to extreme climate and landscape gradients; therefore, high density or high spatial resolution hydro-geochemical observations are rare. Despite such difficulties, the Santa Catalina Mountains Critical Zone Observatory (SCM-CZO), Tucson, AZ, generates long-term hydrogeochemical data for understanding not only hydrological processes and their seasonal characters, but also the geochemical impacts of such processes on streamflow chemical composition. Using existing instrumentation and hydrogeochemical observations from the last 9+ years (2009 through 2016 and an initial part of 2017), we employed a multi-tracer approach along with principal component analysis to identify water sources and their seasonal character. We used our results to inform hydrological process understanding (flow paths, residence times, and water sources) for our study site. Our results indicate that soil water is the largest contributor to streamflow, which is ephemeral in nature. Although a 3-dimensional mixing space involving precipitation, soil water, interflow, and deep groundwater end-members could explain most of the streamflow chemistry, geochemical complexity was observed to grow with catchment storage. In terms of processes and their seasonal character, we found soil water and interflow were the primary end-member contributors to streamflow in all seasons. Deep groundwater only contributes to streamflow at high catchment storage conditions, but it provides major ions such as Na, Mg, and Ca that are lacking in other water types. In this way, our results indicate that any future efforts aimed
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Global Sensitivity Analysis of Environmental Models: Convergence, Robustness and Validation
Sarrazin, Fanny; Pianosi, Francesca; Khorashadi Zadeh, Farkhondeh; Van Griensven, Ann; Wagener, Thorsten
2015-04-01
Global Sensitivity Analysis aims to characterize the impact that variations in model input factors (e.g. the parameters) have on the model output (e.g. simulated streamflow). In sampling-based Global Sensitivity Analysis, the sample size has to be chosen carefully in order to obtain reliable sensitivity estimates while spending computational resources efficiently. Furthermore, insensitive parameters are typically identified through the definition of a screening threshold: the theoretical value of their sensitivity index is zero but in a sampling-base framework they regularly take non-zero values. There is little guidance available for these two steps in environmental modelling though. The objective of the present study is to support modellers in making appropriate choices, regarding both sample size and screening threshold, so that a robust sensitivity analysis can be implemented. We performed sensitivity analysis for the parameters of three hydrological models with increasing level of complexity (Hymod, HBV and SWAT), and tested three widely used sensitivity analysis methods (Elementary Effect Test or method of Morris, Regional Sensitivity Analysis, and Variance-Based Sensitivity Analysis). We defined criteria based on a bootstrap approach to assess three different types of convergence: the convergence of the value of the sensitivity indices, of the ranking (the ordering among the parameters) and of the screening (the identification of the insensitive parameters). We investigated the screening threshold through the definition of a validation procedure. The results showed that full convergence of the value of the sensitivity indices is not necessarily needed to rank or to screen the model input factors. Furthermore, typical values of the sample sizes that are reported in the literature can be well below the sample sizes that actually ensure convergence of ranking and screening.
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Directory of Open Access Journals (Sweden)
S. A. Archfield
2013-01-01
Full Text Available Streamflow information is critical for addressing any number of hydrologic problems. Often, streamflow information is needed at locations that are ungauged and, therefore, have no observations on which to base water management decisions. Furthermore, there has been increasing need for daily streamflow time series to manage rivers for both human and ecological functions. To facilitate negotiation between human and ecological demands for water, this paper presents the first publicly available, map-based, regional software tool to estimate historical, unregulated, daily streamflow time series (streamflow not affected by human alteration such as dams or water withdrawals at any user-selected ungauged river location. The map interface allows users to locate and click on a river location, which then links to a spreadsheet-based program that computes estimates of daily streamflow for the river location selected. For a demonstration region in the northeast United States, daily streamflow was, in general, shown to be reliably estimated by the software tool. Estimating the highest and lowest streamflows that occurred in the demonstration region over the period from 1960 through 2004 also was accomplished but with more difficulty and limitations. The software tool provides a general framework that can be applied to other regions for which daily streamflow estimates are needed.
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Archfield, Stacey A.; Steeves, Peter A.; Guthrie, John D.; Ries, Kernell G.
2013-01-01
Streamflow information is critical for addressing any number of hydrologic problems. Often, streamflow information is needed at locations that are ungauged and, therefore, have no observations on which to base water management decisions. Furthermore, there has been increasing need for daily streamflow time series to manage rivers for both human and ecological functions. To facilitate negotiation between human and ecological demands for water, this paper presents the first publicly available, map-based, regional software tool to estimate historical, unregulated, daily streamflow time series (streamflow not affected by human alteration such as dams or water withdrawals) at any user-selected ungauged river location. The map interface allows users to locate and click on a river location, which then links to a spreadsheet-based program that computes estimates of daily streamflow for the river location selected. For a demonstration region in the northeast United States, daily streamflow was, in general, shown to be reliably estimated by the software tool. Estimating the highest and lowest streamflows that occurred in the demonstration region over the period from 1960 through 2004 also was accomplished but with more difficulty and limitations. The software tool provides a general framework that can be applied to other regions for which daily streamflow estimates are needed.
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Land Use Change Increases Streamflow Across the Arc of Deforestation in Brazil
Levy, M. C.; Lopes, A. V.; Cohn, A.; Larsen, L. G.; Thompson, S. E.
2018-04-01
Nearly half of recent decades' global forest loss occurred in the Amazon and Cerrado (tropical savanna) biomes of Brazil, known as the arc of deforestation. Despite prior analysis in individual river basins, a generalizable empirical understanding of the effect of deforestation on streamflow across this region is lacking. We frame land use change in Brazil as a natural experiment and draw on in situ and remote sensing evidence in 324 river basins covering more than 3 × 106 km2 to estimate streamflow changes caused by deforestation and agricultural development between 1950 and 2013. Deforestation increased dry season low flow by between 4 and 10 percentage points (relative to the forested condition), corresponding to a regional- and time-averaged rate of increase in specific streamflow of 1.29 mm/year2, equivalent to a 4.08 km3/year2 increase, assuming a stationary climate. In conjunction with rainfall and temperature variations, the net (observed) average increase in streamflow over the same period was 0.76 mm/year2, or 2.41 km3/year2. Thus, net increases in regional streamflow in the past half century are 58% of those that would have been experienced with deforestation given a stationary climate. This study uses a causal empirical analysis approach novel to the water sciences to verify the regional applicability of prior basin-scale studies, provides a proof of concept for the use of observational causal identification methods in the water sciences, and demonstrates that deforestation masks the streamflow-reducing effects of climate change in this region.
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Zarriello, Phillip J.; Parker, Gene W.; Armstrong, David S.; Carlson, Carl S.
2010-01-01
Water withdrawals from surface-water reservoirs and groundwater have affected streamflow in the Sudbury and Assabet River Basins. These effects are particularly evident in the upper Sudbury River Basin, which prompted the need to improve the understanding of water resources and aquatic habitat in these basins. In 2004, the U.S. Geological Survey, in cooperation with the Massachusetts Department of Conservation and Recreation, developed a precipitation-runoff model that uses Hydrologic Simulation Program-FORTRAN (HSPF) to evaluate the effects of water use and projected future water-use and land-use change on streamflow. As part of this study, the aquatic habitat in the basins and the effects of streamflow alteration also were evaluated. Chapter 1 of the report covers the development of the HSPF model that focuses on the upper Sudbury River Basin (106 square miles) but covers the entire Sudbury and Assabet River Basins (339 square miles). The model was calibrated to an 11-year period (1993-2003) using observed or estimated streamflow at four streamgages. The model was then used to simulate long-term (1960-2004) streamflows to evaluate the effects of average 1993-2003 water use and projected 2030 water-use and land-use change over long-term climatic conditions. Simulations indicate that the average 1993-2003 withdrawals most altered streamflow relative to no withdrawals in small headwater subbasins where the ratios of mean annual withdrawals to mean annual streamflow are the highest. The effects of withdrawals are also appreciable in other parts of the upper Sudbury River Basin as a result of the perpetuation of the effects of large withdrawals in upstream reaches or in subbasins that also have a high ratio of withdrawal to streamflow. The simulated effects of potential 2030 water-use and land-use change indicate small decreases in flows as a result of increased water demands, but these flow alterations were offset as a result of decreased evapotranspiration
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Directory of Open Access Journals (Sweden)
J. Wang
2018-06-01
Full Text Available Sediment load can provide very important perspective on erosion of river basin. The changes of human-induced vegetation cover, such as deforestation or afforestation, affect sediment yield process of a catchment. We have already evaluated that climate change and land cover change changed the historical streamflow and sediment yield, and land cover change is the main factor in Red river basin. But future streamflow and sediment yield changes under potential future land cover change scenario still have not been evaluated. For this purpose, future scenario of land cover change is developed based on historical land cover changes and land change model (LCM. In addition, future leaf area index (LAI is simulated by ecological model (Biome-BGC based on future land cover scenario. Then future scenarios of land cover change and LAI are used to drive hydrological model and new sediment rating curve. The results of this research provide information that decision-makers need in order to promote water resources planning efforts. Besides that, this study also contributes a basic framework for assessing climate change impacts on streamflow and sediment yield that can be applied in the other basins around the world.
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Climate and terrain factors explaining streamflow response and recession in Australian catchments
Directory of Open Access Journals (Sweden)
A. I. J. M. van Dijk
2010-01-01
Full Text Available Daily streamflow data were analysed to assess which climate and terrain factors best explain streamflow response in 183 Australian catchments. Assessed descriptors of catchment response included the parameters of fitted baseflow models, and baseflow index (BFI, average quick flow and average baseflow derived by baseflow separation. The variation in response between catchments was compared with indicators of catchment climate, morphology, geology, soils and land use. Spatial coherence in the residual unexplained variation was investigated using semi-variogram techniques. A linear reservoir model (one parameter; recession coefficient produced baseflow estimates as good as those obtained using a non-linear reservoir (two parameters and for practical purposes was therefore considered an appropriate balance between simplicity and explanatory performance. About a third (27–34% of the spatial variation in recession coefficients and BFI was explained by catchment climate indicators, with another 53% of variation being spatially correlated over distances of 100–150 km, probably indicative of substrate characteristics not captured by the available soil and geology data. The shortest recession half-times occurred in the driest catchments and were attributed to intermittent occurrence of fast-draining (possibly perched groundwater. Most (70–84% of the variation in average baseflow and quick flow was explained by rainfall and climate characteristics; another 20% of variation was spatially correlated over distances of 300–700 km, possibly reflecting a combination of terrain and climate factors. It is concluded that catchment streamflow response can be predicted quite well on the basis of catchment climate alone. The prediction of baseflow recession response should be improved further if relevant substrate properties were identified and measured.
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Validation of simulation models
DEFF Research Database (Denmark)
Rehman, Muniza; Pedersen, Stig Andur
2012-01-01
In philosophy of science, the interest for computational models and simulations has increased heavily during the past decades. Different positions regarding the validity of models have emerged but the views have not succeeded in capturing the diversity of validation methods. The wide variety...
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Estimating mountain basin-mean precipitation from streamflow using Bayesian inference
Henn, Brian; Clark, Martyn P.; Kavetski, Dmitri; Lundquist, Jessica D.
2015-10-01
Estimating basin-mean precipitation in complex terrain is difficult due to uncertainty in the topographical representativeness of precipitation gauges relative to the basin. To address this issue, we use Bayesian methodology coupled with a multimodel framework to infer basin-mean precipitation from streamflow observations, and we apply this approach to snow-dominated basins in the Sierra Nevada of California. Using streamflow observations, forcing data from lower-elevation stations, the Bayesian Total Error Analysis (BATEA) methodology and the Framework for Understanding Structural Errors (FUSE), we infer basin-mean precipitation, and compare it to basin-mean precipitation estimated using topographically informed interpolation from gauges (PRISM, the Parameter-elevation Regression on Independent Slopes Model). The BATEA-inferred spatial patterns of precipitation show agreement with PRISM in terms of the rank of basins from wet to dry but differ in absolute values. In some of the basins, these differences may reflect biases in PRISM, because some implied PRISM runoff ratios may be inconsistent with the regional climate. We also infer annual time series of basin precipitation using a two-step calibration approach. Assessment of the precision and robustness of the BATEA approach suggests that uncertainty in the BATEA-inferred precipitation is primarily related to uncertainties in hydrologic model structure. Despite these limitations, time series of inferred annual precipitation under different model and parameter assumptions are strongly correlated with one another, suggesting that this approach is capable of resolving year-to-year variability in basin-mean precipitation.
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Linkages between ENSO/PDO signals and precipitation, streamflow in China during the last 100 years
Ouyang, R.; Liu, W.; Fu, G.; Liu, C.; Hu, L.; Wang, H.
2014-09-01
This paper investigates the single and combined impacts of El Niño-Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO) on precipitation and streamflow in China over the last century. Results indicate that the precipitation and streamflow overall decrease during El Niño/PDO warm phase periods and increase during La Niña/PDO cool phase periods in the majority of China, although there are regional and seasonal differences. Precipitation and streamflow in the Yellow River basin, Yangtze River basin and Pearl River basin are more significantly influenced by El Niño and La Niña events than is precipitation and streamflow in the Songhua River basin, especially in October and November. Moreover, significant influence of ENSO on streamflow in the Yangtze River mainly occurs in summer and autumn while in the Pearl River influence primarily occurs in the winter and spring. The precipitation and streamflow are relatively greater in the warm PDO phase in the Songhua River basin and several parts of the Yellow River basin and relatively less in the Pearl River basin and most parts of Northwest China compared to those in the cool PDO phase, though there is little significance detected by Wilcoxon signed-rank test. When considering the combined influence of ENSO and PDO, the responses of precipitation/streamflow are shown to be opposite in northern China and southern China, with ENSO-related precipitation/streamflow enhanced in northern China and decreased in southern China during the warm PDO phases, and enhanced in southern China and decreased in northern China during the cool PDO phases. It is hoped that this study will be beneficial for understanding the precipitation/streamflow responses to the changing climate and will correspondingly provide valuable reference for water resources prediction and management across China.
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International Nuclear Information System (INIS)
Roy, L.G.; Roy, R.; Desrochers, G.E.; Vaillancourt, C.; Chartier, I.
2008-01-01
There are uncertainties associated with the use of hydrological models. This study aims to analyse one source of uncertainty associated with hydrological modeling, particularly in the context of climate change studies on water resources. Additional intent of this study is to compare the ability of some meteorological data sources, used in conjunction with an hydrological model, to reproduce the hydrologic regime of a watershed. A case study on a watershed of south-western Quebec, Canada using five different sources of meteorological data as input to an offline hydrological model are presented in this paper. Data used came from weather stations, NCEP reanalysis, ERA40 reanalysis and two Canadian Regional Climate Model (CRCM) runs driven by NCEP and ERA40 reanalysis, providing atmospheric driving boundary conditions to this limited-area climate model. To investigate the sensitivity of simulated streamflow to different sources of meteorological data, we first calibrated the hydrological model with each of the meteorological data sets over the 1961-1980 period. The five different sets of parameters of the hydrological model were then used to simulate streamflow of the 1981-2000 validation period with the five meteorological data sets as inputs. The 25 simulated streamflow series have been compared to the observed streamflow of the watershed. The five meteorological data sets do not have the same ability, when used with the hydrological model, to reproduce streamflow. Our results show also that the hydrological model parameters used may have an important influence on results such as water balance, but it is linked with the differences that may have in the characteristics of the meteorological data used. For climate change impacts assessments on water resources, we have found that there is an uncertainty associated with the meteorological data used to calibrate the model. For expected changes on mean annual flows of the Chateauguay River, our results vary from a small
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Wood, Molly S.; Fosness, Ryan L.
2013-01-01
The U.S. Geological Survey, in cooperation with the Bureau of Land Management (BLM), collected streamflow data in 2012 and estimated streamflow statistics for stream segments designated "Wild," "Scenic," or "Recreational" under the National Wild and Scenic Rivers System in the Owyhee Canyonlands Wilderness in southwestern Idaho. The streamflow statistics were used by BLM to develop and file a draft, federal reserved water right claim in autumn 2012 to protect federally designated "outstanding remarkable values" in the stream segments. BLM determined that the daily mean streamflow equaled or exceeded 20 and 80 percent of the time during bimonthly periods (two periods per month) and the bankfull streamflow are important streamflow thresholds for maintaining outstanding remarkable values. Prior to this study, streamflow statistics estimated using available datasets and tools for the Owyhee Canyonlands Wilderness were inaccurate for use in the water rights claim. Streamflow measurements were made at varying intervals during February–September 2012 at 14 monitoring sites; 2 of the monitoring sites were equipped with telemetered streamgaging equipment. Synthetic streamflow records were created for 11 of the 14 monitoring sites using a partial‑record method or a drainage-area-ratio method. Streamflow records were obtained directly from an operating, long-term streamgage at one monitoring site, and from discontinued streamgages at two monitoring sites. For 10 sites analyzed using the partial-record method, discrete measurements were related to daily mean streamflow at a nearby, telemetered “index” streamgage. Resulting regression equations were used to estimate daily mean and annual peak streamflow at the monitoring sites during the full period of record for the index sites. A synthetic streamflow record for Sheep Creek was developed using a drainage-area-ratio method, because measured streamflows did not relate well to any index site to allow use of the partial
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An intercomparison of approaches for improving operational seasonal streamflow forecasts
Directory of Open Access Journals (Sweden)
P. A. Mendoza
2017-07-01
Full Text Available For much of the last century, forecasting centers around the world have offered seasonal streamflow predictions to support water management. Recent work suggests that the two major avenues to advance seasonal predictability are improvements in the estimation of initial hydrologic conditions (IHCs and the incorporation of climate information. This study investigates the marginal benefits of a variety of methods using IHCs and/or climate information, focusing on seasonal water supply forecasts (WSFs in five case study watersheds located in the US Pacific Northwest region. We specify two benchmark methods that mimic standard operational approaches – statistical regression against IHCs and model-based ensemble streamflow prediction (ESP – and then systematically intercompare WSFs across a range of lead times. Additional methods include (i statistical techniques using climate information either from standard indices or from climate reanalysis variables and (ii several hybrid/hierarchical approaches harnessing both land surface and climate predictability. In basins where atmospheric teleconnection signals are strong, and when watershed predictability is low, climate information alone provides considerable improvements. For those basins showing weak teleconnections, custom predictors from reanalysis fields were more effective in forecast skill than standard climate indices. ESP predictions tended to have high correlation skill but greater bias compared to other methods, and climate predictors failed to substantially improve these deficiencies within a trace weighting framework. Lower complexity techniques were competitive with more complex methods, and the hierarchical expert regression approach introduced here (hierarchical ensemble streamflow prediction – HESP provided a robust alternative for skillful and reliable water supply forecasts at all initialization times. Three key findings from this effort are (1 objective approaches supporting
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Crow, W. T.; Chen, F.; Reichle, R. H.; Xia, Y.; Liu, Q.
2018-05-01
Accurate partitioning of precipitation into infiltration and runoff is a fundamental objective of land surface models tasked with characterizing the surface water and energy balance. Temporal variability in this partitioning is due, in part, to changes in prestorm soil moisture, which determine soil infiltration capacity and unsaturated storage. Utilizing the National Aeronautics and Space Administration Soil Moisture Active Passive Level-4 soil moisture product in combination with streamflow and precipitation observations, we demonstrate that land surface models (LSMs) generally underestimate the strength of the positive rank correlation between prestorm soil moisture and event runoff coefficients (i.e., the fraction of rainfall accumulation volume converted into stormflow runoff during a storm event). Underestimation is largest for LSMs employing an infiltration-excess approach for stormflow runoff generation. More accurate coupling strength is found in LSMs that explicitly represent subsurface stormflow or saturation-excess runoff generation processes.
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Kumar, Brijesh; Lakshmi, Venkat
2018-03-01
The paper examines the quality of Tropical Rainfall Monitoring Mission (TRMM) 3B42 V7 precipitation product to simulate the streamflow using Soil Water Assessment Tool (SWAT) model for various rainfall intensities over the Himalayan region. The SWAT model has been set up for Gandak River Basin with 41 sub-basins and 420 HRUs. Five stream gauge locations are used to simulate the streamflow for a time span of 10 years (2000-2010). Daily streamflow for the simulation period is collected from Central Water Commission (CWC), India and Department of Hydrology and Meteorology (DHM), Nepal. The simulation results are found good in terms of Nash-Sutcliffe efficiency (NSE) {>}0.65, coefficient of determination (R2) {>}0.67 and Percentage Bias (PBIAS){}124.4 mm/d). The PBIAS and RSR show that TRMM simulated streamflow is suitable for moderate to heavy rainfall intensities. However, it does not perform well for light- and extremely-heavy rainfall intensities. The finding of the present work is useful for the problems related to water resources management, irrigation planning and hazard analysis over the Himalayan regions.
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Brown, Christopher R.
2014-01-01
In 2013, the U.S. Geological Survey (USGS), in cooperation with the U. S. Department of the Army, compiled available precipitation and streamflow data for the years of 2008–2012 from the Fort Carson Military Reservation (Fort Carson) near Colorado Springs, Colo., and precipitation, streamflow, and suspended-sediment loads from the Piñon Canyon Maneuver Site (PCMS) near Trinidad, Colo. Graphical representations of the data presented herein are a continuation of work completed by the USGS in 2008 to gain a better understanding of spatial and temporal trends within the hydrologic data. Precipitation stations at Fort Carson and the PCMS were divided into groups based on their land-surface altitude (LSA) to determine if there is a spatial difference in precipitation amounts based on LSA for either military facility. Two-sample t-tests and Wilcoxon rank-sum tests indicated statistically significant differences exist between precipitation values at different groups for Fort Carson but not for the PCMS. All five precipitation stations at Fort Carson exhibit a decrease in median daily total precipitation from years 2002–2007 to 2008–2012. For the PCMS, median precipitation values decreased from the first study period to the second for the 13 stations monitored year-round except for Burson and Big Hills. Mean streamflow for 2008–2012 is less than mean streamflow for 1983–2007 for all stream-gaging stations at Fort Carson and at the PCMS. During the study period, each of the stream-gaging stations within the tributary channels at the PCMS accounted for less than three percent of the total streamflow at the Purgatoire River at Rock Crossing gage. Peak streamflow for 2008–2012 is less than peak streamflow for 2002–2007 at both Fort Carson and the PCMS. At the PCMS, mean suspended-sediment yield for 2008–2012 increased by 54 percent in comparison to the mean yield for 2002–2007. This increase is likely related to the destruction of groundcover by a series of
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Exploring the Link Between Streamflow Trends and Climate Change in Indiana, USA
Kumar, S.; Kam, J.; Thurner, K.; Merwade, V.
2007-12-01
Streamflow trends in Indiana are evaluated for 85 USGS streamflow gaging stations that have continuous unregulated streamflow records varying from 10 to 80 years. The trends are analyzed by using the non-parametric Mann-Kendall test with prior trend-free pre-whitening to remove serial correlation in the data. Bootstrap method is used to establish field significance of the results. Trends are computed for 12 streamflow statistics to include low-, medium- (median and mean flow), and high-flow conditions on annual and seasonal time step. The analysis is done for six study periods, ranging from 10 years to more than 65 years, all ending in 2003. The trends in annual average streamflow, for 50 years study period, are compared with annual average precipitation trends from 14 National Climatic Data Center (NCDC) stations in Indiana, that have 50 years of continuous daily record. The results show field significant positive trends in annual low and medium streamflow statistics at majority of gaging stations for study periods that include 40 or more years of records. In seasonal analysis, all flow statistics in summer and fall (low flow seasons), and only low flow statistics in winter and spring (high flow seasons) are showing positive trends. No field significant trends in annual and seasonal flow statistics are observed for study periods that include 25 or fewer years of records, except for northern Indiana where localized negative trends are observed in 10 and 15 years study periods. Further, stream flow trends are found to be highly correlated with precipitation trends on annual time step. No apparent climate change signal is observed in Indiana stream flow records.
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Analyzing Future Flooding under Climate Change Scenario using CMIP5 Streamflow Data
Parajuli, Ranjan; Nyaupane, Narayan; Kalra, Ajay
2017-12-01
Flooding is a severe and costlier natural hazard. The effect of climate change has intensified the scenario in recent years. Flood prevention practice along with a proper understanding of flooding event can mitigate the risk of such hazard. The floodplain mapping is one of the technique to quantify the severity of the flooding. Carson City, which is one of the agricultural areas in the desert of Nevada has experienced peak flood in the recent year. The underlying probability distribution for the area, latest Coupled Model Intercomparison Project (CMIP5) streamflow data of Carson River were analyzed for 27 different statistical distributions. The best-fitted distribution underlying was used to forecast the 100yr flood (design flood). The data from 1950-2099 derived from 31 model and total 97 projections were used to predict the future streamflow. Delta change method is adopted to quantify the amount of future (2050-2099) flood. To determine the extent of flooding 3 scenarios (i) historic design flood, (ii) 500yr flood and (iii) future 100yr flood were routed on an HEC-RAS model, prepared using available terrain data. Some of the climate projection shows an extreme increase in future design flood. This study suggests an approach to quantify the future flood and floodplain using climate model projections. The study would provide helpful information to the facility manager, design engineer, and stakeholders.
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Carlson, Carl S.; Desimone, Leslie A.; Weiskel, Peter K.
2008-01-01
Continued population growth and land development for commercial, industrial, and residential uses have created concerns regarding the future supply of potable water and the quantity of ground water discharging to streams in the area of Interstate 495 in eastern Massachusetts. Two ground-water models developed in 2002-2004 for the Assabet and Upper Charles River Basins were used to simulate water supply and land-use scenarios relevant for the entire Interstate-495 corridor. Future population growth, water demands, and commercial and residential growth were projected for year 2030 by the Metropolitan Area Planning Council. To assess the effects of future development on subbasin streamflows, seven scenarios were simulated by using existing computer-based ground-water-flow models with the data projected for year 2030. The scenarios incorporate three categories of projected 2030 water- and land-use data: (1) 2030 water use, (2) 2030 land use, and (3) a combination of 2030 water use and 2030 land use. Hydrologic, land-use, and water-use data from 1997 through 2001 for the Assabet River Basin study and 1989 through 1998 for the Upper Charles River Basin study were used to represent current conditions - referred to as 'basecase' conditions - in each basin to which each 2030 scenario was compared. The effects of projected 2030 land- and water-use change on streamflows in the Assabet River Basin depended upon the time of year, the hydrologic position of the subbasin in the larger basin, and the relative areas of new commercial and residential development projected for a subbasin. Effects of water use and land use on streamflow were evaluated by comparing average monthly nonstorm streamflow (base flow) for March and September simulated by using the models. The greatest decreases in streamflow (up to 76 percent in one subbasin), compared to the basecase, occurred in September, when streamflows are naturally at their lowest level. By contrast, simulated March streamflows
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Gan, Y.; Liang, X. Z.; Duan, Q.; Xu, J.; Zhao, P.; Hong, Y.
2017-12-01
The uncertainties associated with the parameters of a hydrological model need to be quantified and reduced for it to be useful for operational hydrological forecasting and decision support. An uncertainty quantification framework is presented to facilitate practical assessment and reduction of model parametric uncertainties. A case study, using the distributed hydrological model CREST for daily streamflow simulation during the period 2008-2010 over ten watershed, was used to demonstrate the performance of this new framework. Model behaviors across watersheds were analyzed by a two-stage stepwise sensitivity analysis procedure, using LH-OAT method for screening out insensitive parameters, followed by MARS-based Sobol' sensitivity indices for quantifying each parameter's contribution to the response variance due to its first-order and higher-order effects. Pareto optimal sets of the influential parameters were then found by the adaptive surrogate-based multi-objective optimization procedure, using MARS model for approximating the parameter-response relationship and SCE-UA algorithm for searching the optimal parameter sets of the adaptively updated surrogate model. The final optimal parameter sets were validated against the daily streamflow simulation of the same watersheds during the period 2011-2012. The stepwise sensitivity analysis procedure efficiently reduced the number of parameters that need to be calibrated from twelve to seven, which helps to limit the dimensionality of calibration problem and serves to enhance the efficiency of parameter calibration. The adaptive MARS-based multi-objective calibration exercise provided satisfactory solutions to the reproduction of the observed streamflow for all watersheds. The final optimal solutions showed significant improvement when compared to the default solutions, with about 65-90% reduction in 1-NSE and 60-95% reduction in |RB|. The validation exercise indicated a large improvement in model performance with about 40
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M. Safeeq; G.E. Grant; S.L. Lewis; M.G. Kramer; B. Staab
2014-01-01
Summer streamflows in the Pacific Northwest are largely derived from melting snow and groundwater discharge. As the climate warms, diminishing snowpack and earlier snowmelt will cause reductions in summer streamflow. Most regional-scale assessments of climate change impacts on streamflow use downscaled temperature and precipitation projections from general circulation...
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Groundwater recharge in Wisconsin--Annual estimates for 1970-99 using streamflow data
Gebert, Warren A.; Walker, John F.; Hunt, Randall J.
2011-01-01
The groundwater component of streamflow is important because it is indicative of the sustained flow of a stream during dry periods, is often of better quality, and has a smaller range of temperatures, than surface contributions to streamflow. All three of these characteristics are important to the health of aquatic life in a stream. If recharge to the aquifers is to be preserved or enhanced, it is important to understand the present partitioning of total streamflow into base flow and stormflow. Additionally, an estimate of groundwater recharge is important for understanding the flows within a groundwater system-information important for water availability/sustainability or other assessments. The U.S. Geological Survey operates numerous continuous-record streamflow-gaging stations (Hirsch and Norris, 2001), which can be used to provide estimates of average annual base flow. In addition to these continuous record sites, Gebert and others (2007) showed that having a few streamflow measurements in a basin can appreciably reduce the error in a base-flow estimate for that basin. Therefore, in addition to the continuous-record gaging stations, a substantial number of low-flow partial-record sites (6 to 15 discharge measurements) and miscellaneous-measurement sites (1 to 3 discharge measurements) that were operated during 1964-90 throughout the State were included in this work to provide additional insight into spatial distribution of annual base flow and, in turn, groundwater recharge.
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Analysis of trends in selected streamflow statistics for the Concho River Basin, Texas, 1916-2009
Barbie, Dana L.; Wehmeyer, Loren L.; May, Jayne E.
2012-01-01
The Concho River Basin is part of the upper Colorado River Basin in west-central Texas. Monotonic trends in streamflow statistics during various time intervals from 1916-2009 were analyzed to determine whether substantial changes in selected streamflow statistics have occurred within the Concho River Basin. Two types of U.S. Geological Survey streamflow data comprise the foundational data for this report: (1) daily mean discharge (daily discharge) and (2) annual instantaneous peak discharge. Trend directions are reported for the following streamflow statistics: (1) annual mean daily discharge, (2) annual 1-day minimum discharge, (3) annual 7-day minimum discharge, (4) annual maximum daily discharge, and (5) annual instantaneous peak discharge.
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Hydrological model application under data scarcity for multiple watersheds, Java Island, Indonesia
Directory of Open Access Journals (Sweden)
Yanto
2017-02-01
New hydrological insights for the region: Quality control procedures revealed inconsistencies between precipitation and streamflow with only five watersheds possessing data of suitable quality. Simulations and observations confirmed that both precipitation and streamflow variability increase eastward on the island and that rainfall-runoff response was most frequently dominated by baseflow, rather than surface runoff. The most sensitive VIC parameters were identified and then calibrated with an automatic calibration procedure. In the calibration period, model performance was generally deemed satisfactory with Nash Sutcliffe Efficiency (NSE between 0.31 to 0.89, whereas the validation period exhibited poorer performance than expected (0.07 < NSE < 0.79. This drop in performance was attributed to a combination of inconsistent data quality, hydrometeorological outliers during the validation period, and over-fitting parameters during the calibration period. The model indicated that direct runoff exhibits more spatial and temporal variability than both rainfall or baseflow, the latter being associated with variability of soil thickness.
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Test-driven verification/validation of model transformations
Institute of Scientific and Technical Information of China (English)
László LENGYEL; Hassan CHARAF
2015-01-01
Why is it important to verify/validate model transformations? The motivation is to improve the quality of the trans-formations, and therefore the quality of the generated software artifacts. Verified/validated model transformations make it possible to ensure certain properties of the generated software artifacts. In this way, verification/validation methods can guarantee different requirements stated by the actual domain against the generated/modified/optimized software products. For example, a verified/ validated model transformation can ensure the preservation of certain properties during the model-to-model transformation. This paper emphasizes the necessity of methods that make model transformation verified/validated, discusses the different scenarios of model transformation verification and validation, and introduces the principles of a novel test-driven method for verifying/ validating model transformations. We provide a solution that makes it possible to automatically generate test input models for model transformations. Furthermore, we collect and discuss the actual open issues in the field of verification/validation of model transformations.
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Candogan Yossef, N.; Winsemius, H.C.; Weerts, A.; Van Beek, R.; Bierkens, M.F.P.
2013-01-01
We investigate the relative contributions of initial conditions (ICs) and meteorological forcing (MF) to the skill of the global seasonal streamflow forecasting system FEWS-World, using the global hydrological model PCRaster Global Water Balance. Potential improvement in forecasting skill through
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Directory of Open Access Journals (Sweden)
J. M. Santiago
2017-08-01
Full Text Available Climate changes affect aquatic ecosystems by altering temperatures and precipitation patterns, and the rear edges of the distributions of cold-water species are especially sensitive to these effects. The main goal of this study was to predict in detail how changes in air temperature and precipitation will affect streamflow, the thermal habitat of a cold-water fish (the brown trout, Salmo trutta, and the synergistic relationships among these variables at the rear edge of the natural distribution of brown trout. Thirty-one sites in 14 mountain rivers and streams were studied in central Spain. Models of streamflow were built for several of these sites using M5 model trees, and a non-linear regression method was used to estimate stream temperatures. Nine global climate models simulations for Representative Concentration Pathways RCP4.5 and RCP8.5 scenarios were downscaled to the local level. Significant reductions in streamflow were predicted to occur in all of the basins (max. −49 % by the year 2099, and seasonal differences were noted between the basins. The stream temperature models showed relationships between the model parameters, geology and hydrologic responses. Temperature was sensitive to streamflow in one set of streams, and summer reductions in streamflow contributed to additional stream temperature increases (max. 3.6 °C, although the sites that are most dependent on deep aquifers will likely resist warming to a greater degree. The predicted increases in water temperatures were as high as 4.0 °C. Temperature and streamflow changes will cause a shift in the rear edge of the distribution of this species. However, geology will affect the extent of this shift. Approaches like the one used herein have proven to be useful in planning the prevention and mitigation of the negative effects of climate change by differentiating areas based on the risk level and viability of fish populations.
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Li, Y.; Chang, J.; Luo, L.
2017-12-01
It is of great importance for water resources management to model the truly hydrological process under changing environment, especially under significant changes of underlying surfaces like the Wei River Bain (WRB) where the subsurface hydrology is highly influenced by human activities, and to systematically investigate the interactions among LULC change, streamflow variation and changes in runoff generation process. Therefore, we proposed the idea of evolving parameters in hydrological model (SWAT) to reflect the changes in physical environment with different LULC conditions. Then with these evolving parameters, the spatiotemporal impacts of LULC changes on streamflow were quantified, and qualitative analysis was conducted to further explore how LULC changes affect the streamflow from the perspective of runoff generation mechanism. Results indicate the following: 1) evolving parameter calibration is not only effective but necessary to ensure the validity of the model when dealing with significant changes in underlying surfaces due to human activities. 2) compared to the baseline period, the streamflow in wet seasons increased in the 1990s but decreased in the 2000s. While at yearly and dry seasonal scales, the streamflow decreased in both two decades; 3) the expansion of cropland is the major contributor to the reduction of surface water component, thus causing the decline in streamflow at yearly and dry seasonal scales. While compared to the 1990s, the expansions of woodland in the middle stream and grassland in the downstream are the main stressors that increased the soil water component, thus leading to the more decline of the streamflow in the 2000s.
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Asquith, William H.; Cleveland, Theodore G.; Roussel, Meghan C.
2011-01-01
Estimates of peak and time of peak streamflow for small watersheds (less than about 640 acres) in a suburban to urban, low-slope setting are needed for drainage design that is cost-effective and risk-mitigated. During 2007-10, the U.S. Geological Survey (USGS), in cooperation with the Harris County Flood Control District and the Texas Department of Transportation, developed a method to estimate peak and time of peak streamflow from excess rainfall for 10- to 640-acre watersheds in the Houston, Texas, metropolitan area. To develop the method, 24 watersheds in the study area with drainage areas less than about 3.5 square miles (2,240 acres) and with concomitant rainfall and runoff data were selected. The method is based on conjunctive analysis of rainfall and runoff data in the context of the unit hydrograph method and the rational method. For the unit hydrograph analysis, a gamma distribution model of unit hydrograph shape (a gamma unit hydrograph) was chosen and parameters estimated through matching of modeled peak and time of peak streamflow to observed values on a storm-by-storm basis. Watershed mean or watershed-specific values of peak and time to peak ("time to peak" is a parameter of the gamma unit hydrograph and is distinct from "time of peak") of the gamma unit hydrograph were computed. Two regression equations to estimate peak and time to peak of the gamma unit hydrograph that are based on watershed characteristics of drainage area and basin-development factor (BDF) were developed. For the rational method analysis, a lag time (time-R), volumetric runoff coefficient, and runoff coefficient were computed on a storm-by-storm basis. Watershed-specific values of these three metrics were computed. A regression equation to estimate time-R based on drainage area and BDF was developed. Overall arithmetic means of volumetric runoff coefficient (0.41 dimensionless) and runoff coefficient (0.25 dimensionless) for the 24 watersheds were used to express the rational
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Streamflow estimation in ungauged basins using remote sensed hydrological data
Vasquez, Nicolas; Vargas, Ximena
2017-04-01
In several parts of the world the scarcity of streamflow gauging stations produces an important deficit of information, and calibrating these basins remains a challenge for hydrologists. Improvements in remote sensing have provided significant information about hydrological cycle, which can be used to calibrate a hydrological model when streamflow information is not available. Several satellite products related to snow, evapotranspiration, soil moisture, among other variables provide essential information about hydrological processes, and can be used to calibrate physically based hydrological models. Despite this useful information, other aspects are unknown like aquifers dimensions or precipitation heterogeneity. We calibrated three snow driven basins in the Coquimbo Region in Northern Chile, using fSCA from MODIS (MOD10 and MYD10) and NDSI from Landsat. We also considered the MOD16 product to estimate evapotranspiration. Soil Moisture from AMSR-E was considered but it was not useful due to the spatial resolution of the product and the high heterogeneity of the terrain. The Cold Regional Hydrological Modal (CHRM) was selected to represent the hydrological processes due to the importance of snow processes which are, by far, the most important in this area, where precipitation falls as snow principally in winter (June to August) and the melting period begins in spring (September) and ends in the beginning of summer (December and January). The inputs used in the model are precipitation, temperature, short wave radiation, wind speed and relative humidity. The meteorological information was obtained from stations available in the area, and distributed spatially using orographic gradients for wind and precipitation and lapse rates for air temperature and dew point temperature. Short wave radiation was computed and corrected by cloud cover data from MODIS. Streamflow data was available but it was not used in the calibration process. The three basins are Cochiguaz river
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Streamflow response to climate and landuse changes in a coastal watershed in North Carolina
S. Qi; G. Sun; Y. Wang; S.G. McNulty; J.A. Moore Myers
2009-01-01
It is essential to examine the sensitivity of hydrologic responses to climate and landuse change across different physiographic regions in order to formulate sound water management policies for local response to projected global change. This study used the a simulation model to examine the potential impacts of climate and landuse changes on streamflow of the...
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Yoon, Y.; Beighley, E.
2015-12-01
The Amazon River basin is the largest watershed in the world containing thousands of tributaries. Although the mainstream and its larger tributaries have been the focus on much research, there has been few studies focused on the hydrodynamics of smaller rivers in the foothills of the Andes Mountains. These smaller rivers are of particular importance for the fishery industry because fish migrate up these headwater rivers to spawn. During the rainy season, fish wait for storm event to increase water depths to a sufficient level for their passage. Understanding how streamflow dynamics will change in response to future conditions is vital for the sustainable management of the fishery industry. In this paper, we focus on improving the accuracy of river discharge estimates on relatively small-scale sub-catchments (100 ~ 40,000 km2) in the headwaters of the Amazon River basin. The Hillslope River Routing (HRR) hydrologic model and remotely sensed datasets are used. We provide annual runoff, seasonal patterns, and daily discharge characteristics for 81 known migration reaches. The model is calibrated for the period 2000-2014 and climate forecasts for the period 2070-2100 are used to assess future changes in streamflow dynamics. The forecasts for the 2070 to 2100 period were obtained by selecting 5 climate models from IPCC's Fifth Assessment Report (AR5) Coupled Model Intercomparison Project Phase 5 (CMIP5) based on their ability to represent the main aspects of recent (1970 to 2000) Amazon climate. The river network for the HRR model is developing using surface topography based on the SRTM digital elevation model. Key model forcings include precipitation (TRMM 3B42) and evapotranspiration (MODIS ET, MOD16). Model parameters for soil depth, hydraulic conductivity, runoff coefficients and lateral routing were initially approximated based on literature values and adjusted during calibration. Measurements from stream gauges located near the reaches of interest were used for
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Singh, S.; Abebe, A.; Srivastava, P.; Chaubey, I.
2017-12-01
Evaluation of the influences of individual and coupled oceanic-atmospheric oscillations on streamflow at a regional scale in the United States is the focus of this study. The main climatic oscillations considered in this study are: El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), Atlantic Multidecadal Oscillation (AMO), and North Atlantic Oscillation (NAO). Unimpacted or minimally impacted by water management streamflow data from the Model Parameter Estimation Experiment (MOPEX) were used in this study. Two robust and novel non-parametric tests, namely, the rank based partial least square (PLS) and the Joint Rank Fit (JRFit) procedures were used to identify the individual and coupled effect of oscillations on streamflow across continental U.S. (CONUS), respectively. Moreover, the interactive effects of ENSO with decadal and multidecadal cycles were tested and quantified using the JRFit interaction test. The analysis of ENSO indicated higher streamflows during La Niña phase compared to the El Niño phase in Northwest, Northeast and the lower part of Ohio Valley while the opposite occurs for rest of the climatic regions in US. Two distinct climate regions (Northwest and Southeast) were identified from the PDO analysis where PDO negative phase results in increased streamflow than PDO positive phase. Consistent negative and positive correlated regions around the CONUS were identified for AMO and NAO, respectively. The interaction test of ENSO with decadal and multidecadal oscillations showed that El Niño is modulated by the negative phase of PDO and NAO, and the positive phase of AMO, respectively, in the Upper Midwest. However, La Niña is modulated by the positive phase of AMO and PDO in Ohio Valley and Northeast while in Southeast and the South it is modulated by AMO negative phase. Results of this study will assist water managers to understand the streamflow change patterns across the CONUS at decadal and multi-decadal time scales. The
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Haguma, D.; Leconte, R.
2017-12-01
Spatial and temporal water resources variability are associated with large-scale pressure and circulation anomalies known as teleconnections that influence the pattern of the atmospheric circulation. Teleconnection indices have been used successfully to forecast streamflow in short term. However, in some watersheds, classical methods cannot establish relationships between seasonal streamflow and teleconnection indices because of weak correlation. In this study, machine learning algorithms have been applied for seasonal streamflow forecast using teleconnection indices. Machine learning offers an alternative to classical methods to address the non-linear relationship between streamflow and teleconnection indices the context non-stationary climate. Two machine learning algorithms, random forest (RF) and support vector machine (SVM), with teleconnection indices associated with North American climatology, have been used to forecast inflows for one and two leading seasons for the Romaine River and Manicouagan River watersheds, located in Quebec, Canada. The indices are Pacific-North America (PNA), North Atlantic Oscillation (NAO), El Niño-Southern Oscillation (ENSO), Arctic Oscillation (AO) and Pacific Decadal Oscillation (PDO). The results showed that the machine learning algorithms have an important predictive power for seasonal streamflow for one and two leading seasons. The RF performed better for training and SVM generally have better results with high predictive capability for testing. The RF which is an ensemble method, allowed to assess the uncertainty of the forecast. The integration of teleconnection indices responds to the seasonal forecast of streamflow in the conditions of the non-stationarity the climate, although the teleconnection indices have a weak correlation with streamflow.
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Reeve, A. S.; Martin, D.; Smith, S. M.
2013-12-01
hydraulic structures that are not included in the lumped parameter model. Calibrated watershed models tend to substantially underestimate the highest streamflows while overestimating low flows. An early June 2012 event caused extremely high flows with discharge in the Crooked River (the most significant tributary) peaking at about 85 m3/day. The lumped parameter model dramatically underestimated this important and anomalous event, but provided a reasonable prediction of flows throughout the rest of 2012. Ongoing work includes incorporating hydraulic structures in the lumped parameter model and using the available data to drive the lake water-balance model that has been prepared.
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Patrick R. Kormos; Charlie Luce; Seth J. Wenger; Wouter R. Berghuijs
2016-01-01
Path analyses of historical streamflow data from the Pacific Northwest indicate that the precipitation amount has been the dominant control on the magnitude of low streamflow extremes compared to the air temperature-affected timing of snowmelt runoff. The relative sensitivities of low streamflow to precipitation and temperature changes have important...
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Stogner, Sr., Robert W.
2000-01-01
The Fountain Creek watershed, located in and along the eastern slope of the Front Range section of the southern Rocky Mountains, drains approximately 930 square miles of parts of Teller, El Paso, and Pueblo Counties in eastern Colorado. Streamflow in the watershed is dominated by spring snowmelt runoff and storm runoff during the summer monsoon season. Flooding during the 1990?s has resulted in increased streambank erosion. Property loss and damage associated with flooding and bank erosion has cost area residents, businesses, utilities, municipalities, and State and Federal agencies millions of dollars. Precipitation (4 stations) and streamflow (6 stations) data, aerial photographs, and channel reconnaissance were used to evaluate trends in precipitation and streamflow and changes in channel morphology. Trends were evaluated for pre-1977, post-1976, and period-of-record time periods. Analysis revealed the lack of trend in total annual and seasonal precipitation during the pre-1977 time period. In general, the analysis also revealed the lack of trend in seasonal precipitation for all except the spring season during the post-1976 time period. Trend analysis revealed a significant upward trend in long-term (period of record) total annual and spring precipitation data, apparently due to a change in total annual precipitation throughout the Fountain Creek watershed. During the pre-1977 time period, precipitation was generally below average; during the post- 1976 time period, total annual precipitation was generally above average. During the post- 1976 time period, an upward trend in total annual and spring precipitation was indicated at two stations. Because two of four stations evaluated had upward trends for the post-1976 period and storms that produce the most precipitation are isolated convection storms, it is plausible that other parts of the watershed had upward precipitation trends that could affect trends in streamflow. Also, because of the isolated nature of
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Reconstructed streamflow for Citarum River, Java, Indonesia: linkages to tropical climate dynamics
D'Arrigo, Rosanne; Abram, Nerilie; Ummenhofer, Caroline; Palmer, Jonathan; Mudelsee, Manfred
2011-02-01
The Citarum river basin of western Java, Indonesia, which supplies water to 10 million residents in Jakarta, has become increasingly vulnerable to anthropogenic change. Citarum's streamflow record, only ~45 years in length (1963-present), is too short for understanding the full range of hydrometeorological variability in this important region. Here we present a tree-ring based reconstruction of September-November Citarum streamflow (AD 1759-2006), one of the first such records available for monsoon Asia. Close coupling is observed between decreased tree growth and low streamflow levels, which in turn are associated with drought caused by ENSO warm events in the tropical Pacific and Indian Ocean positive dipole-type variability. Over the full length of record, reconstructed variance was at its weakest during the interval from ~1905-1960, overlapping with a period of unusually-low variability (1920-1960) in the ENSO-Indian Ocean dipole systems. In subsequent decades, increased variance in both the streamflow anomalies and a coral-based SST reconstruction of the Indian Ocean Dipole Mode signal the potential for intensified drought activity and related consequences for water supply and crop productivity in western Java, where much of the country's rice is grown.
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Rainfall and streamflow from small tree-covered and fern-covered and burned watersheds in Hawaii
H. W. Anderson; P. D. Duffy; Teruo Yamamoto
1966-01-01
Streamflow from two 30-acre watersheds near Honolulu was studied by using principal components regression analysis. Models using data on monthly, storm, and peak discharges were tested against several variables expressing amount and intensity of rainfall, and against variables expressing antecedent rainfall. Explained variation ranged from 78 to 94 percent. The...
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Norton, Parker A.; Anderson, Mark T.; Stamm, John F.
2014-01-01
The Missouri River and its tributaries are an important resource that serve multiple uses including agriculture, energy, recreation, and municipal water supply. Understanding historical streamflow characteristics provides relevant guidance to adaptive management of these water resources. Streamflow records in the Missouri River watershed were examined for trends in time series of annual, seasonal, and monthly streamflow. A total of 227 streamgages having continuous observational records for water years 1960–2011 were examined. Kendall’s tau nonparametric test was used to determine statistical significance of trends in annual, seasonal, and monthly streamflow. A trend was considered statistically significant for a probability value less than or equal to 0.10 that the Kendall’s tau value equals zero. Significant trends in annual streamflow were indicated for 101 out of a total of 227 streamgages. The Missouri River watershed was divided into six watershed regions and trends within regions were examined. The western and the southern parts of the Missouri River watershed had downward trends in annual streamflow (56 streamgages), whereas the eastern part of the watershed had upward trends in streamflow (45 streamgages). Seasonal and monthly streamflow trends reflected prevailing annual streamflow trends within each watershed region.
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Directory of Open Access Journals (Sweden)
Fei Yuan
2017-03-01
Full Text Available Satellite precipitation products from the Global Precipitation Measurement (GPM mission and its predecessor the Tropical Rainfall Measuring Mission (TRMM are a critical data source for hydrological applications in ungauged basins. This study conducted an initial and early evaluation of the performance of the Integrated Multi-satellite Retrievals for GPM (IMERG final run and the TRMM Multi-satellite Precipitation Analysis 3B42V7 precipitation products, and their feasibility in streamflow simulations in the Chindwin River basin, Myanmar, from April 2014 to December 2015 was also assessed. Results show that, although IMERG and 3B42V7 can potentially capture the spatiotemporal patterns of historical precipitation, the two products contain considerable errors. Compared with 3B42V7, no significant improvements were found in IMERG. Moreover, 3B42V7 outperformed IMERG at daily and monthly scales and in heavy rain detections at four out of five gauges. The large errors in IMERG and 3B42V7 distinctly propagated to streamflow simulations via the Xinanjiang hydrological model, with a significant underestimation of total runoff and high flows. The bias correction of the satellite precipitation effectively improved the streamflow simulations. The 3B42V7-based streamflow simulations performed better than the gauge-based simulations. In general, IMERG and 3B42V7 are feasible for use in streamflow simulations in the study area, although 3B42V7 is better suited than IMERG.
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Forbes, K. A.; Kienzle, S. W.; Coburn, C. A.; Byrne, J. M.
2006-12-01
Multiple threats, including intensification of agricultural production, non-renewable resource extraction and climate change, are threatening Southern Alberta's water supply. The objective of this research is to calibrate/evaluate the Agricultural Catchments Research Unit (ACRU) agrohydrological model; with the end goal of forecasting the impacts of a changing environment on water quantity. The strength of this model is the intensive multi-layered soil water budgeting routine that integrates water movement between the surface and atmosphere. The ACRU model was parameterized using data from Environment Canada's climate database for a twenty year period (1984-2004) and was used to simulate streamflow for Beaver Creek. The simulated streamflow was compared to Environment Canada's historical streamflow database to validate the model output. The Beaver Creek Watershed, located in the Porcupine Hills southwestern Alberta, Canada contains a heterogeneous cover of deciduous, coniferous, native prairie grasslands and forage crops. In a catchment with highly diversified land cover, canopy architecture cannot be overlooked in rainfall interception parameterization. Preliminary testing of ACRU suggests that streamflows were sensitive to varied levels of leaf area index (LAI), a representative fraction of canopy foliage. Further testing using remotely sensed LAI's will provide a more accurate representation of canopy foliage and ultimately best represent this important element of the hydrological cycle and the associated processes which govern the natural hydrology of the Beaver Creek watershed.
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Sando, Steven K.; Morgan, Timothy J.; Dutton, DeAnn M.; McCarthy, Peter M.
2009-01-01
Charles M. Russell National Wildlife Refuge (CMR) encompasses about 1.1 million acres (including Fort Peck Reservoir on the Missouri River) in northeastern Montana. To ensure that sufficient streamflow remains in the tributary streams to maintain the riparian corridors, the U.S. Fish and Wildlife Service is negotiating water-rights issues with the Reserved Water Rights Compact Commission of Montana. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, conducted a study to gage, for a short period, selected streams that cross CMR, and analyze data to estimate long-term streamflow characteristics for CMR. The long-term streamflow characteristics of primary interest include the monthly and annual 90-, 80-, 50-, and 20-percent exceedance streamflows and mean streamflows (Q.90, Q.80, Q.50, Q.20, and QM, respectively), and the 1.5-, 2-, and 2.33- year peak flows (PK1.5, PK2, and PK2.33, respectively). The Regional Adjustment Relationship (RAR) was investigated for estimating the monthly and annual Q.90, Q.80, Q.50, Q.20, and QM, and the PK1.5, PK2, and PK2.33 for the short-term CMR gaging stations (hereinafter referred to as CMR stations). The RAR was determined to provide acceptable results for estimating the long-term Q.90, Q.80, Q.50, Q.20, and QM on a monthly basis for the months of March through June, and also on an annual basis. For the months of September through January, the RAR regression equations did not provide acceptable results for any long-term streamflow characteristic. For the month of February, the RAR regression equations provided acceptable results for the long-term Q.50 and QM, but poor results for the long-term Q.90, Q.80, and Q.20. For the months of July and August, the RAR provided acceptable results for the long-term Q.50, Q.20, and QM, but poor results for the long-term Q.90 and Q.80. Estimation coefficients were developed for estimating the long-term streamflow characteristics for which the RAR did not provide
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Model validation and calibration based on component functions of model output
International Nuclear Information System (INIS)
Wu, Danqing; Lu, Zhenzhou; Wang, Yanping; Cheng, Lei
2015-01-01
The target in this work is to validate the component functions of model output between physical observation and computational model with the area metric. Based on the theory of high dimensional model representations (HDMR) of independent input variables, conditional expectations are component functions of model output, and the conditional expectations reflect partial information of model output. Therefore, the model validation of conditional expectations tells the discrepancy between the partial information of the computational model output and that of the observations. Then a calibration of the conditional expectations is carried out to reduce the value of model validation metric. After that, a recalculation of the model validation metric of model output is taken with the calibrated model parameters, and the result shows that a reduction of the discrepancy in the conditional expectations can help decrease the difference in model output. At last, several examples are employed to demonstrate the rationality and necessity of the methodology in case of both single validation site and multiple validation sites. - Highlights: • A validation metric of conditional expectations of model output is proposed. • HDRM explains the relationship of conditional expectations and model output. • An improved approach of parameter calibration updates the computational models. • Validation and calibration process are applied at single site and multiple sites. • Validation and calibration process show a superiority than existing methods
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Simulation of agricultural non-point source pollution in Xichuan by using SWAT model
Xing, Linan; Zuo, Jiane; Liu, Fenglin; Zhang, Xiaohui; Cao, Qiguang
2018-02-01
This paper evaluated the applicability of using SWAT to access agricultural non-point source pollution in Xichuan area. In order to build the model, DEM, soil sort and land use map, climate monitoring data were collected as basic database. The SWAT model was calibrated and validated for the SWAT was carried out using streamflow, suspended solids, total phosphorus and total nitrogen records from 2009 to 2011. Errors, coefficient of determination and Nash-Sutcliffe coefficient were considered to evaluate the applicability. The coefficient of determination were 0.96, 0.66, 0.55 and 0.66 for streamflow, SS, TN, and TP, respectively. Nash-Sutcliffe coefficient were 0.93, 0.5, 0.52 and 0.63, respectively. The results all meet the requirements. It suggested that the SWAT model can simulate the study area.
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Deforestation effects on soil moisture, streamflow, and water balance in the central Appalachians
James H. Patric; James H. Patric
1973-01-01
Soil moisture, precipitation, and streamflow were measured on three watersheds in West Virginia, two deforested and one forested. Water content of barren soil always exceeded that of forest soil throughout the growing season and especially in dry weather. Streamflow increased 10 inches annually on the watersheds that were cleared, most of the increase occurring between...
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Littell, Jeremy; Pederson, Gregory T.; Gray, Stephen T.; Tjoelker, Michael; Hamlet, Alan F.; Woodhouse, Connie A.
2016-01-01
We developed Columbia River streamflow reconstructions using a network of existing, new, and updated tree-ring records sensitive to the main climatic factors governing discharge. Reconstruction quality is enhanced by incorporating tree-ring chronologies where high snowpack limits growth, which better represent the contribution of cool-season precipitation to flow than chronologies from trees positively sensitive to hydroclimate alone. The best performing reconstruction (back to 1609 CE) explains 59% of the historical variability and the longest reconstruction (back to 1502 CE) explains 52% of the variability. Droughts similar to the high-intensity, long-duration low flows observed during the 1920s and 1940s are rare, but occurred in the early 1500s and 1630s-1640s. The lowest Columbia flow events appear to be reflected in chronologies both positively and negatively related to streamflow, implying low snowpack and possibly low warm-season precipitation. High flows of magnitudes observed in the instrumental record appear to have been relatively common, and high flows from the 1680s to 1740s exceeded the magnitude and duration of observed wet periods in the late-19th and 20th Century. Comparisons between the Columbia River reconstructions and future projections of streamflow derived from global climate and hydrologic models show the potential for increased hydrologic variability, which could present challenges for managing water in the face of competing demands
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A. Srivastava; M. Dobre; E. Bruner; W. J. Elliot; I. S. Miller; J. Q. Wu
2011-01-01
Assessment of water yields from watersheds into streams and rivers is critical to managing water supply and supporting aquatic life. Surface runoff typically contributes the most to peak discharge of a hydrograph while subsurface flow dominates the falling limb of hydrograph and baseflow contributes to streamflow from shallow unconfined aquifers primarily during the...
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Sensitivity of Alpine Snow and Streamflow Regimes to Climate Changes
Rasouli, K.; Pomeroy, J. W.; Marks, D. G.; Bernhardt, M.
2014-12-01
Understanding the sensitivity of hydrological processes to climate change in alpine areas with snow dominated regimes is of paramount importance as alpine basins show both high runoff efficiency associated with the melt of the seasonal snowpack and great sensitivity of snow processes to temperature change. In this study, meteorological data measured in a selection of alpine headwaters basins including Reynolds Mountain East, Idaho, USA, Wolf Creek, Yukon in Canada, and Zugspitze Mountain, Germany with climates ranging from arctic to continental temperate were used to study the snow and streamflow sensitivity to climate change. All research sites have detailed multi-decadal meteorological and snow measurements. The Cold Regions Hydrological Modelling platform (CRHM) was used to create a model representing a typical alpine headwater basin discretized into hydrological response units with physically based representations of snow redistribution by wind, complex terrain snowmelt energetics and runoff processes in alpine tundra. The sensitivity of snow hydrology to climate change was investigated by changing air temperature and precipitation using weather generating methods based on the change factors obtained from different climate model projections for future and current periods. The basin mean and spatial variability of peak snow water equivalent, sublimation loss, duration of snow season, snowmelt rates, streamflow peak, and basin discharge were assessed under varying climate scenarios and the most sensitive hydrological mechanisms to the changes in the different alpine climates were detected. The results show that snow hydrology in colder alpine climates is more resilient to warming than that in warmer climates, but that compensatory factors to warming such as reduced blowing snow sublimation loss and reduced melt rate should also be assessed when considering climate change impacts on alpine hydrology.
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International Nuclear Information System (INIS)
Napier, B.A.; Gilbert, R.O.; Simpson, J.C.; Ramsdell, J.V. Jr.; Thiede, M.E.; Walters, W.H.
1993-06-01
The Hanford Environmental Dose Reconstruction (HEDR) Project has developed a set of computational ''tools'' for estimating the possible radiation dose that individuals may have received from past Hanford Site operations. This document describes the planned activities to ''validate'' these tools. In the sense of the HEDR Project, ''validation'' is a process carried out by comparing computational model predictions with field observations and experimental measurements that are independent of those used to develop the model
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Hidalgo, H.G.; Das, T.; Dettinger, M.D.; Cayan, D.R.; Pierce, D.W.; Barnett, T.P.; Bala, G.; Mirin, A.; Wood, A.W.; Bonfils, Celine; Santer, B.D.; Nozawa, T.
2009-01-01
This article applies formal detection and attribution techniques to investigate the nature of observed shifts in the timing of streamflow in the western United States. Previous studies have shown that the snow hydrology of the western United States has changed in the second half of the twentieth century. Such changes manifest themselves in the form of more rain and less snow, in reductions in the snow water contents, and in earlier snowmelt and associated advances in streamflow "center" timing (the day in the "water-year" on average when half the water-year flow at a point has passed). However, with one exception over a more limited domain, no other study has attempted to formally attribute these changes to anthropogenic increases of greenhouse gases in the atmosphere. Using the observations together with a set of global climate model simulations and a hydrologic model (applied to three major hydrological regions of the western United States_the California region, the upper Colorado River basin, and the Columbia River basin), it is found that the observed trends toward earlier "center" timing of snowmelt-driven streamflows in the western United States since 1950 are detectably different from natural variability (significant at the p analysis, and it is the only basin that showed a detectable signal when the analysis was performed on individual basins. It should be noted that although climate change is an important signal, other climatic processes have also contributed to the hydrologic variability of large basins in the western United States. ?? 2009 American Meteorological Society.
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Validation of models with multivariate output
International Nuclear Information System (INIS)
Rebba, Ramesh; Mahadevan, Sankaran
2006-01-01
This paper develops metrics for validating computational models with experimental data, considering uncertainties in both. A computational model may generate multiple response quantities and the validation experiment might yield corresponding measured values. Alternatively, a single response quantity may be predicted and observed at different spatial and temporal points. Model validation in such cases involves comparison of multiple correlated quantities. Multiple univariate comparisons may give conflicting inferences. Therefore, aggregate validation metrics are developed in this paper. Both classical and Bayesian hypothesis testing are investigated for this purpose, using multivariate analysis. Since, commonly used statistical significance tests are based on normality assumptions, appropriate transformations are investigated in the case of non-normal data. The methodology is implemented to validate an empirical model for energy dissipation in lap joints under dynamic loading
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Reduced streamflow lowers dry-season growth of rainbow trout in a small stream
Bret C. Harvey; Rodney J. Nakamoto; Jason L. White
2006-01-01
A wide variety of resource management activities can affect surface discharge in small streams. Often, the effects of variation in streamflow on fish survival and growth can be difficult to estimate because of possible confounding with the effects of other variables, such as water temperature and fish density. We measured the effect of streamflow on survival and growth...
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Systematic change in global patterns of streamflow following volcanic eruptions.
Iles, Carley E; Hegerl, Gabriele C
2015-11-01
Following large explosive volcanic eruptions precipitation decreases over much of the globe1-6, particularly in climatologically wet regions4,5. Stratospheric volcanic aerosols reflect sunlight, which reduces evaporation, whilst surface cooling stabilises the atmosphere and reduces its water-holding capacity7. Circulation changes modulate this global precipitation reduction on regional scales1,8-10. Despite the importance of rivers to people, it has been unclear whether volcanism causes detectable changes in streamflow given large natural variability. Here we analyse observational records of streamflow volume for fifty large rivers from around the world which cover between two and 6 major volcanic eruptions in the 20 th and late 19 th century. We find statistically significant reductions in flow following eruptions for the Amazon, Congo, Nile, Orange, Ob, Yenisey and Kolyma amongst others. When data from neighbouring rivers are combined - based on the areas where climate models simulate either an increase or a decrease in precipitation following eruptions - a significant (peruptions is detected in northern South American, central African and high-latitude Asian rivers, and on average across wet tropical and subtropical regions. We also detect a significant increase in southern South American and SW North American rivers. This suggests that future volcanic eruptions could substantially affect global water availability.
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Directory of Open Access Journals (Sweden)
W. P. Miller
2011-07-01
Full Text Available The current drought over the Colorado River Basin has raised concerns that the US Department of the Interior, Bureau of Reclamation (Reclamation may impose water shortages over the lower portion of the basin for the first time in history. The guidelines that determine levels of shortage are affected by relatively short-term (3 to 7 month forecasts determined by the Colorado Basin River Forecast Center (CBRFC using the National Weather Service (NWS River Forecasting System (RFS hydrologic model. While these forecasts by the CBRFC are useful, water managers within the basin are interested in long-term projections of streamflow, particularly under changing climate conditions. In this study, a bias-corrected, statistically downscaled dataset of projected climate is used to force the NWS RFS utilized by the CBRFC to derive projections of streamflow over the Green, Gunnison, and San Juan River headwater basins located within the Colorado River Basin. This study evaluates the impact of changing climate to evapotranspiration rates and contributes to a better understanding of how hydrologic processes change under varying climate conditions. The impact to evapotranspiration rates is taken into consideration and incorporated into the development of streamflow projections over Colorado River headwater basins in this study. Additionally, the NWS RFS is modified to account for impacts to evapotranspiration due to changing temperature over the basin. Adjusting evapotranspiration demands resulted in a 6 % to 13 % average decrease in runoff over the Gunnison River Basin when compared to static evapotranspiration rates. Streamflow projections derived using projections of future climate and the NWS RFS provided by the CBRFC resulted in decreased runoff in 2 of the 3 basins considered. Over the Gunnison and San Juan River basins, a 10 % to 15 % average decrease in basin runoff is projected through the year 2099. However, over the Green River basin, a 5 % to 8
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The influence of climate modes on streamflow in the Mid-Atlantic region of the United States
Directory of Open Access Journals (Sweden)
Justin A. Schulte
2016-03-01
Full Text Available Study region: The Mid-Atlantic region of the United States. Study focus: An understanding of past streamflow variability is necessary for developing future management practices that will help mitigate the impacts of extreme events such as drought or floods on agriculture and other human activities. To better understand mechanisms driving streamflow variability at all timescales, annual to multi-decadal streamflow variability of three major rivers in the Mid-Atlantic region of the United States (the Susquehanna, Delaware, and Hudson Rivers was studied in the context of climate modes using correlation and wavelet analyses. New hydrological insights for the region: Results from the correlation analysis detected statistically significant relationships between climate indices and streamflow that were similar for the three rivers. The results from the wavelet analysis showed that 18- and 26-year periodicities were embedded in the streamflow time series. Decadal variability of streamflow was coherent with the El-Niño Southern Oscillation (SO and the Pacific Decadal Oscillation (PDO. The time series for the PDO and SO indices and precipitation were found to be synchronized to the decadal variability of a global circulation pattern consisting of a Rossby wave train emanating from the North Pacific. The SO explained 37–54% of the 1960s drought, 33–49% of the 1970s pluvial, and 19–50% of the 2000s pluvial in the three river basins. Keywords: Streamflow, Climate, Climate variability, Wavelet analysis, El-Niño-Southern Oscillation, Mid-Atlantic region
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Zhang, Qiang; Liu, Jianyu; Singh, Vijay P.; Shi, Peijun; Sun, Peng
2017-11-01
Prediction of streamflow of the Yellow River basin was done using downscaled precipitation and temperature based on outputs of 12 GCMs under RCP2.6 and RCP8.5 scenarios. Streamflow changes of 37 tributaries of the Yellow River basin during 2070-2099 were predicted related to different GCMs and climatic scenarios using Budyko framework. The results indicated that: (1) When compared to precipitation and temperature during 1960-1979, increasing precipitation and temperature are dominant during 2070-2099. Particularly, under RCP8.5, increase of 10% and 30% can be detected for precipitation and temperature respectively; (2) Precipitation changes have larger fractional contribution to streamflow changes than temperature changes, being the major driver for spatial and temporal patterns of water resources across the Yellow River basin; (3) 2070-2099 period will witness increased streamflow depth and decreased streamflow can be found mainly in the semi-humid regions and headwater regions of the Yellow River basin, which can be attributed to more significant increase of temperature than precipitation in these regions; (4) Distinctly different picture of streamflow changes can be observed with consideration of different outputs of GCMs which can be attributed to different outputs of GCMs under different scenarios. Even so, under RCP2.6 and RCP8.5 scenarios, 36.8% and 71.1% of the tributaries of the Yellow River basin are dominated by increasing streamflow. The results of this study are of theoretical and practical merits in terms of management of water resources and also irrigated agriculture under influences of changing climate.
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Directory of Open Access Journals (Sweden)
Guangju Zhao
Full Text Available Variation of streamflow and sediment load in the Yellow River basin has received considerable attention due to its drastic reduction during the past several decades. This paper presents a detailed investigation on the changes of streamflow and sediment load from 1952 to 2011 using monthly observations at four gauging stations along the Yellow River. The results show significant decreasing trends for both streamflow and sediment load at all four gauging stations over the past 60 years. The wavelet transform demonstrated discontinuous periodicities from 1969 to 1973 and after 1986 due to the construction of large reservoirs and implementation of numerous soil and water conservations practices. The sediment rating curves with the power-law function was applied to investigate the relationship between discharge and sediment load. The results indicate distinct variations of the relationship between streamflow and sediment and implied significant hydro-morphological changes within different periods. The reducing sediment supply from the source region and the increased erosive power of the river are detected at Lanzhou station, while the decrease of the transport capacity at Toudaoguai is caused by severe siltation. Significant changes in the relationship between streamflow and sediment load are found at Huayuankou and Gaocun stations, which are largely induced by evident sediment income and trapping effects of large reservoirs. It is estimated that numerous reservoirs have strongly altered the regime and magnitude of streamflow and trapped large amount of sediment, leading to severe siltation and evident reduction of their total volumes. A decrease in precipitation, incoming water from the upper reaches, soil and water conservation measures as well as water consumption contribute most to the significant reduction of streamflow. The decrease of sediment load mainly resulted from various soil and water conservation measures and trapping in reservoirs
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Model Validation in Ontology Based Transformations
Directory of Open Access Journals (Sweden)
Jesús M. Almendros-Jiménez
2012-10-01
Full Text Available Model Driven Engineering (MDE is an emerging approach of software engineering. MDE emphasizes the construction of models from which the implementation should be derived by applying model transformations. The Ontology Definition Meta-model (ODM has been proposed as a profile for UML models of the Web Ontology Language (OWL. In this context, transformations of UML models can be mapped into ODM/OWL transformations. On the other hand, model validation is a crucial task in model transformation. Meta-modeling permits to give a syntactic structure to source and target models. However, semantic requirements have to be imposed on source and target models. A given transformation will be sound when source and target models fulfill the syntactic and semantic requirements. In this paper, we present an approach for model validation in ODM based transformations. Adopting a logic programming based transformational approach we will show how it is possible to transform and validate models. Properties to be validated range from structural and semantic requirements of models (pre and post conditions to properties of the transformation (invariants. The approach has been applied to a well-known example of model transformation: the Entity-Relationship (ER to Relational Model (RM transformation.
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Reconstructed streamflow for Citarum River, Java, Indonesia: linkages to tropical climate dynamics
Energy Technology Data Exchange (ETDEWEB)
D' Arrigo, Rosanne [Tree-Ring Laboratory, Lamont-Doherty Earth Observatory, Palisades, NY (United States); Abram, Nerilie [The Australian National University, Research School of Earth Sciences, Canberra (Australia); Natural Environment Research Council, British Antarctic Survey, Cambridge (United Kingdom); Ummenhofer, Caroline [University of New South Wales, Sydney, NSW (Australia); Palmer, Jonathan [Gondwana Tree-Ring Laboratory, Canterbury (New Zealand); Mudelsee, Manfred [Climate Risk Analysis, Hannover (Germany)
2011-02-15
The Citarum river basin of western Java, Indonesia, which supplies water to 10 million residents in Jakarta, has become increasingly vulnerable to anthropogenic change. Citarum's streamflow record, only {proportional_to}45 years in length (1963-present), is too short for understanding the full range of hydrometeorological variability in this important region. Here we present a tree-ring based reconstruction of September-November Citarum streamflow (AD 1759-2006), one of the first such records available for monsoon Asia. Close coupling is observed between decreased tree growth and low streamflow levels, which in turn are associated with drought caused by ENSO warm events in the tropical Pacific and Indian Ocean positive dipole-type variability. Over the full length of record, reconstructed variance was at its weakest during the interval from {proportional_to}1905-1960, overlapping with a period of unusually-low variability (1920-1960) in the ENSO-Indian Ocean dipole systems. In subsequent decades, increased variance in both the streamflow anomalies and a coral-based SST reconstruction of the Indian Ocean Dipole Mode signal the potential for intensified drought activity and related consequences for water supply and crop productivity in western Java, where much of the country's rice is grown. (orig.)
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Capesius, Joseph P.; Sullivan, Joseph R.; O'Neill, Gregory B.; Williams, Cory A.
2005-01-01
Accurate ice-affected streamflow records are difficult to obtain for several reasons, which makes the management of instream-flow water rights in the wintertime a challenging endeavor. This report documents a method to improve ice-affected streamflow records for two gaging stations in Colorado. In January and February 2002, the U.S. Geological Survey, in cooperation with the Colorado Water Conservation Board, conducted an experiment using a sodium chloride tracer to measure streamflow under ice cover by the tracer-dilution discharge method. The purpose of this study was to determine the feasibility of obtaining accurate ice-affected streamflow records by using a sodium chloride tracer that was injected into the stream. The tracer was injected at two gaging stations once per day for approximately 20 minutes for 25 days. Multiple-parameter water-quality sensors at the two gaging stations monitored background and peak chloride concentrations. These data were used to determine discharge at each site. A comparison of the current-meter streamflow record to the tracer-dilution streamflow record shows different levels of accuracy and precision of the tracer-dilution streamflow record at the two sites. At the lower elevation and warmer site, Brandon Ditch near Whitewater, the tracer-dilution method overestimated flow by an average of 14 percent, but this average is strongly biased by outliers. At the higher elevation and colder site, Keystone Gulch near Dillon, the tracer-dilution method experienced problems with the tracer solution partially freezing in the injection line. The partial freezing of the tracer contributed to the tracer-dilution method underestimating flow by 52 percent at Keystone Gulch. In addition, a tracer-pump-reliability test was conducted to test how accurately the tracer pumps can discharge the tracer solution in conditions similar to those used at the gaging stations. Although the pumps were reliable and consistent throughout the 25-day study period
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Patterns of Precipitation and Streamflow Responses to Moisture Fluxes during Atmospheric Rivers
Henn, B. M.; Wilson, A. M.; Asgari Lamjiri, M.; Ralph, M.
2017-12-01
Precipitation from landfalling atmospheric rivers (ARs) have been shown to dominate the hydroclimate of many parts of the world. ARs are associated with saturated, neutrally-stable profiles in the lower atmosphere, in which forced ascent by topography induces precipitation. Understanding the spatial and temporal variability of precipitation over complex terrain during AR-driven precipitation is critical for accurate forcing of distributed hydrologic models and streamflow forecasts. Past studies using radar wind profilers and radiosondes have demonstrated predictability of precipitation rates based on upslope water vapor flux over coastal terrain, with certain levels of moisture flux exhibiting the greatest influence on precipitation. Additionally, these relationships have been extended to show that streamflow in turn responds predictably to upslope vapor flux. However, past studies have focused on individual pairs of profilers and precipitation gauges; the question of how orographic precipitation in ARs is distributed spatially over complex terrain, at different topographic scales, is less well known. Here, we examine profiles of atmospheric moisture transport from radiosondes and wind profilers, against a relatively dense network of precipitation gauges, as well as stream gauges, to assess relationships between upslope moisture flux and the spatial response of precipitation and streamflow. We focus on California's Russian River watershed in the 2016-2017 cool season, when regular radiosonde launches were made at two locations during an active sequence of landfalling ARs. We examine how atmospheric water vapor flux results in precipitation patterns across gauges with different topographic relationships to the prevailing moisture-bearing winds, and conduct a similar comparison of runoff volume response from several unimpaired watersheds in the upper Russian watershed, taking into account antecedent soil moisture conditions that influence runoff generation. Finally
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Loizu, Javier; Massari, Christian; Álvarez-Mozos, Jesús; Casalí, Javier; Goñi, Mikel
2016-04-01
Assimilation of Surface Soil Moisture (SSM) observations obtained from remote sensing techniques have been shown to improve streamflow prediction at different time scales of hydrological modeling. Different sensors and methods have been tested for their application in SSM estimation, especially in the microwave region of the electromagnetic spectrum. The available observation devices include passive microwave sensors such as the Advanced Microwave Scanning Radiometer - Earth Observation System (AMSR-E) onboard the Aqua satellite and the Soil Moisture and Ocean Salinity (SMOS) mission. On the other hand, active microwave systems include Scatterometers (SCAT) onboard the European Remote Sensing satellites (ERS-1/2) and the Advanced Scatterometer (ASCAT) onboard MetOp-A satellite. Data assimilation (DA) include different techniques that have been applied in hydrology and other fields for decades. These techniques include, among others, Kalman Filtering (KF), Variational Assimilation or Particle Filtering. From the initial KF method, different techniques were developed to suit its application to different systems. The Ensemble Kalman Filter (EnKF), extensively applied in hydrological modeling improvement, shows its capability to deal with nonlinear model dynamics without linearizing model equations, as its main advantage. The objective of this study was to investigate whether data assimilation of SSM ASCAT observations, through the EnKF method, could improve streamflow simulation of mediterranean catchments with TOPLATS hydrological complex model. The DA technique was programmed in FORTRAN, and applied to hourly simulations of TOPLATS catchment model. TOPLATS (TOPMODEL-based Land-Atmosphere Transfer Scheme) was applied on its lumped version for two mediterranean catchments of similar size, located in northern Spain (Arga, 741 km2) and central Italy (Nestore, 720 km2). The model performs a separated computation of energy and water balances. In those balances, the soil
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Estimation of Tile Drainage Contribution to Streamflow and Nutrient Export Loads
Schilling, K. E.; Arenas Amado, A.; Jones, C. S.; Weber, L. J.
2015-12-01
Subsurface drainage is a very common practice in the agricultural U.S. Midwest. It is typically installed in poorly drained soils in order to enhance crop yields. The presence of tile drains creates a route for agrichemicals to travel and therefore negatively impacts stream water quality. This study estimated through end-member analyses the contributions of tile drainage, groundwater, and surface runoff to streamflow at the watershed scale based on continuously monitored data. Especial attention was devoted to quantifying tile drainage impact on watershed streamflow and nutrient export loads. Data analyzed includes streamflow, rainfall, soil moisture, shallow groundwater levels, in-stream nitrate+nitrite concentrations and specific conductance. Data were collected at a HUC12 watershed located in Northeast Iowa, USA. Approximately 60% of the total watershed area is devoted to agricultural activities and forest and grassland are the other two predominant land uses. Results show that approximately 20% of total annual streamflow comes from tile drainage and during rainfall events tile drainage contribution can go up to 30%. Furthermore, for most of the analyzed rainfall events groundwater responded faster and in a more dramatic fashion than tile drainage. The State of Iowa is currently carrying out a plan to reduce nutrients in Iowa waters and the Gulf of Mexico (Iowa Nutrient Reduction Strategy). The outcome of this investigation has the potential to assist in Best Management Practice (BMP) scenario selection and therefore help the state achieve water quality goals.
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Integrating Artificial Neural Networks into the VIC Model for Rainfall-Runoff Modeling
Directory of Open Access Journals (Sweden)
Changqing Meng
2016-09-01
Full Text Available A hybrid rainfall-runoff model was developed in this study by integrating the variable infiltration capacity (VIC model with artificial neural networks (ANNs. In the proposed model, the prediction interval of the ANN replaces separate, individual simulation (i.e., single simulation. The spatial heterogeneity of horizontal resolution, subgrid-scale features and their influence on the streamflow can be assessed according to the VIC model. In the routing module, instead of a simple linear superposition of the streamflow generated from each subbasin, ANNs facilitate nonlinear mappings of the streamflow produced from each subbasin into the total streamflow at the basin outlet. A total of three subbasins were delineated and calibrated independently via the VIC model; daily runoff errors were simulated for each subbasin, then corrected by an ANN bias-correction model. The initial streamflow and corrected runoff from the simulation for individual subbasins serve as inputs to the ANN routing model. The feasibility of this proposed method was confirmed according to the performance of its application to a case study on rainfall-runoff prediction in the Jinshajiang River Basin, the headwater area of the Yangtze River.
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Stochastic Watershed Models for Risk Based Decision Making
Vogel, R. M.
2017-12-01
Over half a century ago, the Harvard Water Program introduced the field of operational or synthetic hydrology providing stochastic streamflow models (SSMs), which could generate ensembles of synthetic streamflow traces useful for hydrologic risk management. The application of SSMs, based on streamflow observations alone, revolutionized water resources planning activities, yet has fallen out of favor due, in part, to their inability to account for the now nearly ubiquitous anthropogenic influences on streamflow. This commentary advances the modern equivalent of SSMs, termed `stochastic watershed models' (SWMs) useful as input to nearly all modern risk based water resource decision making approaches. SWMs are deterministic watershed models implemented using stochastic meteorological series, model parameters and model errors, to generate ensembles of streamflow traces that represent the variability in possible future streamflows. SWMs combine deterministic watershed models, which are ideally suited to accounting for anthropogenic influences, with recent developments in uncertainty analysis and principles of stochastic simulation
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Dale, Joseph; Zou, Chris B.; Andrews, William J.; Long, James M.; Liang, Ye; Qiao, Lei
2015-01-01
Climatic variability and land surface change have a wide range of effects on streamflow and are often difficult to separate. We analyzed long-term records of climate, land use and land cover, and re-constructed the water budget based on precipitation, groundwater levels, and water use from 1950 through 2010 in the Cimarron–Skeleton watershed and a portion of the Cimarron–Eagle Chief watershed in Oklahoma, an irrigation-intensive agricultural watershed in the Southern Great Plains, USA. Our results show that intensive irrigation through alluvial aquifer withdrawal modifies climatic feedback and alters streamflow response to precipitation. Increase in consumptive water use was associated with decreases in annual streamflow, while returning croplands to non-irrigated grasslands was associated with increases in streamflow. Along with groundwater withdrawal, anthropogenic-induced factors and activities contributed nearly half to the observed variability of annual streamflow. Streamflow was more responsive to precipitation during the period of intensive irrigation between 1965 and 1984 than the period of relatively lower water use between 1985 and 2010. The Cimarron River is transitioning from a historically flashy river to one that is more stable with a lower frequency of both high and low flow pulses, a higher baseflow, and an increased median flow due in part to the return of cropland to grassland. These results demonstrated the interrelationship among climate, land use, groundwater withdrawal and streamflow regime and the potential to design agricultural production systems and adjust irrigation to mitigate impact of increasing climate variability on streamflow in irrigation intensive agricultural watershed.
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Directory of Open Access Journals (Sweden)
Dagbegnon Clement Sohoulande Djebou
2015-09-01
New hydrological insights for the region: Over the period 1961–2012, I conduct a change point analysis of the streamflow and report two sub-periods 1961–1982 and 1983–2012. A comparison of precipitation and streamflow during these two time-slices shows meaningful changes. I describe a Kernel density analysis of streamflow and yield a probabilistic estimate of discharge anomalies along the river. Later, I evaluate seasonal trends of precipitation and streamflow. The analyses bring out critical alterations in time and space. However, these alterations seem to foreshadow critical environmental degradations occurring across the watershed. I consider LAI series derived from MODIS images, then I examine and discuss trends in land-cover dynamics in relation with the patterns in precipitation and streamflow. This late analytical step yields a holistic picture of the ongoing alterations in the Niger River Basin. Finally, I emphasize suggestions, valuable for a comprehensive water resources and environment management.
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Exploring the link between meteorological drought and streamflow to inform water resource management
Lennard, Amy; Macdonald, Neil; Hooke, Janet
2015-04-01
Drought indicators are an under-used metric in UK drought management. Standardised drought indicators offer a potential monitoring and management tool for operational water resource management. However, the use of these metrics needs further investigation. This work uses statistical analysis of the climatological drought signal based on meteorological drought indicators and observed streamflow data to explore the link between meteorological drought and hydrological drought to inform water resource management for a single water resource region. The region, covering 21,000 km2 of the English Midlands and central Wales, includes a variety of landscapes and climatological conditions. Analysis of the links between meteorological drought and hydrological drought performed using streamflow data from 'natural' catchments indicates a close positive relationship between meteorological drought indicators and streamflow, enhancing confidence in the application of drought indicators for monitoring and management. However, many of the catchments in the region are subject to modification through impoundments, abstractions and discharge. Therefore, it is beneficial to explore how climatological drought signal propagates into managed hydrological systems. Using a longitudinal study of catchments and sub-catchments that include natural and modified river reaches the relationship between meteorological and hydrological drought is explored. Initial statistical analysis of meteorological drought indicators and streamflow data from modified catchments shows a significantly weakened statistical relationship and reveals how anthropogenic activities may alter hydrological drought characteristics in modified catchments. Exploring how meteorological drought indicators link to streamflow across the water supply region helps build an understanding of their utility for operational water resource management.
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Yang, Yuhui; Chen, Yaning; Wang, Minzhong; Sun, Huilan
2017-07-01
We examined the changes in streamflow on the northern slopes of the Tianshan Mountains in northern Xinjiang, China, over two time scales: the past 500 years, based on dendrochronology data; and the past 50 years, based on streamflow data from hydrological stations. The method of artificial neural networks built from the data of the 50-year period was used to reconstruct the streamflow of the 500-year period. The results indicate that streamflow has undergone seven high-flow periods and four low-flow periods during the past 500 years. To identify possible transition points in the streamflow, we applied the Mann-Kendall and running T tests to the 50- and 500-year periods, respectively. During the past 500 years, streamflow has changed significantly from low to high flow about three to four times, and from high to low flow about three to five times. Over the recent 50 years, there have been three phases of variation in river runoff, and the most distinct transition of streamflow occurred in 1996.
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Global modelling of river water quality under climate change
van Vliet, Michelle T. H.; Franssen, Wietse H. P.; Yearsley, John R.
2017-04-01
Climate change will pose challenges on the quality of freshwater resources for human use and ecosystems for instance by changing the dilution capacity and by affecting the rate of chemical processes in rivers. Here we assess the impacts of climate change and induced streamflow changes on a selection of water quality parameters for river basins globally. We used the Variable Infiltration Capacity (VIC) model and a newly developed global water quality module for salinity, temperature, dissolved oxygen and biochemical oxygen demand. The modelling framework was validated using observed records of streamflow, water temperature, chloride, electrical conductivity, dissolved oxygen and biochemical oxygen demand for 1981-2010. VIC and the water quality module were then forced with an ensemble of bias-corrected General Circulation Model (GCM) output for the representative concentration pathways RCP2.6 and RCP8.5 to study water quality trends and identify critical regions (hotspots) of water quality deterioration for the 21st century.
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Ground-water models: Validate or invalidate
Bredehoeft, J.D.; Konikow, Leonard F.
1993-01-01
The word validation has a clear meaning to both the scientific community and the general public. Within the scientific community the validation of scientific theory has been the subject of philosophical debate. The philosopher of science, Karl Popper, argued that scientific theory cannot be validated, only invalidated. Popper’s view is not the only opinion in this debate; however, many scientists today agree with Popper (including the authors). To the general public, proclaiming that a ground-water model is validated carries with it an aura of correctness that we do not believe many of us who model would claim. We can place all the caveats we wish, but the public has its own understanding of what the word implies. Using the word valid with respect to models misleads the public; verification carries with it similar connotations as far as the public is concerned. Our point is this: using the terms validation and verification are misleading, at best. These terms should be abandoned by the ground-water community.
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Wright, David; Thyer, Mark; Westra, Seth
2015-04-01
Highly influential data points are those that have a disproportionately large impact on model performance, parameters and predictions. However, in current hydrological modelling practice the relative influence of individual data points on hydrological model calibration is not commonly evaluated. This presentation illustrates and evaluates several influence diagnostics tools that hydrological modellers can use to assess the relative influence of data. The feasibility and importance of including influence detection diagnostics as a standard tool in hydrological model calibration is discussed. Two classes of influence diagnostics are evaluated: (1) computationally demanding numerical "case deletion" diagnostics; and (2) computationally efficient analytical diagnostics, based on Cook's distance. These diagnostics are compared against hydrologically orientated diagnostics that describe changes in the model parameters (measured through the Mahalanobis distance), performance (objective function displacement) and predictions (mean and maximum streamflow). These influence diagnostics are applied to two case studies: a stage/discharge rating curve model, and a conceptual rainfall-runoff model (GR4J). Removing a single data point from the calibration resulted in differences to mean flow predictions of up to 6% for the rating curve model, and differences to mean and maximum flow predictions of up to 10% and 17%, respectively, for the hydrological model. When using the Nash-Sutcliffe efficiency in calibration, the computationally cheaper Cook's distance metrics produce similar results to the case-deletion metrics at a fraction of the computational cost. However, Cooks distance is adapted from linear regression with inherit assumptions on the data and is therefore less flexible than case deletion. Influential point detection diagnostics show great potential to improve current hydrological modelling practices by identifying highly influential data points. The findings of this
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Hydro-Climatic Data Network (HCDN) Streamflow Data Set, 1874-1988
Slack, James Richard; Lumb, Alan M.; Landwehr, Jurate Maciunas
1993-01-01
The potential consequences of climate change to continental water resources are of great concern in the management of those resources. Critically important to society is what effect fluctuations in the prevailing climate may have on hydrologic conditions, such as the occurrence and magnitude of floods or droughts and the seasonal distribution of water supplies within a region. Records of streamflow that are unaffected by artificial diversions, storage, or other works of man in or on the natural stream channels or in the watershed can provide an account of hydrologic responses to fluctuations in climate. By examining such records given known past meteorologic conditions, we can better understand hydrologic responses to those conditions and anticipate the effects of postulated changes in current climate regimes. Furthermore, patterns in streamflow records can indicate when a change in the prevailing climate regime may have occurred in the past, even in the absence of concurrent meteorologic records. A streamflow data set, which is specifically suitable for the study of surface-water conditions throughout the United States under fluctuations in the prevailing climatic conditions, has been developed. This data set, called the Hydro-Climatic Data Network, or HCDN, consists of streamflow records for 1,659 sites throughout United States and its Territories. Records cumulatively span the period 1874 through 1988, inclusive, and represent a total of 73,231 water years of information. Development of the HCDN Data Set: Records for the HCDN were obtained through a comprehensive search of the extensive surface- water data holdings of the U.S. Geological Survey (USGS), which are contained in the USGS National Water Storage and Retrieval System (WATSTORE). All streamflow discharge records in WATSTORE through September 30, 1988, were examined for inclusion in the HCDN in accordance with strictly defined criteria of measurement accuracy and natural conditions. No reconstructed
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Directory of Open Access Journals (Sweden)
Laurent Ahiablame
2017-12-01
Full Text Available Study region: North and South Dakotas, United States Study focus: Changes in watershed hydrology are mainly driven by changes in land use and climate. This study evaluated the impacts of climate and land use changes on streamflow in an agricultural watershed in the Upper Midwest. Three projected climate change scenarios (A1B, A2 and B1 of three general circulation models (CGCM3.1, GFDL-CM2.1, and HADCM3 were developed for mid (2046â2065 and end (2080â2099 of the 21st century. Corresponding land use maps for years 2055 and 2090 were obtained from the FOREcasting SCEnarios of Land-Cover (FORE-SCE model. The scenarios were designed in a way that land use was changed while climate conditions remain constant, land use was then held constant under a changing climate, and finally both land use and climate were changed simultaneously to reflect possible future land use and climate conditions. New hydrological insights for the region: Potential land use and climate changes would result in 12â18% % and 17â41% increases in annual streamflow, respectively, by end of the century. The combined effects of land use and climate changes would intensify future streamflow responses with 13â60% increases in the region. This study provides a broad perspective on plausible hydrologic alterations in the region, prompting individual and collective opportunities to engage with this topic for sustainable planning and management of watersheds. Keywords: Watershed modeling, Precipitation, Agricultural land, Grassland, Dakota, SWAT
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Modelling the hydrological behaviour of a coffee agroforestry basin in Costa Rica
Directory of Open Access Journals (Sweden)
F. Gómez-Delgado
2011-01-01
Full Text Available The profitability of hydropower in Costa Rica is affected by soil erosion and sedimentation in dam reservoirs, which are in turn influenced by land use, infiltration and aquifer interactions with surface water. In order to foster the provision and payment for Hydrological Environmental Services (HES, a quantitative assessment of the impact of specific land uses on the functioning of drainage-basins is required. The present paper aims to study the water balance partitioning in a volcanic coffee agroforestry micro-basin (1 km2, steep slopes in Costa Rica, as a first step towards evaluating sediment or contaminant loads. The main hydrological processes were monitored during one year, using flume, eddy-covariance flux tower, soil water profiles and piezometers. A new Hydro-SVAT lumped model is proposed, that balances SVAT (Soil Vegetation Atmosphere Transfer and basin-reservoir routines. The purpose of such a coupling was to achieve a trade-off between the expected performance of ecophysiological and hydrological models, which are often employed separately and at different spatial scales, either the plot or the basin. The calibration of the model to perform streamflow yielded a Nash-Sutcliffe (NS coefficient equal to 0.89 for the year 2009, while the validation of the water balance partitioning was consistent with the independent measurements of actual evapotranspiration (R2 = 0.79, energy balance closed independently, soil water content (R2 = 0.35 and water table level (R2 = 0.84. Eight months of data from 2010 were used to validate modelled streamflow, resulting in a NS = 0.75. An uncertainty analysis showed that the streamflow modelling was precise for nearly every time step, while a sensitivity analysis revealed which parameters mostly affected model precision, depending on the season. It was observed that 64% of the incident rainfall R flowed out of the basin as streamflow
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Trends in Mean Annual Streamflows in Serra da Mantiqueira Environmental Protection Area
Mateus Ricardo Nogueira Vilanova
2014-01-01
The aim of this study was to detect trends in the mean annual streamflow in watersheds of Serra da Mantiqueira Environmental Protection Area, an important Brazilian conservation area located between Minas Gerais, São Paulo and Rio de Janeiro States. Historical series of four selected streamgage stations were analyzed for the periods of 1980-1998 and 1980-2009, using the Mann-Kendall and Regional Mann-Kendall tests. The results showed that the mean annual streamflows of Serra da Mantiqueira En...
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Directory of Open Access Journals (Sweden)
É. Gaborit
2017-09-01
Full Text Available This work explores the potential of the distributed GEM-Hydro runoff modeling platform, developed at Environment and Climate Change Canada (ECCC over the last decade. More precisely, the aim is to develop a robust implementation methodology to perform reliable streamflow simulations with a distributed model over large and partly ungauged basins, in an efficient manner. The latest version of GEM-Hydro combines the SVS (Soil, Vegetation and Snow land-surface scheme and the WATROUTE routing scheme. SVS has never been evaluated from a hydrological point of view, which is done here for all major rivers flowing into Lake Ontario. Two established hydrological models are confronted to GEM-Hydro, namely MESH and WATFLOOD, which share the same routing scheme (WATROUTE but rely on different land-surface schemes. All models are calibrated using the same meteorological forcings, objective function, calibration algorithm, and basin delineation. GEM-Hydro is shown to be competitive with MESH and WATFLOOD: the NSE √ (Nash–Sutcliffe criterion computed on the square root of the flows is for example equal to 0.83 for MESH and GEM-Hydro in validation on the Moira River basin, and to 0.68 for WATFLOOD. A computationally efficient strategy is proposed to calibrate SVS: a simple unit hydrograph is used for routing instead of WATROUTE. Global and local calibration strategies are compared in order to estimate runoff for ungauged portions of the Lake Ontario basin. Overall, streamflow predictions obtained using a global calibration strategy, in which a single parameter set is identified for the whole basin of Lake Ontario, show accuracy comparable to the predictions based on local calibration: the average NSE √ in validation and over seven subbasins is 0.73 and 0.61, respectively for local and global calibrations. Hence, global calibration provides spatially consistent parameter values, robust performance at gauged locations, and reduces the
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Gaborit, Étienne; Fortin, Vincent; Xu, Xiaoyong; Seglenieks, Frank; Tolson, Bryan; Fry, Lauren M.; Hunter, Tim; Anctil, François; Gronewold, Andrew D.
2017-09-01
This work explores the potential of the distributed GEM-Hydro runoff modeling platform, developed at Environment and Climate Change Canada (ECCC) over the last decade. More precisely, the aim is to develop a robust implementation methodology to perform reliable streamflow simulations with a distributed model over large and partly ungauged basins, in an efficient manner. The latest version of GEM-Hydro combines the SVS (Soil, Vegetation and Snow) land-surface scheme and the WATROUTE routing scheme. SVS has never been evaluated from a hydrological point of view, which is done here for all major rivers flowing into Lake Ontario. Two established hydrological models are confronted to GEM-Hydro, namely MESH and WATFLOOD, which share the same routing scheme (WATROUTE) but rely on different land-surface schemes. All models are calibrated using the same meteorological forcings, objective function, calibration algorithm, and basin delineation. GEM-Hydro is shown to be competitive with MESH and WATFLOOD: the NSE √ (Nash-Sutcliffe criterion computed on the square root of the flows) is for example equal to 0.83 for MESH and GEM-Hydro in validation on the Moira River basin, and to 0.68 for WATFLOOD. A computationally efficient strategy is proposed to calibrate SVS: a simple unit hydrograph is used for routing instead of WATROUTE. Global and local calibration strategies are compared in order to estimate runoff for ungauged portions of the Lake Ontario basin. Overall, streamflow predictions obtained using a global calibration strategy, in which a single parameter set is identified for the whole basin of Lake Ontario, show accuracy comparable to the predictions based on local calibration: the average NSE √ in validation and over seven subbasins is 0.73 and 0.61, respectively for local and global calibrations. Hence, global calibration provides spatially consistent parameter values, robust performance at gauged locations, and reduces the complexity and computation burden of the
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Banta, J. Ryan; Lambert, Rebecca B.; Slattery, Richard N.; Ockerman, Darwin J.
2012-01-01
The U.S. Geological Survey-in cooperation with the U.S. Army Corps of Engineers, The Nature Conservancy, the Real Edwards Conservation and Reclamation District, and the Texas Parks and Wildlife Department-investigated streamflow gain and loss and water quality in the upper Nueces River Basin, south-central Texas, specifically in the watersheds of the West Nueces, Nueces, Dry Frio, Frio, and Sabinal Rivers upstream from the Edwards aquifer outcrop. Streamflow in these rivers is sustained by groundwater contributions (for example, from springs) and storm runoff from rainfall events. To date (2012), there are few data available that describe streamflow and water-quality conditions of the rivers within the upper Nueces River Basin. This report describes streamflow gain-loss characteristics from three reconnaissance-level synoptic measurement surveys (hereinafter referred to as "surveys") during 2008-10 in the upper Nueces River Basin. To help characterize the hydrology, groundwater-level measurements were made, and water-quality samples were collected from both surface-water and groundwater sites in the study area from two surveys during 2009-10. The hydrologic (streamflow, springflow, and groundwater) measurements were made during three reconnaissance-level synoptic measurement surveys occurring in July 21-23, 2008; August 8-18, 2009; and March 22-24, 2010. These survey periods were selected to represent different hydrologic conditions. Streamflow gains and losses were based on streamflow and springflow measurements made at 74 sites in the study area, although not all sites were measured during each survey. Possible water chemistry relations among sample types (streamflow, springflow, or groundwater), between surveys, and among watersheds were examined using water-quality samples collected from as many as 20 sites in the study area.
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Remote Sensing-based Methodologies for Snow Model Adjustments in Operational Streamflow Prediction
Bender, S.; Miller, W. P.; Bernard, B.; Stokes, M.; Oaida, C. M.; Painter, T. H.
2015-12-01
Water management agencies rely on hydrologic forecasts issued by operational agencies such as NOAA's Colorado Basin River Forecast Center (CBRFC). The CBRFC has partnered with the Jet Propulsion Laboratory (JPL) under funding from NASA to incorporate research-oriented, remotely-sensed snow data into CBRFC operations and to improve the accuracy of CBRFC forecasts. The partnership has yielded valuable analysis of snow surface albedo as represented in JPL's MODIS Dust Radiative Forcing in Snow (MODDRFS) data, across the CBRFC's area of responsibility. When dust layers within a snowpack emerge, reducing the snow surface albedo, the snowmelt rate may accelerate. The CBRFC operational snow model (SNOW17) is a temperature-index model that lacks explicit representation of snowpack surface albedo. CBRFC forecasters monitor MODDRFS data for emerging dust layers and may manually adjust SNOW17 melt rates. A technique was needed for efficient and objective incorporation of the MODDRFS data into SNOW17. Initial development focused in Colorado, where dust-on-snow events frequently occur. CBRFC forecasters used retrospective JPL-CBRFC analysis and developed a quantitative relationship between MODDRFS data and mean areal temperature (MAT) data. The relationship was used to generate adjusted, MODDRFS-informed input for SNOW17. Impacts of the MODDRFS-SNOW17 MAT adjustment method on snowmelt-driven streamflow prediction varied spatially and with characteristics of the dust deposition events. The largest improvements occurred in southwestern Colorado, in years with intense dust deposition events. Application of the method in other regions of Colorado and in "low dust" years resulted in minimal impact. The MODDRFS-SNOW17 MAT technique will be implemented in CBRFC operations in late 2015, prior to spring 2016 runoff. Collaborative investigation of remote sensing-based adjustment methods for the CBRFC operational hydrologic forecasting environment will continue over the next several years.
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Ground-Water Occurrence and Contribution to Streamflow, Northeast Maui, Hawaii
Gingerich, Stephen B.
1999-01-01
The study area lies on the northern flank of the East Maui Volcano (Haleakala) and covers about 129 square miles between the drainage basins of Maliko Gulch to the west and Makapipi Stream to the east. About 989 million gallons per day of rainfall and 176 million gallons per day of fog drip reaches the study area and about 529 million gallons per day enters the ground-water system as recharge. Average annual ground-water withdrawal from wells totals only about 3 million gallons per day; proposed (as of 1998) additional withdrawals total about 18 million gallons per day. Additionally, tunnels and ditches of an extensive irrigation network directly intercept at least 10 million gallons per day of ground water. The total amount of average annual streamflow in gaged stream subbasins upstream of 1,300 feet altitude is about 255 million gallons per day and the total amount of average annual base flow is about 62 million gallons per day. Six major surface-water diversion systems in the study area have diverted an average of 163 million gallons per day of streamflow (including nearly all base flow of diverted streams) for irrigation and domestic supply in central Maui during 1925-97. Fresh ground water is found in two main forms. West of Keanae Valley, ground-water flow appears to be dominated by a variably saturated system. A saturated zone in the uppermost rock unit, the Kula Volcanics, is separated from a freshwater lens near sea level by an unsaturated zone in the underlying Honomanu Basalt. East of Keanae Valley, the ground-water system appears to be fully saturated above sea level to altitudes greater than 2,000 feet. The total average annual streamflow of gaged streams west of Keanae Valley is about 140 million gallons per day at 1,200 feet to 1,300 feet altitude. It is not possible to estimate the total average annual streamflow at the coast. All of the base flow measured in the study area west of Keanae Valley represents ground-water discharge from the high
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McKean, Sarah E.; Anderholm, Scott K.
2014-01-01
The Albuquerque Bernalillo County Water Utility Authority supplements the municipal water supply for the Albuquerque metropolitan area, in central New Mexico, with surface water diverted from the Rio Grande. The U.S. Geological Survey, in cooperation with the Albuquerque Bernalillo County Water Utility Authority, undertook this study in which water-chemistry data and historical streamflow were compiled and new water-chemistry data were collected to characterize the water chemistry and streamflow of the San Juan-Chama Project (SJCP). Characterization of streamflow included analysis of the variability of annual streamflow and comparison of the theoretical amount of water that could have been diverted into the SJCP to the actual amount of water that was diverted for the SJCP. Additionally, a seepage investigation was conducted along the channel between Azotea Tunnel Outlet and the streamflow-gaging station at Willow Creek above Heron Reservoir to estimate the magnitude of the gain or loss in streamflow resulting from groundwater interaction over the approximately 10-mile reach. Generally, surface-water chemistry varied with streamflow throughout the year. Streamflow ranged from high flow to low flow on the basis of the quantity of water diverted from the Rio Blanco, Little Navajo River, and Navajo River for the SJCP. Vertical profiles of the water temperature over the depth of the water column at Heron Reservoir indicated that the reservoir is seasonally stratified. The results from the seepage investigations indicated a small amount of loss of streamflow along the channel. Annual variability in streamflow for the SJCP was an indication of the variation in the climate parameters that interact to contribute to streamflow in the Rio Blanco, Little Navajo River, Navajo River, and Willow Creek watersheds. For most years, streamflow at Azotea Tunnel Outlet started in March and continued for approximately 3 months until the middle of July. The majority of annual streamflow
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Streamflow variability and optimal capacity of run-of-river hydropower plants
Basso, S.; Botter, G.
2012-10-01
The identification of the capacity of a run-of-river plant which allows for the optimal utilization of the available water resources is a challenging task, mainly because of the inherent temporal variability of river flows. This paper proposes an analytical framework to describe the energy production and the economic profitability of small run-of-river power plants on the basis of the underlying streamflow regime. We provide analytical expressions for the capacity which maximize the produced energy as a function of the underlying flow duration curve and minimum environmental flow requirements downstream of the plant intake. Similar analytical expressions are derived for the capacity which maximize the economic return deriving from construction and operation of a new plant. The analytical approach is applied to a minihydro plant recently proposed in a small Alpine catchment in northeastern Italy, evidencing the potential of the method as a flexible and simple design tool for practical application. The analytical model provides useful insight on the major hydrologic and economic controls (e.g., streamflow variability, energy price, costs) on the optimal plant capacity and helps in identifying policy strategies to reduce the current gap between the economic and energy optimizations of run-of-river plants.
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A broad view of model validation
International Nuclear Information System (INIS)
Tsang, C.F.
1989-10-01
The safety assessment of a nuclear waste repository requires the use of models. Such models need to be validated to ensure, as much as possible, that they are a good representation of the actual processes occurring in the real system. In this paper we attempt to take a broad view by reviewing step by step the modeling process and bringing out the need to validating every step of this process. This model validation includes not only comparison of modeling results with data from selected experiments, but also evaluation of procedures for the construction of conceptual models and calculational models as well as methodologies for studying data and parameter correlation. The need for advancing basic scientific knowledge in related fields, for multiple assessment groups, and for presenting our modeling efforts in open literature to public scrutiny is also emphasized. 16 refs
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Li, Qiang; Wei, Xiaohua; Zhang, Mingfang; Liu, Wenfei; Giles-Hansen, Krysta; Wang, Yi
2018-02-01
Assessing how forest disturbance and climate variability affect streamflow components is critical for watershed management, ecosystem protection, and engineering design. Previous studies have mainly evaluated the effects of forest disturbance on total streamflow, rarely with attention given to its components (e.g., base flow and surface runoff), particularly in large watersheds (>1000 km2). In this study, the Upper Similkameen River watershed (1810 km2), an international watershed situated between Canada and the USA, was selected to examine how forest disturbance and climate variability interactively affect total streamflow, baseflow, and surface runoff. Baseflow was separated using a combination of the recursive digital filter method and conductivity mass balance method. Time series analysis and modified double mass curves were then employed to quantitatively separate the relative contributions of forest disturbance and climate variability to each streamflow component. Our results showed that average annual baseflow and baseflow index (baseflow/streamflow) were 113.3 ± 35.6 mm year-1 and 0.27 for 1954-2013, respectively. Forest disturbance increased annual streamflow, baseflow, and surface runoff of 27.7 ± 13.7 mm, 7.4 ± 3.6 mm, and 18.4 ± 12.9 mm, respectively, with its relative contributions to the changes in respective streamflow components being 27.0 ± 23.0%, 29.2 ± 23.1%, and 25.7 ± 23.4%, respectively. In contrast, climate variability decreased them by 74.9 ± 13.7 mm, 17.9 ± 3.6 mm, and 53.3 ± 12.9 mm, respectively, with its relative contributions to the changes in respective streamflow components being 73.0 ± 23.0%, 70.8 ± 23.1% and 73.1 ± 23.4%, respectively. Despite working in opposite ways, the impacts of climate variability on annual streamflow, baseflow, and surface runoff were of a much greater magnitude than forest disturbance impacts. This study has important implications for the protection of aquatic habitat, engineering design, and
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Winter cyclone frequency and following freshet streamflow formation on the rivers in Belarus
Partasenok, Irina S.; Groisman, Pavel Ya; Chekan, Grigoriy S.; Melnik, Viktor I.
2014-09-01
We studied long-term fluctuations of streamflow and occurrence of extreme phenomena on the rivers of Belarus during the post-World War II period. It was found that formation of annual runoff within the nation has no constant tendencies and varies from year to year. At the same time, analysis of intra-annual distribution of streamflow reveals significant changes since the 1970s, first of all, increase of winter and decrease of spring streamflow. As a result, the frequency of extreme floods has decreased. These changes in water regime are associated with climatic anomalies (increase of the surface air temperatures) caused by large-scale alterations in atmospheric circulation, specifically in trajectories of cyclones. During the last two decades, the frequency of Atlantic and southern cyclones has changed and caused decreasing of cold season storms and extreme phenomena on the rivers.
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Directory of Open Access Journals (Sweden)
Farshad Fathian
2017-02-01
Full Text Available Introduction: Time series models are one of the most important tools for investigating and modeling hydrological processes in order to solve problems related to water resources management. Many hydrological time series shows nonstationary and nonlinear behaviors. One of the important hydrological modeling tasks is determining the existence of nonstationarity and the way through which we can access the stationarity accordingly. On the other hand, streamflow processes are usually considered as nonlinear mechanisms while in many studies linear time series models are used to model streamflow time series. However, it is not clear what kind of nonlinearity is acting underlying the streamflowprocesses and how intensive it is. Materials and Methods: Streamflow time series of 6 hydro-gauge stations located in the upstream basin rivers of ZarrinehRoud dam (located in the southern part of Urmia Lake basin have been considered to investigate stationarity and nonlinearity. All data series used here to startfrom January 1, 1997, and end on December 31, 2011. In this study, stationarity is tested by ADF and KPSS tests and nonlinearity is tested by BDS, Keenan and TLRT tests. The stationarity test is carried out with two methods. Thefirst one method is the augmented Dickey-Fuller (ADF unit root test first proposed by Dickey and Fuller (1979 and modified by Said and Dickey (1984, which examinsthe presence of unit roots in time series.The second onemethod is KPSS test, proposed by Kwiatkowski et al. (1992, which examinesthestationarity around a deterministic trend (trend stationarity and the stationarity around a fixed level (level stationarity. The BDS test (Brock et al., 1996 is a nonparametric method for testing the serial independence and nonlinear structure in time series based on the correlation integral of the series. The null hypothesis is the time series sample comes from an independent identically distributed (i.i.d. process. The alternative hypothesis
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Model performance analysis and model validation in logistic regression
Directory of Open Access Journals (Sweden)
Rosa Arboretti Giancristofaro
2007-10-01
Full Text Available In this paper a new model validation procedure for a logistic regression model is presented. At first, we illustrate a brief review of different techniques of model validation. Next, we define a number of properties required for a model to be considered "good", and a number of quantitative performance measures. Lastly, we describe a methodology for the assessment of the performance of a given model by using an example taken from a management study.
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Multidecadal change in streamflow associated with anthropogenic disturbances in the tropical Andes
Molina, A.; Vanacker, V.; Brisson, E.; Mora, D.; Balthazar, V.
2015-10-01
Andean headwater catchments are an important source of freshwater for downstream water users. However, few long-term studies exist on the relative importance of climate change and direct anthropogenic perturbations on flow regimes in these catchments. In this paper, we assess change in streamflow based on long time series of hydrometeorological data (1974-2008) and land cover reconstructions (1963-2009) in the Pangor catchment (282 km2) located in the tropical Andes. Three main land cover change trajectories can be distinguished during the period 1963-2009: (1) expansion of agricultural land by an area equal to 14 % of the catchment area (or 39 km2) in 46 years' time, (2) deforestation of native forests by 11 % (or -31 km2) corresponding to a mean rate of 67 ha yr-1, and (3) afforestation with exotic species in recent years by about 5 % (or 15 km2). Over the time period 1963-2009, about 50 % of the 64 km2 of native forests was cleared and converted to agricultural land. Given the strong temporal variability of precipitation and streamflow data related to El Niño-Southern Oscillation, we use empirical mode decomposition techniques to detrend the time series. The long-term increasing trend in rainfall is remarkably different from the observed changes in streamflow, which exhibit a decreasing trend. Hence, observed changes in streamflow are not the result of long-term change in precipitation but very likely result from anthropogenic disturbances associated with land cover change.
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Establishing model credibility involves more than validation
International Nuclear Information System (INIS)
Kirchner, T.
1991-01-01
One widely used definition of validation is that the quantitative test of the performance of a model through the comparison of model predictions to independent sets of observations from the system being simulated. The ability to show that the model predictions compare well with observations is often thought to be the most rigorous test that can be used to establish credibility for a model in the scientific community. However, such tests are only part of the process used to establish credibility, and in some cases may be either unnecessary or misleading. Naylor and Finger extended the concept of validation to include the establishment of validity for the postulates embodied in the model and the test of assumptions used to select postulates for the model. Validity of postulates is established through concurrence by experts in the field of study that the mathematical or conceptual model contains the structural components and mathematical relationships necessary to adequately represent the system with respect to the goals for the model. This extended definition of validation provides for consideration of the structure of the model, not just its performance, in establishing credibility. Evaluation of a simulation model should establish the correctness of the code and the efficacy of the model within its domain of applicability. (24 refs., 6 figs.)
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Yeates, E.; Dreaper, G.; Afshari, S.; Tavakoly, A. A.
2017-12-01
Over the past six fiscal years, the United States Army Corps of Engineers (USACE) has contracted an average of about a billion dollars per year for navigation channel dredging. To execute these funds effectively, USACE Districts must determine which navigation channels need to be dredged in a given year. Improving this prioritization process results in more efficient waterway maintenance. This study uses the Streamflow Prediction Tool, a runoff routing model based on global weather forecast ensembles, to estimate dredged volumes. This study establishes regional linear relationships between cumulative flow and dredged volumes over a long-term simulation covering 30 years (1985-2015), using drainage area and shoaling parameters. The study framework integrates the National Hydrography Dataset (NHDPlus Dataset) with parameters from the Corps Shoaling Analysis Tool (CSAT) and dredging record data from USACE District records. Results in the test cases of the Houston Ship Channel and the Sabine and Port Arthur Harbor waterways in Texas indicate positive correlation between the simulated streamflows and actual dredging records.
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Analysis of streamflow variability in Alpine catchments at multiple spatial and temporal scales
Pérez Ciria, T.; Chiogna, G.
2017-12-01
Alpine watersheds play a pivotal role in Europe for water provisioning and for hydropower production. In these catchments, temporal fluctuations of river discharge occur at multiple temporal scales due to natural as well as anthropogenic driving forces. In the last decades, modifications of the flow regime have been observed and their origin lies in the complex interplay between construction of dams for hydro power production, changes in water management policies and climatic changes. The alteration of the natural flow has negative impacts on the freshwater biodiversity and threatens the ecosystem integrity of the Alpine region. Therefore, understanding the temporal and spatial variability of river discharge has recently become a particular concern for environmental protection and represents a crucial contribution to achieve sustainable water resources management in the Alps. In this work, time series analysis is conducted for selected gauging stations in the Inn and the Adige catchments, which cover a large part of the central and eastern region of the Alps. We analyze the available time series using the continuous wavelet transform and change-point analyses for determining how and where changes have taken place. Although both catchments belong to different climatic zones of the Greater Alpine Region, streamflow properties share some similar characteristics. The comparison of the collected streamflow time series in the two catchments permits detecting gradients in the hydrological system dynamics that depend on station elevation, longitudinal location in the Alps and catchment area. This work evidences that human activities (e.g., water management practices and flood protection measures, changes in legislation and market regulation) have major impacts on streamflow and should be rigorously considered in hydrological models.
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Towards policy relevant environmental modeling: contextual validity and pragmatic models
Miles, Scott B.
2000-01-01
"What makes for a good model?" In various forms, this question is a question that, undoubtedly, many people, businesses, and institutions ponder with regards to their particular domain of modeling. One particular domain that is wrestling with this question is the multidisciplinary field of environmental modeling. Examples of environmental models range from models of contaminated ground water flow to the economic impact of natural disasters, such as earthquakes. One of the distinguishing claims of the field is the relevancy of environmental modeling to policy and environment-related decision-making in general. A pervasive view by both scientists and decision-makers is that a "good" model is one that is an accurate predictor. Thus, determining whether a model is "accurate" or "correct" is done by comparing model output to empirical observations. The expected outcome of this process, usually referred to as "validation" or "ground truthing," is a stamp on the model in question of "valid" or "not valid" that serves to indicate whether or not the model will be reliable before it is put into service in a decision-making context. In this paper, I begin by elaborating on the prevailing view of model validation and why this view must change. Drawing from concepts coming out of the studies of science and technology, I go on to propose a contextual view of validity that can overcome the problems associated with "ground truthing" models as an indicator of model goodness. The problem of how we talk about and determine model validity has much to do about how we perceive the utility of environmental models. In the remainder of the paper, I argue that we should adopt ideas of pragmatism in judging what makes for a good model and, in turn, developing good models. From such a perspective of model goodness, good environmental models should facilitate communication, convey—not bury or "eliminate"—uncertainties, and, thus, afford the active building of consensus decisions, instead
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Rice, Joshua S.; Emanuel, Ryan E.
2017-05-01
Understanding the factors that influence how global climate phenomena, such as the El-Nino Southern Oscillation (ENSO), affect streamflow behavior is an important area of research in the hydrologic sciences. While large-scale patterns in ENSO-streamflow relationships have been thoroughly studied, and are relatively well-understood, information is scarce concerning factors that affect variation in ENSO responses from one watershed to another. To this end, we examined relationships between variability in ENSO activity and streamflow for 2731 watersheds across the conterminous U.S. from 1970 to 2014 using a novel approach to account for the intermediary role of precipitation. We applied an ensemble of regression techniques to describe relationships between variability in ENSO activity and streamflow as a function of watershed characteristics including: hydroclimate, topography, geomorphology, geographic location, land cover, soil characteristics, bedrock geology, and anthropogenic influences. We found that variability in watershed scale ENSO-streamflow relationships was strongly related to factors including: precipitation timing and phase, forest cover, and interactions between watershed topography and geomorphology. These, and other influential factors, share in common the ability to affect the partitioning and movement of water within watersheds. Our results demonstrate that the conceptualization of watersheds as signal filters for hydroclimate inputs, commonly applied to short-term rainfall-runoff responses, also applies to long-term hydrologic responses to sources of recurrent climate variability. These results also show that watershed processes, which are typically studied at relatively fine spatial scales, are also critical for understanding continental scale hydrologic responses to global climate.
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Tree-ring reconstruction of streamflow in the Snare River Basin, Northwest Territories, Canada
Martin, J. P.; Pisaric, M. F.
2017-12-01
Drought is a component of many ecosystems in North America causing environmental and socioeconomical impacts. In the ongoing context of climatic and environmental changes, drought-related issues are becoming problematic in northern Canada, which have not been associated with drought-like conditions in the past. Dryer than average conditions threatens the energy security of northern canadian communities, since this region relies on the production of hydroelectricity as an energy source. In the North Slave Region of Northwest Territory (NWT), water levels and streamflows were significantly lower in 2014/2015. The Government of the NWT had to spend nearly $50 million to purchase diesel fuel to generate enough electricity to supplement the reduced power generation of the Snare River hydroelectric system, hence the need to better understand the multi-decadal variability in streamflow. The aims of this presentation are i) to present jack pine and white spruce tree-ring chronologies of Southern NWT; ii) to reconstruct past streamflow of the Snare River Basin; iii) to evaluate the frequency and magnitude of extreme drought conditions, and iv) to identify which large-scale atmospheric or oceanic patterns are teleconnected to regional hydraulic conditions. Preliminary results show that the growth of jack pine and white spruce populations is better correlated with precipitation and temperature, respectively, than hydraulic conditions. Nonetheless, we present a robust streamflow reconstruction of the Snare River that is well correlated with the summer North Atlantic Oscillation (NAO) index, albeit the strength of the correlation is non-stationary. Spectral analysis corroborate the synchronicity between negative NAO conditions and drought conditions. From an operational standpoint, considering that the general occurrence of positive/negative NAO can be predicted, it the hope of the authors that these results can facilitate energetic planning in the Northwest Territories through
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Eng, K.; Kiang, J.E.; Chen, Y.-Y.; Carlisle, D.M.; Granato, G.E.
2011-01-01
Low-flow characteristics can be estimated by multiple linear regressions or the index-streamgage approach. The latter transfers streamflow information from a hydrologically similar, continuously gaged basin ('index streamgage') to one with a very limited streamflow record, but often results in biased estimates. The application of the index-streamgage approach can be generalized into three steps: (1) selection of streamflow information of interest, (2) definition of hydrologic similarity and selection of index streamgage, and (3) application of an information-transfer approach. Here, we explore the effects of (1) the range of streamflow values, (2) the areal density of streamgages, and (3) index-streamgage selection criteria on the bias of three information-transfer approaches on estimates of the 7-day, 10-year minimum streamflow (Q7, 10). The three information-transfer approaches considered are maintenance of variance extension, base-flow correlation, and ratio of measured to concurrent gaged streamflow (Q-ratio invariance). Our results for 1120 streamgages throughout the United States suggest that only a small portion of the total bias in estimated streamflow values is explained by the areal density of the streamgages and the hydrologic similarity between the two basins. However, restricting the range of streamflow values used in the index-streamgage approach reduces the bias of estimated Q7, 10 values substantially. Importantly, estimated Q7, 10 values are heavily biased when the observed Q7, 10 values are near zero. Results of the analysis also showed that Q7, 10 estimates from two of the three index-streamgage approaches have lower root-mean-square error values than estimates derived from multiple regressions for the large regions considered in this study.
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Saxe, Samuel; Hogue, Terri S.; Hay, Lauren
2018-02-01
This research investigates the impact of wildfires on watershed flow regimes, specifically focusing on evaluation of fire events within specified hydroclimatic regions in the western United States, and evaluating the impact of climate and geophysical variables on response. Eighty-two watersheds were identified with at least 10 years of continuous pre-fire daily streamflow records and 5 years of continuous post-fire daily flow records. Percent change in annual runoff ratio, low flows, high flows, peak flows, number of zero flow days, baseflow index, and Richards-Baker flashiness index were calculated for each watershed using pre- and post-fire periods. Independent variables were identified for each watershed and fire event, including topographic, vegetation, climate, burn severity, percent area burned, and soils data. Results show that low flows, high flows, and peak flows increase in the first 2 years following a wildfire and decrease over time. Relative response was used to scale response variables with the respective percent area of watershed burned in order to compare regional differences in watershed response. To account for variability in precipitation events, runoff ratio was used to compare runoff directly to PRISM precipitation estimates. To account for regional differences in climate patterns, watersheds were divided into nine regions, or clusters, through k-means clustering using climate data, and regression models were produced for watersheds grouped by total area burned. Watersheds in Cluster 9 (eastern California, western Nevada, Oregon) demonstrate a small negative response to observed flow regimes after fire. Cluster 8 watersheds (coastal California) display the greatest flow responses, typically within the first year following wildfire. Most other watersheds show a positive mean relative response. In addition, simple regression models show low correlation between percent watershed burned and streamflow response, implying that other watershed factors
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Statistical validation of normal tissue complication probability models.
Xu, Cheng-Jian; van der Schaaf, Arjen; Van't Veld, Aart A; Langendijk, Johannes A; Schilstra, Cornelis
2012-09-01
To investigate the applicability and value of double cross-validation and permutation tests as established statistical approaches in the validation of normal tissue complication probability (NTCP) models. A penalized regression method, LASSO (least absolute shrinkage and selection operator), was used to build NTCP models for xerostomia after radiation therapy treatment of head-and-neck cancer. Model assessment was based on the likelihood function and the area under the receiver operating characteristic curve. Repeated double cross-validation showed the uncertainty and instability of the NTCP models and indicated that the statistical significance of model performance can be obtained by permutation testing. Repeated double cross-validation and permutation tests are recommended to validate NTCP models before clinical use. Copyright © 2012 Elsevier Inc. All rights reserved.
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Statistical Validation of Normal Tissue Complication Probability Models
Energy Technology Data Exchange (ETDEWEB)
Xu Chengjian, E-mail: c.j.xu@umcg.nl [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands); Schaaf, Arjen van der; Veld, Aart A. van' t; Langendijk, Johannes A. [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands); Schilstra, Cornelis [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands); Radiotherapy Institute Friesland, Leeuwarden (Netherlands)
2012-09-01
Purpose: To investigate the applicability and value of double cross-validation and permutation tests as established statistical approaches in the validation of normal tissue complication probability (NTCP) models. Methods and Materials: A penalized regression method, LASSO (least absolute shrinkage and selection operator), was used to build NTCP models for xerostomia after radiation therapy treatment of head-and-neck cancer. Model assessment was based on the likelihood function and the area under the receiver operating characteristic curve. Results: Repeated double cross-validation showed the uncertainty and instability of the NTCP models and indicated that the statistical significance of model performance can be obtained by permutation testing. Conclusion: Repeated double cross-validation and permutation tests are recommended to validate NTCP models before clinical use.
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National Research Council Canada - National Science Library
Kuhn, Gerhard
2003-01-01
The U.S Geological Survey, in cooperation with the Grand Mesa, Uncompahgre, and Gunnison National Forests, began a study in 2000 to develop selected streamflow characteristics for 60 streamflow-gaging...
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Climate and Land Use Changes on Streamflow and Subsurface Recharge in the Fluvià Basin, Spain
Directory of Open Access Journals (Sweden)
Lucila Candela
2016-05-01
Full Text Available Climate change impact on water resources (streamflow and deep natural recharge based on the downscaled outputs from the ECHAM5 general circulation model (GCM has been investigated in the Mediterranean basin (Fluvià, Spain for the A2, B1 greenhouse scenarios and 2000–2024/2025–2050 time slices. The HEC-HMS 3.4 rainfall-runoff numerical model was the basic tool used to generate streamflow for the historical period, and deep natural recharge was calculated from Visual-BALAN 2.0, a water-soil-plant distributed model. The hydrologic and recharge models were employed to generate future climate change hydrographs and the deep recharge amount. Furthermore, the selected future climate scenarios, subject to possible changes in the land use/land cover forecast, were integrated into the models, and water resource impacts were assessed. The multiple combinations of climate model, time slices, greenhouse scenarios, land use/land cover scenarios and hydrological estimation methods resulted in six scenarios. The obtained results estimate an increase in temperature (1.5 °C, a decline in precipitation (17% and a maximum decrease of 49.5% and 16.8% in runoff and groundwater recharge, respectively, for 2050 (A2 compared to the historical values. Planned land cover scenarios, implying small changes of agricultural and forested land, show no major contribution to future water resource changes. According to the results, the most sensitive parameters conditioning future water resources are changes in temperature and precipitation.
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Asquith, William H.; Kiang, Julie E.; Cohn, Timothy A.
2017-07-17
log-normal, generalized Pareto, and Weibull. Uncertainties in streamflow estimates for corresponding AEP are depicted and quantified as two primary forms: quantile (aleatoric [random sampling] uncertainty) and distribution-choice (epistemic [model] uncertainty). Sampling uncertainties of a given distribution are relatively straightforward to compute from analytical or Monte Carlo-based approaches. Distribution-choice uncertainty stems from choices of potentially applicable probability distributions for which divergence among the choices increases as AEP decreases. Conventional goodness-of-fit statistics, such as Cramér-von Mises, and L-moment ratio diagrams are demonstrated in order to hone distribution choice. The results generally show that distribution choice uncertainty is larger than sampling uncertainty for very low AEP values.
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Validation process of simulation model
International Nuclear Information System (INIS)
San Isidro, M. J.
1998-01-01
It is presented a methodology on empirical validation about any detailed simulation model. This king of validation it is always related with an experimental case. The empirical validation has a residual sense, because the conclusions are based on comparisons between simulated outputs and experimental measurements. This methodology will guide us to detect the fails of the simulation model. Furthermore, it can be used a guide in the design of posterior experiments. Three steps can be well differentiated: Sensitivity analysis. It can be made with a DSA, differential sensitivity analysis, and with a MCSA, Monte-Carlo sensitivity analysis. Looking the optimal domains of the input parameters. It has been developed a procedure based on the Monte-Carlo methods and Cluster techniques, to find the optimal domains of these parameters. Residual analysis. This analysis has been made on the time domain and on the frequency domain, it has been used the correlation analysis and spectral analysis. As application of this methodology, it is presented the validation carried out on a thermal simulation model on buildings, Esp., studying the behavior of building components on a Test Cell of LECE of CIEMAT. (Author) 17 refs
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Jamaludin, Suhaila
2017-05-01
Extreme rainfall events such as floods and prolonged dry spells have become common phenomena in tropical countries like Malaysia. Floods are regular natural disasters in Malaysia, and happen nearly every year during the monsoon season. Recently, the magnitude of streamflow seems to have altered frequently, both spatially and temporally. Therefore, in order to have effective planning and an efficient water management system, it is advisable that streamflow data are analysed continuously over a period of time. If the data are treated as a set of functions rather than as a set of discrete values, then this ensures that they are not restricted by physical time. In addition, the derivatives of the functions may themselves be treated as functional data, which provides new information. The objective of this study is to develop a functional framework for hydrological applications using streamflow as the functional data. The daily flow series from the Kelantan River Basin were used as the main input in this study. Seven streamflow stations were employed in the analysis. Classification between the stations was done using the functional principal component, which was based on the results of the factor scores. The results indicated that two stations, namely the Kelantan River (Guillemard Bridge) and the Galas River, have a different flow pattern from the other streamflow stations. The flow curves of these two rivers are considered as the extreme curves because of their different magnitude and shape.
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Ladd, David E.; Law, George S.
2007-01-01
The U.S. Geological Survey (USGS) provides streamflow and other stream-related information needed to protect people and property from floods, to plan and manage water resources, and to protect water quality in the streams. Streamflow statistics provided by the USGS, such as the 100-year flood and the 7-day 10-year low flow, frequently are used by engineers, land managers, biologists, and many others to help guide decisions in their everyday work. In addition to streamflow statistics, resource managers often need to know the physical and climatic characteristics (basin characteristics) of the drainage basins for locations of interest to help them understand the mechanisms that control water availability and water quality at these locations. StreamStats is a Web-enabled geographic information system (GIS) application that makes it easy for users to obtain streamflow statistics, basin characteristics, and other information for USGS data-collection stations and for ungaged sites of interest. If a user selects the location of a data-collection station, StreamStats will provide previously published information for the station from a database. If a user selects a location where no data are available (an ungaged site), StreamStats will run a GIS program to delineate a drainage basin boundary, measure basin characteristics, and estimate streamflow statistics based on USGS streamflow prediction methods. A user can download a GIS feature class of the drainage basin boundary with attributes including the measured basin characteristics and streamflow estimates.
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Benchmarking ensemble streamflow prediction skill in the UK
Harrigan, Shaun; Prudhomme, Christel; Parry, Simon; Smith, Katie; Tanguy, Maliko
2018-03-01
Skilful hydrological forecasts at sub-seasonal to seasonal lead times would be extremely beneficial for decision-making in water resources management, hydropower operations, and agriculture, especially during drought conditions. Ensemble streamflow prediction (ESP) is a well-established method for generating an ensemble of streamflow forecasts in the absence of skilful future meteorological predictions, instead using initial hydrologic conditions (IHCs), such as soil moisture, groundwater, and snow, as the source of skill. We benchmark when and where the ESP method is skilful across a diverse sample of 314 catchments in the UK and explore the relationship between catchment storage and ESP skill. The GR4J hydrological model was forced with historic climate sequences to produce a 51-member ensemble of streamflow hindcasts. We evaluated forecast skill seamlessly from lead times of 1 day to 12 months initialized at the first of each month over a 50-year hindcast period from 1965 to 2015. Results showed ESP was skilful against a climatology benchmark forecast in the majority of catchments across all lead times up to a year ahead, but the degree of skill was strongly conditional on lead time, forecast initialization month, and individual catchment location and storage properties. UK-wide mean ESP skill decayed exponentially as a function of lead time with continuous ranked probability skill scores across the year of 0.75, 0.20, and 0.11 for 1-day, 1-month, and 3-month lead times, respectively. However, skill was not uniform across all initialization months. For lead times up to 1 month, ESP skill was higher than average when initialized in summer and lower in winter months, whereas for longer seasonal and annual lead times skill was higher when initialized in autumn and winter months and lowest in spring. ESP was most skilful in the south and east of the UK, where slower responding catchments with higher soil moisture and groundwater storage are mainly located
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A proposed best practice model validation framework for banks
Directory of Open Access Journals (Sweden)
Pieter J. (Riaan de Jongh
2017-06-01
Full Text Available Background: With the increasing use of complex quantitative models in applications throughout the financial world, model risk has become a major concern. The credit crisis of 2008–2009 provoked added concern about the use of models in finance. Measuring and managing model risk has subsequently come under scrutiny from regulators, supervisors, banks and other financial institutions. Regulatory guidance indicates that meticulous monitoring of all phases of model development and implementation is required to mitigate this risk. Considerable resources must be mobilised for this purpose. The exercise must embrace model development, assembly, implementation, validation and effective governance. Setting: Model validation practices are generally patchy, disparate and sometimes contradictory, and although the Basel Accord and some regulatory authorities have attempted to establish guiding principles, no definite set of global standards exists. Aim: Assessing the available literature for the best validation practices. Methods: This comprehensive literature study provided a background to the complexities of effective model management and focussed on model validation as a component of model risk management. Results: We propose a coherent ‘best practice’ framework for model validation. Scorecard tools are also presented to evaluate if the proposed best practice model validation framework has been adequately assembled and implemented. Conclusion: The proposed best practice model validation framework is designed to assist firms in the construction of an effective, robust and fully compliant model validation programme and comprises three principal elements: model validation governance, policy and process.
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Rainfall-runoff model for prediction of waterborne viral contamination in a small river catchment
Gelati, E.; Dommar, C.; Lowe, R.; Polcher, J.; Rodó, X.
2013-12-01
We present a lumped rainfall-runoff model aimed at providing useful information for the prediction of waterborne viral contamination in small rivers. Viral contamination of water bodies may occur because of the discharge of sewage effluents and of surface runoff over areas affected by animal waste loads. Surface runoff is caused by precipitation that cannot infiltrate due to its intensity and to antecedent soil water content. It may transport animal feces to adjacent water bodies and cause viral contamination. We model streamflow by separating it into two components: subsurface flow, which is produced by infiltrated precipitation; and surface runoff. The model estimates infiltrated and non-infiltrated precipitation and uses impulse-response functions to compute the corresponding fractions of streamflow. The developed methodologies are applied to the Glafkos river, whose catchment extends for 102 km2 and includes the city of Patra. Streamflow and precipitation observations are available at a daily time resolution. Waterborne virus concentration measurements were performed approximately every second week from the beginning of 2011 to mid 2012. Samples were taken at several locations: in river water upstream of Patras and in the urban area; in sea water at the river outlet and approximately 2 km south-west of Patras; in sewage effluents before and after treatment. The rainfall-runoff model was calibrated and validated using observed streamflow and precipitation data. The model contribution to waterborne viral contamination prediction was benchmarked by analyzing the virus concentration measurements together with the estimated surface runoff values. The presented methodology may be a first step towards the development of waterborne viral contamination alert systems. Predicting viral contamination of water bodies would benefit sectors such as water supply and tourism.
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Lu, Mengqian; Lall, Upmanu; Robertson, Andrew W.; Cook, Edward
2017-03-01
Streamflow forecasts at multiple time scales provide a new opportunity for reservoir management to address competing objectives. Market instruments such as forward contracts with specified reliability are considered as a tool that may help address the perceived risk associated with the use of such forecasts in lieu of traditional operation and allocation strategies. A water allocation process that enables multiple contracts for water supply and hydropower production with different durations, while maintaining a prescribed level of flood risk reduction, is presented. The allocation process is supported by an optimization model that considers multitime scale ensemble forecasts of monthly streamflow and flood volume over the upcoming season and year, the desired reliability and pricing of proposed contracts for hydropower and water supply. It solves for the size of contracts at each reliability level that can be allocated for each future period, while meeting target end of period reservoir storage with a prescribed reliability. The contracts may be insurable, given that their reliability is verified through retrospective modeling. The process can allow reservoir operators to overcome their concerns as to the appropriate skill of probabilistic forecasts, while providing water users with short-term and long-term guarantees as to how much water or energy they may be allocated. An application of the optimization model to the Bhakra Dam, India, provides an illustration of the process. The issues of forecast skill and contract performance are examined. A field engagement of the idea is useful to develop a real-world perspective and needs a suitable institutional environment.
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Altered stream-flow regimes and invasive plant species: The Tamarix case
Stromberg, J.C.; Lite, S.J.; Marler, R.; Paradzick, C.; Shafroth, P.B.; Shorrock, D.; White, J.M.; White, M.S.
2007-01-01
Aim: To test the hypothesis that anthropogenic alteration of stream-flow regimes is a key driver of compositional shifts from native to introduced riparian plant species. Location: The arid south-western United States; 24 river reaches in the Gila and Lower Colorado drainage basins of Arizona. Methods: We compared the abundance of three dominant woody riparian taxa (native Populus fremontii and Salix gooddingii, and introduced Tamarix) between river reaches that varied in stream-flow permanence (perennial vs. intermittent), presence or absence of an upstream flow-regulating dam, and presence or absence of municipal effluent as a stream water source. Results: Populus and Salix were the dominant pioneer trees along the reaches with perennial flow and a natural flood regime. In contrast, Tamarix had high abundance (patch area and basal area) along reaches with intermittent stream flows (caused by natural and cultural factors), as well as those with dam-regulated flows. Main conclusions: Stream-flow regimes are strong determinants of riparian vegetation structure, and hydrological alterations can drive dominance shifts to introduced species that have an adaptive suite of traits. Deep alluvial groundwater on intermittent rivers favours the deep-rooted, stress-adapted Tamarix over the shallower-rooted and more competitive Populus and Salix. On flow-regulated rivers, shifts in flood timing favour the reproductively opportunistic Tamarix over Populus and Salix, both of which have narrow germination windows. The prevailing hydrological conditions thus favour a new dominant pioneer species in the riparian corridors of the American Southwest. These results reaffirm the importance of reinstating stream-flow regimes (inclusive of groundwater flows) for re-establishing the native pioneer trees as the dominant forest type. ?? 2007 The Authors Journal compilation ?? 2007 Blackwell Publishing Ltd.
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Increased evaporation following widespread tree mortality limits streamflow response
Biederman, J. A.; Harpold, A. A.; Gochis, D. J.; Ewers, B. E.; Reed, D. E.; Papuga, S. A.; Brooks, P. D.
2014-07-01
A North American epidemic of mountain pine beetle (MPB) has disturbed over 5 million ha of forest containing headwater catchments crucial to water resources. However, there are limited observations of MPB effects on partitioning of precipitation between vapor loss and streamflow, and to our knowledge these fluxes have not been observed simultaneously following disturbance. We combined eddy covariance vapor loss (V), catchment streamflow (Q), and stable isotope indicators of evaporation (E) to quantify hydrologic partitioning over 3 years in MPB-impacted and control sites. Annual control V was conservative, varying only from 573 to 623 mm, while MPB site V varied more widely from 570 to 700 mm. During wet periods, MPB site V was greater than control V in spite of similar above-canopy potential evapotranspiration (PET). During a wet year, annual MPB V was greater and annual Q was lower as compared to an average year, while in a dry year, essentially all water was partitioned to V. Ratios of 2H and 18O in stream and soil water showed no kinetic evaporation at the control site, while MPB isotope ratios fell below the local meteoric water line, indicating greater E and snowpack sublimation (Ss) counteracted reductions in transpiration (T) and sublimation of canopy-intercepted snow (Sc). Increased E was possibly driven by reduced canopy shading of shortwave radiation, which averaged 21 W m-2 during summer under control forest as compared to 66 W m-2 under MPB forest. These results show that abiotic vapor losses may limit widely expected streamflow increases.
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Directory of Open Access Journals (Sweden)
H. Wang
2017-04-01
impact on both soil flow and baseflow by compensating for reduced surface runoff, which leads to a slight increase in the streamflow in the Wei River with the mixed landscapes on the Loess Plateau that include earth–rock mountain area.
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Tian, Xin; Negenborn, Rudy R.; van Overloop, Peter-Jules; María Maestre, José; Sadowska, Anna; van de Giesen, Nick
2017-11-01
Model Predictive Control (MPC) is one of the most advanced real-time control techniques that has been widely applied to Water Resources Management (WRM). MPC can manage the water system in a holistic manner and has a flexible structure to incorporate specific elements, such as setpoints and constraints. Therefore, MPC has shown its versatile performance in many branches of WRM. Nonetheless, with the in-depth understanding of stochastic hydrology in recent studies, MPC also faces the challenge of how to cope with hydrological uncertainty in its decision-making process. A possible way to embed the uncertainty is to generate an Ensemble Forecast (EF) of hydrological variables, rather than a deterministic one. The combination of MPC and EF results in a more comprehensive approach: Multi-scenario MPC (MS-MPC). In this study, we will first assess the model performance of MS-MPC, considering an ensemble streamflow forecast. Noticeably, the computational inefficiency may be a critical obstacle that hinders applicability of MS-MPC. In fact, with more scenarios taken into account, the computational burden of solving an optimization problem in MS-MPC accordingly increases. To deal with this challenge, we propose the Adaptive Control Resolution (ACR) approach as a computationally efficient scheme to practically reduce the number of control variables in MS-MPC. In brief, the ACR approach uses a mixed-resolution control time step from the near future to the distant future. The ACR-MPC approach is tested on a real-world case study: an integrated flood control and navigation problem in the North Sea Canal of the Netherlands. Such an approach reduces the computation time by 18% and up in our case study. At the same time, the model performance of ACR-MPC remains close to that of conventional MPC.
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Statistical Validation of Engineering and Scientific Models: Background
International Nuclear Information System (INIS)
Hills, Richard G.; Trucano, Timothy G.
1999-01-01
A tutorial is presented discussing the basic issues associated with propagation of uncertainty analysis and statistical validation of engineering and scientific models. The propagation of uncertainty tutorial illustrates the use of the sensitivity method and the Monte Carlo method to evaluate the uncertainty in predictions for linear and nonlinear models. Four example applications are presented; a linear model, a model for the behavior of a damped spring-mass system, a transient thermal conduction model, and a nonlinear transient convective-diffusive model based on Burger's equation. Correlated and uncorrelated model input parameters are considered. The model validation tutorial builds on the material presented in the propagation of uncertainty tutoriaI and uses the damp spring-mass system as the example application. The validation tutorial illustrates several concepts associated with the application of statistical inference to test model predictions against experimental observations. Several validation methods are presented including error band based, multivariate, sum of squares of residuals, and optimization methods. After completion of the tutorial, a survey of statistical model validation literature is presented and recommendations for future work are made
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Fernández, Alfonso; Muñoz, Ariel; González-Reyes, Álvaro; Aguilera-Betti, Isabella; Toledo, Isadora; Puchi, Paulina; Sauchyn, David; Crespo, Sebastián; Frene, Cristian; Mundo, Ignacio; González, Mauro; Vignola, Raffaele
2018-05-01
Streamflow in south-central Chile (SCC, ˜ 37-42° S) is vital for agriculture, forestry production, hydroelectricity, and human consumption. Recent drought episodes have generated hydrological deficits with damaging effects on these activities. This region is projected to undergo major reductions in water availability, concomitant with projected increases in water demand. However, the lack of long-term records hampers the development of accurate estimations of natural variability and trends. In order to provide more information on long-term streamflow variability and trends in SCC, here we report findings of an analysis of instrumental records and a tree-ring reconstruction of the summer streamflow of the Río Imperial ( ˜ 37° 40' S-38° 50' S). This is the first reconstruction in Chile targeted at this season. Results from the instrumental streamflow record ( ˜ 1940 onwards) indicated that the hydrological regime is fundamentally pluvial with a small snowmelt contribution during spring, and evidenced a decreasing trend, both for the summer and the full annual record. The reconstruction showed that streamflow below the average characterized the post-1980 period, with more frequent, but not more intense, drought episodes. We additionally found that the recent positive phase of the Southern Annular Mode has significantly influenced streamflow. These findings agree with previous studies, suggesting a robust regional signal and a shift to a new hydrological scenario. In this paper, we also discuss implications of these results for water managers and stakeholders; we provide rationale and examples that support the need for the incorporation of tree-ring reconstructions into water resources management.
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Chen, R.; Wang, G.; Yang, Y.; Liu, J.; Han, C.; Song, Y.; Liu, Z.; Kang, E.
2018-04-01
Cryospheric changes have great effects on alpine hydrology, but these effects are still unclear owing to rare observations and suitable models in the western cold regions of China. Based on long-term field observations in the western cold regions of China, a cryospheric basin hydrological model was proposed to evaluate the cryospheric effects on streamflow in the upper Hei River basin (UHR), and the relationship between the cryosphere and streamflow was further discussed with measured data. The Norwegian Earth System Model outputs were chosen to project future streamflow under scenarios Representative Concentration Pathways (RCP)2.6, RCP4.5, and RCP8.5. The cryospheric basin hydrological model results were well validated by the measured precipitation, streamflow, evapotranspiration, soil temperature, glacier and snow cover area, and the water balance of land cover in the UHR. The moraine-talus region contributed most of the runoff (60%), even though it made up only about 20% of the area. On average, glacier and snow cover, respectively, contributed 3.5% and 25.4% of the fresh water to the streamflow in the UHR between 1960 and 2013. Because of the increased air temperature (2.9°C/54a) and precipitation (69.2 mm/54a) over the past 54 years, glacial and snowmelt runoff increased by 9.8% and 12.1%, respectively. The increase in air temperature brought forward the snowmelt flood peak and increased the winter flow due to permafrost degradation. Glaciers may disappear in the near future because of their small size, but snowmelt would increase due to increases in snowfall in the higher mountainous areas, and the basin runoff would increase slightly in the future.
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Model Validation Using Coordinate Distance with Performance Sensitivity
Directory of Open Access Journals (Sweden)
Jiann-Shiun Lew
2008-01-01
Full Text Available This paper presents an innovative approach to model validation for a structure with significant parameter variations. Model uncertainty of the structural dynamics is quantified with the use of a singular value decomposition technique to extract the principal components of parameter change, and an interval model is generated to represent the system with parameter uncertainty. The coordinate vector, corresponding to the identified principal directions, of the validation system is computed. The coordinate distance between the validation system and the identified interval model is used as a metric for model validation. A beam structure with an attached subsystem, which has significant parameter uncertainty, is used to demonstrate the proposed approach.
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Some considerations for validation of repository performance assessment models
International Nuclear Information System (INIS)
Eisenberg, N.
1991-01-01
Validation is an important aspect of the regulatory uses of performance assessment. A substantial body of literature exists indicating the manner in which validation of models is usually pursued. Because performance models for a nuclear waste repository cannot be tested over the long time periods for which the model must make predictions, the usual avenue for model validation is precluded. Further impediments to model validation include a lack of fundamental scientific theory to describe important aspects of repository performance and an inability to easily deduce the complex, intricate structures characteristic of a natural system. A successful strategy for validation must attempt to resolve these difficulties in a direct fashion. Although some procedural aspects will be important, the main reliance of validation should be on scientific substance and logical rigor. The level of validation needed will be mandated, in part, by the uses to which these models are put, rather than by the ideal of validation of a scientific theory. Because of the importance of the validation of performance assessment models, the NRC staff has engaged in a program of research and international cooperation to seek progress in this important area. 2 figs., 16 refs
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Directory of Open Access Journals (Sweden)
Jie Wang
2016-01-01
Full Text Available Located in the southeastern China and northern Vietnam, the Red River is an important international trans-boundary river that has experienced rapid deforestation and environmental changes over the past decades. We conducted attribution analysis of impacts of various environmental changes on streamflow and sediment load. The contribution of reclassified environmental changes to total change of the streamflow and sediment load was separated. Land cover change based on climate-induced and human-induced indicators were defined. We found that human-induced land cover change was the main factor affecting changes of the streamflow and sediment load. Changes of the land cover were more pronounced in the dry season than in the wet season whereas sediment load changed more in the wet season than in the dry season. In addition, changes in sediment load were mainly caused by human-induced land cover change and the changes of land cover were more influential on sediment load than on streamflow in the Red River basin.
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Controls on streamflow intermittence in the Colorado Front Range
Kampf, S. K.; Puntenney, K.; Martin, C.; Weber, R.; Gerlich, J.; Hammond, J. C.; Lefsky, M. A.
2017-12-01
Intermittent streams comprise more than 60% of the channel length in semiarid northern Colorado, yet little is known about their flow magnitude and timing. We used field surveys, stream sensors, and remote sensing to quantify spatial and temporal patterns of streamflow intermittence in the Cache la Poudre basin in 2016-2017. To evaluate potential controls on streamflow intermittence, we delineated the drainage area to each monitored point and quantified the catchment's mean precipitation, temperature, snow persistence, slope, aspect, vegetation type, soil type, and bedrock geology. During the period of study, most streams below 2500 m elevation and drainage areas >1 km2 had perennial flow, whereas nearly all streams with drainage areas <1 km2 had intermittent flow. For the high elevation intermittent streams, stream locations often differed substantially from the locations mapped in standard GIS data products. Initial analyses have identified no clearly quantifiable controls on flow duration of high elevation streams, but field observations indicate subsurface flow paths are important contributors to surface streams.
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SDG and qualitative trend based model multiple scale validation
Gao, Dong; Xu, Xin; Yin, Jianjin; Zhang, Hongyu; Zhang, Beike
2017-09-01
Verification, Validation and Accreditation (VV&A) is key technology of simulation and modelling. For the traditional model validation methods, the completeness is weak; it is carried out in one scale; it depends on human experience. The SDG (Signed Directed Graph) and qualitative trend based multiple scale validation is proposed. First the SDG model is built and qualitative trends are added to the model. And then complete testing scenarios are produced by positive inference. The multiple scale validation is carried out by comparing the testing scenarios with outputs of simulation model in different scales. Finally, the effectiveness is proved by carrying out validation for a reactor model.
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Lind, Greg D.; Stonewall, Adam J.
2018-02-13
In this study, “naturalized” daily streamflow records, created by the U.S. Army Corps of Engineers and the Bureau of Reclamation, were used to compute 1-, 3-, 7-, 10-, 15-, 30-, and 60-day annual maximum streamflow durations, which are running averages of daily streamflow for the number of days in each duration. Once the annual maximum durations were computed, the floodduration frequencies could be estimated. The estimated flood-duration frequencies correspond to the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent probabilities of their occurring or being exceeded each year. For this report, the focus was on the Willamette River Basin in Oregon, which is a subbasin of the Columbia River Basin. This study is part of a larger one encompassing the entire Columbia Basin.
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A review of methods for monitoring streamflow for sustainable water resource management
Dobriyal, Pariva; Badola, Ruchi; Tuboi, Chongpi; Hussain, Syed Ainul
2017-10-01
Monitoring of streamflow may help to determine the optimum levels of its use for sustainable water management in the face of climate change. We reviewed available methods for monitoring streamflow on the basis of six criteria viz. their applicability across different terrains and size of the streams, operational ease, time effectiveness, accuracy, environmental impact that they may cause and cost involve in it. On the basis of the strengths and weaknesses of each of the methods reviewed, we conclude that the timed volume method is apt for hilly terrain having smaller streams due to its operational ease and accuracy of results. Although comparatively expensive, the weir and flume methods are suitable for long term studies of small hill streams, since once the structure is put in place, it yields accurate results. In flat terrain, the float method is best suited for smaller streams for its operational ease and cost effectiveness, whereas, for larger streams, the particle image velocimetry may be used for its accuracy. Our review suggests that the selection of a method for monitoring streamflow may be based on volume of the stream, accuracy of the method, accessibility of the terrain and financial and physical resources available.
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von Freyberg, J.; Schirmer, M.
2013-12-01
have identified three hydrological landscape units with very characteristic subsurface properties, with which the overall catchment behavior can be predicted by applying a parsimonious modeling approach. By implementing solute, electrical conductivity and temperature time series data from ground- and river water into the model, the spatio-temporal streamflow contribution from these landscape units reveals new insights into the hydrological functioning of the Rietholzbach catchment. The landscape units defined in our study are considered typical for the Swiss pre-Alps and, therefore, our results will provide valuable input for local and regional hydrological modeling studies in similar pre-Alpine watersheds.
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Validating EHR clinical models using ontology patterns.
Martínez-Costa, Catalina; Schulz, Stefan
2017-12-01
Clinical models are artefacts that specify how information is structured in electronic health records (EHRs). However, the makeup of clinical models is not guided by any formal constraint beyond a semantically vague information model. We address this gap by advocating ontology design patterns as a mechanism that makes the semantics of clinical models explicit. This paper demonstrates how ontology design patterns can validate existing clinical models using SHACL. Based on the Clinical Information Modelling Initiative (CIMI), we show how ontology patterns detect both modeling and terminology binding errors in CIMI models. SHACL, a W3C constraint language for the validation of RDF graphs, builds on the concept of "Shape", a description of data in terms of expected cardinalities, datatypes and other restrictions. SHACL, as opposed to OWL, subscribes to the Closed World Assumption (CWA) and is therefore more suitable for the validation of clinical models. We have demonstrated the feasibility of the approach by manually describing the correspondences between six CIMI clinical models represented in RDF and two SHACL ontology design patterns. Using a Java-based SHACL implementation, we found at least eleven modeling and binding errors within these CIMI models. This demonstrates the usefulness of ontology design patterns not only as a modeling tool but also as a tool for validation. Copyright © 2017 Elsevier Inc. All rights reserved.
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A spatial assessment of stream-flow characteristics and hydrologic ...
African Journals Online (AJOL)
The global hydrologic regime has been intensively altered through activities such as dam construction, water abstraction, and inter-basin transfers. This paper uses the Range of Variability Approach (RVA) and daily stream flow records from nine gauging stations to characterize stream-flow post dam construction in the ...
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Kiah, Richard G.; Stasulis, Nicholas W.
2018-03-08
Rainfall from a storm on October 24–27, 2017, and Tropical Storm Philippe on October 29–30, created conditions that led to flooding across portions of New Hampshire and western Maine. On the basis of streamflow data collected at 30 selected U.S. Geological Survey (USGS) streamgages in the Androscoggin River, Connecticut River, Merrimack River, and Saco River Basins, the storms caused minor to moderate flooding in those basins on October 30–31, 2017. During the storms, the USGS deployed hydrographers to take discrete measurements of streamflow. The measurements were used to confirm the stage-to-streamflow relation (rating curve) at the selected USGS streamgages. Following the storms, hydrographers documented high-water marks in support of indirect measurements of streamflow. Seven streamgages with greater than 50 years of streamflow data recorded preliminary streamflow peaks within the top five for the periods of record. Twelve streamgages recorded preliminary peak streamflows greater than an estimate of the 100-year streamflow based on drainage area.
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Directory of Open Access Journals (Sweden)
Mikołaj Piniewski
2017-04-01
Full Text Available There is considerable concern that the water resources of Central and Eastern Europe region can be adversely affected by climate change. Projections of future water balance and streamflow conditions can be obtained by forcing hydrological models with the output from climate models. In this study, we employed the SWAT hydrological model driven with an ensemble of nine bias-corrected EURO-CORDEX climate simulations to generate future hydrological projections for the Vistula and Odra basins in two future horizons (2024–2050 and 2074–2100 under two Representative Concentration Pathways (RCPs. The data set consists of three parts: (1 model inputs; (2 raw model outputs; (3 aggregated model outputs. The first one allows the users to reproduce the outputs or to create the new ones. The second one contains the simulated time series of 10 variables simulated by SWAT: precipitation, snow melt, potential evapotranspiration, actual evapotranspiration, soil water content, percolation, surface runoff, baseflow, water yield and streamflow. The third one consists of the multi-model ensemble statistics of the relative changes in mean seasonal and annual variables developed in a GIS format. The data set should be of interest of climate impact scientists, water managers and water-sector policy makers. In any case, it should be noted that projections included in this data set are associated with high uncertainties explained in this data descriptor paper.
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Directory of Open Access Journals (Sweden)
S. Saxe
2018-02-01
Full Text Available This research investigates the impact of wildfires on watershed flow regimes, specifically focusing on evaluation of fire events within specified hydroclimatic regions in the western United States, and evaluating the impact of climate and geophysical variables on response. Eighty-two watersheds were identified with at least 10 years of continuous pre-fire daily streamflow records and 5 years of continuous post-fire daily flow records. Percent change in annual runoff ratio, low flows, high flows, peak flows, number of zero flow days, baseflow index, and Richards–Baker flashiness index were calculated for each watershed using pre- and post-fire periods. Independent variables were identified for each watershed and fire event, including topographic, vegetation, climate, burn severity, percent area burned, and soils data. Results show that low flows, high flows, and peak flows increase in the first 2 years following a wildfire and decrease over time. Relative response was used to scale response variables with the respective percent area of watershed burned in order to compare regional differences in watershed response. To account for variability in precipitation events, runoff ratio was used to compare runoff directly to PRISM precipitation estimates. To account for regional differences in climate patterns, watersheds were divided into nine regions, or clusters, through k-means clustering using climate data, and regression models were produced for watersheds grouped by total area burned. Watersheds in Cluster 9 (eastern California, western Nevada, Oregon demonstrate a small negative response to observed flow regimes after fire. Cluster 8 watersheds (coastal California display the greatest flow responses, typically within the first year following wildfire. Most other watersheds show a positive mean relative response. In addition, simple regression models show low correlation between percent watershed burned and streamflow response, implying that
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Longer-term effects of pine and eucalypt plantations on streamflow
CSIR Research Space (South Africa)
Scott, DF
2008-10-01
Full Text Available The longer-term effects of afforestation with Pinus radiata and Eucalyptus grandis on streamflows were analyzed using data from two paired-catchment experiments in South Africa. The experiments are rare in that they have been maintained over longer...
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Tracer travel time and model validation
International Nuclear Information System (INIS)
Tsang, Chin-Fu.
1988-01-01
The performance assessment of a nuclear waste repository demands much more in comparison to the safety evaluation of any civil constructions such as dams, or the resource evaluation of a petroleum or geothermal reservoir. It involves the estimation of low probability (low concentration) of radionuclide transport extrapolated 1000's of years into the future. Thus models used to make these estimates need to be carefully validated. A number of recent efforts have been devoted to the study of this problem. Some general comments on model validation were given by Tsang. The present paper discusses some issues of validation in regards to radionuclide transport. 5 refs
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Model validation: a systemic and systematic approach
International Nuclear Information System (INIS)
Sheng, G.; Elzas, M.S.; Cronhjort, B.T.
1993-01-01
The term 'validation' is used ubiquitously in association with the modelling activities of numerous disciplines including social, political natural, physical sciences, and engineering. There is however, a wide range of definitions which give rise to very different interpretations of what activities the process involves. Analyses of results from the present large international effort in modelling radioactive waste disposal systems illustrate the urgent need to develop a common approach to model validation. Some possible explanations are offered to account for the present state of affairs. The methodology developed treats model validation and code verification in a systematic fashion. In fact, this approach may be regarded as a comprehensive framework to assess the adequacy of any simulation study. (author)
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Baseflow simulation using SWAT model in an inland river basin in Tianshan Mountains, Northwest China
Directory of Open Access Journals (Sweden)
Y. Luo
2012-04-01
Full Text Available Baseflow is an important component in hydrological modeling. The complex streamflow recession process complicates the baseflow simulation. In order to simulate the snow and/or glacier melt dominated streamflow receding quickly during the high-flow period but very slowly during the low-flow period in rivers in arid and cold northwest China, the current one-reservoir baseflow approach in SWAT (Soil Water Assessment Tool model was extended by adding a slow- reacting reservoir and applying it to the Manas River basin in the Tianshan Mountains. Meanwhile, a digital filter program was employed to separate baseflow from streamflow records for comparisons. Results indicated that the two-reservoir method yielded much better results than the one-reservoir one in reproducing streamflow processes, and the low-flow estimation was improved markedly. Nash-Sutcliff efficiency values at the calibration and validation stages are 0.68 and 0.62 for the one-reservoir case, and 0.76 and 0.69 for the two-reservoir case. The filter-based method estimated the baseflow index as 0.60, while the model-based as 0.45. The filter-based baseflow responded almost immediately to surface runoff occurrence at onset of rising limb, while the model-based responded with a delay. In consideration of watershed surface storage retention and soil freezing/thawing effects on infiltration and recharge during initial snowmelt season, a delay response is considered to be more reasonable. However, a more detailed description of freezing/thawing processes should be included in soil modules so as to determine recharge to aquifer during these processes, and thus an accurate onset point of rising limb of the simulated baseflow.
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A comprehensive analysis of high-magnitude streamflow and trends in the Central Valley, California
Kocis, T. N.; Dahlke, H. E.
2017-12-01
California's climate is characterized by the largest precipitation and streamflow variability observed within the conterminous US. This, combined with chronic groundwater overdraft of 0.6-3.5 km3 yr-1, creates the need to identify additional surface water sources available for groundwater recharge using methods such as agricultural groundwater banking, aquifer storage and recovery, and spreading basins. High-magnitude streamflow, i.e. flow above the 90th percentile, that exceeds environmental flow requirements and current surface water allocations under California water rights, could be a viable source of surface water for groundwater banking. Here, we present a comprehensive analysis of the magnitude, frequency, duration and timing of high-magnitude streamflow (HMF "metrics") over multiple time periods for 93 stream gauges covering the Sacramento, San Joaquin and Tulare basins in California. In addition, we present trend analyses conducted on the same dataset and all HMF metrics using generalized additive models, the Mann-Kendall trend test, and the Signal to Noise Ratio test. The results of the comprehensive analysis show, in short, that in an average year with HMF approximately 3.2 km3 of high-magnitude flow is exported from the entire Central Valley to the Sacramento-San Joaquin Delta, often at times when environmental flow requirements of the Delta and major rivers are exceeded. High-magnitude flow occurs, on average, during 7 and 4.7 out of 10 years in the Sacramento River and the San Joaquin-Tulare Basins, respectively, from just a few storm events (5-7 1-day peak events) lasting for a total of 25-30 days between November and April. Preliminary trend tests suggest that all HMF metrics show limited change over the last 50 years. As a whole, the results suggest that there is sufficient unmanaged surface water physically available to mitigate long-term groundwater overdraft in the Central Valley.
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Oliver, C W; Radcliffe, D E; Risse, L M; Habteselassie, M; Mukundan, R; Jeong, J; Hoghooghi, N
2014-03-01
In the southeastern United States, on-site wastewater treatment systems (OWTSs) are widely used for domestic wastewater treatment. The degree to which OWTSs represent consumptive water use has been questioned in Georgia. The goal of this study was to estimate the effect of OWTSs on streamflow in a gauged watershed in Gwinnett County, Georgia using the Soil and Water Assessment Tool (SWAT) watershed-scale model, which includes a new OWTS algorithm. Streamflow was modeled with and without the presence of OWTSs. The model was calibrated using data from 1 Jan. 2003 to 31 Dec. 2006 and validated from 1 Jan. 2007 to 31 Dec. 2010 using the auto-calibration tool SWAT-CUP 4. The daily and monthly streamflow Nash-Sutcliffe coefficients were 0.49 and 0.71, respectively, for the calibration period and 0.37 and 0.68, respectively, for the validation period, indicating a satisfactory fit. Analysis of water balance output variables between simulations showed a 3.1% increase in total water yield at the watershed scale and a 5.9% increase at the subbasin scale for a high-density OWTS area. The percent change in water yield between simulations was the greatest in dry years, implying that the influence of OWTSs on the water yield is greatest under drought conditions. Mean OWTS water use was approximately 5.7% consumptive, contrary to common assumptions by water planning agencies in Georgia. Results from this study may be used by OWTS users and by watershed planners to understand the influence of OWTSs on water quantity within watersheds in this region. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.
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Increasing influence of air temperature on upper Colorado River streamflow
Woodhouse, Connie A.; Pederson, Gregory T.; Morino, Kiyomi; McAfee, Stephanie A.; McCabe, Gregory J.
2016-01-01
This empirical study examines the influence of precipitation, temperature, and antecedent soil moisture on upper Colorado River basin (UCRB) water year streamflow over the past century. While cool season precipitation explains most of the variability in annual flows, temperature appears to be highly influential under certain conditions, with the role of antecedent fall soil moisture less clear. In both wet and dry years, when flow is substantially different than expected given precipitation, these factors can modulate the dominant precipitation influence on streamflow. Different combinations of temperature, precipitation, and soil moisture can result in flow deficits of similar magnitude, but recent droughts have been amplified by warmer temperatures that exacerbate the effects of relatively modest precipitation deficits. Since 1988, a marked increase in the frequency of warm years with lower flows than expected, given precipitation, suggests continued warming temperatures will be an increasingly important influence in reducing future UCRB water supplies.
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Validation of models in an imaging infrared simulation
CSIR Research Space (South Africa)
Willers, C
2007-10-01
Full Text Available threeprocessesfortransformingtheinformationbetweentheentities. Reality/ Problem Entity Conceptual Model Computerized Model Model Validation ModelVerification Model Qualification Computer Implementation Analysisand Modelling Simulationand Experimentation “Substantiationthata....C.Refsgaard ,ModellingGuidelines-terminology andguidingprinciples, AdvancesinWaterResources, Vol27,No1,January2004,?pp.71-82(12),Elsevier. et.al. [5]N.Oreskes,et.al.,Verification,Validation,andConfirmationof NumericalModelsintheEarthSciences,Science,Vol263, Number...
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Barbarossa, Valerio; Huijbregts, Mark A. J.; Beusen, Arthur H. W.; Beck, Hylke E.; King, Henry; Schipper, Aafke M.
2018-03-01
Streamflow data is highly relevant for a variety of socio-economic as well as ecological analyses or applications, but a high-resolution global streamflow dataset is yet lacking. We created FLO1K, a consistent streamflow dataset at a resolution of 30 arc seconds (~1 km) and global coverage. FLO1K comprises mean, maximum and minimum annual flow for each year in the period 1960-2015, provided as spatially continuous gridded layers. We mapped streamflow by means of artificial neural networks (ANNs) regression. An ensemble of ANNs were fitted on monthly streamflow observations from 6600 monitoring stations worldwide, i.e., minimum and maximum annual flows represent the lowest and highest mean monthly flows for a given year. As covariates we used the upstream-catchment physiography (area, surface slope, elevation) and year-specific climatic variables (precipitation, temperature, potential evapotranspiration, aridity index and seasonality indices). Confronting the maps with independent data indicated good agreement (R2 values up to 91%). FLO1K delivers essential data for freshwater ecology and water resources analyses at a global scale and yet high spatial resolution.
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Zhaohua Dai; Carl Trettin; Changsheng Li; Devendra M. Amatya; Ge Sun; Harbin Li
2010-01-01
A physically based distributed hydrological model, MIKE SHE, was used to evaluate the effects of altered temperature and precipitation regimes on the streamflow and water table in a forested watershed on the southeastern Atlantic coastal plain. The model calibration and validation against both streamflow and water table depth showed that the MIKE SHE was applicable for...
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Henn, Brian; Painter, Thomas H.; Bormann, Kat J.; McGurk, Bruce; Flint, Alan L.; Flint, Lorraine E.; White, Vince; Lundquist, Jessica D.
2018-02-01
Hydrologic variables such as evapotranspiration (ET) and soil water storage are difficult to observe across spatial scales in complex terrain. Streamflow and lidar-derived snow observations provide information about distributed hydrologic processes such as snowmelt, infiltration, and storage. We use a distributed streamflow data set across eight basins in the upper Tuolumne River region of Yosemite National Park in the Sierra Nevada mountain range, and the NASA Airborne Snow Observatory (ASO) lidar-derived snow data set over 3 years (2013-2015) during a prolonged drought in California, to estimate basin-scale water balance components. We compare snowmelt and cumulative precipitation over periods from the ASO flight to the end of the water year against cumulative streamflow observations. The basin water balance residual term (snow melt plus precipitation minus streamflow) is calculated for each basin and year. Using soil moisture observations and hydrologic model simulations, we show that the residual term represents short-term changes in basin water storage over the snowmelt season, but that over the period from peak snow water equivalent (SWE) to the end of summer, it represents cumulative basin-mean ET. Warm-season ET estimated from this approach is 168 (85-252 at 95% confidence), 162 (0-326) and 191 (48-334) mm averaged across the basins in 2013, 2014, and 2015, respectively. These values are lower than previous full-year and point ET estimates in the Sierra Nevada, potentially reflecting reduced ET during drought, the effects of spatial variability, and the part-year time period. Using streamflow and ASO snow observations, we quantify spatially-distributed hydrologic processes otherwise difficult to observe.
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Kentel, E.; Cetinkaya, M. A.
2013-12-01
Global issues such as population increase, power supply crises, oil prices, social and environmental concerns have been forcing countries to search for alternative energy sources such as renewable energy to satisfy the sustainable development goals. Hydropower is the most common form of renewable energy in the world. Hydropower does not require any fuel, produces relatively less pollution and waste and it is a reliable energy source with relatively low operating cost. In order to estimate the average annual energy production of a hydropower plant, sufficient and dependable streamflow data is required. The goal of this study is to investigate impact of streamflow data on annual energy generation of Balkusan HEPP which is a small run-of-river hydropower plant at Karaman, Turkey. Two different stream gaging stations are located in the vicinity of Balkusan HEPP and these two stations have different observation periods: one from 1986 to 2004 and the other from 2000 to 2009. These two observation periods show different climatic characteristics. Thus, annual energy estimations based on data from these two different stations differ considerably. Additionally, neither of these stations is located at the power plant axis, thus streamflow observations from these two stream gaging stations need to be transferred to the plant axis. This requirement introduces further errors into energy estimations. Impact of different streamflow data and transfer of streamflow observations to plant axis on annual energy generation of a small hydropower plant is investigated in this study.
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Senior, Lisa A.; Koerkle, Edward H.
2003-01-01
The Christina River Basin drains 565 square miles (mi2) in Pennsylvania, Maryland, and Delaware. Water from the basin is used for recreation, drinking water supply, and to support aquatic life. The Christina River Basin includes the major subbasins of Brandywine Creek, White Clay Creek, and Red Clay Creek. The White Clay Creek is the second largest of the subbasins and drains an area of 108 mi2. Water quality in some parts of the Christina River Basin is impaired and does not support designated uses of the streams. A multi-agency water-quality management strategy included a modeling component to evaluate the effects of point and nonpoint-source contributions of nutrients and suspended sediment on stream water quality. To assist in non point-source evaluation, four independent models, one for each of the three major subbasins and for the Christina River, were developed and calibrated using the model code Hydrological Simulation Program—Fortran (HSPF). Water-quality data for model calibration were collected in each of the four main subbasins and in smaller subbasins predominantly covered by one land use following a nonpoint-source monitoring plan. Under this plan, stormflow and base- flow samples were collected during 1998 at two sites in the White Clay Creek subbasin and at nine sites in the other subbasins.The HSPF model for the White Clay Creek Basin simulates streamflow, suspended sediment, and the nutrients, nitrogen and phosphorus. In addition, the model simulates water temperature, dissolved oxygen, biochemical oxygen demand, and plankton as secondary objectives needed to support the sediment and nutrient simulations. For the model, the basin was subdivided into 17 reaches draining areas that ranged from 1.37 to 13 mi2. Ten different pervious land uses and two impervious land uses were selected for simulation. Land-use areas were determined from 1995 land-use data. The predominant land uses in the White Clay Creek Basin are agricultural, forested
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Metz, P.A.; Lewelling, B.R.
2009-01-01
The upper Peace River from Bartow to Fort Meade, Florida, is described as a groundwater recharge area, reflecting a reversal from historical groundwater discharge patterns that existed prior to the 1950s. The upper Peace River channel and floodplain are characterized by extensive karst development, with numerous fractures, crevasses, and sinks that have been eroded in the near-surface and underlying carbonate bedrock. With the reversal in groundwater head gradients, river water is lost to the underlying groundwater system through these karst features. An investigation was conducted to evaluate the hydrologic conditions that influence streamflow losses in the karst region of the upper Peace River. The upper Peace River is located in a basin that has been altered substantially by phosphate mining and increases in groundwater use. These alterations have changed groundwater flow patterns and caused streamflow declines through time. Hydrologic factors that have had the greatest influence on streamflow declines in the upper Peace River include the lowering of the potentiometric surfaces of the intermediate aquifer system and Upper Floridan aquifer beneath the riverbed elevation due to below-average rainfall (droughts), increases in groundwater use, and the presence of numerous karst features in the low-water channel and floodplain that enhance the loss of streamflow. Seepage runs conducted along the upper Peace River, from Bartow to Fort Meade, indicate that the greatest streamflow losses occurred along an approximate 2-mile section of the river beginning about 1 mile south of the Peace River at Bartow gaging station. Along the low-water and floodplain channel of this 2-mile section, there are about 10 prominent karst features that influence streamflow losses. Losses from the individual karst features ranged from 0.22 to 16 cubic feet per second based on measurements made between 2002 and 2007. The largest measured flow loss for all the karst features was about 50 cubic
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Dietsch, Benjamin J.; Godberson, Julie A.; Steele, Gregory V.
2009-01-01
The Nebraska Department of Natural Resources approved instream-flow appropriations on the Platte River to maintain fish communities, whooping crane roost habitat, and wet meadows used by several wild bird species. In the lower Platte River region, the Nebraska Game and Parks Commission owns an appropriation filed to maintain streamflow for fish communities between the Platte River confluence with the Elkhorn River and the mouth of the Platte River. Because Elkhorn River flow is an integral part of the flow in the reach addressed by this appropriation, the Upper Elkhorn and Lower Elkhorn Natural Resources Districts are involved in overall management of anthropogenic effects on the availability of surface water for instream requirements. The Physical Habitat Simulation System (PHABSIM) and other estimation methodologies were used previously to determine instream requirements for Platte River biota, which led to the filing of five water appropriations applications with the Nebraska Department of Natural Resources in 1993 by the Nebraska Game and Parks Commission. One of these requested instream-flow appropriations of 3,700 cubic feet per second was for the reach from the Elkhorn River to the mouth of the Platte River. Four appropriations were granted with modifications in 1998, by the Nebraska Department of Natural Resources. Daily streamflow data for the periods of record were summarized for 17 streamflow-gaging stations in Nebraska to evaluate streamflow characteristics, including low-flow intervals for consecutive durations of 1, 3, 7, 14, 30, 60, and 183 days. Temporal trends in selected streamflow statistics were not adjusted for variability in precipitation. Results indicated significant positive temporal trends in annual flow for the period of record at eight streamflow-gaging stations - Platte River near Duncan (06774000), Platte River at North Bend (06796000), Elkhorn River at Neligh (06798500), Logan Creek near Uehling (06799500), Maple Creek near Nickerson
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Brasher, Anne M.D.; Konrad, Chris P.; May, Jason T.; Edmiston, C. Scott; Close, Rebecca N.
2010-01-01
Hydrographic characteristics of streamflow, such as high-flow pulses, base flow (background discharge between floods), extreme low flows, and floods, significantly influence aquatic organisms. Streamflow can be described in terms of magnitude, timing, duration, frequency, and variation (hydrologic regime). These characteristics have broad effects on ecosystem productivity, habitat structure, and ultimately on resident fish, invertebrate, and algae communities. Increasing human use of limited water resources has modified hydrologic regimes worldwide. Identifying the most ecologically significant hydrographic characteristics would facilitate the development of water-management strategies.Benthic invertebrates include insects, mollusks (snails and clams), worms, and crustaceans (shrimp) that live on the streambed. Invertebrates play an important role in the food web, consuming other invertebrates and algae and being consumed by fish and birds. Hydrologic alteration associated with land and water use can change the natural hydrologic regime and may affect benthic invertebrate assemblage composition and structure through changes in density of invertebrates or taxa richness (number of different species).This study examined associations between the hydrologic regime and characteristics of benthic invertebrate assemblages across the western United States and developed tools to identify streamflow characteristics that are likely to affect benthic invertebrate assemblages.
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Stream Flow Simulation of a Snow-Fed Mountainous Basin Using the SWAT Model
Shukla, S.; Kansal, M. L.; Jain, S. K.
2017-12-01
Hydrological budget of the Satluj River (a major tributary of Indus river system) in Western Himalaya, is dominated by monsoonal rainfall and snowmelt during the non-monsoon months. The river watershed experiences extensive snowfall in the winters and snowmelt runoff substantially contributes to the streamflow of the river in the spring and summer months. In order to understand the hydrologic response of Satluj basin, hydrological modeling study is carried out using a semi distributed hydrological model Soil and Water Assessment Tool (SWAT), for the period of thirty years (1985-2014). The basic intent of this study is to derive the parameters required for runoff modeling using the geospatial database. The Sequential Uncertainty Fitting (SUFI-2) algorithm is used to calibrate and validate the model and incorporate uncertainties in the analysis. The results are validated with the observed daily streamflow data at Rampur, in terms of Nash-Sutcliffe Coefficient (NSC), R2 and Root Mean Square Error (RMSE). Further, the snowmelt-runoff mechanism is modelled by relating the temperature changes to the elevation band in the basin. The northern part of the basin and the south part of the basin on the high elevation zones have the coldest maximum temperatures that is about 7°C. It is found that the average contribution of snow and glacier runoff in the annual flow of the Satluj River at Rampur is about 66% and remaining 34% is from rainfall.
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Krug, W.R.; Goddard, G.L.
1986-01-01
A 5-year, data-collection and modeling study was conducted on Pheasant Branch basin in and near Middleton, Wisconsin. The objectives of the study were to: (1) describe the streamflow characteristics, sediment transport, and stream-channel morphology in the Pheasant Branch basin; and (2) relate the above factors to changes caused by urbanization and project the effect of urbanization on the hydrology and channel morphology of the study area.
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Directory of Open Access Journals (Sweden)
Orville P. Grey
2014-09-01
Full Text Available The Great River Watershed, located in north-west Jamaica, is critical for development, particularly for housing, tourism, agriculture, and mining. It is a source of sediment and nutrient loading to the coastal environment including the Montego Bay Marine Park. We produced a modeling framework using the Soil and Water Assessment Tool (SWAT and GIS. The calculated model performance statistics for high flow discharge yielded a Nash-Sutcliffe Efficiency (NSE value of 0.68 and a R² value of 0.70 suggesting good measured and simulated (calibrated discharge correlation. Calibration and validation results for streamflow were similar to the observed streamflows. For the dry season the simulated urban landuse scenario predicted an increase in surface runoff in excess of 150%. During the wet season it is predicted to range from 98 to 234% presenting a significant risk of flooding, erosion and other environmental issues. The model should be used for the remaining 25 watersheds in Jamaica and elsewhere in the Caribbean. The models suggests that projected landuse changes will have serious impacts on available water (streamflow, stream health, potable water treatment, flooding and sensitive coastal ecosystems.
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Sloto, Ronald A.; Stuckey, Marla H.; Hoffman, Scott A.
2017-05-10
characteristics of the reference streamgages. There were 320 HUC12 subwatersheds, or 19 percent of the study area, with basin characteristics outside the range represented by the reference streamgage watersheds.A GIS spatial analysis was used to identify geographic gaps in the streamgage network. For each streamgage, a watershed area, called the gage statistical area (GSA), was delineated. The GSA shows the drainage area within a specific drainage-area ratio of the streamgage for transfer of streamflow statistics from that streamgage to ungaged sites on the valid statistical reach of the GSA for a streamgage. In Pennsylvania, a drainage-area ratio of 0.33–3 times the drainage area of the ungaged site was found to perform as well as, if not better than, more traditional ratios such as 0.5–1.5 (or 2) for transfer of selected streamflow statistics. A total of 1,102 HUC12 subwatersheds, or 66 percent of the study area, are outside the GSA for a reference streamgage.The USGS Baseline Streamflow Estimator (BaSE) program was used to determine how well HUC12 subwatersheds outside the streamgage GSAs are represented by the reference streamgage network in Pennsylvania, based on estimated streamflow correlation. The centroid of each HUC12 subwatershed was run through the BaSE program to determine the reference streamgage with the highest estimated streamflow correlation. There were 929 HUC12 subwatersheds in Pennsylvania, or 56 percent of the State, with an estimated correlation coefficient less than 0.96.The results from the basin characteristic, geographic, and streamflow correlation analyses were combined to identify 1,405 HUC12 subwatersheds in Pennsylvania and the Susquehanna River Basin in Pennsylvania and New York that lack a representative reference, based on at least one identified gap. Of the 1,405 HUC12 subwatersheds, 139 exhibited all three gaps, indicating a 8-percent gap in the reference streamgage network.Streamgages in areas with similar hydrologic characteristics and in
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How do extreme streamflow due to hurricane IRMA compare during 1938-2017 in South Eastern US?
Anandhi, A.
2017-12-01
The question related to Irma, Harvey, Maria, and other hurricanes is: are hurricane more frequent and intense than they have been in the past. Recent hurricanes were unusually strong hitting the US Coastline or territories as a category 4 or 5, dropping unusually large amounts of precipitation on the affected areas creating extreme high-flow events in rivers and streams in affected areas. The objective of the study is to determine how extreme are streamflows from recent hurricanes (e.g. IRMA) when compared to streamflow's during 1938-2017 time-period. Additionally, in this study, the extreme precipitations are also compared during IRMA. Extreme high flows are selected from Indicators of Hydrologic Alteration (IHA). They are distributions, timing, duration, frequency, magnitude, pulses, and days of extreme events in rivers of the southeastern United States and Gulf of Mexico Hydrologic Region—03. Streamflow data from 30 stations in the region with at least 79 years of record (1938-2017) are used. Historical precipitation changes is obtained from meta-analysis of published literature. Our preliminary results indicate the extremeness of streamflow from recent hurricanes vary with the IHA indicator selected. Some potential implications of these extreme events on the region's ecosystem are also discussed using causal chains and loops.
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Past and future changes in streamflow in the U.S. Midwest: Bridging across time scales
Villarini, G.; Slater, L. J.; Salvi, K. A.
2017-12-01
Streamflows have increased notably across the U.S. Midwest over the past century, principally due to changes in precipitation and land use / land cover. Improving our understanding of the physical drivers that are responsible for the observed changes in discharge may enhance our capability of predicting and projecting these changes, and may have large implications for water resources management over this area. This study will highlight our efforts towards the statistical attribution of changes in discharge across the U.S. Midwest, with analyses performed at the seasonal scale from low to high flows. The main drivers of changing streamflows that we focus on are: urbanization, agricultural land cover, basin-averaged temperature, basin-averaged precipitation, and antecedent soil moisture. Building on the insights from this attribution, we will examine the potential predictability of streamflow across different time scales, with lead times ranging from seasonal to decadal, and discuss a potential path forward for engineering design for future conditions.
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Merging Satellite Precipitation Products for Improved Streamflow Simulations
Maggioni, V.; Massari, C.; Barbetta, S.; Camici, S.; Brocca, L.
2017-12-01
statistics, as well as bias reduction and correlation coefficient, with the Bayesian approach being superior to other methods. A study case in the Tiber river basin is also presented to discuss the performance of forcing a hydrological model with the merged satellite precipitation product to simulate streamflow time series.
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Directory of Open Access Journals (Sweden)
Donizete dos R. Pereira
2016-09-01
New hydrological insights: The SWAT model was qualified for simulating the Pomba River sub-basin in the sites where rainfall representation was reasonable to good. The model can be used in the simulation of maximum, average and minimum annual daily streamflow based on the paired t-test, contributing with the water resources management of region, although the model still needs to be improved, mainly in the representativeness of rainfall, to give better estimates of extreme values.
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Smith, Kirk P.
2015-01-01
Streamflow and concentrations of sodium and chloride estimated from records of specific conductance were used to calculate loads of sodium and chloride during water year (WY) 2013 (October 1, 2012, through September 30, 2013) for tributaries to the Scituate Reservoir, Rhode Island. Streamflow and water-quality data used in the study were collected by the U.S. Geological Survey (USGS) or the Providence Water Supply Board (PWSB) in the cooperative study. Streamflow was measured or estimated by the USGS following standard methods at 23 streamgages; 14 of these streamgages are equipped with instrumentation capable of continuously monitoring water level, specific conductance, and water temperature. Water-quality samples were collected at 37 sampling stations by the PWSB and at 14 continuous-record streamgages by the USGS during WY 2013 as part of a long-term sampling program; all stations are in the Scituate Reservoir drainage area. Water-quality data collected by the PWSB are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for WY 2013.
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Feature Extraction for Structural Dynamics Model Validation
Energy Technology Data Exchange (ETDEWEB)
Farrar, Charles [Los Alamos National Laboratory; Nishio, Mayuko [Yokohama University; Hemez, Francois [Los Alamos National Laboratory; Stull, Chris [Los Alamos National Laboratory; Park, Gyuhae [Chonnam Univesity; Cornwell, Phil [Rose-Hulman Institute of Technology; Figueiredo, Eloi [Universidade Lusófona; Luscher, D. J. [Los Alamos National Laboratory; Worden, Keith [University of Sheffield
2016-01-13
As structural dynamics becomes increasingly non-modal, stochastic and nonlinear, finite element model-updating technology must adopt the broader notions of model validation and uncertainty quantification. For example, particular re-sampling procedures must be implemented to propagate uncertainty through a forward calculation, and non-modal features must be defined to analyze nonlinear data sets. The latter topic is the focus of this report, but first, some more general comments regarding the concept of model validation will be discussed.
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The concept of validation of numerical models for consequence analysis
International Nuclear Information System (INIS)
Borg, Audun; Paulsen Husted, Bjarne; Njå, Ove
2014-01-01
Numerical models such as computational fluid dynamics (CFD) models are increasingly used in life safety studies and other types of analyses to calculate the effects of fire and explosions. The validity of these models is usually established by benchmark testing. This is done to quantitatively measure the agreement between the predictions provided by the model and the real world represented by observations in experiments. This approach assumes that all variables in the real world relevant for the specific study are adequately measured in the experiments and in the predictions made by the model. In this paper the various definitions of validation for CFD models used for hazard prediction are investigated to assess their implication for consequence analysis in a design phase. In other words, how is uncertainty in the prediction of future events reflected in the validation process? The sources of uncertainty are viewed from the perspective of the safety engineer. An example of the use of a CFD model is included to illustrate the assumptions the analyst must make and how these affect the prediction made by the model. The assessments presented in this paper are based on a review of standards and best practice guides for CFD modeling and the documentation from two existing CFD programs. Our main thrust has been to assess how validation work is performed and communicated in practice. We conclude that the concept of validation adopted for numerical models is adequate in terms of model performance. However, it does not address the main sources of uncertainty from the perspective of the safety engineer. Uncertainty in the input quantities describing future events, which are determined by the model user, outweighs the inaccuracies in the model as reported in validation studies. - Highlights: • Examine the basic concept of validation applied to models for consequence analysis. • Review standards and guides for validation of numerical models. • Comparison of the validation
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Validation of ASTEC core degradation and containment models
International Nuclear Information System (INIS)
Kruse, Philipp; Brähler, Thimo; Koch, Marco K.
2014-01-01
Ruhr-Universitaet Bochum performed in a German funded project validation of in-vessel and containment models of the integral code ASTEC V2, jointly developed by IRSN (France) and GRS (Germany). In this paper selected results of this validation are presented. In the in-vessel part, the main point of interest was the validation of the code capability concerning cladding oxidation and hydrogen generation. The ASTEC calculations of QUENCH experiments QUENCH-03 and QUENCH-11 show satisfactory results, despite of some necessary adjustments in the input deck. Furthermore, the oxidation models based on the Cathcart–Pawel and Urbanic–Heidrick correlations are not suitable for higher temperatures while the ASTEC model BEST-FIT based on the Prater–Courtright approach at high temperature gives reliable enough results. One part of the containment model validation was the assessment of three hydrogen combustion models of ASTEC against the experiment BMC Ix9. The simulation results of these models differ from each other and therefore the quality of the simulations depends on the characteristic of each model. Accordingly, the CPA FRONT model, corresponding to the simplest necessary input parameters, provides the best agreement to the experimental data
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Identifying needs for streamflow forecasting in the Incomati basin, Southern Africa
Sunday, Robert; Werner, Micha; Masih, Ilyas; van der Zaag, Pieter
2013-04-01
Despite being widely recognised as an efficient tool in the operational management of water resources, rainfall and streamflow forecasts are currently not utilised in water management practice in the Incomati Basin in Southern Africa. Although, there have been initiatives for forecasting streamflow in the Sabie and Crocodile sub-basins, the outputs of these have found little use because of scepticism on the accuracy and reliability of the information, or the relevance of the information provided to the needs of the water managers. The process of improving these forecasts is underway, but as yet the actual needs of the forecasts are unclear and scope of the ongoing initiatives remains very limited. In this study questionnaires and focused group interviews were used to establish the need, potential use, benefit and required accuracy of rainfall and streamflow forecasts in the Incomati Basin. Thirty five interviews were conducted with professionals engaged in water sector and detailed discussions were held with water institutions, including the Inkomati Catchment Management Agency (ICMA), Komati Basin Water Authority (KOBWA), South African Weather Service (SAWS), water managers, dam operators, water experts, farmers and other water users in the Basin. Survey results show that about 97% of the respondents receive weather forecasts. In contrast to expectations, only 5% have access to the streamflow forecast. In the weather forecast, the most important variables were considered to be rainfall and temperature at daily and weekly time scales. Moreover, forecasts of global climatic indices such as El Niño or La Niña were neither received nor demanded. There was limited demand and/or awareness of flood and drought forecasts including the information on their linkages with global climatic indices. While the majority of respondents indicate the need and indeed use the weather forecast, the provision, communication and interpretation were in general found to be with too
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Analytical models approximating individual processes: a validation method.
Favier, C; Degallier, N; Menkès, C E
2010-12-01
Upscaling population models from fine to coarse resolutions, in space, time and/or level of description, allows the derivation of fast and tractable models based on a thorough knowledge of individual processes. The validity of such approximations is generally tested only on a limited range of parameter sets. A more general validation test, over a range of parameters, is proposed; this would estimate the error induced by the approximation, using the original model's stochastic variability as a reference. This method is illustrated by three examples taken from the field of epidemics transmitted by vectors that bite in a temporally cyclical pattern, that illustrate the use of the method: to estimate if an approximation over- or under-fits the original model; to invalidate an approximation; to rank possible approximations for their qualities. As a result, the application of the validation method to this field emphasizes the need to account for the vectors' biology in epidemic prediction models and to validate these against finer scale models. Copyright © 2010 Elsevier Inc. All rights reserved.
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Pfister, Laurent; McDonnell, Jeffrey J.; Hissler, Christophe; Martinez-Carreras, Nuria; Gourdol, Laurent; Klaus, Julian; François Iffly, Jean; Barnich, François; Stewart, Mike K.
2014-05-01
Controls of geology and topography on hydrological metrics, like summer low flow (Grant and Tague, 2004) or dynamic storage (Sayama et al., 2011), have been identified in nested catchment experiments. However, most tracer-based studies on streamflow generation have been carried out in small (10 km2) homogenous catchments (Klaus and McDonnell, 2013). The controlling effects of catchment physiography on how catchments store and release water, and how this eventually controls stream isotope behaviour over a large range of scale are poorly understood. Here, we present results from a nested catchment analysis in the Alzette River basin (Luxembourg, Europe). Our hydro-climatological network consists of 16 recording streamgauges and 21 pluviographs. Catchment areas range from 0.47 to 285 km2, with clean and mixed combinations of distinct geologies ranging from schists to marls, sandstone, dolomite and limestone. Our objective was to identify geological controls on (i) winter runoff ratios, (ii) maximum storage and (iii) isotopic signatures in streamflow. For each catchment we determined average runoff ratios from winter season precipitation-discharge double-mass curves. Maximum catchment storage was based on the dynamic storage change approach of Sayama et al. (2011). Changes in isotopic signatures of streamflow were documented along individual catchment flow duration curves. We found strong correlations between average winter runoff ratios, maximum storage and the prevailing geological settings. Catchments with impermeable bedrock (e.g. marls or schists) were characterised by small storage potential and high average filling ratios. As a consequence, these catchments also exhibited the highest average runoff ratios. In catchments underlain by permeable bedrock (e.g. sandstone), storage potential was significantly higher and runoff ratios were considerably smaller. The isotopic signatures of streamflow showed large differences between catchments. In catchments dominated by
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Frederick, S. E.; Woodhouse, C. A.; Martin, J. T.; Pederson, G. T.
2017-12-01
The Missouri River supplies water to over 3 million basin residents and is a driving force for the nation's agricultural and energy sectors. However, with changing climate and declining snowpack in western North America, seasonal water yields are becoming less predictable, revealing a gap in our understanding of regional hydroclimate and drivers of streamflow within the basin. By analyzing the relationship between seasonal precipitation and streamflow in the Missouri River Headwaters sub-basin, this study seeks to expand our knowledge based on the instrumental record alone. Here we present the first annually-resolved tree-ring reconstruction of spring precipitation for the Missouri River Headwaters. This reconstruction along with existing tree-ring reconstructions of April 1 snow-water equivalence (SWE) (Pederson et al. 2011) and natural streamflow (Martin, J.T. & Pederson, G.T., personal communication, June 2017) are used to test the feasibility of detecting a variable influence of winter and spring precipitation on streamflow over past centuries, and relative to the modern period. Initial analyses indicate that April 1 SWE is a significant control on streamflow, however, the April 1 SWE record does not fully account for anomalies observed in the streamflow record. This study therefore seeks to determine whether spring precipitation can account for some of this asynchronous variability observed between the April 1 SWE and streamflow records. Aside from improved understanding of the relationship between hydroclimate and streamflow in the headwaters of the Missouri River, our findings offer insights relating to changing contributions from snowmelt and spring precipitation, and long-term hydrologic variability and trends relevant to water resource management and planning efforts.
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A discussion on validation of hydrogeological models
International Nuclear Information System (INIS)
Carrera, J.; Mousavi, S.F.; Usunoff, E.J.; Sanchez-Vila, X.; Galarza, G.
1993-01-01
Groundwater flow and solute transport are often driven by heterogeneities that elude easy identification. It is also difficult to select and describe the physico-chemical processes controlling solute behaviour. As a result, definition of a conceptual model involves numerous assumptions both on the selection of processes and on the representation of their spatial variability. Validating a numerical model by comparing its predictions with actual measurements may not be sufficient for evaluating whether or not it provides a good representation of 'reality'. Predictions will be close to measurements, regardless of model validity, if these are taken from experiments that stress well-calibrated model modes. On the other hand, predictions will be far from measurements when model parameters are very uncertain, even if the model is indeed a very good representation of the real system. Hence, we contend that 'classical' validation of hydrogeological models is not possible. Rather, models should be viewed as theories about the real system. We propose to follow a rigorous modeling approach in which different sources of uncertainty are explicitly recognized. The application of one such approach is illustrated by modeling a laboratory uranium tracer test performed on fresh granite, which was used as Test Case 1b in INTRAVAL. (author)
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Verification and validation for waste disposal models
International Nuclear Information System (INIS)
1987-07-01
A set of evaluation criteria has been developed to assess the suitability of current verification and validation techniques for waste disposal methods. A survey of current practices and techniques was undertaken and evaluated using these criteria with the items most relevant to waste disposal models being identified. Recommendations regarding the most suitable verification and validation practices for nuclear waste disposal modelling software have been made
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Randrianasolo, A.; Thirel, G.; Ramos, M. H.; Martin, E.
2014-11-01
Data assimilation has gained wide recognition in hydrologic forecasting due mainly to its capacity to improve the quality of short-term forecasts. In this study, a comparative analysis is conducted to assess the impact of discharge data assimilation on the quality of streamflow forecasts issued by two different modeling conceptualizations of catchment response. The sensitivity of the performance metrics to the length of the verification period is also investigated. The hydrological modeling approaches are: the coupled physically-based hydro-meteorological model SAFRAN-ISBA-MODCOU, a distributed model with a data assimilation procedure that uses streamflow measurements to assess the initial state of soil water content that optimizes discharge simulations, and the lumped soil moisture-accounting type rainfall-runoff model GRP, which assimilates directly the last observed discharge to update the state of the routing store. The models are driven by the weather ensemble prediction system PEARP of Météo-France, which is based on the global spectral ARPEGE model zoomed over France. It runs 11 perturbed members for a forecast range of 60 h. Forecast and observed data are available for 86 catchments over a 17-month period (March 2005-July 2006) for both models and for 82 catchments over a 52-month period (April 2005-July 2009) for the GRP model. The first dataset is used to investigate the impact of streamflow data assimilation on forecast quality, while the second is used to evaluate the impact of the length of the verification period on the assessment of forecast quality. Forecasts are compared to daily observed discharges and scores are computed for lead times 24 h and 48 h. Results indicate an overall good performance of both hydrological models forced by the PEARP ensemble predictions when the models are run with their data assimilation procedures. In general, when data assimilation is performed, the quality of the forecasts increases: median differences between
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Cravotta, Charles A.; Sherrod, Laura; Galeone, Daniel G.; Lehman, Wayne G.; Ackman, Terry E.; Kramer, Alexa
2017-01-01
Longitudinal discharge and water-quality campaigns (seepage runs) were combined with surface-geophysical surveys, hyporheic-temperature profiling, and watershed-scale hydrological monitoring to evaluate the locations, magnitude, and impact of streamwater losses from the West Creek subbasin of the West West Branch Schuylkill River into the underground Oak Hill Mine complex that extends beneath the watershed divide. Abandoned mine drainage (AMD), containing iron and other contaminants, from the Oak Hill Boreholes to the West Branch Schuylkill River was sustained during low-flow conditions and correlated to streamflow lost through the West Creek streambed. During high-flow conditions, streamflow was transmitted throughout West Creek; however, during low-flow conditions, all streamflow from the perennial headwaters was lost within the 300-to-600-m "upper reach" where an 1889 mine map indicated steeply dipping coalbeds underlie the channel. During low-flow conditions, the channel within the "intermediate reach" 700-to-1650-m downstream gained groundwater seepage with higher pH and specific conductance than upstream; however, all streamflow 1650-to-2050-m downstream was lost to underlying mines. Electrical resistivity and electromagnetic conductivity surveys indicated conductive zones beneath the upper reach, where flow loss occurred, and through the intermediate reach, where gains and losses occurred. Temperature probes at 0.06-to-0.10-m depth within the hyporheic zone of the intermediate reach indicated potential downward fluxes as high as 2.1x10-5 m/s. Cumulative streamflow lost from West Creek during seepage runs averaged 53.4 L/s, which equates to 19.3 percent of the daily average discharge of AMD from the Oak Hill Boreholes and a downward flux of 1.70x10-5 m/s across the 2.1-km-by-1.5-m West Creek stream-channel area.
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G.W. Moore; J.A. Jones; B.J. Bond
2011-01-01
The water balance equation dictates that streamflow may be reduced by transpiration. Yet temporal disequilibrium weakens the relationship between transpiration and streamflow in many cases where inputs and outputs are unbalanced. We address two critical knowledge barriers in ecohydrology with respect to time, scale dependence and lags. Study objectives were to...
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Structural system identification: Structural dynamics model validation
Energy Technology Data Exchange (ETDEWEB)
Red-Horse, J.R.
1997-04-01
Structural system identification is concerned with the development of systematic procedures and tools for developing predictive analytical models based on a physical structure`s dynamic response characteristics. It is a multidisciplinary process that involves the ability (1) to define high fidelity physics-based analysis models, (2) to acquire accurate test-derived information for physical specimens using diagnostic experiments, (3) to validate the numerical simulation model by reconciling differences that inevitably exist between the analysis model and the experimental data, and (4) to quantify uncertainties in the final system models and subsequent numerical simulations. The goal of this project was to develop structural system identification techniques and software suitable for both research and production applications in code and model validation.
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Validating the passenger traffic model for Copenhagen
DEFF Research Database (Denmark)
Overgård, Christian Hansen; VUK, Goran
2006-01-01
The paper presents a comprehensive validation procedure for the passenger traffic model for Copenhagen based on external data from the Danish national travel survey and traffic counts. The model was validated for the years 2000 to 2004, with 2004 being of particular interest because the Copenhagen...... matched the observed traffic better than those of the transit assignment model. With respect to the metro forecasts, the model over-predicts metro passenger flows by 10% to 50%. The wide range of findings from the project resulted in two actions. First, a project was started in January 2005 to upgrade...
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Bayesian risk-based decision method for model validation under uncertainty
International Nuclear Information System (INIS)
Jiang Xiaomo; Mahadevan, Sankaran
2007-01-01
This paper develops a decision-making methodology for computational model validation, considering the risk of using the current model, data support for the current model, and cost of acquiring new information to improve the model. A Bayesian decision theory-based method is developed for this purpose, using a likelihood ratio as the validation metric for model assessment. An expected risk or cost function is defined as a function of the decision costs, and the likelihood and prior of each hypothesis. The risk is minimized through correctly assigning experimental data to two decision regions based on the comparison of the likelihood ratio with a decision threshold. A Bayesian validation metric is derived based on the risk minimization criterion. Two types of validation tests are considered: pass/fail tests and system response value measurement tests. The methodology is illustrated for the validation of reliability prediction models in a tension bar and an engine blade subjected to high cycle fatigue. The proposed method can effectively integrate optimal experimental design into model validation to simultaneously reduce the cost and improve the accuracy of reliability model assessment
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Temporal variability in the suspended sediment load and streamflow of the Doce River
Oliveira, Kyssyanne Samihra Santos; Quaresma, Valéria da Silva
2017-10-01
Long-term records of streamflow and suspended sediment load provide a better understanding of the evolution of a river mouth, and its adjacent waters and a support for mitigation programs associated with extreme events and engineering projects. The aim of this study is to investigate the temporal variability in the suspended sediment load and streamflow of the Doce River to the Atlantic Ocean, between 1990 and 2013. Streamflow and suspended sediment load were analyzed at the daily, seasonal, and interannual scales. The results showed that at the daily scale, Doce River flood events are due to high intensity and short duration rainfalls, which means that there is a flashy response to rainfall. At the monthly and season scales, approximately 94% of the suspended sediment supply occurs during the wet season. Extreme hydrological events are important for the interannual scale for Doce River sediment supply to the Atlantic Ocean. The results suggest that a summation of anthropogenic interferences (deforestation, urbanization and soil degradation) led to an increase of extreme hydrological events. The findings of this study shows the importance of understanding the typical behavior of the Doce River, allowing the detection of extreme hydrological conditions, its causes and possible environmental and social consequences.
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K.L. Hatcher; J.A. Jones
2013-01-01
Large river basins transfer the water signal from the atmosphere to the ocean. Climate change is widely expected to alter streamflow and potentially disrupt water management systems. We tested the ecological resilienceâcapacity of headwater ecosystems to sustain streamflow under climate changeâand the engineering resilienceâcapacity of dam and reservoir management to...
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Validation of mentorship model for newly qualified professional ...
African Journals Online (AJOL)
Newly qualified professional nurses (NQPNs) allocated to community health care services require the use of validated model to practice independently. Validation was done to adapt and assess if the model is understood and could be implemented by NQPNs and mentors employed in community health care services.
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Validation and Adaptation of Router and Switch Models
Boltjes, B.; Fernandez Diaz, I.; Kock, B.A.; Langeveld, R.J.G.M.; Schoenmaker, G.
2003-01-01
This paper describes validating OPNET models of key devices for the next generation IP-based tactical network of the Royal Netherlands Army (RNLA). The task of TNO-FEL is to provide insight in scalability and performance of future deployed networks. Because validated models ol key Cisco equipment
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Bera, Maitreyee; Ortel, Terry W.
2018-01-12
The U.S. Geological Survey, in cooperation with DuPage County Stormwater Management Department, is testing a near real-time streamflow simulation system that assists in the management and operation of reservoirs and other flood-control structures in the Salt Creek and West Branch DuPage River drainage basins in DuPage County, Illinois. As part of this effort, the U.S. Geological Survey maintains a database of hourly meteorological and hydrologic data for use in this near real-time streamflow simulation system. Among these data are next generation weather radar-multisensor precipitation estimates and quantitative precipitation forecast data, which are retrieved from the North Central River Forecasting Center of the National Weather Service. The DuPage County streamflow simulation system uses these quantitative precipitation forecast data to create streamflow predictions for the two simulated drainage basins. This report discusses in detail how these data are processed for inclusion in the Watershed Data Management files used in the streamflow simulation system for the Salt Creek and West Branch DuPage River drainage basins.
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Mat Jan, Nur Amalina; Shabri, Ani
2017-01-01
TL-moments approach has been used in an analysis to identify the best-fitting distributions to represent the annual series of maximum streamflow data over seven stations in Johor, Malaysia. The TL-moments with different trimming values are used to estimate the parameter of the selected distributions namely: Three-parameter lognormal (LN3) and Pearson Type III (P3) distribution. The main objective of this study is to derive the TL-moments ( t 1,0), t 1 = 1,2,3,4 methods for LN3 and P3 distributions. The performance of TL-moments ( t 1,0), t 1 = 1,2,3,4 was compared with L-moments through Monte Carlo simulation and streamflow data over a station in Johor, Malaysia. The absolute error is used to test the influence of TL-moments methods on estimated probability distribution functions. From the cases in this study, the results show that TL-moments with four trimmed smallest values from the conceptual sample (TL-moments [4, 0]) of LN3 distribution was the most appropriate in most of the stations of the annual maximum streamflow series in Johor, Malaysia.
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Minihane, M.; Lettenmaier, D. P.
2012-12-01
Economic development and public health are tied to water resources development in many parts of the world. Effective use of water management infrastructure investments requires projections of future climatic and water use conditions. This is particularly true in developing countries. We explore in this work water resource availability in the Rovuma River, which lies in a sparsely-populated region of southeastern Africa, on the border of Mozambique and Tanzania. While there are only limited documented observations of flow of the Rovuma River and it's tributaries, particularly in recent years, there is widespread interest in development of the water resources of the region. The national governments are interested in hydropower potential while private companies, many of them large multinational organizations, have started irrigation programs to increase agricultural output. While the Mozambique and Tanzania governments have a joint agreement over the river development, there is a need to assess both current and potential future water resource conditions in the basin. The sustainability of these developments, however, may be affected by climate change. Here we quantify potential changes in streamflow in the Rovuma River under dry and wet climate projection scenarios using the delta method and the Variable Infiltration Capacity (VIC) macro-scale hydrology model. We then evaluate streamflow changes relative to water withdrawals required for a range of irrigated agriculture scenarios. Our analysis is intended to be a starting point for planners to consider potential impacts of both streamflow withdrawal permits (for irrigated agriculture) and future uncertain climate conditions.
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Directory of Open Access Journals (Sweden)
Huanqing Bian
2017-01-01
Full Text Available Tuotuo River basin, known as the source region of the Yangtze River, is the key area where the impact of climate change has been observed on many of the hydrological processes of this central region of the Tibetan Plateau. In this study, we examined six Global Climate Models (GCMs under three Representative Concentration Pathways (RCPs scenarios. First, the already impacted climate change was analyzed, based on the historical data available and then, the simulation results of the GCMs and RCPs were used for future scenario assessments. Results indicated that the annual mean temperature will likely be increased, ranging from −0.66 °C to 6.68 °C during the three future prediction periods (2020s, 2050s and 2080s, while the change in the annual precipitation ranged from −1.18% to 66.14%. Then, a well-known distributed hydrological soil vegetation model (DHSVM was utilized to evaluate the effects of future climate change on the streamflow dynamics. The seasonal mean streamflows, predicted by the six GCMs and the three RCPs scenarios, were also shown to likely increase, ranging from −0.52% to 22.58%. Watershed managers and regulators can use the findings from this study to better implement their conservation practices in the face of climate change.
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Directory of Open Access Journals (Sweden)
N. Wever
2017-08-01
Full Text Available The assessment of flood risks in alpine, snow-covered catchments requires an understanding of the linkage between the snow cover, soil and discharge in the stream network. Here, we apply the comprehensive, distributed model Alpine3D to investigate the role of soil moisture in the predisposition of the Dischma catchment in Switzerland to high flows from rainfall and snowmelt. The recently updated soil module of the physics-based multilayer snow cover model SNOWPACK, which solves the surface energy and mass balance in Alpine3D, is verified against soil moisture measurements at seven sites and various depths inside and in close proximity to the Dischma catchment. Measurements and simulations in such terrain are difficult and consequently, soil moisture was simulated with varying degrees of success. Differences between simulated and measured soil moisture mainly arise from an overestimation of soil freezing and an absence of a groundwater description in the Alpine3D model. Both were found to have an influence in the soil moisture measurements. Using the Alpine3D simulation as the surface scheme for a spatially explicit hydrologic response model using a travel time distribution approach for interflow and baseflow, streamflow simulations were performed for the discharge from the catchment. The streamflow simulations provided a closer agreement with observed streamflow when driving the hydrologic response model with soil water fluxes at 30 cm depth in the Alpine3D model. Performance decreased when using the 2 cm soil water flux, thereby mostly ignoring soil processes. This illustrates that the role of soil moisture is important to take into account when understanding the relationship between both snowpack runoff and rainfall and catchment discharge in high alpine terrain. However, using the soil water flux at 60 cm depth to drive the hydrologic response model also decreased its performance, indicating that an optimal soil depth to include in
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A New Streamflow-Routing (SFR1) Package to Simulate Stream-Aquifer Interaction with MODFLOW-2000
Prudic, David E.; Konikow, Leonard F.; Banta, Edward R.
2004-01-01
The increasing concern for water and its quality require improved methods to evaluate the interaction between streams and aquifers and the strong influence that streams can have on the flow and transport of contaminants through many aquifers. For this reason, a new Streamflow-Routing (SFR1) Package was written for use with the U.S. Geological Survey's MODFLOW-2000 ground-water flow model. The SFR1 Package is linked to the Lake (LAK3) Package, and both have been integrated with the Ground-Water Transport (GWT) Process of MODFLOW-2000 (MODFLOW-GWT). SFR1 replaces the previous Stream (STR1) Package, with the most important difference being that stream depth is computed at the midpoint of each reach instead of at the beginning of each reach, as was done in the original Stream Package. This approach allows for the addition and subtraction of water from runoff, precipitation, and evapotranspiration within each reach. Because the SFR1 Package computes stream depth differently than that for the original package, a different name was used to distinguish it from the original Stream (STR1) Package. The SFR1 Package has five options for simulating stream depth and four options for computing diversions from a stream. The options for computing stream depth are: a specified value; Manning's equation (using a wide rectangular channel or an eight-point cross section); a power equation; or a table of values that relate flow to depth and width. Each stream segment can have a different option. Outflow from lakes can be computed using the same options. Because the wetted perimeter is computed for the eight-point cross section and width is computed for the power equation and table of values, the streambed conductance term no longer needs to be calculated externally whenever the area of streambed changes as a function of flow. The concentration of solute is computed in a stream network when MODFLOW-GWT is used in conjunction with the SFR1 Package. The concentration of a solute in a
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Matte, Simon; Boucher, Marie-Amélie; Boucher, Vincent; Fortier Filion, Thomas-Charles
2017-06-01
A large effort has been made over the past 10 years to promote the operational use of probabilistic or ensemble streamflow forecasts. Numerous studies have shown that ensemble forecasts are of higher quality than deterministic ones. Many studies also conclude that decisions based on ensemble rather than deterministic forecasts lead to better decisions in the context of flood mitigation. Hence, it is believed that ensemble forecasts possess a greater economic and social value for both decision makers and the general population. However, the vast majority of, if not all, existing hydro-economic studies rely on a cost-loss ratio framework that assumes a risk-neutral decision maker. To overcome this important flaw, this study borrows from economics and evaluates the economic value of early warning flood systems using the well-known Constant Absolute Risk Aversion (CARA) utility function, which explicitly accounts for the level of risk aversion of the decision maker. This new framework allows for the full exploitation of the information related to a forecasts' uncertainty, making it especially suited for the economic assessment of ensemble or probabilistic forecasts. Rather than comparing deterministic and ensemble forecasts, this study focuses on comparing different types of ensemble forecasts. There are multiple ways of assessing and representing forecast uncertainty. Consequently, there exist many different means of building an ensemble forecasting system for future streamflow. One such possibility is to dress deterministic forecasts using the statistics of past error forecasts. Such dressing methods are popular among operational agencies because of their simplicity and intuitiveness. Another approach is the use of ensemble meteorological forecasts for precipitation and temperature, which are then provided as inputs to one or many hydrological model(s). In this study, three concurrent ensemble streamflow forecasting systems are compared: simple statistically dressed
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Development of a Conservative Model Validation Approach for Reliable Analysis
2015-01-01
CIE 2015 August 2-5, 2015, Boston, Massachusetts, USA [DRAFT] DETC2015-46982 DEVELOPMENT OF A CONSERVATIVE MODEL VALIDATION APPROACH FOR RELIABLE...obtain a conservative simulation model for reliable design even with limited experimental data. Very little research has taken into account the...3, the proposed conservative model validation is briefly compared to the conventional model validation approach. Section 4 describes how to account
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Wang, Taihua; Yang, Hanbo; Yang, Dawen; Qin, Yue; Wang, Yuhan
2018-03-01
The source region of the Yellow River (SRYR) is greatly important for water resources throughout the entire Yellow River Basin. Streamflow in the SRYR has experienced great changes over the past few decades, which is closely related to the frozen ground degradation; however, the extent of this influence is still unclear. In this study, the air freezing index (DDFa) is selected as an indicator for the degree of frozen ground degradation. A water-energy balance equation within the Budyko framework is employed to quantify the streamflow response to the direct impact of climate change, which manifests as changes in the precipitation and potential evapotranspiration, as well as the impact of frozen ground degradation, which can be regarded as part of the indirect impact of climate change. The results show that the direct impact of climate change and the impact of frozen ground degradation can explain 55% and 33%, respectively, of the streamflow decrease for the entire SRYR from Period 1 (1965-1989) to Period 2 (1990-2003). In the permafrost-dominated region upstream of the Jimai hydrological station, the impact of frozen ground degradation can explain 71% of the streamflow decrease. From Period 2 (1990-2003) to Period 3 (2004-2015), the observed streamflow did not increase as much as the precipitation; this could be attributed to the combined effects of increasing potential evapotranspiration and more importantly, frozen ground degradation. Frozen ground degradation could influence streamflow by increasing the groundwater storage when the active layer thickness increases in permafrost-dominated regions. These findings will help develop a better understanding of the impact of frozen ground degradation on water resources in the Tibetan Plateau.
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Lombard, Pamela J.
2018-04-30
The U.S. Geological Survey, in cooperation with the International Joint Commission, compiled historical data on regulated streamflows and lake levels and estimated unregulated streamflows and lake levels on Forest City Stream at Forest City, Maine, and East Grand Lake on the United States-Canada border between Maine and New Brunswick to study the effects on streamflows and lake levels if two or all three dam gates are left open. Historical regulated monthly mean streamflows in Forest City Stream at the outlet of East Grand Lake (referred to as Grand Lake by Environment Canada) fluctuated between 114 cubic feet per second (ft3 /s) (3.23 cubic meters per second [m3 /s]) in November and 318 ft3 /s (9.01 m3 /s) in September from 1975 to 2015 according to Environment Canada streamgaging data. Unregulated monthly mean streamflows at this location estimated from regression equations for unregulated sites range from 59.2 ft3 /s (1.68 m3 /s) in September to 653 ft3 /s (18.5 m3 /s) in April. Historical lake levels in East Grand Lake fluctuated between 431.3 feet (ft) (131.5 meters [m]) in October and 434.0 ft (132.3 m) in May from 1969 to 2016 according to Environment Canada lake level data for East Grand Lake. Average monthly lake levels modeled by using the estimated hydrology for unregulated flows, and an outflow rating built from a hydraulic model with all gates at the dam open, range from 427.7 ft (130.4 m) in September to 431.1 ft (131.4 m) in April. Average monthly lake levels would likely be from 1.8 to 5.4 ft (0.55 to 1.6 m) lower with the gates at the dam opened than they have been historically. The greatest lake level changes would be from June through September.
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Wood, Andy; Clark, Elizabeth; Mendoza, Pablo; Nijssen, Bart; Newman, Andy; Clark, Martyn; Nowak, Kenneth; Arnold, Jeffrey
2017-04-01
Many if not most national operational streamflow prediction systems rely on a forecaster-in-the-loop approach that require the hands-on-effort of an experienced human forecaster. This approach evolved from the need to correct for long-standing deficiencies in the models and datasets used in forecasting, and the practice often leads to skillful flow predictions despite the use of relatively simple, conceptual models. Yet the 'in-the-loop' forecast process is not reproducible, which limits opportunities to assess and incorporate new techniques systematically, and the effort required to make forecasts in this way is an obstacle to expanding forecast services - e.g., though adding new forecast locations or more frequent forecast updates, running more complex models, or producing forecast and hindcasts that can support verification. In the last decade, the hydrologic forecasting community has begun develop more centralized, 'over-the-loop' systems. The quality of these new forecast products will depend on their ability to leverage research in areas including earth system modeling, parameter estimation, data assimilation, statistical post-processing, weather and climate prediction, verification, and uncertainty estimation through the use of ensembles. Currently, many national operational streamflow forecasting and water management communities have little experience with the strengths and weaknesses of over-the-loop approaches, even as such systems are beginning to be deployed operationally in centers such as ECMWF. There is thus a need both to evaluate these forecasting advances and to demonstrate their potential in a public arena, raising awareness in forecast user communities and development programs alike. To address this need, the US National Center for Atmospheric Research is collaborating with the University of Washington, the Bureau of Reclamation and the US Army Corps of Engineers, using the NCAR 'System for Hydromet Analysis Research and Prediction Applications
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Validation of ecological state space models using the Laplace approximation
DEFF Research Database (Denmark)
Thygesen, Uffe Høgsbro; Albertsen, Christoffer Moesgaard; Berg, Casper Willestofte
2017-01-01
Many statistical models in ecology follow the state space paradigm. For such models, the important step of model validation rarely receives as much attention as estimation or hypothesis testing, perhaps due to lack of available algorithms and software. Model validation is often based on a naive...... for estimation in general mixed effects models. Implementing one-step predictions in the R package Template Model Builder, we demonstrate that it is possible to perform model validation with little effort, even if the ecological model is multivariate, has non-linear dynamics, and whether observations...... useful directions in which the model could be improved....
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A national study of the streamflow data-collection program
Benson, Manuel A.; Carter, Rolland William
1973-01-01
The streamflow data program of the U.S. Geological Survey was evaluated in a nationwide study during 1970. The principal elements of the study were (1) establishing the objectives and goals of the program, (2) analyzing all available data to determine which of the goals have already been met, (3) considering alternate means of meeting the remaining goals, and (4) identifying the elements which should be included in the future program.
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Bayless, E. Randall; Cinotto, Peter J.; Ulery, Randy L.; Taylor, Charles J.; McCombs, Gregory K.; Kim, Moon H.; Nelson, Hugh L.
2014-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Army Corps of Engineers (USACE) and the Indiana Office of Community and Rural Affairs (OCRA), conducted a study of the upper Lost River watershed in Orange County, Indiana, from 2012 to 2013. Streamflow and groundwater data were collected at 10 data-collection sites from at least October 2012 until April 2013, and a preliminary Water Availability Tool for Environmental Resources (WATER)-TOPMODEL based hydrologic model was created to increase understanding of the complex, karstic hydraulic and hydrologic system present in the upper Lost River watershed, Orange County, Ind. Statistical assessment of the optimized hydrologic-model results were promising and returned correlation coefficients for simulated and measured stream discharge of 0.58 and 0.60 and Nash-Sutcliffe efficiency values of 0.56 and 0.39 for USGS streamflow-gaging stations 03373530 (Lost River near Leipsic, Ind.), and 03373560 (Lost River near Prospect, Ind.), respectively. Additional information to refine drainage divides is needed before applying the model to the entire karst region of south-central Indiana. Surface-water and groundwater data were used to tentatively quantify the complex hydrologic processes taking place within the watershed and provide increased understanding for future modeling and management applications. The data indicate that during wet-weather periods and after certain intense storms, the hydraulic capacity of swallow holes and subsurface conduits is overwhelmed with excess water that flows onto the surface in dry-bed relic stream channels and karst paleovalleys. Analysis of discharge data collected at USGS streamflow-gaging station 03373550 (Orangeville Rise, at Orangeville, Ind.), and other ancillary data-collection sites in the watershed, indicate that a bounding condition is likely present, and drainage from the underlying karst conduit system is potentially limited to near 200 cubic feet per second. This
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Advanced training simulator models. Implementation and validation
International Nuclear Information System (INIS)
Borkowsky, Jeffrey; Judd, Jerry; Belblidia, Lotfi; O'farrell, David; Andersen, Peter
2008-01-01
Modern training simulators are required to replicate plant data for both thermal-hydraulic and neutronic response. Replication is required such that reactivity manipulation on the simulator properly trains the operator for reactivity manipulation at the plant. This paper discusses advanced models which perform this function in real-time using the coupled code system THOR/S3R. This code system models the all fluids systems in detail using an advanced, two-phase thermal-hydraulic a model. The nuclear core is modeled using an advanced, three-dimensional nodal method and also by using cycle-specific nuclear data. These models are configured to run interactively from a graphical instructor station or handware operation panels. The simulator models are theoretically rigorous and are expected to replicate the physics of the plant. However, to verify replication, the models must be independently assessed. Plant data is the preferred validation method, but plant data is often not available for many important training scenarios. In the absence of data, validation may be obtained by slower-than-real-time transient analysis. This analysis can be performed by coupling a safety analysis code and a core design code. Such a coupling exists between the codes RELAP5 and SIMULATE-3K (S3K). RELAP5/S3K is used to validate the real-time model for several postulated plant events. (author)
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Roberts, James J.; Bruce, James F.; Zuellig, Robert E.
2018-01-08
The analysis described in this report is part of a longterm project monitoring the biological communities, habitat, and water quality of the Fountain Creek Basin. Biology, habitat, and water-quality data have been collected at 10 sites since 2003. These data include annual samples of aquatic invertebrate communities, fish communities, water quality, and quantitative riverine habitat. This report examines trends in biological communities from 2003 to 2016 and explores relationships between biological communities and abiotic variables (antecedent streamflow, physical habitat, and water quality). Six biological metrics (three invertebrate and three fish) and four individual fish species were used to examine trends in these data and how streamflow, habitat, and (or) water quality may explain these trends. The analysis of 79 trends shows that the majority of significant trends decreased over the trend period. Overall, 19 trends before adjustments for streamflow in the fish (12) and invertebrate (7) metrics were all decreasing except for the metric Invertebrate Species Richness at the most upstream site in Monument Creek. Seven of these trends were explained by streamflow and four trends were revealed that were originally masked by variability in antecedent streamflow. Only two sites (Jimmy Camp Creek at Fountain, CO and Fountain Creek near Pinon, CO) had no trends in the fish or invertebrate metrics. Ten of the streamflow-adjusted trends were explained by habitat, one was explained by water quality, and five were not explained by any of the variables that were tested. Overall, from 2003 to 2016, all the fish metric trends were decreasing with an average decline of 40 percent, and invertebrate metrics decreased on average by 9.5 percent. A potential peak streamflow threshold was identified above which there is severely limited production of age-0 flathead chub (Platygobio gracilis).
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Wood, Molly S.
2014-01-01
The U.S. Geological Survey (USGS), in cooperation with the Bureau of Land Management (BLM), estimated streamflow statistics for stream segments designated “Wild,” “Scenic,” or “Recreational” under the National Wild and Scenic Rivers System in the Owyhee Canyonlands Wilderness in southwestern Idaho. The streamflow statistics were used by the BLM to develop and file a draft, federal reserved water right claim to protect federally designated “outstanding remarkable values” in the Jarbidge River. The BLM determined that the daily mean streamflow equaled or exceeded 20, 50, and 80 percent of the time during bimonthly periods (two periods per month) and the bankfull (66.7-percent annual exceedance probability) streamflow are important thresholds for maintaining outstanding remarkable values. Although streamflow statistics for the Jarbidge River below Jarbidge, Nevada (USGS 13162225) were published previously in 2013 and used for the draft water right claim, the BLM and USGS have since recognized the need to refine streamflow statistics given the approximate 40 river mile distance and intervening tributaries between the original point of estimation (USGS 13162225) and at the mouth of the Jarbidge River, which is the downstream end of the Wild and Scenic River segment. A drainage-area-ratio method was used in 2013 to estimate bimonthly exceedance probability streamflow statistics at the mouth of the Jarbidge River based on available streamgage data on the Jarbidge and East Fork Jarbidge Rivers. The resulting bimonthly streamflow statistics were further adjusted using a scaling factor calculated from a water balance on streamflow statistics calculated for the Bruneau and East Fork Bruneau Rivers and Sheep Creek. The final, adjusted bimonthly exceedance probability and bankfull streamflow statistics compared well with available verification datasets (including discrete streamflow measurements made at the mouth of the Jarbidge River) and are considered the
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Streamflow investigations on a reach of Hobble Creek near Springville, Utah
Gerner, Steven J.
2017-07-27
The Central Utah Water Conservancy District (CUWCD) is proposing to deliver supplemental flow to Hobble Creek from Strawberry Reservoir through the Mapleton-Springville Lateral pipeline. A substantial portion of the supplemental water is intended to benefit June Sucker recovery and other fish and wildlife along Hobble Creek. The objective of this study was to determine gains or losses of water in a section of Hobble Creek between the Island Dam and the Swenson Dam (the primary study reach) during different seasons and flow conditions.Paired measurements of flow in Hobble Creek were made during June to November 2016, at sites bracketing the primary study reach from site HC3 to HC6. These measurements showed increased streamflow in this reach that ranged from 6.1 cubic feet per second (ft3/s) to 9.3 ft3/s. During August and November, two sets of measurements were made at several locations along the study reach to document baseline conditions, and then an additional amount of water (a pulse of about 9–10 ft3/s) from Strawberry Reservoir through the Mapleton-Springville Lateral pipeline, was added to the reach. During the August 23 measurements, the average change at the upstream site (HC3) relative to the pulse was 9.3 ft3/s, and the average change at the downstream site (HC6) was about 8.4 ft3/s, leaving about 0.9 ft3/s of the additional water unaccounted for at site HC6. However, there was no significant difference between the net streamflow volume at sites HC3 and HC6 associated with the pulse that would indicate water was being lost. During the November 7–9 streamflow measurements, the average change in discharge at site HC3 relative to an increase in flow from the Mapleton-Springville Lateral pipeline (the pulse) was 9.6 ft3/s, and the average change at site HC6 was about 9.8 ft3/s. On the basis of these measurements it appears that the entire amount of the pulse added to the stream at site HC3 was accounted for at site HC6. Additionally, there was no
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Influence of diurnal variations in stream temperature on streamflow loss and groundwater recharge
Constantz, Jim; Thomas, Carole L.; Zellweger, Gary W.
1994-01-01
We demonstrate that for losing reaches with significant diurnal variations in stream temperature, the effect of stream temperature on streambed seepage is a major factor contributing to reduced afternoon streamflows. An explanation is based on the effect of stream temperature on the hydraulic conductivity of the streambed, which can be expected to double in the 0° to 25°C temperature range. Results are presented for field experiments in which stream discharge and temperature were continuously measured for several days over losing reaches at St. Kevin Gulch, Colorado, and Tijeras Arroyo, New Mexico. At St. Kevin Gulch in July 1991, the diurnal stream temperature in the 160-m study reach ranged from about 4° to 18°C, discharges ranged from 10 to 18 L/s, and streamflow loss in the study reach ranged from 2.7 to 3.7 L/s. On the basis of measured stream temperature variations, the predicted change in conductivity was about 38%; the measured change in stream loss was about 26%, suggesting that streambed temperature varied less than the stream temperature. At Tijeras Arroyo in May 1992, diurnal stream temperature in the 655-m study reach ranged from about 10° to 25°C and discharge ranged from 25 to 55 L/s. Streamflow loss was converted to infiltration rates by factoring in the changing stream reach surface area and streamflow losses due to evaporation rates as measured in a hemispherical evaporation chamber. Infiltration rates ranged from about 0.7 to 2.0 m/d, depending on time and location. Based on measured stream temperature variations, the predicted change in conductivity was 29%; the measured change in infiltration was also about 27%. This suggests that high infiltration rates cause rapid convection of heat to the streambed. Evapotranspiration losses were estimated for the reach and adjacent flood plain within the arroyo. On the basis of these estimates, only about 5% of flow loss was consumed via stream evaporation and stream-side evapotranspiration
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Changes in streamflow characteristics in Wisconsin as related to precipitation and land use
Gebert, Warren A.; Garn, Herbert S.; Rose, William J.
2016-01-19
Streamflow characteristics were determined for 15 longterm streamflow-gaging stations for the periods 1915–2008, 1915–68, and 1969–2008 to identify trends. Stations selected represent flow characteristics for the major river basins in Wisconsin. Trends were statistically significant at the 95 percent confidence level at 13 of the 15 streamflow-gaging stations for various streamflow characteristics for 1915–2008. Most trends indicated increases in low flows for streams with agriculture as the dominant land use. The three most important findings are: increases in low flows and average flows in agricultural watersheds, decreases in flood peak discharge for many streams in both agricultural and forested watersheds, and climatic change occurred with increasing annual precipitation and changes in monthly occurrence of precipitation. When the 1915–68 period is compared to the 1969–2008 period, the annual 7-day low flow increased an average of 60 percent for nine streams in agricultural areas as compared to a 15 percent increase for the five forested streams. Average annual flow for the same periods increased 23 percent for the agriculture streams and 0.6 percent for the forested streams. The annual flood peak discharge for the same periods decreased 15 percent for agriculture streams and 8 percent for forested streams. The largest increase in the annual 7-day low flow was 117 percent, the largest increase in annual average flow was 41 percent, and the largest decrease in annual peak discharge was 51 percent. The trends in streamflow characteristics affect frequency characteristics, which are used for a variety of design and compliance purposes. The frequencies for the 1969–2008 period were compared to frequencies for the 1915–68 period. The 7-day, 10-year (Q7, 10) low flow increased 91 percent for nine agricultural streams, while the five forested streams had an increase of 18 percent. The 100-year flood peak discharge decreased an average of 15 percent
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Using hydrologic landscape classification to assess streamflow vulnerability to changes in climate
Identifying regions with similar hydrology is useful for assessing water quality and quantity across the U.S., especially areas that are difficult or costly to monitor. For example, hydrologic landscapes (HLs) have been used to map streamflow variability and assess the spatial di...
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A dynamical-systems approach for computing ice-affected streamflow
Holtschlag, David J.
1996-01-01
A dynamical-systems approach was developed and evaluated for computing ice-affected streamflow. The approach provides for dynamic simulation and parameter estimation of site-specific equations relating ice effects to routinely measured environmental variables. Comparison indicates that results from the dynamical-systems approach ranked higher than results from 11 analytical methods previously investigated on the basis of accuracy and feasibility criteria. Additional research will likely lead to further improvements in the approach.
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Temporal rainfall estimation using input data reduction and model inversion
Wright, A. J.; Vrugt, J. A.; Walker, J. P.; Pauwels, V. R. N.
2016-12-01
Floods are devastating natural hazards. To provide accurate, precise and timely flood forecasts there is a need to understand the uncertainties associated with temporal rainfall and model parameters. The estimation of temporal rainfall and model parameter distributions from streamflow observations in complex dynamic catchments adds skill to current areal rainfall estimation methods, allows for the uncertainty of rainfall input to be considered when estimating model parameters and provides the ability to estimate rainfall from poorly gauged catchments. Current methods to estimate temporal rainfall distributions from streamflow are unable to adequately explain and invert complex non-linear hydrologic systems. This study uses the Discrete Wavelet Transform (DWT) to reduce rainfall dimensionality for the catchment of Warwick, Queensland, Australia. The reduction of rainfall to DWT coefficients allows the input rainfall time series to be simultaneously estimated along with model parameters. The estimation process is conducted using multi-chain Markov chain Monte Carlo simulation with the DREAMZS algorithm. The use of a likelihood function that considers both rainfall and streamflow error allows for model parameter and temporal rainfall distributions to be estimated. Estimation of the wavelet approximation coefficients of lower order decomposition structures was able to estimate the most realistic temporal rainfall distributions. These rainfall estimates were all able to simulate streamflow that was superior to the results of a traditional calibration approach. It is shown that the choice of wavelet has a considerable impact on the robustness of the inversion. The results demonstrate that streamflow data contains sufficient information to estimate temporal rainfall and model parameter distributions. The extent and variance of rainfall time series that are able to simulate streamflow that is superior to that simulated by a traditional calibration approach is a
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van Soest, Johan; Meldolesi, Elisa; van Stiphout, Ruud; Gatta, Roberto; Damiani, Andrea; Valentini, Vincenzo; Lambin, Philippe; Dekker, Andre
2017-09-01
Multiple models have been developed to predict pathologic complete response (pCR) in locally advanced rectal cancer patients. Unfortunately, validation of these models normally omit the implications of cohort differences on prediction model performance. In this work, we will perform a prospective validation of three pCR models, including information whether this validation will target transferability or reproducibility (cohort differences) of the given models. We applied a novel methodology, the cohort differences model, to predict whether a patient belongs to the training or to the validation cohort. If the cohort differences model performs well, it would suggest a large difference in cohort characteristics meaning we would validate the transferability of the model rather than reproducibility. We tested our method in a prospective validation of three existing models for pCR prediction in 154 patients. Our results showed a large difference between training and validation cohort for one of the three tested models [Area under the Receiver Operating Curve (AUC) cohort differences model: 0.85], signaling the validation leans towards transferability. Two out of three models had a lower AUC for validation (0.66 and 0.58), one model showed a higher AUC in the validation cohort (0.70). We have successfully applied a new methodology in the validation of three prediction models, which allows us to indicate if a validation targeted transferability (large differences between training/validation cohort) or reproducibility (small cohort differences). © 2017 American Association of Physicists in Medicine.
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Ryberg, Karen R.; Vecchia, Aldo V.
2013-01-01
The seawaveQ R package fits a parametric regression model (seawaveQ) to pesticide concentration data from streamwater samples to assess variability and trends. The model incorporates the strong seasonality and high degree of censoring common in pesticide data and users can incorporate numerous ancillary variables, such as streamflow anomalies. The model is fitted to pesticide data using maximum likelihood methods for censored data and is robust in terms of pesticide, stream location, and degree of censoring of the concentration data. This R package standardizes this methodology for trend analysis, documents the code, and provides help and tutorial information, as well as providing additional utility functions for plotting pesticide and other chemical concentration data.
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Voss, Frank D.; Mastin, Mark C.
2012-01-01
The purpose of this project was to demonstrate the capabilities of an existing watershed model and downscaling procedures to provide simulated hydrological data over various greenhouse gas emission scenarios for use in the Methow River framework prototype. An existing watershed model was used to simulate daily time series of streamflow and basin-wide hydrologic variables for baseline conditions (1990–2000), and then for all combinations of three greenhouse gas emission scenarios and five general circulation models for future conditions (2008–2095). Input data for 18 precipitation and 17 temperature model input sites were generated using statistical techniques to downscale general circulation model data. The simulated results were averaged using an 11-year moving window to characterize the central year of the window to provide simulated data for water years 2008–2095.