Sample records for hydrology model predictions

  1. Refining the committee approach and uncertainty prediction in hydrological modelling

    NARCIS (Netherlands)

    Kayastha, N.


    Due to the complexity of hydrological systems a single model may be unable to capture the full range of a catchment response and accurately predict the streamflows. The multi modelling approach opens up possibilities for handling such difficulties and allows improve the predictive capability of

  2. Merging Multiple Climate Model Forecasts for Seasonal Hydrologic Predictions (United States)

    Luo, L.; Wood, E. F.; Pan, M.; Li, H.


    Skillful seasonal hydrologic predictions are required in water resource management, preparation for drought and its impacts, energy planning, and many other related sectors. In this study, a seasonal hydrologic ensemble prediction system is developed and evaluated over the Eastern U.S., with focus on the Ohio River basin. The seasonal hydrologic prediction system utilizes a hydrologic model (in this case the Variable Infiltration Capacity model) as the central element for producing ensemble hydrologic predictions of soil moisture, snow and streamflow with lead times up to 6 months. The uniqueness of this forecast system is in the method for generating ensemble atmospheric forcings for the forecast period. It merges seasonal climate predictions from multiple climate models with observed climatology in a Bayesian framework such that the uncertainties related to the atmospheric forcings can be reduced and better quantified. This framework also downscales the climate model forecasts to scales appropriate for hydrologic prediction and uses a rank structure of selected historical forcings to ensure that generated ensembles of daily meteorological forcings have reasonable patterns in space and time. Three types of forecasts were performed in the study: those using information from NCEP's Climate Forecast System (CFS), those using information from CFS and the European Union funded multi-model prediction project called DEMETER, and those based the Extended Streamflow Prediction (ESP) approach. Forecasts (CFS, CFS+DEMETER and ESP) were made with the system for the summer periods (May to October) for 1981 - 1999, and represent forecast information from one climate model, eight climate models and none, respectively. The differences in forecast skills between CFS, CFS+DEMETER and ESP reflect the improvement with the new forecast method against the current hydrological operational approach, which is based on ESP. The forecast for the summer 1988 shows very promising skill in

  3. OpenDA-WFLOW framework for improving hydrologic predictions using distributed hydrologic models (United States)

    Weerts, Albrecht; Schellekens, Jaap; Kockx, Arno; Hummel, Stef


    Data assimilation (DA) holds considerable potential for improving hydrologic predictions (Liu et al., 2012) and increase the potential for early warning and/or smart water management. However, advances in hydrologic DA research have not yet been adequately or timely implemented in operational forecast systems to improve the skill of forecasts for better informed real-world decision making. The objective of this work is to highlight the development of a generic linkage of the open source OpenDA package and the open source community hydrologic modeling framework Openstreams/WFLOW and its application in operational hydrological forecasting on various spatial scales. The coupling between OpenDA and Openstreams/wflow framework is based on the emerging standard Basic Model Interface (BMI) as advocated by CSDMS using cross-platform webservices (i.e. Apache Thrift) developed by Hut et al. (2016). The potential application of the OpenDA-WFLOW for operational hydrologic forecasting including its integration with Delft-FEWS (used by more than 40 operational forecast centers around the world (Werner et al., 2013)) is demonstrated by the presented case studies. We will also highlight the possibility to give real-time insight into the working of the DA methods applied for supporting the forecaster as mentioned as one of the burning issues by Liu et al., (2012).

  4. Statistical procedures for evaluating daily and monthly hydrologic model predictions (United States)

    Coffey, M.E.; Workman, S.R.; Taraba, J.L.; Fogle, A.W.


    The overall study objective was to evaluate the applicability of different qualitative and quantitative methods for comparing daily and monthly SWAT computer model hydrologic streamflow predictions to observed data, and to recommend statistical methods for use in future model evaluations. Statistical methods were tested using daily streamflows and monthly equivalent runoff depths. The statistical techniques included linear regression, Nash-Sutcliffe efficiency, nonparametric tests, t-test, objective functions, autocorrelation, and cross-correlation. None of the methods specifically applied to the non-normal distribution and dependence between data points for the daily predicted and observed data. Of the tested methods, median objective functions, sign test, autocorrelation, and cross-correlation were most applicable for the daily data. The robust coefficient of determination (CD*) and robust modeling efficiency (EF*) objective functions were the preferred methods for daily model results due to the ease of comparing these values with a fixed ideal reference value of one. Predicted and observed monthly totals were more normally distributed, and there was less dependence between individual monthly totals than was observed for the corresponding predicted and observed daily values. More statistical methods were available for comparing SWAT model-predicted and observed monthly totals. The 1995 monthly SWAT model predictions and observed data had a regression Rr2 of 0.70, a Nash-Sutcliffe efficiency of 0.41, and the t-test failed to reject the equal data means hypothesis. The Nash-Sutcliffe coefficient and the R r2 coefficient were the preferred methods for monthly results due to the ability to compare these coefficients to a set ideal value of one.

  5. Predicting hydrological signatures in ungauged catchments using spatial interpolation, index model, and rainfall-runoff modelling (United States)

    Zhang, Yongqiang; Vaze, Jai; Chiew, Francis H. S.; Teng, Jin; Li, Ming


    Understanding a catchment's behaviours in terms of its underlying hydrological signatures is a fundamental task in surface water hydrology. It can help in water resource management, catchment classification, and prediction of runoff time series. This study investigated three approaches for predicting six hydrological signatures in southeastern Australia. These approaches were (1) spatial interpolation with three weighting schemes, (2) index model that estimates hydrological signatures using catchment characteristics, and (3) classical rainfall-runoff modelling. The six hydrological signatures fell into two categories: (1) long-term aggregated signatures - annual runoff coefficient, mean of log-transformed daily runoff, and zero flow ratio, and (2) signatures obtained from daily flow metrics - concavity index, seasonality ratio of runoff, and standard deviation of log-transformed daily flow. A total of 228 unregulated catchments were selected, with half the catchments randomly selected as gauged (or donors) for model building and the rest considered as ungauged (or receivers) to evaluate performance of the three approaches. The results showed that for two long-term aggregated signatures - the log-transformed daily runoff and runoff coefficient, the index model and rainfall-runoff modelling performed similarly, and were better than the spatial interpolation methods. For the zero flow ratio, the index model was best and the rainfall-runoff modelling performed worst. The other three signatures, derived from daily flow metrics and considered to be salient flow characteristics, were best predicted by the spatial interpolation methods of inverse distance weighting (IDW) and kriging. Comparison of flow duration curves predicted by the three approaches showed that the IDW method was best. The results found here provide guidelines for choosing the most appropriate approach for predicting hydrological behaviours at large scales.

  6. Hydrologic Predictions in the Anthropocene: Exploration with Co-evolutionary Socio-hydrologic Models (United States)

    Sivapalan, Murugesu; Tian, Fuqiang; Liu, Dengfeng


    Socio-hydrology studies the co-evolution and self-organization of humans in the hydrologic landscape, which requires a thorough understanding of the complex interactions between humans and water. On the one hand, the nature of water availability greatly impacts the development of society. On the other hand, humans can significantly alter the spatio-temporal distribution of water and in this way provide feedback to the society itself. The human-water system functions underlying such complex human-water interactions are not well understood. Exploratory models with the appropriate level of simplification in any given area can be valuable to understand these functions and the self-organization associated with socio-hydrology. In this study, a simple coupled modeling framework for socio-hydrology co-evolution is developed, and is used to illustrate the explanatory power of such models. In the Tarim River, humans depend heavily on agricultural production (other industries can be ignored for a start), and the social processes can be described principally by two variables, i.e., irrigated-area and human population. The eco-hydrological processes are expressed in terms of area under natural vegetation and stream discharge. The study area is the middle and the lower reaches of the Tarim River, which is divided into two modeling units, i.e. middle reach and lower reach. In each modeling unit, four ordinary differential equations are used to simulate the dynamics of the hydrological system represented by stream discharge, ecological system represented by area under natural vegetation, the economic system represented by irrigated area under agriculture and social system represented by human population. The four dominant variables are coupled together by several internal variables. For example, the stream discharge is coupled to irrigated area by the colonization rate and mortality rate of the irrigated area in the middle reach and the irrigated area is coupled to stream

  7. Hydrological modelling in forested systems (United States)

    This chapter provides a brief overview of forest hydrology modelling approaches for answering important global research and management questions. Many hundreds of hydrological models have been applied globally across multiple decades to represent and predict forest hydrological p...

  8. Improved understanding and prediction of the hydrologic response of highly urbanized catchments through development of the Illinois Urban Hydrologic Model (United States)

    Cantone, Joshua; Schmidt, Arthur


    What happens to the rain in highly urbanized catchments? That is the question that urban hydrologists must ask themselves when trying to integrate the hydrologic and hydraulic processes that affect the hydrologic response of urban catchments. The Illinois Urban Hydrologic Model (IUHM) has been developed to help answer this question and improve understanding and prediction of hydrologic response in highly urbanized catchments. Urban catchments are significantly different than natural watersheds, but there are similarities that allow features of the pioneering geomorphologic instantaneous unit hydrograph concept developed for natural watersheds to be adapted to the urban setting. This probabilistically based approach is a marked departure from the traditional deterministic models used to design and simulate urban sewer systems and does not have the burdensome input data requirements that detailed deterministic models possess. Application of IUHM to the CDS-51 catchment located in the village of Dolton, Illinois, highlights the model's ability to predict the hydrologic response of the catchment as well as the widely accepted SWMM model and is in accordance with observed data recorded by the United States Geological Survey. In addition, the unique structure and organization of urban sewer networks make it possible to characterize a set of ratios for urban catchments that allow IUHM to be applied when detailed input data are not available.

  9. Hydrological-niche models predict water plant functional group distributions in diverse wetland types. (United States)

    Deane, David C; Nicol, Jason M; Gehrig, Susan L; Harding, Claire; Aldridge, Kane T; Goodman, Abigail M; Brookes, Justin D


    Human use of water resources threatens environmental water supplies. If resource managers are to develop policies that avoid unacceptable ecological impacts, some means to predict ecosystem response to changes in water availability is necessary. This is difficult to achieve at spatial scales relevant for water resource management because of the high natural variability in ecosystem hydrology and ecology. Water plant functional groups classify species with similar hydrological niche preferences together, allowing a qualitative means to generalize community responses to changes in hydrology. We tested the potential for functional groups in making quantitative prediction of water plant functional group distributions across diverse wetland types over a large geographical extent. We sampled wetlands covering a broad range of hydrogeomorphic and salinity conditions in South Australia, collecting both hydrological and floristic data from 687 quadrats across 28 wetland hydrological gradients. We built hydrological-niche models for eight water plant functional groups using a range of candidate models combining different surface inundation metrics. We then tested the predictive performance of top-ranked individual and averaged models for each functional group. Cross validation showed that models achieved acceptable predictive performance, with correct classification rates in the range 0.68-0.95. Model predictions can be made at any spatial scale that hydrological data are available and could be implemented in a geographical information system. We show the response of water plant functional groups to inundation is consistent enough across diverse wetland types to quantify the probability of hydrological impacts over regional spatial scales. © 2017 by the Ecological Society of America.

  10. Integrating geophysics and hydrology for reducing the uncertainty of groundwater model predictions and improved prediction performance

    DEFF Research Database (Denmark)

    Christensen, Nikolaj Kruse; Christensen, Steen; Ferre, Ty

    constructed from geological and hydrological data. However, geophysical data are increasingly used to inform hydrogeologic models because they are collected at lower cost and much higher density than geological and hydrological data. Despite increased use of geophysics, it is still unclear whether......, ‘true’, hydrogeological and geophysical systems. The two types of ‘true’ systems can be used together with corresponding forward codes to generate hydrological and geophysical datasets, respectively. These synthetic datasets can be interpreted using any hydrogeophysical inversion scheme...

  11. Benchmarking hydrological model predictive capability for UK River flows and flood peaks. (United States)

    Lane, Rosanna; Coxon, Gemma; Freer, Jim; Wagener, Thorsten


    Data and hydrological models are now available for national hydrological analyses. However, hydrological model performance varies between catchments, and lumped, conceptual models are not able to produce adequate simulations everywhere. This study aims to benchmark hydrological model performance for catchments across the United Kingdom within an uncertainty analysis framework. We have applied four hydrological models from the FUSE framework to 1128 catchments across the UK. These models are all lumped models and run at a daily timestep, but differ in the model structural architecture and process parameterisations, therefore producing different but equally plausible simulations. We apply FUSE over a 20 year period from 1988-2008, within a GLUE Monte Carlo uncertainty analyses framework. Model performance was evaluated for each catchment, model structure and parameter set using standard performance metrics. These were calculated both for the whole time series and to assess seasonal differences in model performance. The GLUE uncertainty analysis framework was then applied to produce simulated 5th and 95th percentile uncertainty bounds for the daily flow time-series and additionally the annual maximum prediction bounds for each catchment. The results show that the model performance varies significantly in space and time depending on catchment characteristics including climate, geology and human impact. We identify regions where models are systematically failing to produce good results, and present reasons why this could be the case. We also identify regions or catchment characteristics where one model performs better than others, and have explored what structural component or parameterisation enables certain models to produce better simulations in these catchments. Model predictive capability was assessed for each catchment, through looking at the ability of the models to produce discharge prediction bounds which successfully bound the observed discharge. These results

  12. Prediction Of Hydrological Models’ Uncertainty By A Committee Of Machine Learning-Models

    NARCIS (Netherlands)

    Kayastha, N.; Solomatine, D.P.; Lal Shrestha, D.; Piasecki, M


    In the MLUE method (reported in Shrestha et al. [1, 2]) we run a hydrological model M for multiple realizations of parameters vectors (Monte Carlo simulations), and use this data to build a machine learning model V to predict uncertainty (quantiles) of the model M output. In this paper, for model V,

  13. Model structural uncertainty quantification and hydrologic parameter and prediction error analysis using airborne electromagnetic data

    DEFF Research Database (Denmark)

    Minsley, B. J.; Christensen, Nikolaj Kruse; Christensen, Steen

    is never perfectly known, however, and incorrect assumptions can be a significant source of error when making model predictions. We describe a systematic approach for quantifying model structural uncertainty that is based on the integration of sparse borehole observations and large-scale airborne...... indicator simulation, we produce many realizations of model structure that are consistent with observed datasets and prior knowledge. Given estimates of model structural uncertainty, we incorporate hydrologic observations to evaluate the errors in hydrologic parameter or prediction errors that occur when...

  14. The Rangeland Hydrology and Erosion Model: A dynamic approach for predicting soil loss on rangelands (United States)

    In this study we present the improved Rangeland Hydrology and Erosion Model (RHEM V2.3), a process-based erosion prediction tool specific for rangeland application. The article provides the mathematical formulation of the model and parameter estimation equations. Model performance is assessed agains...

  15. Evaluation of remote-sensing-based rainfall products through predictive capability in hydrological runoff modelling

    DEFF Research Database (Denmark)

    Stisen, Simon; Sandholt, Inge


    advantage of this evaluation methodology is the integration of the rainfall model input in time and space when evaluated at the sub-catchment scale. An initial data analysis revealed significant biases in the SRFE products and large variations in rainfall amounts between SRFEs, although the spatial patterns......The emergence of regional and global satellite-based rainfall products with high spatial and temporal resolution has opened up new large-scale hydrological applications in data-sparse or ungauged catchments. Particularly, distributed hydrological models can benefit from the good spatial coverage...... and distributed nature of satellite-based rainfall estimates (SRFE). In this study, five SRFEs with temporal resolution of 24 h and spatial resolution between 8 and 27 km have been evaluated through their predictive capability in a distributed hydrological model of the Senegal River basin in West Africa. The main...

  16. Prediction of Hydrologic Characteristics for Ungauged Catchments to Support Hydroecological Modeling (United States)

    Bond, Nick R.; Kennard, Mark J.


    Hydrologic variability is a fundamental driver of ecological processes and species distribution patterns within river systems, yet the paucity of gauges in many catchments means that streamflow data are often unavailable for ecological survey sites. Filling this data gap is an important challenge in hydroecological research. To address this gap, we first test the ability to spatially extrapolate hydrologic metrics calculated from gauged streamflow data to ungauged sites as a function of stream distance and catchment area. Second, we examine the ability of statistical models to predict flow regime metrics based on climate and catchment physiographic variables. Our assessment focused on Australia's largest catchment, the Murray-Darling Basin (MDB). We found that hydrologic metrics were predictable only between sites within ˜25 km of one another. Beyond this, correlations between sites declined quickly. We found less than 40% of fish survey sites from a recent basin-wide monitoring program (n = 777 sites) to fall within this 25 km range, thereby greatly limiting the ability to utilize gauge data for direct spatial transposition of hydrologic metrics to biological survey sites. In contrast, statistical model-based transposition proved effective in predicting ecologically relevant aspects of the flow regime (including metrics describing central tendency, high- and low-flows intermittency, seasonality, and variability) across the entire gauge network (median R2 ˜ 0.54, range 0.39-0.94). Modeled hydrologic metrics thus offer a useful alternative to empirical data when examining biological survey data from ungauged sites. More widespread use of these statistical tools and modeled metrics could expand our understanding of flow-ecology relationships.

  17. Remote sensing inputs to landscape models which predict future spatial land use patterns for hydrologic models (United States)

    Miller, L. D.; Tom, C.; Nualchawee, K.


    A tropical forest area of Northern Thailand provided a test case of the application of the approach in more natural surroundings. Remote sensing imagery subjected to proper computer analysis has been shown to be a very useful means of collecting spatial data for the science of hydrology. Remote sensing products provide direct input to hydrologic models and practical data bases for planning large and small-scale hydrologic developments. Combining the available remote sensing imagery together with available map information in the landscape model provides a basis for substantial improvements in these applications.

  18. Runoff Prediction Using an Aggregation Hydrology Model on Seulimum River Sub Watershed, Aceh Province, Indonesia

    Directory of Open Access Journals (Sweden)

    Susi Chairani


    Full Text Available The objective of the present study was to predict the runoff in Seulimeum River sub watershed by utilizing an aggregation hydrology model. The method in this research consisted of field observation, collecting data and map, testing model, and analyzing data. Some parameters were used as the inputs on the model, such as: maximum storage, actual groundwater storage, soil moisture, and the constant of soil moisture k(t. The aggregation hydrology model was tested using 3 (three statistical parameters, such as; determination coefficient (R2, biased percentage (PBIAS, and Nash-Sutcliffe coefficient (ENS. The result showed that the minimum runoff occured in 1998 was 70.22 mm and the maximum runoff occurred in 1987 was 759.12 mm. The model testing showed that the aggregation hydrology model had a good performance in predicting the discharge of Krueng Seulimemum Sub Watershed; the R2, P biased, and ENS resulted 0.92, -5.21%, and 0.90, respectively

  19. Hydrological land surface modelling

    DEFF Research Database (Denmark)

    Ridler, Marc-Etienne Francois

    Recent advances in integrated hydrological and soil-vegetation-atmosphere transfer (SVAT) modelling have led to improved water resource management practices, greater crop production, and better flood forecasting systems. However, uncertainty is inherent in all numerical models ultimately leading...... and disaster management. The objective of this study is to develop and investigate methods to reduce hydrological model uncertainty by using supplementary data sources. The data is used either for model calibration or for model updating using data assimilation. Satellite estimates of soil moisture and surface...... hydrological and tested by assimilating synthetic hydraulic head observations in a catchment in Denmark. Assimilation led to a substantial reduction of model prediction error, and better model forecasts. Also, a new assimilation scheme is developed to downscale and bias-correct coarse satellite derived soil...

  20. A radar-based hydrological model for flash flood prediction in the dry regions of Israel (United States)

    Ronen, Alon; Peleg, Nadav; Morin, Efrat


    Flash floods are floods which follow shortly after rainfall events, and are among the most destructive natural disasters that strike people and infrastructures in humid and arid regions alike. Using a hydrological model for the prediction of flash floods in gauged and ungauged basins can help mitigate the risk and damage they cause. The sparsity of rain gauges in arid regions requires the use of radar measurements in order to get reliable quantitative precipitation estimations (QPE). While many hydrological models use radar data, only a handful do so in dry climate. This research presents a robust radar-based hydro-meteorological model built specifically for dry climate. Using this model we examine the governing factors of flash floods in the arid and semi-arid regions of Israel in particular and in dry regions in general. The hydrological model built is a semi-distributed, physically-based model, which represents the main hydrological processes in the area, namely infiltration, flow routing and transmission losses. Three infiltration functions were examined - Initial & Constant, SCS-CN and Green&Ampt. The parameters for each function were found by calibration based on 53 flood events in three catchments, and validation was performed using 55 flood events in six catchments. QPE were obtained from a C-band weather radar and adjusted using a weighted multiple regression method based on a rain gauge network. Antecedent moisture conditions were calculated using a daily recharge assessment model (DREAM). We found that the SCS-CN infiltration function performed better than the other two, with reasonable agreement between calculated and measured peak discharge. Effects of storm characteristics were studied using synthetic storms from a high resolution weather generator (HiReS-WG), and showed a strong correlation between storm speed, storm direction and rain depth over desert soils to flood volume and peak discharge.

  1. Predictive Models of the Hydrological Regime of Unregulated Streams in Arizona (United States)

    Anning, David W.; Parker, John T.C.


    Three statistical models were developed by the U.S. Geological Survey in cooperation with the Arizona Department of Environmental Quality to improve the predictability of flow occurrence in unregulated streams throughout Arizona. The models can be used to predict the probabilities of the hydrological regime being one of four categories developed by this investigation: perennial, which has streamflow year-round; nearly perennial, which has streamflow 90 to 99.9 percent of the year; weakly perennial, which has streamflow 80 to 90 percent of the year; or nonperennial, which has streamflow less than 80 percent of the year. The models were developed to assist the Arizona Department of Environmental Quality in selecting sites for participation in the U.S. Environmental Protection Agency's Environmental Monitoring and Assessment Program. One model was developed for each of the three hydrologic provinces in Arizona - the Plateau Uplands, the Central Highlands, and the Basin and Range Lowlands. The models for predicting the hydrological regime were calibrated using statistical methods and explanatory variables of discharge, drainage-area, altitude, and location data for selected U.S. Geological Survey streamflow-gaging stations and a climate index derived from annual precipitation data. Models were calibrated on the basis of streamflow data from 46 stations for the Plateau Uplands province, 82 stations for the Central Highlands province, and 90 stations for the Basin and Range Lowlands province. The models were developed using classification trees that facilitated the analysis of mixed numeric and factor variables. In all three models, a threshold stream discharge was the initial variable to be considered within the classification tree and was the single most important explanatory variable. If a stream discharge value at a station was below the threshold, then the station record was determined as being nonperennial. If, however, the stream discharge was above the threshold

  2. Using a dynamic hydrology model to predict mosquito abundances in flood and swamp water. (United States)

    Shaman, Jeffrey; Stieglitz, Marc; Stark, Colin; Le Blancq, Sylvie; Cane, Mark


    We modeled surface wetness at high resolution, using a dynamic hydrology model, to predict flood and swamp water mosquito abundances. Historical meteorologic data, as well as topographic, soil, and vegetation data, were used to model surface wetness and identify potential fresh and swamp water breeding habitats in two northern New Jersey watersheds. Surface wetness was positively associated with the subsequent abundance of the dominant floodwater mosquito species, Aedes vexans, and the swamp water species, Anopheles walkeri. The subsequent abundance of Culex pipiens, a species that breeds in polluted, eutrophic waters, was negatively correlated with local modeled surface wetness. These associations permit real-time monitoring and forecasting of these floodwater and nonfloodwater species at high spatial and temporal resolution. These predictions will enable public health agencies to institute control measures before the mosquitoes emerge as adults, when their role as transmitters of disease comes into play.

  3. Flood Prediction for the Tam Nong District in Mekong Delta Using Hydrological Modelling and Hydrologic Remote Sensing Technique (United States)

    Kappas, Martin; Nguyen Hong, Quang; Thanh, Nga Pham Thi; Thu, Hang Le Thi; Nguyen Vu, Giang; Degener, Jan; Rafiei Emam, Ammar


    There has been an increasing attention to the large trans-boundary Mekong river basin due to various problems related to water management and flood control, for instance. Vietnam Mekong delta is located at the downstream of the river basin where is affected most by this human-induced reduction in flows from the upstream. On the other hand, the flood plain of nine anastomosing channels is increasingly effected by the seawater intrusion due to sea level rising of climate change. This results in negative impacts of salinization, drought, and floods, while formerly flooding had frequently brought positive natural gain of irrigation water and alluvial aggradation. In this research, our aim is to predict flooding for the better water management adaptation and control. We applied the model HEC-SSP 2.1 to analyze flood flow frequency, two-dimensional unsteady flow calculations in HEC-RAS 5.0 for simulating a floodplain inundation. Remote sensing-based water level (Jason-2) and inundation map were used for validation and comparison with the model simulations. The results revealed a reduction of water level at all the monitoring stations, particularly in the last decade. In addition, a trend of the inundation extension gradually declined, but in some periods it remained severe due to water release from upstream reservoirs during the rainy season (October-November). We found an acceptable agreement between the HEC-RAS and remote sensing flooding maps (around 70%). Based on the flood routine analysis, we could conclude that the water level will continue lower and lead to a trend of drought and salinization harsher in the near future. Keywords: Mekong delta, flood control, inundation, water management, hydrological modelling, remote sensing

  4. Data assimilation in hydrological modelling

    DEFF Research Database (Denmark)

    Drecourt, Jean-Philippe

    Data assimilation is an invaluable tool in hydrological modelling as it allows to efficiently combine scarce data with a numerical model to obtain improved model predictions. In addition, data assimilation also provides an uncertainty analysis of the predictions made by the hydrological model...... with model non-linearities and biased errors. A literature review analyzes the most popular techniques and their application in hydrological modelling. Since bias is an important problem in groundwater modelling, two bias aware Kalman filters have been implemented and compared using an artificial test case...

  5. Using Predictive Uncertainty Analysis to Assess Hydrologic Model Performance for a Watershed in Oregon (United States)

    Brannan, K. M.; Somor, A.


    A variety of statistics are used to assess watershed model performance but these statistics do not directly answer the question: what is the uncertainty of my prediction. Understanding predictive uncertainty is important when using a watershed model to develop a Total Maximum Daily Load (TMDL). TMDLs are a key component of the US Clean Water Act and specify the amount of a pollutant that can enter a waterbody when the waterbody meets water quality criteria. TMDL developers use watershed models to estimate pollutant loads from nonpoint sources of pollution. We are developing a TMDL for bacteria impairments in a watershed in the Coastal Range of Oregon. We setup an HSPF model of the watershed and used the calibration software PEST to estimate HSPF hydrologic parameters and then perform predictive uncertainty analysis of stream flow. We used Monte-Carlo simulation to run the model with 1,000 different parameter sets and assess predictive uncertainty. In order to reduce the chance of specious parameter sets, we accounted for the relationships among parameter values by using mathematically-based regularization techniques and an estimate of the parameter covariance when generating random parameter sets. We used a novel approach to select flow data for predictive uncertainty analysis. We set aside flow data that occurred on days that bacteria samples were collected. We did not use these flows in the estimation of the model parameters. We calculated a percent uncertainty for each flow observation based 1,000 model runs. We also used several methods to visualize results with an emphasis on making the data accessible to both technical and general audiences. We will use the predictive uncertainty estimates in the next phase of our work, simulating bacteria fate and transport in the watershed.

  6. Multi-variable evaluation of hydrological model predictions for a headwater basin in the Canadian Rocky Mountains

    Directory of Open Access Journals (Sweden)

    X. Fang


    Full Text Available One of the purposes of the Cold Regions Hydrological Modelling platform (CRHM is to diagnose inadequacies in the understanding of the hydrological cycle and its simulation. A physically based hydrological model including a full suite of snow and cold regions hydrology processes as well as warm season, hillslope and groundwater hydrology was developed in CRHM for application in the Marmot Creek Research Basin (~ 9.4 km2, located in the Front Ranges of the Canadian Rocky Mountains. Parameters were selected from digital elevation model, forest, soil, and geological maps, and from the results of many cold regions hydrology studies in the region and elsewhere. Non-calibrated simulations were conducted for six hydrological years during the period 2005–2011 and were compared with detailed field observations of several hydrological cycle components. The results showed good model performance for snow accumulation and snowmelt compared to the field observations for four seasons during the period 2007–2011, with a small bias and normalised root mean square difference (NRMSD ranging from 40 to 42% for the subalpine conifer forests and from 31 to 67% for the alpine tundra and treeline larch forest environments. Overestimation or underestimation of the peak SWE ranged from 1.6 to 29%. Simulations matched well with the observed unfrozen moisture fluctuation in the top soil layer at a lodgepole pine site during the period 2006–2011, with a NRMSD ranging from 17 to 39%, but with consistent overestimation of 7 to 34%. Evaluations of seasonal streamflow during the period 2006–2011 revealed that the model generally predicted well compared to observations at the basin scale, with a NRMSD of 60% and small model bias (1%, while at the sub-basin scale NRMSDs were larger, ranging from 72 to 76%, though overestimation or underestimation for the cumulative seasonal discharge was within 29%. Timing of discharge was better predicted at the Marmot Creek basin outlet

  7. Advances in Predicting Soil Erosion After Fire Using the Rangeland Hydrology and Erosion Model (United States)

    Al-Hamdan, Osama Z.; Pierson, Frederick B.; Nearing, Mark A.; Williams, C. Jason; Hernandez, Mariano; Boll, Jan; Nouwakpo, Sayjro; Weltz, Mark A.; Spaeth, Kenneth E.


    The magnitude of erosion from a hillslope is governed by the availability of sediment and connectivity of overland flow and erosion processes. For undisturbed conditions, sediment is mainly detached and transported by rainsplash and sheetflow (splash-sheet) processes in bare batches, but sediment generally only travels a short distance before deposition. On recently disturbed sites (e.g., after fire), bare ground is more extensive and runoff and erosion rates are higher relative to undisturbed conditions. Increased erosion following disturbance occurs largely due to a shift from splash-sheet to concentrated-flow-dominated processes. On long-disturbed sites (e.g., after woody plant encroachment), years of soil loss can limit sediment availability and soil erosion. In contrast, recently burned landscapes typically have ample sediment available and generate high erosion rates. This presentation highlights recent advancements in hillslope erosion prediction by the Rangeland Hydrology and Erosion Model (RHEM) that accommodate recently burned conditions. The RHEM tool is a process-based model that was developed specifically for predicting hillslope runoff and erosion on rangeland ecosystems. The advancements presented here include development of empirical equations to predict erodibility parameters for conditions in which erosion by concentrated flow processes is limited (by runoff or sediment availability) and an erodibility parameter for conditions in which erosion by concentrated flow processes is the dominant erosion mechanism and sediment is amply available (burned conditions). The data used for developing and evaluating the erodibility parameter equations were obtained from rainfall simulation databases maintained by the USDA-Agricultural Research Service. The data span undisturbed, long-disturbed, and recently burned conditions. For undisturbed and long-disturbed conditions, a regression analysis was applied to derive the relationship between splash

  8. Monitoring and Predicting Land-use Changes and the Hydrology of the Urbanized Paochiao Watershed in Taiwan Using Remote Sensing Data, Urban Growth Models and a Hydrological Model (United States)

    Lin, Yu-Pin; Lin, Yun-Bin; Wang, Yen-Tan; Hong, Nien-Ming


    Monitoring and simulating urban sprawl and its effects on land-use patterns and hydrological processes in urbanized watersheds are essential in land-use and water-resource planning and management. This study applies a novel framework to the urban growth model Slope, Land use, Excluded land, Urban extent, Transportation, and Hillshading (SLEUTH) and land-use change with the Conversion of Land use and its Effects (CLUE-s) model using historical SPOT images to predict urban sprawl in the Paochiao watershed in Taipei County, Taiwan. The historical and predicted land-use data was input into Patch Analyst to obtain landscape metrics. This data was also input to the Generalized Watershed Loading Function (GWLF) model to analyze the effects of future urban sprawl on the land-use patterns and watershed hydrology. The landscape metrics of the historical SPOT images show that land-use patterns changed between 1990–2000. The SLEUTH model accurately simulated historical land-use patterns and urban sprawl in the Paochiao watershed, and simulated future clustered land-use patterns (2001–2025). The CLUE-s model also simulated land-use patterns for the same period and yielded historical trends in the metrics of land-use patterns. The land-use patterns predicted by the SLEUTH and CLUE-s models show the significant impact urban sprawl will have on land-use patterns in the Paochiao watershed. The historical and predicted land-use patterns in the watershed tended to fragment, had regular shapes and interspersion patterns, but were relatively less isolated in 2001–2025 and less interspersed from 2005–2025 compared with land-use pattern in 1990. During the study, the variability and magnitude of hydrological components based on the historical and predicted land-use patterns were cumulatively affected by urban sprawl in the watershed; specifically, surface runoff increased significantly by 22.0% and baseflow decreased by 18.0% during 1990–2025. The proposed approach is an

  9. Comparing large-scale hydrological model predictions with observed streamflow in the Pacific Northwest: effects of climate and groundwater (United States)

    Mohammad Safeeq; Guillaume S. Mauger; Gordon E. Grant; Ivan Arismendi; Alan F. Hamlet; Se-Yeun Lee


    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...

  10. The Rangeland Hydrology and Erosion Model: A Dynamic Approach for Predicting Soil Loss on Rangelands (United States)

    Hernandez, Mariano; Nearing, Mark A.; Al-Hamdan, Osama Z.; Pierson, Frederick B.; Armendariz, Gerardo; Weltz, Mark A.; Spaeth, Kenneth E.; Williams, C. Jason; Nouwakpo, Sayjro K.; Goodrich, David C.; Unkrich, Carl L.; Nichols, Mary H.; Holifield Collins, Chandra D.


    In this study, we present the improved Rangeland Hydrology and Erosion Model (RHEM V2.3), a process-based erosion prediction tool specific for rangeland application. The article provides the mathematical formulation of the model and parameter estimation equations. Model performance is assessed against data collected from 23 runoff and sediment events in a shrub-dominated semiarid watershed in Arizona, USA. To evaluate the model, two sets of primary model parameters were determined using the RHEM V2.3 and RHEM V1.0 parameter estimation equations. Testing of the parameters indicated that RHEM V2.3 parameter estimation equations provided a 76% improvement over RHEM V1.0 parameter estimation equations. Second, the RHEM V2.3 model was calibrated to measurements from the watershed. The parameters estimated by the new equations were within the lowest and highest values of the calibrated parameter set. These results suggest that the new parameter estimation equations can be applied for this environment to predict sediment yield at the hillslope scale. Furthermore, we also applied the RHEM V2.3 to demonstrate the response of the model as a function of foliar cover and ground cover for 124 data points across Arizona and New Mexico. The dependence of average sediment yield on surface ground cover was moderately stronger than that on foliar cover. These results demonstrate that RHEM V2.3 predicts runoff volume, peak runoff, and sediment yield with sufficient accuracy for broad application to assess and manage rangeland systems.

  11. Influence of forest roads standards and networks on water yield as predicted by the distributed hydrology-soil-vegetation model (United States)

    Salli F. Dymond; W. Michael Aust; Steven P. Prisley; Mark H. Eisenbies; James M. Vose


    Throughout the country, foresters are continually looking at the effects of logging and forest roads on stream discharge and overall stream health. In the Pacific Northwest, a distributed hydrology-soil-vegetation model (DHSVM) has been used to predict the effects of logging on peak discharge in mountainous regions. DHSVM uses elevation, meteorological, vegetation, and...

  12. A Hierarchical Approach Embedding Hydrologic and Population Modeling for a West Nile Virus Vector Prediction (United States)

    Jian, Y.; Silvestri, S.; Marani, M.; Saltarin, A.; Chillemi, G.


    We applied a hierarchical state space model to predict the abundance of Cx.pipiens (a West Nile Virus vector) in the Po River Delta Region, Northeastern Italy. The study area has large mosquito abundance, due to a favorable environment and climate as well as dense human population. Mosquito data were collected on a weekly basis at more than 20 sites from May to September in 2010 and 2011. Cx.pipiens was the dominant species in our samples, accounting for about 90% of the more than 300,000 total captures. The hydrological component of the model accounted for evapotranspiration, infiltration and deep percolation to infer, in a 0D context, the local dynamics of soil moisture as a direct exogenous forcing of mosquito dynamics. The population model had a Gompertz structure, which included exogenous meteorological forcings and delayed internal dynamics. The models were coupled within a hierarchical statistical structure to overcome the relatively short length of the samples by exploiting the large number of concurrent observations available. The results indicated that Cx.pipiens abundance had significant density dependence at 1 week lag, which approximately matched its development time from larvae to adult. Among the exogenous controls, temperature, daylight hours, and soil moisture explained most of the dynamics. Longer daylight hours and lower soil moisture values resulted in higher abundance. The negative correlation of soil moisture and mosquito population can be explained with the abundance of water in the region (e.g. due to irrigation) and the preference for eutrophic habitats by Cx.pipien. Variations among sites were explained by land use factors as represented by distance to the nearest rice field and NDVI values: the carrying capacity decreased with increased distance to the nearest rice filed, while the maximum growth rate was positively related with NDVI. The model shows a satisfactory performance in predicting (potentially one week in advance) mosquito

  13. Developing soil erodibility prediction equations for the Rangeland Hydrology and Erosion Model (RHEM) (United States)

    Soil erodibility is a key factor for estimating soil erosion using physically based models. In this study, a new parameterization approach for estimating erodibility was developed for the Rangeland Hydrology and Erosion Model (RHEM). The approach uses empirical equations that were developed by apply...

  14. Predicting debris flow occurrence in Eastern Italian Alps based on hydrological and geomorphological modelling (United States)

    Nikolopoulos, Efthymios I.; Borga, Marco; Destro, Elisa; Marchi, Lorenzo


    Most of the work so far on the prediction of debris flow occurrence is focused on the identification of critical rainfall conditions. However, findings in the literature have shown that critical rainfall thresholds cannot always accurately identify debris flow occurrence, leading to false detections (positive or negative). One of the main reasons for this limitation is attributed to the fact that critical rainfall thresholds do not account for the characteristics of underlying land surface (e.g. geomorphology, moisture conditions, sediment availability, etc), which are strongly related to debris flow triggering. In addition, in areas where debris flows occur predominantly as a result of channel bed failure (as in many Alpine basins), the triggering factor is runoff, which suggests that identification of critical runoff conditions for debris flow prediction is more pertinent than critical rainfall. The primary objective of this study is to investigate the potential of a triggering index (TI), which combines variables related to runoff generation and channel morphology, for predicting debris flows occurrence. TI is based on a threshold criterion developed on past works (Tognacca et al., 2000; Berti and Simoni, 2005; Gregoretti and Dalla Fontana, 2008) and combines information on unit width peak flow, local channel slope and mean grain size. Estimation of peak discharge is based on the application of a distributed hydrologic model, while local channel slope is derived from a high-resolution (5m) DEM. Scaling functions of peak flows and channel width with drainage area are adopted since it is not possible to measure channel width or simulate peak flow at all channel nodes. TI values are mapped over the channel network thus allowing spatially distributed prediction but instead of identifying debris flow occurrence on single points, we identify their occurrence with reference to the tributary catchment involved. Evaluation of TI is carried out for five different basins

  15. Evaluating the role of evapotranspiration remote sensing data in improving hydrological modeling predictability (United States)

    Herman, Matthew R.; Nejadhashemi, A. Pouyan; Abouali, Mohammad; Hernandez-Suarez, Juan Sebastian; Daneshvar, Fariborz; Zhang, Zhen; Anderson, Martha C.; Sadeghi, Ali M.; Hain, Christopher R.; Sharifi, Amirreza


    As the global demands for the use of freshwater resources continues to rise, it has become increasingly important to insure the sustainability of this resources. This is accomplished through the use of management strategies that often utilize monitoring and the use of hydrological models. However, monitoring at large scales is not feasible and therefore model applications are becoming challenging, especially when spatially distributed datasets, such as evapotranspiration, are needed to understand the model performances. Due to these limitations, most of the hydrological models are only calibrated for data obtained from site/point observations, such as streamflow. Therefore, the main focus of this paper is to examine whether the incorporation of remotely sensed and spatially distributed datasets can improve the overall performance of the model. In this study, actual evapotranspiration (ETa) data was obtained from the two different sets of satellite based remote sensing data. One dataset estimates ETa based on the Simplified Surface Energy Balance (SSEBop) model while the other one estimates ETa based on the Atmosphere-Land Exchange Inverse (ALEXI) model. The hydrological model used in this study is the Soil and Water Assessment Tool (SWAT), which was calibrated against spatially distributed ETa and single point streamflow records for the Honeyoey Creek-Pine Creek Watershed, located in Michigan, USA. Two different techniques, multi-variable and genetic algorithm, were used to calibrate the SWAT model. Using the aforementioned datasets, the performance of the hydrological model in estimating ETa was improved using both calibration techniques by achieving Nash-Sutcliffe efficiency (NSE) values >0.5 (0.73-0.85), percent bias (PBIAS) values within ±25% (±21.73%), and root mean squared error - observations standard deviation ratio (RSR) values model performance for estimating the streamflow (NSE: 0.32-0.52, PBIAS: ±32.73%, and RSR: 0.63-0.82). Meanwhile, using the

  16. Effect of radar rainfall time resolution on the predictive capability of a distributed hydrologic model (United States)

    Atencia, A.; Llasat, M. C.; Garrote, L.; Mediero, L.


    The performance of distributed hydrological models depends on the resolution, both spatial and temporal, of the rainfall surface data introduced. The estimation of quantitative precipitation from meteorological radar or satellite can improve hydrological model results, thanks to an indirect estimation at higher spatial and temporal resolution. In this work, composed radar data from a network of three C-band radars, with 6-minutal temporal and 2 × 2 km2 spatial resolution, provided by the Catalan Meteorological Service, is used to feed the RIBS distributed hydrological model. A Window Probability Matching Method (gage-adjustment method) is applied to four cases of heavy rainfall to improve the observed rainfall sub-estimation in both convective and stratiform Z/R relations used over Catalonia. Once the rainfall field has been adequately obtained, an advection correction, based on cross-correlation between two consecutive images, was introduced to get several time resolutions from 1 min to 30 min. Each different resolution is treated as an independent event, resulting in a probable range of input rainfall data. This ensemble of rainfall data is used, together with other sources of uncertainty, such as the initial basin state or the accuracy of discharge measurements, to calibrate the RIBS model using probabilistic methodology. A sensitivity analysis of time resolutions was implemented by comparing the various results with real values from stream-flow measurement stations.

  17. Monitoring and Predicting Land-use Changes and the Hydrology of the Urbanized Paochiao Watershed in Taiwan Using Remote Sensing Data, Urban Growth Models and a Hydrological Model

    Directory of Open Access Journals (Sweden)

    Nien-Ming Hong


    Full Text Available Monitoring and simulating urban sprawl and its effects on land-use patterns andhydrological processes in urbanized watersheds are essential in land-use and waterresourceplanning and management. This study applies a novel framework to the urbangrowth model Slope, Land use, Excluded land, Urban extent, Transportation, andHillshading (SLEUTH and land-use change with the Conversion of Land use and itsEffects (CLUE-s model using historical SPOT images to predict urban sprawl in thePaochiao watershed in Taipei County, Taiwan. The historical and predicted land-use datawas input into Patch Analyst to obtain landscape metrics. This data was also input to theGeneralized Watershed Loading Function (GWLF model to analyze the effects of futureurban sprawl on the land-use patterns and watershed hydrology. The landscape metrics ofthe historical SPOT images show that land-use patterns changed between 1990–2000. TheSLEUTH model accurately simulated historical land-use patterns and urban sprawl in thePaochiao watershed, and simulated future clustered land-use patterns (2001–2025. TheCLUE-s model also simulated land-use patterns for the same period and yielded historical trends in the metrics of land-use patterns. The land-use patterns predicted by the SLEUTHand CLUE-s models show the significant impact urban sprawl will have on land-usepatterns in the Paochiao watershed. The historical and predicted land-use patterns in thewatershed tended to fragment, had regular shapes and interspersion patterns, but wererelatively less isolated in 2001–2025 and less interspersed from 2005–2025 compared withland-use pattern in 1990. During the study, the variability and magnitude of hydrologicalcomponents based on the historical and predicted land-use patterns were cumulativelyaffected by urban sprawl in the watershed; specifically, surface runoff increasedsignificantly by 22.0% and baseflow decreased by 18.0% during 1990

  18. Hydrological modelling in forested systems | Science ... (United States)

    This chapter provides a brief overview of forest hydrology modelling approaches for answering important global research and management questions. Many hundreds of hydrological models have been applied globally across multiple decades to represent and predict forest hydrological processes. The focus of this chapter is on process-based models and approaches, specifically 'forest hydrology models'; that is, physically based simulation tools that quantify compartments of the forest hydrological cycle. Physically based models can be considered those that describe the conservation of mass, momentum and/or energy. The purpose of this chapter is to provide a brief overview of forest hydrology modeling approaches for answering important global research and management questions. The focus of this chapter is on process-based models and approaches, specifically “forest hydrology models”, i.e., physically-based simulation tools that quantify compartments of the forest hydrological cycle.

  19. Development and application of a conceptual hydrologic model to predict soil salinity within modern Tunisian oases (United States)

    Askri, Brahim; Bouhlila, Rachida; Job, Jean Olivier


    SummaryIn modern oases situated in the south of Tunisia, secondary salination of irrigated lands is a crucial problem. The visible salt deposits and soil salination processes are the consequence of several factors including the excessive use of saline irrigation water, seepage from earthen canal systems, inefficient irrigation practices and inadequate drainage. Understanding the mechanism of the secondary salination is of interest in order to maintain existing oases, and thus ensure the sustainability of date production in this part of the country. Therefore, a conceptual, daily, semi-distributed hydrologic model (OASIS_MOD) was developed to analyse the impact of irrigation management on the water table fluctuation, soil salinity and drain discharge, and to evaluate measures to control salinity within an oasis ecosystem. The basic processes incorporated in the model are irrigation, infiltration, percolation to the shallow groundwater, soil evaporation, crop transpiration, groundwater flow, capillary rise flux, and drain discharge. OASIS_MOD was tested with data collected in a parcel of farmland situated in the Segdoud oasis, in the south-west of Tunisia. The calibration results showed that groundwater levels were simulated with acceptable accuracy, since the differences between the simulated and measured values are less than 0.22 m. However, the model under-predicted some water table peaks when irrigation occurs due to inconsistencies in the irrigation water data. The validation results showed that deviations between observed and simulated groundwater levels have increased to about 0.5 m due to under-estimation of groundwater inflow from an upstream palm plantation. A long-term simulation scenario revealed that the soil salinity and groundwater level have three types of variability in time: a daily variability due to irrigation practices, seasonal fluctuation due to climatic conditions and annual variability explained by the increase in cultivated areas. The

  20. Nitrate reduction in geologically heterogeneous catchments — A framework for assessing the scale of predictive capability of hydrological models

    Energy Technology Data Exchange (ETDEWEB)

    Refsgaard, Jens Christian, E-mail: [Geological Survey of Denmark and Greenland (GEUS) (Denmark); Auken, Esben [Department of Earth Sciences, Aarhus University (Denmark); Bamberg, Charlotte A. [City of Aarhus (Denmark); Christensen, Britt S.B. [Geological Survey of Denmark and Greenland (GEUS) (Denmark); Clausen, Thomas [DHI, Hørsholm (Denmark); Dalgaard, Esben [Department of Earth Sciences, Aarhus University (Denmark); Effersø, Flemming [SkyTEM Aps, Beder (Denmark); Ernstsen, Vibeke [Geological Survey of Denmark and Greenland (GEUS) (Denmark); Gertz, Flemming [Knowledge Center for Agriculture, Skejby (Denmark); Hansen, Anne Lausten [Department of Geosciences and Natural Resource Management, University of Copenhagen (Denmark); He, Xin [Geological Survey of Denmark and Greenland (GEUS) (Denmark); Jacobsen, Brian H. [Department of Food and Resource Economics, University of Copenhagen (Denmark); Jensen, Karsten Høgh [Department of Geosciences and Natural Resource Management, University of Copenhagen (Denmark); Jørgensen, Flemming; Jørgensen, Lisbeth Flindt [Geological Survey of Denmark and Greenland (GEUS) (Denmark); Koch, Julian [Department of Geosciences and Natural Resource Management, University of Copenhagen (Denmark); Nilsson, Bertel [Geological Survey of Denmark and Greenland (GEUS) (Denmark); Petersen, Christian [City of Odder (Denmark); De Schepper, Guillaume [Université Laval, Québec (Canada); Schamper, Cyril [Department of Earth Sciences, Aarhus University (Denmark); and others


    In order to fulfil the requirements of the EU Water Framework Directive nitrate load from agricultural areas to surface water in Denmark needs to be reduced by about 40%. The regulations imposed until now have been uniform, i.e. the same restrictions for all areas independent of the subsurface conditions. Studies have shown that on a national basis about 2/3 of the nitrate leaching from the root zone is reduced naturally, through denitrification, in the subsurface before reaching the streams. Therefore, it is more cost-effective to identify robust areas, where nitrate leaching through the root zone is reduced in the saturated zone before reaching the streams, and vulnerable areas, where no subsurface reduction takes place, and then only impose regulations/restrictions on the vulnerable areas. Distributed hydrological models can make predictions at grid scale, i.e. at much smaller scale than the entire catchment. However, as distributed models often do not include local scale hydrogeological heterogeneities, they are typically not able to make accurate predictions at scales smaller than they are calibrated. We present a framework for assessing nitrate reduction in the subsurface and for assessing at which spatial scales modelling tools have predictive capabilities. A new instrument has been developed for airborne geophysical measurements, Mini-SkyTEM, dedicated to identifying geological structures and heterogeneities with horizontal and lateral resolutions of 30–50 m and 2 m, respectively, in the upper 30 m. The geological heterogeneity and uncertainty are further analysed by use of the geostatistical software TProGS by generating stochastic geological realisations that are soft conditioned against the geophysical data. Finally, the flow paths within the catchment are simulated by use of the MIKE SHE hydrological modelling system for each of the geological models generated by TProGS and the prediction uncertainty is characterised by the variance between the

  1. Evaluation of Satellite Precipitation and Hydrological Model Predictions for Flood Events Over The Guadalupe River Basin, Texas (United States)

    Sharif, H. O.; Furl, C.


    In this study, we evaluate the quality of several satellite precipitation products in comparison to gauge corrected ground based radar estimaties for moderate to high magnitude events across the Guadalupe River system in south Texas. The analysis is conducted across four partially nested watersheds (200-10,000 km2) such that scale effects can also be examined. Additionally, the precipitation data sets are used as input to the fully-distributed, physics-based Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model to examine rainfall error propagation through the hydrologic model predictions. Both gauge corrected and uncorrected satellite products are used encompassing a variety of latent delivery times, spatial resolutions, and temporal resolutions. Satellite precipitation datasets used in the study include various products from GPM, the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) system, the NOAA CPC Morphing Technique (CMORPH), and the Tropical Rainfall Measuring Mission (TRMM).

  2. Sustainable co-evolution of society, ecology and hydrology: forward-looking modelling and prediction of the ecosystem and hydrology of the Lake of Monate - Italy (United States)

    Montanari, Alberto; Attilio, Castellarin; Cervi, Federico


    The catchment of the Lake of Monate, in Northern Italy, is a unique example of sustainable and long-term co-evolution of society, exploitation of environmental resources, ecology and hydrology. The catchment is intensively managed since Roman times for the extraction of limestone and the whole basin area was intensively urbanized in recent times, so that the lake is now placed within a profoundly impacted environment. Notwithstanding the above relevant anthropogenic activity, the ecosystem of the lake is still very close to pristine conditions, therefore offering unique research opportunities. Sustainable co-evolution was ensured by the absence of significant surface inflows to the lake, which is mainly alimented by groundwater flows, and a wise and forward looking land use planning and management since ancient times. Today, the increasing pace of limestone extraction, and consequent land recovery, as well as urbanization, poses the need for an improved understanding of sustainability, to support long term prediction and planning. The target is to ensure that the ecosystemic value of the lake is preserved for the benefit of future generations and societal development. The above need calls for improved modelling tools where the co-evolution of society, ecology and hydrology is modelled by focusing on the time scales of the related interactions and the planning horizon. A theoretical framework will be presented to identify the above relevant scales and to properly incorporate the feedbacks between human activity and natural systems.

  3. The incorrect usage of singular spectral analysis and discrete wavelet transform in hybrid models to predict hydrological time series (United States)

    Du, Kongchang; Zhao, Ying; Lei, Jiaqiang


    In hydrological time series prediction, singular spectrum analysis (SSA) and discrete wavelet transform (DWT) are widely used as preprocessing techniques for artificial neural network (ANN) and support vector machine (SVM) predictors. These hybrid or ensemble models seem to largely reduce the prediction error. In current literature researchers apply these techniques to the whole observed time series and then obtain a set of reconstructed or decomposed time series as inputs to ANN or SVM. However, through two comparative experiments and mathematical deduction we found the usage of SSA and DWT in building hybrid models is incorrect. Since SSA and DWT adopt 'future' values to perform the calculation, the series generated by SSA reconstruction or DWT decomposition contain information of 'future' values. These hybrid models caused incorrect 'high' prediction performance and may cause large errors in practice.

  4. Hydrological land surface modelling

    DEFF Research Database (Denmark)

    Ridler, Marc-Etienne Francois

    and disaster management. The objective of this study is to develop and investigate methods to reduce hydrological model uncertainty by using supplementary data sources. The data is used either for model calibration or for model updating using data assimilation. Satellite estimates of soil moisture and surface...

  5. A physically based model of the hydrological cycle of forest watershed and predicting the deforestation effects (United States)

    Kuchment, L. S.; Gelfan, A. N.; Demidov, V.


    A physically based model of the hydrologic cycle of forest watershed for the whole year, including warm and cold seasons, has been developed. The model includes a detailed description of liquid water and snow interception by forest canopy, snow accumulation and melt, vertical soil moisture transfer and evapotranspiration, overland and subsurface flow. The evapotranspiration is separated on the evaporation from the wet part of canopy, the transpiration and the evaporation from bare soil. To describe the vertical soil moisture transfer, the Richards equation in the diffusion form including the uptake of water by plant roots. At describing snow accumulation and melt, the influence of canopy characteristics (forest density, tree structure, age, etc.) on radiation and turbulent heat fluxes are taking into account. Case-study has been carried out on the basis of experimental observations at a small completely forested watershed of the Valday water balance station situated in the north-western part of Russia. The watershed is completely covered by old fir forest. Most model parameters were either assigned directly from soil and vegetation measurements or calculated by empirical formulas using standard observations. After calibration, the model was applied to estimate possible changes of the water balance components after forest cutting. To take into account changing the soil characteristics after forest cutting, some soil constants in the model had been assigned from the measurements at the neighbouring deforested watershed. The simulated averaged snow water equivalent before snowmelt increased after deforestation by 15%; the snow sublimation losses decreased almost twice .The simulated annual runoff decreased by 10%, but its seasonal distribution changes essentially larger and the spring flood peak discharge from the deforested basin increased, on average, by 50%. Sensitivity of the hydrologic cycle processes to changes of the leaf area index as a representative

  6. Observational breakthroughs lead the way to improved hydrological predictions (United States)

    Lettenmaier, Dennis P.


    New data sources are revolutionizing the hydrological sciences. The capabilities of hydrological models have advanced greatly over the last several decades, but until recently model capabilities have outstripped the spatial resolution and accuracy of model forcings (atmospheric variables at the land surface) and the hydrologic state variables (e.g., soil moisture; snow water equivalent) that the models predict. This has begun to change, as shown in two examples here: soil moisture and drought evolution over Africa as predicted by a hydrology model forced with satellite-derived precipitation, and observations of snow water equivalent at very high resolution over a river basin in California's Sierra Nevada.

  7. Nitrate reduction in geologically heterogeneous catchments--a framework for assessing the scale of predictive capability of hydrological models. (United States)

    Refsgaard, Jens Christian; Auken, Esben; Bamberg, Charlotte A; Christensen, Britt S B; Clausen, Thomas; Dalgaard, Esben; Effersø, Flemming; Ernstsen, Vibeke; Gertz, Flemming; Hansen, Anne Lausten; He, Xin; Jacobsen, Brian H; Jensen, Karsten Høgh; Jørgensen, Flemming; Jørgensen, Lisbeth Flindt; Koch, Julian; Nilsson, Bertel; Petersen, Christian; De Schepper, Guillaume; Schamper, Cyril; Sørensen, Kurt I; Therrien, Rene; Thirup, Christian; Viezzoli, Andrea


    In order to fulfil the requirements of the EU Water Framework Directive nitrate load from agricultural areas to surface water in Denmark needs to be reduced by about 40%. The regulations imposed until now have been uniform, i.e. the same restrictions for all areas independent of the subsurface conditions. Studies have shown that on a national basis about 2/3 of the nitrate leaching from the root zone is reduced naturally, through denitrification, in the subsurface before reaching the streams. Therefore, it is more cost-effective to identify robust areas, where nitrate leaching through the root zone is reduced in the saturated zone before reaching the streams, and vulnerable areas, where no subsurface reduction takes place, and then only impose regulations/restrictions on the vulnerable areas. Distributed hydrological models can make predictions at grid scale, i.e. at much smaller scale than the entire catchment. However, as distributed models often do not include local scale hydrogeological heterogeneities, they are typically not able to make accurate predictions at scales smaller than they are calibrated. We present a framework for assessing nitrate reduction in the subsurface and for assessing at which spatial scales modelling tools have predictive capabilities. A new instrument has been developed for airborne geophysical measurements, Mini-SkyTEM, dedicated to identifying geological structures and heterogeneities with horizontal and lateral resolutions of 30-50 m and 2m, respectively, in the upper 30 m. The geological heterogeneity and uncertainty are further analysed by use of the geostatistical software TProGS by generating stochastic geological realisations that are soft conditioned against the geophysical data. Finally, the flow paths within the catchment are simulated by use of the MIKE SHE hydrological modelling system for each of the geological models generated by TProGS and the prediction uncertainty is characterised by the variance between the

  8. The Challenge of Fully-Predictive Hydrologic Models Supported by Observations: Recent Experiences and Prospects in Semiarid Systems (Invited) (United States)

    Vivoni, E. R.


    After several decades of development and applications, distributed watershed models are now common tools in hydrologic research and increasingly used in practice. Unfortunately, the sophistication of these tools has not been accompanied by comparable levels of observational data collection. Ultimately, predictions from distributed watershed models need to be verified to build confidence in their ability to simulate the past and subsequently the future, under changing conditions. This talk will describe our efforts to develop, apply and test a distributed watershed model for semiarid regions in the southwestern United States and northwestern Mexico. We will provide examples from forested mountain, semiarid desert and subtropical shrubland systems which all have marked seasonality due to the North American monsoon. Our previous efforts include comparisons to eddy covariance data, distributed soil moisture patterns and runoff observations, among others. After building model confidence, we explore the underlying patterns, processes and mechanisms in the distributed simulations to identify emergent behavior. The intent of this synthesis stage is to infer generalizable features of the hydrologic system that may help explain the observed data and build predictive capacity for other settings. We also discuss prospects for improved joint use of distributed watershed models and distributed observations from ground, aerial and satellite platforms.

  9. Prediction of soil stability and erosion in semiarid regions using numerical hydrological model (MCAT) and airborne hyperspectral imagery (United States)

    Brook, Anna; Wittenberg, Lea


    Long-term environmental monitoring is addressed to identify physical and biological changes and progresses taking place in the ecosystem. This basic action of landscape monitoring is an essential part of the systematic long-term surveillance, aiming to evaluate, assess and predict the spatial change and progresses. Indeed, it provides a context for wide range of diverse studies and research frameworks from regional or global scale. Spatial-temporal trends and changes at various scales (massive to less certain) require establishing consistent baseline data over time. One of the spatial cases of landscape monitoring is dedicated to soil formation and pedological progresses. It is previously acknowledged that changes in soil affect the functionality of the environment, so monitoring changes recently become important cause considerable resources in areas such as environmental management, sustainability services, and protecting the environment healthy. Given the above, it can be concluded that monitoring changes in the base for sustainable development. The hydrological response of bare soils and watersheds in semiarid regions to intense rainfall events is known to be complex due to multiply physical and structural impacts and feedbacks. As a result, the comprehensive evaluations of mathematical models including detailed consideration of uncertainties in the modeling of hydrological and environmental systems are of increasing importance. The presented method incorporates means of remote sensing data, hydrological and climate data and implementing dedicated and integrative Monte Carlo Analysis Toolbox (MCAT) model for semiarid region. Complexity of practical models to represent spatial systems requires an extensive understanding of the spatial phenomena, while providing realistic balance of sensitivity and corresponding uncertainty levels. Nowadays a large number of dedicated mathematical models applied to assess environmental hydrological process. Among the most

  10. On the optimal design of experiments for conceptual and predictive discrimination of hydrologic system models (United States)

    Kikuchi, C. P.; Ferré, T. P. A.; Vrugt, J. A.


    Experimental design and data collection constitute two main steps of the iterative research cycle (aka the scientific method). To help evaluate competing hypotheses, it is critical to ensure that the experimental design is appropriate and maximizes information retrieval from the system of interest. Scientific hypothesis testing is implemented by comparing plausible model structures (conceptual discrimination) and sets of predictions (predictive discrimination). This research presents a new Discrimination-Inference (DI) methodology to identify prospective data sets highly suitable for either conceptual or predictive discrimination. The DI methodology uses preposterior estimation techniques to evaluate the expected change in the conceptual or predictive probabilities, as measured by the Kullback-Leibler divergence. We present two case studies with increasing complexity to illustrate implementation of the DI for maximizing information withdrawal from a system of interest. The case studies show that highly informative data sets for conceptual discrimination are in general those for which between-model (conceptual) uncertainty is large relative to the within-model (parameter) uncertainty, and the redundancy between individual measurements in the set is minimized. The optimal data set differs if predictive, rather than conceptual, discrimination is the experimental design objective. Our results show that DI analyses highlight measurements that can be used to address critical uncertainties related to the prediction of interest. Finally, we find that the optimal data set for predictive discrimination is sensitive to the predictive grouping definition in ways that are not immediately apparent from inspection of the model structure and parameter values.

  11. netherland hydrological modeling instrument (United States)

    Hoogewoud, J. C.; de Lange, W. J.; Veldhuizen, A.; Prinsen, G.


    Netherlands Hydrological Modeling Instrument A decision support system for water basin management. J.C. Hoogewoud , W.J. de Lange ,A. Veldhuizen , G. Prinsen , The Netherlands Hydrological modeling Instrument (NHI) is the center point of a framework of models, to coherently model the hydrological system and the multitude of functions it supports. Dutch hydrological institutes Deltares, Alterra, Netherlands Environmental Assessment Agency, RWS Waterdienst, STOWA and Vewin are cooperating in enhancing the NHI for adequate decision support. The instrument is used by three different ministries involved in national water policy matters, for instance the WFD, drought management, manure policy and climate change issues. The basis of the modeling instrument is a state-of-the-art on-line coupling of the groundwater system (MODFLOW), the unsaturated zone (metaSWAP) and the surface water system (MOZART-DM). It brings together hydro(geo)logical processes from the column to the basin scale, ranging from 250x250m plots to the river Rhine and includes salt water flow. The NHI is validated with an eight year run (1998-2006) with dry and wet periods. For this run different parts of the hydrology have been compared with measurements. For instance, water demands in dry periods (e.g. for irrigation), discharges at outlets, groundwater levels and evaporation. A validation alone is not enough to get support from stakeholders. Involvement from stakeholders in the modeling process is needed. There fore to gain sufficient support and trust in the instrument on different (policy) levels a couple of actions have been taken: 1. a transparent evaluation of modeling-results has been set up 2. an extensive program is running to cooperate with regional waterboards and suppliers of drinking water in improving the NHI 3. sharing (hydrological) data via newly setup Modeling Database for local and national models 4. Enhancing the NHI with "local" information. The NHI is and has been used for many

  12. Acting, predicting and intervening in a socio-hydrological world (United States)

    Lane, S. N.


    This paper asks a simple question: if humans and their actions co-evolve with hydrological systems (Sivapalan et al., 2012), what is the role of hydrological scientists, who are also humans, within this system? To put it more directly, as traditionally there is a supposed separation of scientists and society, can we maintain this separation as socio-hydrologists studying a socio-hydrological world? This paper argues that we cannot, using four linked sections. The first section draws directly upon the concern of science-technology studies to make a case to the (socio-hydrological) community that we need to be sensitive to constructivist accounts of science in general and socio-hydrology in particular. I review three positions taken by such accounts and apply them to hydrological science, supported with specific examples: (a) the ways in which scientific activities frame socio-hydrological research, such that at least some of the knowledge that we obtain is constructed by precisely what we do; (b) the need to attend to how socio-hydrological knowledge is used in decision-making, as evidence suggests that hydrological knowledge does not flow simply from science into policy; and (c) the observation that those who do not normally label themselves as socio-hydrologists may actually have a profound knowledge of socio-hydrology. The second section provides an empirical basis for considering these three issues by detailing the history of the practice of roughness parameterisation, using parameters like Manning's n, in hydrological and hydraulic models for flood inundation mapping. This history sustains the third section that is a more general consideration of one type of socio-hydrological practice: predictive modelling. I show that as part of a socio-hydrological analysis, hydrological prediction needs to be thought through much more carefully: not only because hydrological prediction exists to help inform decisions that are made about water management; but also because

  13. Toward seamless hydrologic predictions across spatial scales

    Directory of Open Access Journals (Sweden)

    L. Samaniego


    Full Text Available Land surface and hydrologic models (LSMs/HMs are used at diverse spatial resolutions ranging from catchment-scale (1–10 km to global-scale (over 50 km applications. Applying the same model structure at different spatial scales requires that the model estimates similar fluxes independent of the chosen resolution, i.e., fulfills a flux-matching condition across scales. An analysis of state-of-the-art LSMs and HMs reveals that most do not have consistent hydrologic parameter fields. Multiple experiments with the mHM, Noah-MP, PCR-GLOBWB, and WaterGAP models demonstrate the pitfalls of deficient parameterization practices currently used in most operational models, which are insufficient to satisfy the flux-matching condition. These examples demonstrate that J. Dooge's 1982 statement on the unsolved problem of parameterization in these models remains true. Based on a review of existing parameter regionalization techniques, we postulate that the multiscale parameter regionalization (MPR technique offers a practical and robust method that provides consistent (seamless parameter and flux fields across scales. Herein, we develop a general model protocol to describe how MPR can be applied to a particular model and present an example application using the PCR-GLOBWB model. Finally, we discuss potential advantages and limitations of MPR in obtaining the seamless prediction of hydrological fluxes and states across spatial scales.

  14. Combining earth observations, gis data and eco-hydrological modelling for predicting carbon budgets and water balance (United States)

    Boegh, E.; Butts, M.; Hansen, S.; Soegaard, H.; Hasager, C. B.; Pilegaard, K.; Haastrup, M.; Henriksen, H. J.; Jensen, N. O.; Kristensen, M.


    Remote sensing data, GIS data and an eco-hydrological model (Daisy) are coupled within the project EO-FLUX-BUDGET for the prediction of CO2 budgets and water balance at Zealand which is the major island of Denmark (covering approximately 7.000 km2). In order to catch the surface heterogeneity shaped by the large variety of small fields, a high-resolution (30 m) land surface map is produced from satellite observations and validated using GIS data and national statistics on agricultural land use. GIS information on the housing density of built-up areas was superimposed on the land use map to facilitate the implementation of engineering methods for assessment of surface runoff in these regions. A geological soil map is combined with soil texture data registered in 5439 locations to construct a 3-layer GIS based soil map. The ground water depth is represented by the 10 year average water head elevation which is simulated by a distributed hydrological model (MIKE SHE). The Daisy model is run using grid based meteorological data and the results are evaluated by comparing with eddy covariance atmospheric fluxes recorded in agricultural, forest and urban regions. Temporal maps of vegetation properties are produced using multi-scale remote sensing data (Landsat TM, Terra-MODIS and SPOT-VEGETATION) and used to adjust the simulated leaf area indices. The initial result shows that the model efficiency is improved by the implementation of satellite data.

  15. gis-based hydrological model based hydrological model upstream

    African Journals Online (AJOL)


    er river catchments in Nigeria graphical data [2]. A spatial hydrology which simulates the water flow and pecified region of the earth using GIS. In view of this, the use of modeling with GIS provides the platform to processes tailored towards hydrologic dely applied hydrological models for in recent time is the Soil and Water.

  16. Performance of two predictive uncertainty estimation approaches for conceptual Rainfall-Runoff Model: Bayesian Joint Inference and Hydrologic Uncertainty Post-processing (United States)

    Hernández-López, Mario R.; Romero-Cuéllar, Jonathan; Camilo Múnera-Estrada, Juan; Coccia, Gabriele; Francés, Félix


    It is noticeably important to emphasize the role of uncertainty particularly when the model forecasts are used to support decision-making and water management. This research compares two approaches for the evaluation of the predictive uncertainty in hydrological modeling. First approach is the Bayesian Joint Inference of hydrological and error models. Second approach is carried out through the Model Conditional Processor using the Truncated Normal Distribution in the transformed space. This comparison is focused on the predictive distribution reliability. The case study is applied to two basins included in the Model Parameter Estimation Experiment (MOPEX). These two basins, which have different hydrological complexity, are the French Broad River (North Carolina) and the Guadalupe River (Texas). The results indicate that generally, both approaches are able to provide similar predictive performances. However, the differences between them can arise in basins with complex hydrology (e.g. ephemeral basins). This is because obtained results with Bayesian Joint Inference are strongly dependent on the suitability of the hypothesized error model. Similarly, the results in the case of the Model Conditional Processor are mainly influenced by the selected model of tails or even by the selected full probability distribution model of the data in the real space, and by the definition of the Truncated Normal Distribution in the transformed space. In summary, the different hypotheses that the modeler choose on each of the two approaches are the main cause of the different results. This research also explores a proper combination of both methodologies which could be useful to achieve less biased hydrological parameter estimation. For this approach, firstly the predictive distribution is obtained through the Model Conditional Processor. Secondly, this predictive distribution is used to derive the corresponding additive error model which is employed for the hydrological parameter

  17. Seasonal changes in the European gravity field from GRACE: A comparison with superconducting gravimeters and hydrology model predictions

    DEFF Research Database (Denmark)

    Hinderer, J.; Andersen, Ole Baltazar; Lemoine, F.


    This paper is devoted to the investigation of seasonal changes of the Earth's gravity field from GRACE satellites and the comparison with surface gravity measurements in Europe from the Global Geodynamics Project (GGP) sub-network, as well as with recent hydrology models for continental soil......-derived and ground gravity changes due to continental hydrology is studied and we also compute the theoretical ratio of gravity versus radial displacement (in mu Gal/mm) involved in the hydrological loading process. The 'mean' value (averaged in time and in space over Europe) from hydrologic forward modeling...... is found to be close to - 1.0 mu Gal/mm and we show that this value can be explained by a strong low degree (n = 5-6) peak in the hydrology amplitude spectrum. The dominant time-variable signal from GRACE is found to be annual with an amplitude and a phase both of which are in fair agreement...

  18. Attribution of hydrologic trends using integrated hydrologic and economic models (United States)

    Maneta, M. P.; Brugger, D. R.; Silverman, N. L.


    Hydrologic change has been detected in many regions of the world in the form of trends in annual streamflows, varying depths to the regional water table, or other alterations of the hydrologic balance. Most models used to investigate these changes implement sophisticated descriptions of the physical system but use simplified descriptions of the socioeconomic system. These simplifications come in the form of prescribed water diversions and land use change scenarios, which provide little insight into coupled natural-human systems and have limited predictive capabilities. We present an integrated model that adds realism to the description of the hydrologic system in agricultural regions by incorporating a component that updates the allocation of land and water to crops in response to hydroclimatic (water available) and economic conditions (prices of commodities and agricultural inputs). This component assumes that farmers allocate resources to maximize their net revenues, thus justifying the use of optimality conditions to constrain the parameters of an empirical production function that captures the economic behavior of farmers. Because the model internalizes the feedback between climate, agricultural markets, and farming activity into the hydrologic system, it can be used to understand to what extent human economic activity can exacerbate or buffer the regional hydrologic impacts of climate change in agricultural regions. It can also help in the attribution of causes of hydrologic change. These are important issues because local policy and management cannot solve climate change, but they can address land use and agricultural water use. We demonstrate the model in a case study.

  19. Assimilating high resolution remotely sensed soil moisture into a distributed hydrologic model to improve runoff prediction: a case study. (United States)

    Mason, David; Garcia-Pintado, Javier; Cloke, Hannah; Dance, Sarah


    The susceptibility of a catchment to flooding during an extreme rainfall event is affected by its soil moisture condition prior to the event. This paper describes a study attempting to improve a distributed hydrological model by assimilating remotely sensed soil moisture in order to keep the model flow rate predictions on track in readiness for an intense rainfall event. The work is being funded within the SINATRA project of the UK NERC Flooding from Intense Rainfall (FFIR) programme. The recent launch of Sentinel-1 has stimulated interest in measuring soil moisture at high resolution suitable for hydrological studies using active SARs. One advantage of high resolution data may be that, when used in conjunction with land cover data, soil moisture values may be obtained over pixels of low vegetation cover (e.g. grassland). This may reduce the component of the backscattered signal due to vegetation, which for dense vegetation types may be a significant proportion of the whole. Additionally, backscatter contamination problems caused by mixed pixels containing unknown amounts of more than one land cover type within their coverage can be avoided. Sentinel-1 has been launched only recently, and has yet to build up a substantive sequence of flood event data suitable for analysis. As a result, ASAR WS data were used for this study. ASAR is C-band like Sentinel-1, and has a long data record. The hydrologic model HSPF was made fully spatially distributed to make it able to properly ingest the high resolution satellite surface soil moisture information, and to conduct assimilation analyses. A 1 km grid cell size was used. The study area covered the catchments of the Severn, Avon and Teme rivers (plus a further 4 sub-catchments) in the South West UK. The results of assimilating ASAR soil moisture readings over this area were compared with those of assimilating low resolution ASCAT readings. For the ASAR data, in each 1 km model grid cell, the 75 m surface soil moisture values

  20. Hydrologic model calibration using remotely sensed soil moisture and discharge measurements: The impact on predictions at gauged and ungauged locations (United States)

    Li, Yuan; Grimaldi, Stefania; Pauwels, Valentijn R. N.; Walker, Jeffrey P.


    The skill of hydrologic models, such as those used in operational flood prediction, is currently restricted by the availability of flow gauges and by the quality of the streamflow data used for calibration. The increased availability of remote sensing products provides the opportunity to further improve the model forecasting skill. A joint calibration scheme using streamflow measurements and remote sensing derived soil moisture values was examined and compared with a streamflow only calibration scheme. The efficacy of the two calibration schemes was tested in three modelling setups: 1) a lumped model; 2) a semi-distributed model with only the outlet gauge available for calibration; and 3) a semi-distributed model with multiple gauges available for calibration. The joint calibration scheme was found to slightly degrade the streamflow prediction at gauged sites during the calibration period compared with streamflow only calibration, but improvement was found at the same gauged sites during the independent validation period. A more consistent and statistically significant improvement was achieved at gauged sites not used in the calibration, due to the spatial information introduced by the remotely sensed soil moisture data. It was also found that the impact of using soil moisture for calibration tended to be stronger at the upstream and tributary sub-catchments than at the downstream sub-catchments.

  1. Rangeland Hydrology and Erosion Model (United States)

    Nearing, Mark; Pierson, Fred; Hernandez, Mariano; Al-Hamdan, Osama; Weltz, Mark; Spaeth, Ken; Wei, Haiyan; Stone, Jeff


    Soil loss rates on rangelands are considered one of the few quantitative indicators for assessing rangeland health and conservation practice effectiveness. An erosion model to predict soil loss specific for rangeland applications has been needed for many years. Most erosion models were developed from croplands where the hydrologic and erosion processes are different, largely due to much higher levels of heterogeneity in soil and plant properties at the plot scale and the consolidated nature of the soils. The Rangeland Hydrology and Erosion Model (RHEM) was designed to fill that need. RHEM is an event-based model that estimates runoff, erosion, and sediment delivery rates and volumes at the spatial scale of the hillslope and the temporal scale of a single rainfall event. It represents erosion processes under normal and fire-impacted rangeland conditions, it adopts a new splash erosion and thin sheet-flow transport equation developed from rangeland data, and it links the model hydrologic and erosion parameters with rangeland plant communities by providing a new system of parameter estimation equations based on 204 plots at 49 rangeland sites distributed across 15 western U.S. states. Recent work on the model is focused on representing intra-storm dynamics, using stream-power as the driver for detachment by flow, and deriving parameters for after-fire conditions.

  2. Hydrologic Prediction Through Earthcube Enabled Hydrogeophysical Cyberinfrastructure (United States)

    Versteeg, R. J.; Johnson, D.


    Accurate prediction of hydrologic processes is contingent on the successful interaction of multiple components, including (1) accurate conceptual and numerical models describing physical, chemical and biological processes (2) a numerical framework for integration of such processes and (3) multidisciplinary temporal data streams which feeds such models. Over the past ten years the main focus in the hydrogeophysical community has been the advancement and developments of conceptual and numerical models. While this advancement still poses numerous challenges (e.g. the in silico modeling of microbiological processes and the coupling of models across different interfaces) there is now a fairly good high level understanding of the types, scales of and interplay between processes. In parallel with this advancement there have been rapid developments in data acquisition capabilities (ranging from satellite based remote sensing to low cost sensor networks) and the associated cyberinfrastructure which allows for mash ups of data from heterogeneous and independent sensor networks. The tools for this in generally have come from outside the hydrogeophysical community - partly these are specific scientific tools developed through NSF, DOE and NASA funding, and partly these are general web2.0 tools or tools developed under commercial initiatives (e.g. the IBM Smarter Planet initiative). One challenge facing the hydrogeophysical community is how to effectively harness all these tools to develop hydrologic prediction tools. One of the primary opportunities for this is the NSF funded EarthCube effort ( ). The goal of EarthCube is to transform the conduct of research by supporting the development of community-guided cyberinfrastructure to integrate data and information for knowledge management across the Geosciences. Note that Earthcube is part of a larger NSF effort (Cyberinfrastructure for the 21st Century (CIF21), and that Earthcube is driven by the vision

  3. Gradation of complexity and predictability of hydrological processes (United States)

    Sang, Yan-Fang; Singh, Vijay P.; Wen, Jun; Liu, Changming


    Quantification of the complexity and predictability of hydrological systems is important for evaluating the impact of climate change on hydrological processes, and for guiding water activities. In the literature, the focus seems to have been on describing the complexity of spatiotemporal distribution of hydrological variables, but little attention has been paid to the study of complexity gradation, because the degree of absolute complexity of hydrological systems cannot be objectively evaluated. Here we show that complexity and predictability of hydrological processes can be graded into three ranks (low, middle, and high). The gradation is based on the difference in the energy distribution of hydrological series and that of white noise under multitemporal scales. It reflects different energy concentration levels and contents of deterministic components of the hydrological series in the three ranks. Higher energy concentration level reflects lower complexity and higher predictability, but scattered energy distribution being similar to white noise has the highest complexity and is almost unpredictable. We conclude that the three ranks (low, middle, and high) approximately correspond to deterministic, stochastic, and random hydrological systems, respectively. The result of complexity gradation can guide hydrological observations and modeling, and identification of similarity patterns among different hydrological systems.

  4. PATHS groundwater hydrologic model

    Energy Technology Data Exchange (ETDEWEB)

    Nelson, R.W.; Schur, J.A.


    A preliminary evaluation capability for two-dimensional groundwater pollution problems was developed as part of the Transport Modeling Task for the Waste Isolation Safety Assessment Program (WISAP). Our approach was to use the data limitations as a guide in setting the level of modeling detail. PATHS Groundwater Hydrologic Model is the first level (simplest) idealized hybrid analytical/numerical model for two-dimensional, saturated groundwater flow and single component transport; homogeneous geology. This document consists of the description of the PATHS groundwater hydrologic model. The preliminary evaluation capability prepared for WISAP, including the enhancements that were made because of the authors' experience using the earlier capability is described. Appendixes A through D supplement the report as follows: complete derivations of the background equations are provided in Appendix A. Appendix B is a comprehensive set of instructions for users of PATHS. It is written for users who have little or no experience with computers. Appendix C is for the programmer. It contains information on how input parameters are passed between programs in the system. It also contains program listings and test case listing. Appendix D is a definition of terms.

  5. StreamFlow 1.0: an extension to the spatially distributed snow model Alpine3D for hydrological modelling and deterministic stream temperature prediction (United States)

    Gallice, Aurélien; Bavay, Mathias; Brauchli, Tristan; Comola, Francesco; Lehning, Michael; Huwald, Hendrik


    Climate change is expected to strongly impact the hydrological and thermal regimes of Alpine rivers within the coming decades. In this context, the development of hydrological models accounting for the specific dynamics of Alpine catchments appears as one of the promising approaches to reduce our uncertainty of future mountain hydrology. This paper describes the improvements brought to StreamFlow, an existing model for hydrological and stream temperature prediction built as an external extension to the physically based snow model Alpine3D. StreamFlow's source code has been entirely written anew, taking advantage of object-oriented programming to significantly improve its structure and ease the implementation of future developments. The source code is now publicly available online, along with a complete documentation. A special emphasis has been put on modularity during the re-implementation of StreamFlow, so that many model aspects can be represented using different alternatives. For example, several options are now available to model the advection of water within the stream. This allows for an easy and fast comparison between different approaches and helps in defining more reliable uncertainty estimates of the model forecasts. In particular, a case study in a Swiss Alpine catchment reveals that the stream temperature predictions are particularly sensitive to the approach used to model the temperature of subsurface flow, a fact which has been poorly reported in the literature to date. Based on the case study, StreamFlow is shown to reproduce hourly mean discharge with a Nash-Sutcliffe efficiency (NSE) of 0.82 and hourly mean temperature with a NSE of 0.78.

  6. gis-based hydrological model based hydrological model upstream

    African Journals Online (AJOL)


    Hydrological. Hydrological modeling tools have been increasingl modeling tools have been increasingl watershed watershed level. The application of these tools hav. The application of these tools hav sensing and G sensing and Geographical Information System (GIS) eographical Information System (GIS) based models ...

  7. Design storm prediction and hydrologic modeling using a web-GIS approach on a free-software platform (United States)

    Castrogiovanni, E. M.; La Loggia, G.; Noto, L. V.


    The aim of this work has been to implement a set of procedures useful to automatise the evaluation, the design storm prediction and the flood discharge associated with a selected risk level. For this purpose a Geographic Information System has been implemented using Grass 5.0. One of the main topics of such a system is a georeferenced database of the highest intensity rainfalls and their assigned duration recorded in Sicily. This database contains the main characteristics for more than 250 raingauges, as well as the values of intense rainfall events recorded by these raingauges. These data are managed through the combined use of the PostgreSQL and GRASS-GIS 5.0 databases. Some of the best-known probability distributions have been implemented within the Geographical Information System in order to determine the point and/or areal rain values once duration and return period have been defined. The system also includes a hydrological module necessary to compute the probable flow, for a selected risk level, at points chosen by the user. A peculiarity of the system is the possibility to querying the model using a web-interface. The assumption is that the rising needs of geographic information, and dealing with the rising importance of peoples participation in the decision process, requires new forms for the diffusion of territorial data. Furthermore, technicians as well as public administrators needs to get customized and specialist data to support planning, particularly in emergencies. In this perspective a Web-interface has been developed for the hydrologic system. The aim is to allow remote users to access a centralized database and processing-power to serve the needs of knowledge without complex hardware/software infrastructures.

  8. A Combined Hydrological and Hydraulic Model for Flood Prediction in Vietnam Applied to the Huong River Basin as a Test Case Study

    Directory of Open Access Journals (Sweden)

    Dang Thanh Mai


    Full Text Available A combined hydrological and hydraulic model is presented for flood prediction in Vietnam. This model is applied to the Huong river basin as a test case study. Observed flood flows and water surface levels of the 2002–2005 flood seasons are used for model calibration, and those of the 2006–2007 flood seasons are used for validation of the model. The physically based distributed hydrologic model WetSpa is used for predicting the generation and propagation of flood flows in the mountainous upper sub-basins, and proves to predict flood flows accurately. The Hydrologic Engineering Center River Analysis System (HEC-RAS hydraulic model is applied to simulate flood flows and inundation levels in the downstream floodplain, and also proves to predict water levels accurately. The predicted water profiles are used for mapping of inundations in the floodplain. The model may be useful in developing flood forecasting and early warning systems to mitigate losses due to flooding in Vietnam.

  9. Uncertainty in hydrological change modelling

    DEFF Research Database (Denmark)

    Seaby, Lauren Paige

    Hydrological change modelling methodologies generally use climate models outputs to force hydrological simulations under changed conditions. There are nested sources of uncertainty throughout this methodology, including choice of climate model and subsequent bias correction methods. This Ph.......D. study evaluates the uncertainty of the impact of climate change in hydrological simulations given multiple climate models and bias correction methods of varying complexity. Three distribution based scaling methods (DBS) were developed and benchmarked against a more simplistic and commonly used delta...... change (DC) approach. These climate model projections were then used to force hydrological simulations under climate change for the island Sjælland in Denmark to analyse the contribution of different climate models and bias correction methods to overall uncertainty in the hydrological change modelling...

  10. Testing a distributed hydrological model to predict scenarios of extreme events on a marginal olive orchard microcatchment (United States)

    Guzmán, Enrique; Aguilar, Cristina; Taguas, Encarnación V.


    Olive groves constitute a traditional Mediterranean crop and thus, an important source of income to these regions and a crucial landscape component. Despite its importance, most of the olive groves in the region of Andalusia, Southern Spain, are located in sloping areas, which implies a significant risk of erosion. The combination of data and models allow enhancing the knowledge about processes taking place in these areas as well as the prediction of future scenarios. This aspect might be essential to plan soil protection strategies within a context of climate change where the IPCC estimates a significant increase of soil aridity and torrential events by the end of the century. The objective of this study is to estimate the rainfall-runoff-sediment dynamics in a microcatchment olive grove with the aid of a physically-based distributed hydrological model in order to evaluate the effect of extreme events on runoff and erosion. This study will allow to improve land-use and management planning activities in similar areas. In addition, the scale of the study (microcatchment) will allow to contrast the results in larger areas such as catchment regional spatial scales.

  11. Hydrological modeling in forested systems (United States)

    H.E. Golden; G.R. Evenson; S. Tian; Devendra Amatya; Ge Sun


    Characterizing and quantifying interactions among components of the forest hydrological cycle is complex and usually requires a combination of field monitoring and modelling approaches (Weiler and McDonnell, 2004; National Research Council, 2008). Models are important tools for testing hypotheses, understanding hydrological processes and synthesizing experimental data...

  12. An Implementation of Estimation Techniques to a Hydrological Model for Prediction of Runoff to a Hydroelectric Power-Station

    Directory of Open Access Journals (Sweden)

    Magne Fjeld


    Full Text Available Parameter and state estimation algorithms have been applied to a hydrological model of a catchment area in southern Norway to yield improved control of the household of water resources and better economy and efficiency in the running of the power station, as experience proves since the system was installed on-line in the summer of 1978.

  13. A CN-Based Ensembled Hydrological Model for Enhanced Watershed Runoff Prediction

    Directory of Open Access Journals (Sweden)

    Muhammad Ajmal


    Full Text Available A major structural inconsistency of the traditional curve number (CN model is its dependence on an unstable fixed initial abstraction, which normally results in sudden jumps in runoff estimation. Likewise, the lack of pre-storm soil moisture accounting (PSMA procedure is another inherent limitation of the model. To circumvent those problems, we used a variable initial abstraction after ensembling the traditional CN model and a French four-parameter (GR4J model to better quantify direct runoff from ungauged watersheds. To mimic the natural rainfall-runoff transformation at the watershed scale, our new parameterization designates intrinsic parameters and uses a simple structure. It exhibited more accurate and consistent results than earlier methods in evaluating data from 39 forest-dominated watersheds, both for small and large watersheds. In addition, based on different performance evaluation indicators, the runoff reproduction results show that the proposed model produced more consistent results for dry, normal, and wet watershed conditions than the other models used in this study.

  14. Integrated climate and hydrology modelling

    DEFF Research Database (Denmark)

    Larsen, Morten Andreas Dahl

    global warming and increased frequency of extreme events. The skill in developing projections of both the present and future climate depends essentially on the ability to numerically simulate the processes of atmospheric circulation, hydrology, energy and ecology. Previous modelling efforts of climate...... and hydrology have used each model component in an offline mode where the models are run in sequential steps and one model serves as a boundary condition or data input source to the other. Within recent years a new field of research has emerged where efforts have been made to dynamically couple existing climate....... The modelling tool consists of a fully dynamic two-way coupling of the HIRHAM regional climate model and the MIKE SHE hydrological model. The expected gain is twofold. Firstly, HIRHAM utilizes the land surface component of the combined MIKE SHE/SWET hydrology and land surface model (LSM), which is superior...

  15. Comment on Can assimilation of crowdsourced data in hydrological modelling improve flood prediction? by Mazzoleni et al. (2017)


    Viero, Daniele P.


    In their recent contribution, Mazzoleni et al. (2017) investigated the integration of crowdsourced data (CSD) in hydrological models to improve the accuracy of real-time flood forecast. They showed that assimilation of CSD improves the overall model performance in all the considered case studies. The impact of irregular frequency of available crowdsourced data, and that of data uncertainty, were also deeply assessed. However, it has to be remarked that, in their work, the Authors used synthe...

  16. The Hydrologic Ensemble Prediction Experiment (HEPEX) (United States)

    Wood, A. W.; Thielen, J.; Pappenberger, F.; Schaake, J. C.; Hartman, R. K.


    The Hydrologic Ensemble Prediction Experiment was established in March, 2004, at a workshop hosted by the European Center for Medium Range Weather Forecasting (ECMWF). With support from the US National Weather Service (NWS) and the European Commission (EC), the HEPEX goal was to bring the international hydrological and meteorological communities together to advance the understanding and adoption of hydrological ensemble forecasts for decision support in emergency management and water resources sectors. The strategy to meet this goal includes meetings that connect the user, forecast producer and research communities to exchange ideas, data and methods; the coordination of experiments to address specific challenges; and the formation of testbeds to facilitate shared experimentation. HEPEX has organized about a dozen international workshops, as well as sessions at scientific meetings (including AMS, AGU and EGU) and special issues of scientific journals where workshop results have been published. Today, the HEPEX mission is to demonstrate the added value of hydrological ensemble prediction systems (HEPS) for emergency management and water resources sectors to make decisions that have important consequences for economy, public health, safety, and the environment. HEPEX is now organised around six major themes that represent core elements of a hydrologic ensemble prediction enterprise: input and pre-processing, ensemble techniques, data assimilation, post-processing, verification, and communication and use in decision making. This poster presents an overview of recent and planned HEPEX activities, highlighting case studies that exemplify the focus and objectives of HEPEX.

  17. Rain or snow: hydrologic processes, observations, prediction, and research needs (United States)

    Harpold, Adrian A.; Kaplan, Michael L.; Zion Klos, P.; Link, Timothy; McNamara, James P.; Rajagopal, Seshadri; Schumer, Rina; Steele, Caitriana M.


    The phase of precipitation when it reaches the ground is a first-order driver of hydrologic processes in a watershed. The presence of snow, rain, or mixed-phase precipitation affects the initial and boundary conditions that drive hydrological models. Despite their foundational importance to terrestrial hydrology, typical phase partitioning methods (PPMs) specify the phase based on near-surface air temperature only. Our review conveys the diversity of tools available for PPMs in hydrological modeling and the advancements needed to improve predictions in complex terrain with large spatiotemporal variations in precipitation phase. Initially, we review the processes and physics that control precipitation phase as relevant to hydrologists, focusing on the importance of processes occurring aloft. There is a wide range of options for field observations of precipitation phase, but there is a lack of a robust observation networks in complex terrain. New remote sensing observations have the potential to increase PPM fidelity, but generally require assumptions typical of other PPMs and field validation before they are operational. We review common PPMs and find that accuracy is generally increased at finer measurement intervals and by including humidity information. One important tool for PPM development is atmospheric modeling, which includes microphysical schemes that have not been effectively linked to hydrological models or validated against near-surface precipitation-phase observations. The review concludes by describing key research gaps and recommendations to improve PPMs, including better incorporation of atmospheric information, improved validation datasets, and regional-scale gridded data products. Two key points emerge from this synthesis for the hydrologic community: (1) current PPMs are too simple to capture important processes and are not well validated for most locations, (2) lack of sophisticated PPMs increases the uncertainty in estimation of hydrological

  18. Integrating SMOS brightness temperatures with a new conceptual spatially distributed hydrological model for improving flood and drought predictions at large scale. (United States)

    Hostache, Renaud; Rains, Dominik; Chini, Marco; Lievens, Hans; Verhoest, Niko E. C.; Matgen, Patrick


    Motivated by climate change and its impact on the scarcity or excess of water in many parts of the world, several agencies and research institutions have taken initiatives in monitoring and predicting the hydrologic cycle at a global scale. Such a monitoring/prediction effort is important for understanding the vulnerability to extreme hydrological events and for providing early warnings. This can be based on an optimal combination of hydro-meteorological models and remote sensing, in which satellite measurements can be used as forcing or calibration data or for regularly updating the model states or parameters. Many advances have been made in these domains and the near future will bring new opportunities with respect to remote sensing as a result of the increasing number of spaceborn sensors enabling the large scale monitoring of water resources. Besides of these advances, there is currently a tendency to refine and further complicate physically-based hydrologic models to better capture the hydrologic processes at hand. However, this may not necessarily be beneficial for large-scale hydrology, as computational efforts are therefore increasing significantly. As a matter of fact, a novel thematic science question that is to be investigated is whether a flexible conceptual model can match the performance of a complex physically-based model for hydrologic simulations at large scale. In this context, the main objective of this study is to investigate how innovative techniques that allow for the estimation of soil moisture from satellite data can help in reducing errors and uncertainties in large scale conceptual hydro-meteorological modelling. A spatially distributed conceptual hydrologic model has been set up based on recent developments of the SUPERFLEX modelling framework. As it requires limited computational efforts, this model enables early warnings for large areas. Using as forcings the ERA-Interim public dataset and coupled with the CMEM radiative transfer model

  19. An Integrated Modelling System to Predict Hydrological Processes under Climate and Land-Use/Cover Change Scenarios

    Directory of Open Access Journals (Sweden)

    Babak Farjad


    Full Text Available This study proposes an integrated modeling system consisting of the physically-based MIKE SHE/MIKE 11 model, a cellular automata model, and general circulation models (GCMs scenarios to investigate the independent and combined effects of future climate and land-use/land-cover (LULC changes on the hydrology of a river system. The integrated modelling system is applied to the Elbow River watershed in southern Alberta, Canada in conjunction with extreme GCM scenarios and two LULC change scenarios in the 2020s and 2050s. Results reveal that LULC change substantially modifies the river flow regime in the east sub-catchment, where rapid urbanization is occurring. It is also shown that the change in LULC causes an increase in peak flows in both the 2020s and 2050s. The impacts of climate and LULC change on streamflow are positively correlated in winter and spring, which intensifies their influence and leads to a significant rise in streamflow, and, subsequently, increases the vulnerability of the watershed to spring floods. This study highlights the importance of using an integrated modeling approach to investigate both the independent and combined impacts of climate and LULC changes on the future of hydrology to improve our understanding of how watersheds will respond to climate and LULC changes.

  20. Evaluating spatial patterns in hydrological modelling

    DEFF Research Database (Denmark)

    Koch, Julian

    is not fully exploited by current modelling frameworks due to the lack of suitable spatial performance metrics. Furthermore, the traditional model evaluation using discharge is found unsuitable to lay confidence on the predicted catchment inherent spatial variability of hydrological processes in a fully...... the contiguous United Sates (10^6 km2). To this end, the thesis at hand applies a set of spatial performance metrics on various hydrological variables, namely land-surface-temperature (LST), evapotranspiration (ET) and soil moisture. The inspiration for the applied metrics is found in related fields...

  1. The Hydrologic Ensemble Prediction Experiment (HEPEX) (United States)

    Wood, Andy; Wetterhall, Fredrik; Ramos, Maria-Helena


    The Hydrologic Ensemble Prediction Experiment was established in March, 2004, at a workshop hosted by the European Center for Medium Range Weather Forecasting (ECMWF), and co-sponsored by the US National Weather Service (NWS) and the European Commission (EC). The HEPEX goal was to bring the international hydrological and meteorological communities together to advance the understanding and adoption of hydrological ensemble forecasts for decision support. HEPEX pursues this goal through research efforts and practical implementations involving six core elements of a hydrologic ensemble prediction enterprise: input and pre-processing, ensemble techniques, data assimilation, post-processing, verification, and communication and use in decision making. HEPEX has grown through meetings that connect the user, forecast producer and research communities to exchange ideas, data and methods; the coordination of experiments to address specific challenges; and the formation of testbeds to facilitate shared experimentation. In the last decade, HEPEX has organized over a dozen international workshops, as well as sessions at scientific meetings (including AMS, AGU and EGU) and special issues of scientific journals where workshop results have been published. Through these interactions and an active online blog (, HEPEX has built a strong and active community of nearly 400 researchers & practitioners around the world. This poster presents an overview of recent and planned HEPEX activities, highlighting case studies that exemplify the focus and objectives of HEPEX.

  2. Stochastic Modelling of Hydrologic Systems

    DEFF Research Database (Denmark)

    Jonsdottir, Harpa


    In this PhD project several stochastic modelling methods are studied and applied on various subjects in hydrology. The research was prepared at Informatics and Mathematical Modelling at the Technical University of Denmark. The thesis is divided into two parts. The first part contains an introduct......In this PhD project several stochastic modelling methods are studied and applied on various subjects in hydrology. The research was prepared at Informatics and Mathematical Modelling at the Technical University of Denmark. The thesis is divided into two parts. The first part contains...... an introduction and an overview of the papers published. Then an introduction to basic concepts in hydrology along with a description of hydrological data is given. Finally an introduction to stochastic modelling is given. The second part contains the research papers. In the research papers the stochastic methods...... are described, as at the time of publication these methods represent new contribution to hydrology. The second part also contains additional description of software used and a brief introduction to stiff systems. The system in one of the papers is stiff....

  3. Model Calibration in Watershed Hydrology (United States)

    Yilmaz, Koray K.; Vrugt, Jasper A.; Gupta, Hoshin V.; Sorooshian, Soroosh


    Hydrologic models use relatively simple mathematical equations to conceptualize and aggregate the complex, spatially distributed, and highly interrelated water, energy, and vegetation processes in a watershed. A consequence of process aggregation is that the model parameters often do not represent directly measurable entities and must, therefore, be estimated using measurements of the system inputs and outputs. During this process, known as model calibration, the parameters are adjusted so that the behavior of the model approximates, as closely and consistently as possible, the observed response of the hydrologic system over some historical period of time. This Chapter reviews the current state-of-the-art of model calibration in watershed hydrology with special emphasis on our own contributions in the last few decades. We discuss the historical background that has led to current perspectives, and review different approaches for manual and automatic single- and multi-objective parameter estimation. In particular, we highlight the recent developments in the calibration of distributed hydrologic models using parameter dimensionality reduction sampling, parameter regularization and parallel computing.

  4. On the sources of global land surface hydrologic predictability

    Directory of Open Access Journals (Sweden)

    S. Shukla


    Full Text Available Global seasonal hydrologic prediction is crucial to mitigating the impacts of droughts and floods, especially in the developing world. Hydrologic predictability at seasonal lead times (i.e., 1–6 months comes from knowledge of initial hydrologic conditions (IHCs and seasonal climate forecast skill (FS. In this study we quantify the contributions of two primary components of IHCs – soil moisture and snow water content – and FS (of precipitation and temperature to seasonal hydrologic predictability globally on a relative basis throughout the year. We do so by conducting two model-based experiments using the variable infiltration capacity (VIC macroscale hydrology model, one based on ensemble streamflow prediction (ESP and another based on Reverse-ESP (Rev-ESP, both for a 47 yr re-forecast period (1961–2007. We compare cumulative runoff (CR, soil moisture (SM and snow water equivalent (SWE forecasts from each experiment with a VIC model-based reference data set (generated using observed atmospheric forcings and estimate the ratio of root mean square error (RMSE of both experiments for each forecast initialization date and lead time, to determine the relative contribution of IHCs and FS to the seasonal hydrologic predictability. We find that in general, the contributions of IHCs to seasonal hydrologic predictability is highest in the arid and snow-dominated climate (high latitude regions of the Northern Hemisphere during forecast periods starting on 1 January and 1 October. In mid-latitude regions, such as the Western US, the influence of IHCs is greatest during the forecast period starting on 1 April. In the arid and warm temperate dry winter regions of the Southern Hemisphere, the IHCs dominate during forecast periods starting on 1 April and 1 July. In equatorial humid and monsoonal climate regions, the contribution of FS is generally higher than IHCs through most of the year. Based on our findings, we argue that despite the limited FS

  5. Integrating hydrology within a fully coupled environmental prediction system (United States)

    Best, Martin; Lewis, Huw; Ashton, Heather; Blyth, Eleanor; Martinez, Alberto


    Historically the hydrological community and the community developing the land surface component of atmospheric models have both been tasked with representing the terrestrial hydrological cycle, but have focused on different ends, namely streamflow and evaporation respectively. To date the lack of computational resources and representative observations have limited the integration of the skills within these two communities. However, this is no longer the case. In addition, the drive toward fully integrated high resolution environmental prediction systems, coupling atmosphere, land and ocean on regional domains, requires an accurate representation for all aspects of terrestrial hydrology. Hence a new focus is emerging to integrate improved hydrological processes within the land surface components of atmospheric models. The UK Environmental Prediction (UKEP) project is a research experiment aimed at understanding the potential benefits for detailed environmental forecasting from a fully coupled atmosphere/land/ocean system at km-scale resolution for the UK. The prototype model utilises the Joint UK Land Environment Simulator (JULES) as its land surface component, coupled to the RFM river flow model. Although JULES has been previously used for climate studies that close the global water cycle, the JULES/RFM system has not been comprehensively evaluated for its ability to simulate river discharge. In this study we attempt some initial evaluation of the JULES/RFM system for all aspects of the terrestrial hydrological cycle, including evaporation, soil moisture and streamflow. In addition, comparisons are made between the results from the fully coupled environmental prediction system and stand alone JULES/RFM simulations forced by atmospheric driving data from the UK weather forecasting model. This provides an opportunity to assess the impact of fully coupled versus a one way coupled response for terrestrial hydrology. Finally we consider the potential for coupling JULES

  6. Assessing the impact of land use change on hydrology by ensemble modelling (LUCHEM) II: Ensemble combinations and predictions (United States)

    Viney, N.R.; Bormann, H.; Breuer, L.; Bronstert, A.; Croke, B.F.W.; Frede, H.; Graff, T.; Hubrechts, L.; Huisman, J.A.; Jakeman, A.J.; Kite, G.W.; Lanini, J.; Leavesley, G.; Lettenmaier, D.P.; Lindstrom, G.; Seibert, J.; Sivapalan, M.; Willems, P.


    This paper reports on a project to compare predictions from a range of catchment models applied to a mesoscale river basin in central Germany and to assess various ensemble predictions of catchment streamflow. The models encompass a large range in inherent complexity and input requirements. In approximate order of decreasing complexity, they are DHSVM, MIKE-SHE, TOPLATS, WASIM-ETH, SWAT, PRMS, SLURP, HBV, LASCAM and IHACRES. The models are calibrated twice using different sets of input data. The two predictions from each model are then combined by simple averaging to produce a single-model ensemble. The 10 resulting single-model ensembles are combined in various ways to produce multi-model ensemble predictions. Both the single-model ensembles and the multi-model ensembles are shown to give predictions that are generally superior to those of their respective constituent models, both during a 7-year calibration period and a 9-year validation period. This occurs despite a considerable disparity in performance of the individual models. Even the weakest of models is shown to contribute useful information to the ensembles they are part of. The best model combination methods are a trimmed mean (constructed using the central four or six predictions each day) and a weighted mean ensemble (with weights calculated from calibration performance) that places relatively large weights on the better performing models. Conditional ensembles, in which separate model weights are used in different system states (e.g. summer and winter, high and low flows) generally yield little improvement over the weighted mean ensemble. However a conditional ensemble that discriminates between rising and receding flows shows moderate improvement. An analysis of ensemble predictions shows that the best ensembles are not necessarily those containing the best individual models. Conversely, it appears that some models that predict well individually do not necessarily combine well with other models in

  7. Eco-Hydrological Modelling of Stream Valleys

    DEFF Research Database (Denmark)

    Johansen, Ole

    Predicting the effects of hydrological alterations on terrestrial stream valley ecosystems requires multidisciplinary approaches involving both engineers and ecologists. Groundwater discharge in stream valleys and other lowland areas support a number of species rich ecosystems, and their protection...... is prioritised worldwide. Protection requires improved knowledge on the functioning of these ecosystems and especially the linkages between vegetation, groundwater discharge and water level conditions are crucial for management applications. Groundwater abstraction affects catchment hydrology and thereby also...... groundwater discharge. Numerical hydrological modelling has been widely used for evaluation of sustainable groundwater resources and effects of abstraction, however, the importance of local scale heterogeneity becomes increasingly important in the assessment of local damage to these groundwater dependent...

  8. Time Changes of the European Gravity Field from GRACE: A Comparison with Ground Measurements from Superconducting Gravimeters and with Hydrology Model Predictions (United States)

    Hinderer, J.; Lemoine, Frank G.; Crossley, D.; Boy, J.-P.


    We investigate the time-variable gravity changes in Europe retrieved from the initial GRACE monthly solutions spanning a 18 month duration from April 2002 to October 2003. Gravity anomaly maps are retrieved in Central Europe from the monthly satellite solutions we compare the fields according to various truncation levels (typically between degree 10 and 20) of the initial fields (expressed in spherical harmonics to degree 120). For these different degrees, an empirical orthogonal function (EOF) decomposition of the time-variable gravity field leads us to its main spatial and temporal characteristics. We show that the dominant signal is found to be annual with an amplitude and a phase both in agreement with predictions in Europe modeled using snow and soil-moisture variations from recent hydrology models. We compare these GRACE gravity field changes to surface gravity observations from 6 superconducting gravimeters of the GGP (Global Geodynamics Project) European sub-network, with a special attention to loading corrections. Initial results suggest that all 3 data sets (GRACE, hydrology and GGP) are responding to annual changes in near-surface water in Europe of a few microGal (at length scales of approx.1000 km) that show a high value in winter and a summer minimum. We also point out that the GRACE gravity field evolution seems to indicate that there is a trend in gravity between summer 2002 and summer 2003 which can be related to the 2003 heatwave in Europe and its hydrological consequences (drought). Despite the limited time span of our analysis and the uncertainties in retrieving a regional solution from the network of gravimeters, the calibration and validation aspects of the GRACE data processing based on the annual hydrology cycle in Europe are in progress.

  9. Integrated climate and hydrology modelling

    DEFF Research Database (Denmark)

    Larsen, Morten Andreas Dahl

    To ensure optimal management and sustainable strategies for water resources, infrastructures, food production and ecosystems there is a need for an improved understanding of feedback and interaction mechanisms between the atmosphere and the land surface. This is especially true in light of expected...... global warming and increased frequency of extreme events. The skill in developing projections of both the present and future climate depends essentially on the ability to numerically simulate the processes of atmospheric circulation, hydrology, energy and ecology. Previous modelling efforts of climate...... and hydrology models to more directly include the interaction between the atmosphere and the land surface. The present PhD study is motivated by an ambition of developing and applying a modelling tool capable of including the interaction and feedback mechanisms between the atmosphere and the land surface...

  10. Socio-hydrological flood models (United States)

    Barendrecht, Marlies; Viglione, Alberto; Blöschl, Günter


    Long-term feedbacks between humans and floods may lead to complex phenomena such as coping strategies, levee effects, call effects, adaptation effects, and poverty traps. Such phenomena cannot be represented by traditional flood risk approaches that are based on scenarios. Instead, dynamic models of the coupled human-flood interactions are needed. These types of models should include both social and hydrological variables as well as other relevant variables, such as economic, environmental, political or technical, in order to adequately represent the feedbacks and processes that are of importance in human-flood systems. These socio-hydrological models may play an important role in integrated flood risk management by exploring a wider range of possible futures, including unexpected phenomena, than is possible by creating and studying scenarios. New insights might come to light about the long term effects of certain measures on society and the natural system. Here we discuss a dynamic framework for flood risk and review the models that are presented in literature. We propose a way forward for socio-hydrological modelling of the human-flood system.

  11. Using precise data sets on farming and pesticide properties to verify a diffuse pollution hydrological model for predicting pesticide concentration. (United States)

    Matsui, Y; Narita, K; Inoue, T; Matsushita, T


    Verification of a diffuse pollution model involves comparing results actually observed with those predicted by precise model inputs. Acquisition of precise model inputs is, however, problematic. In particular, when the target catchment is large and substantial estimation uncertainty exists, not only model verification but also prediction is difficult. Therefore, in this study, rice-farming data were collected for all paddy fields from all farmers in a catchment and pesticide adsorption and degradation rates in paddy field soil samples were measured to obtain precise model inputs. The model inputs successfully verified the model's capability to predict pesticide concentrations in river water. Sensitivity analyses of the model inputs elucidated the processes significantly affecting pesticide runoff from rice farms. Pesticide adsorption and degradation rates of the soil did not significantly affect pesticide concentrations, although pesticide discharge to river water accounted for less than 50% of the total quantity of pesticide applied to fields, possibly owing to pesticide adsorption and degradation. The timing of increases in pesticide concentrations in river water was affected mostly by the farming schedule, including the time of pesticide application and irrigation, and secondarily by rainfall events.

  12. Impacts of Spatial Climatic Representation on Hydrological Model Calibration and Prediction Uncertainty: A Mountainous Catchment of Three Gorges Reservoir Region, China

    Directory of Open Access Journals (Sweden)

    Yan Li


    Full Text Available Sparse climatic observations represent a major challenge for hydrological modeling of mountain catchments with implications for decision-making in water resources management. Employing elevation bands in the Soil and Water Assessment Tool-Sequential Uncertainty Fitting (SWAT2012-SUFI2 model enabled representation of precipitation and temperature variation with altitude in the Daning river catchment (Three Gorges Reservoir Region, China where meteorological inputs are limited in spatial extent and are derived from observations from relatively low lying locations. Inclusion of elevation bands produced better model performance for 1987–1993 with the Nash–Sutcliffe efficiency (NSE increasing by at least 0.11 prior to calibration. During calibration prediction uncertainty was greatly reduced. With similar R-factors from the earlier calibration iterations, a further 11% of observations were included within the 95% prediction uncertainty (95PPU compared to the model without elevation bands. For behavioral simulations defined in SWAT calibration using a NSE threshold of 0.3, an additional 3.9% of observations were within the 95PPU while the uncertainty reduced by 7.6% in the model with elevation bands. The calibrated model with elevation bands reproduced observed river discharges with the performance in the calibration period changing to “very good” from “poor” without elevation bands. The output uncertainty of calibrated model with elevation bands was satisfactory, having 85% of flow observations included within the 95PPU. These results clearly demonstrate the requirement to account for orographic effects on precipitation and temperature in hydrological models of mountainous catchments.

  13. Hydrological modelling of drained blanket peatland (United States)

    Ballard, C. E.; McIntyre, N.; Wheater, H. S.; Holden, J.; Wallage, Z. E.


    SummaryOpen ditch drainage is a commonly implemented land management practice in upland blanket peatlands, particularly in the UK, where policy decisions between the 1940s and 1970s led to widespread drainage of the uplands. The change in the hydrological regime associated with the drainage of blanket peat is poorly understood, yet has perceived importance for flooding, low flows and water quality. We propose a new simplified physics-based model that allows the associated hydrological processes and flow responses to be explored. The model couples four one-dimensional models to represent a three-dimensional hillslope, allowing for the exploration of flow and water table response throughout the model domain for a range of drainage configurations and peat properties. The model is tested against a data set collected from Oughtershaw Beck, UK, with results showing good model performance for wet periods although less conformity with borehole observations during rewetting periods. A wider exploration of model behaviour indicates that the model is consistent with the hydrological response reported in the literature for a number of drained blanket peat sites, and therefore has potential to provide guidance to decision makers concerning the effects of management practices. Through a global sensitivity analysis, we conclude that further field investigations to assist in the surface and drain roughness parameterisation would help reduce the uncertainty in the model predictions.

  14. Performance of Two Hydrological Models in Predicting Daily Flow under a Climate Change Scenario for Mountainous Catchments in Northwestern Costa Rica

    Directory of Open Access Journals (Sweden)

    César D. Jiménez-Rodríguez 


    Full Text Available Tropical mountain regions contain the main headwaters of important rivers in Central America. We selected 2 contrasting catchments located in a mountainous region to evaluate the precision of daily flow estimates based on the Hydrological Land Use Change (HYLUC and Nedbør-Afstrømnings Model (NAM hydrological models. A second objective was to simulate the impact of expected climate change for the year 2050 on stream flows and seasonal distribution of rainfall. We studied the catchments of the Tempisquito and Cucaracho streams, located in the Guanacaste volcanic mountain range of Costa Rica, from April 2008 to October 2010. Modeling of discharge using the NAM and HYLUC models suggested difficulties in their calibration due to intrinsic catchment characteristics because of their volcanic origin. The climate change scenario applied in both catchments depicted a strong reduction in discharge. However, the Cucaracho catchment, on the Caribbean slope, is predicted to experience a smaller reduction in discharge than the Tempisquito catchment, located on the Pacific slope.

  15. Development and comparison of multiple regression models to predict bankfull channel dimensions for use in hydrologic models (United States)

    Bankfull hydraulic geometry relationships are used to estimate channel dimensions for streamflow simulation models, which require channel geometry data as input parameters. Often, one nationwide curve is used across the entire United States (U.S.) (e.g., in Soil and Water Assessment Tool), even tho...

  16. Using the Storm Water Management Model to predict urban headwater stream hydrological response to climate and land cover change (United States)

    Wu, J. Y.; Thompson, J. R.; Kolka, R. K.; Franz, K. J.; Stewart, T. W.


    Streams are natural features in urban landscapes that can provide ecosystem services for urban residents. However, urban streams are under increasing pressure caused by multiple anthropogenic impacts, including increases in human population and associated impervious surface area, and accelerated climate change. The ability to anticipate these changes and better understand their effects on streams is important for developing and implementing strategies to mitigate potentially negative effects. In this study, stream flow was monitored during April-November (2011 and 2012), and the data were used to apply the Storm Water Management Model (SWMM) for five urban watersheds in central Iowa, USA, representing a gradient of percent impervious surface (IS, ranging from 5.3 to 37.1%). A set of three scenarios was designed to quantify hydrological responses to independent and combined effects of climate change (18% increase in precipitation), and land cover change (absolute increases between 5.2 and 17.1%, based on separate projections of impervious surfaces for the five watersheds) for the year 2040 compared to a current condition simulation. An additional set of three scenarios examined stream response to different distributions of land cover change within a single watershed. Hydrological responses were quantified using three indices: unit-area peak discharge, flashiness (R-B Index; Richards-Baker Index), and runoff ratio. Stream hydrology was strongly affected by watershed percent IS. For the current condition simulation, values for all three indices were five to seven times greater in the most developed watershed compared to the least developed watershed. The climate change scenario caused a 20.8% increase in unit-area peak discharge on average across the five watersheds compared to the current condition simulation. The land cover change scenario resulted in large increases for all three indices: 49.5% for unit-area peak discharge, 39.3% for R-B Index, and 73.9% for runoff

  17. Climate Sensitivity Runs and Regional Hydrologic Modeling for Predicting the Response of the Greater Florida Everglades Ecosystem to Climate Change (United States)

    Obeysekera, Jayantha; Barnes, Jenifer; Nungesser, Martha


    It is important to understand the vulnerability of the water management system in south Florida and to determine the resilience and robustness of greater Everglades restoration plans under future climate change. The current climate models, at both global and regional scales, are not ready to deliver specific climatic datasets for water resources investigations involving future plans and therefore a scenario based approach was adopted for this first study in restoration planning. We focused on the general implications of potential changes in future temperature and associated changes in evapotranspiration, precipitation, and sea levels at the regional boundary. From these, we developed a set of six climate and sea level scenarios, used them to simulate the hydrologic response of the greater Everglades region including agricultural, urban, and natural areas, and compared the results to those from a base run of current conditions. The scenarios included a 1.5 °C increase in temperature, ±10 % change in precipitation, and a 0.46 m (1.5 feet) increase in sea level for the 50-year planning horizon. The results suggested that, depending on the rainfall and temperature scenario, there would be significant changes in water budgets, ecosystem performance, and in water supply demands met. The increased sea level scenarios also show that the ground water levels would increase significantly with associated implications for flood protection in the urbanized areas of southeastern Florida.

  18. iTree-Hydro: Snow hydrology update for the urban forest hydrology model (United States)

    Yang Yang; Theodore A. Endreny; David J. Nowak


    This article presents snow hydrology updates made to iTree-Hydro, previously called the Urban Forest Effects—Hydrology model. iTree-Hydro Version 1 was a warm climate model developed by the USDA Forest Service to provide a process-based planning tool with robust water quantity and quality predictions given data limitations common to most urban areas. Cold climate...

  19. Comment on “Can assimilation of crowdsourced data in hydrological modelling improve flood prediction?” by Mazzoleni et al. (2017

    Directory of Open Access Journals (Sweden)

    D. P. Viero


    Full Text Available Citizen science and crowdsourcing are gaining increasing attention among hydrologists. In a recent contribution, Mazzoleni et al. (2017 investigated the integration of crowdsourced data (CSD into hydrological models to improve the accuracy of real-time flood forecasts. The authors used synthetic CSD (i.e. not actually measured, because real CSD were not available at the time of the study. In their work, which is a proof-of-concept study, Mazzoleni et al. (2017 showed that assimilation of CSD improves the overall model performance; the impact of irregular frequency of available CSD, and that of data uncertainty, were also deeply assessed. However, the use of synthetic CSD in conjunction with (semi-distributed hydrological models deserves further discussion. As a result of equifinality, poor model identifiability, and deficiencies in model structure, internal states of (semi-distributed models can hardly mimic the actual states of complex systems away from calibration points. Accordingly, the use of synthetic CSD that are drawn from model internal states under best-fit conditions can lead to overestimation of the effectiveness of CSD assimilation in improving flood prediction. Operational flood forecasting, which results in decisions of high societal value, requires robust knowledge of the model behaviour and an in-depth assessment of both model structure and forcing data. Additional guidelines are given that are useful for the a priori evaluation of CSD for real-time flood forecasting and, hopefully, for planning apt design strategies for both model calibration and collection of CSD.

  20. Solid phase evolution in the Biosphere 2 hillslope experiment as predicted by modeling of hydrologic and geochemical fluxes

    Energy Technology Data Exchange (ETDEWEB)

    Dontsova, K.; Steefel, C.I.; Desilets, S.; Thompson, A.; Chorover, J.


    A reactive transport geochemical modeling study was conducted to help predict the mineral transformations occurring over a ten year time-scale that are expected to impact soil hydraulic properties in the Biosphere 2 (B2) synthetic hillslope experiment. The modeling sought to predict the rate and extent of weathering of a granular basalt (selected for hillslope construction) as a function of climatic drivers, and to assess the feedback effects of such weathering processes on the hydraulic properties of the hillslope. Flow vectors were imported from HYDRUS into a reactive transport code, CrunchFlow2007, which was then used to model mineral weathering coupled to reactive solute transport. Associated particle size evolution was translated into changes in saturated hydraulic conductivity using Rosetta software. We found that flow characteristics, including velocity and saturation, strongly influenced the predicted extent of incongruent mineral weathering and neo-phase precipitation on the hillslope. Results were also highly sensitive to specific surface areas of the soil media, consistent with surface reaction controls on dissolution. Effects of fluid flow on weathering resulted in significant differences in the prediction of soil particle size distributions, which should feedback to alter hillslope hydraulic conductivities.

  1. Grid based calibration of SWAT hydrological models

    Directory of Open Access Journals (Sweden)

    D. Gorgan


    Full Text Available The calibration and execution of large hydrological models, such as SWAT (soil and water assessment tool, developed for large areas, high resolution, and huge input data, need not only quite a long execution time but also high computation resources. SWAT hydrological model supports studies and predictions of the impact of land management practices on water, sediment, and agricultural chemical yields in complex watersheds. The paper presents the gSWAT application as a web practical solution for environmental specialists to calibrate extensive hydrological models and to run scenarios, by hiding the complex control of processes and heterogeneous resources across the grid based high computation infrastructure. The paper highlights the basic functionalities of the gSWAT platform, and the features of the graphical user interface. The presentation is concerned with the development of working sessions, interactive control of calibration, direct and basic editing of parameters, process monitoring, and graphical and interactive visualization of the results. The experiments performed on different SWAT models and the obtained results argue the benefits brought by the grid parallel and distributed environment as a solution for the processing platform. All the instances of SWAT models used in the reported experiments have been developed through the enviroGRIDS project, targeting the Black Sea catchment area.

  2. Merging Real-Time Channel Sensor Networks with Continental-Scale Hydrologic Models: A Data Assimilation Approach for Improving Accuracy in Flood Depth Predictions

    Directory of Open Access Journals (Sweden)

    Amir Javaheri


    Full Text Available This study proposes a framework that (i uses data assimilation as a post processing technique to increase the accuracy of water depth prediction, (ii updates streamflow generated by the National Water Model (NWM, and (iii proposes a scope for updating the initial condition of continental-scale hydrologic models. Predicted flows by the NWM for each stream were converted to the water depth using the Height Above Nearest Drainage (HAND method. The water level measurements from the Iowa Flood Inundation System (a test bed sensor network in this study were converted to water depths and then assimilated into the HAND model using the ensemble Kalman filter (EnKF. The results showed that after assimilating the water depth using the EnKF, for a flood event during 2015, the normalized root mean square error was reduced by 0.50 m (51% for training tributaries. Comparison of the updated modeled water stage values with observations at testing locations showed that the proposed methodology was also effective on the tributaries with no observations. The overall error reduced from 0.89 m to 0.44 m for testing tributaries. The updated depths were then converted to streamflow using rating curves generated by the HAND model. The error between updated flows and observations at United States Geological Survey (USGS station at Squaw Creek decreased by 35%. For future work, updated streamflows could also be used to dynamically update initial conditions in the continental-scale National Water Model.

  3. Hydrological now- and forecasting : Integration of operationally available remotely sensed and forecasted hydrometeorological variables into distributed hydrological models

    NARCIS (Netherlands)

    Schuurmans, J.M.|info:eu-repo/dai/nl/304832650


    Keywords: hydrology, models, soil moisture, rainfall, radar, rain gauge, remote sensing, evapotranspiration, forecasting, numerical weather prediction, Netherlands, Langbroekerwetering, Lopikerwaard. Computer simulation models are an important tool for hydrologists. With these models they can

  4. Why hydrological predictions should be evaluated using information theory

    Directory of Open Access Journals (Sweden)

    S. V. Weijs


    Full Text Available Probabilistic predictions are becoming increasingly popular in hydrology. Equally important are methods to test such predictions, given the topical debate on uncertainty analysis in hydrology. Also in the special case of hydrological forecasting, there is still discussion about which scores to use for their evaluation. In this paper, we propose to use information theory as the central framework to evaluate predictions. From this perspective, we hope to shed some light on what verification scores measure and should measure. We start from the ''divergence score'', a relative entropy measure that was recently found to be an appropriate measure for forecast quality. An interpretation of a decomposition of this measure provides insight in additive relations between climatological uncertainty, correct information, wrong information and remaining uncertainty. When the score is applied to deterministic forecasts, it follows that these increase uncertainty to infinity. In practice, however, deterministic forecasts tend to be judged far more mildly and are widely used. We resolve this paradoxical result by proposing that deterministic forecasts either are implicitly probabilistic or are implicitly evaluated with an underlying decision problem or utility in mind. We further propose that calibration of models representing a hydrological system should be the based on information-theoretical scores, because this allows extracting all information from the observations and avoids learning from information that is not there. Calibration based on maximizing utility for society trains an implicit decision model rather than the forecasting system itself. This inevitably results in a loss or distortion of information in the data and more risk of overfitting, possibly leading to less valuable and informative forecasts. We also show this in an example. The final conclusion is that models should preferably be explicitly probabilistic and calibrated to maximize the

  5. Why hydrological predictions should be evaluated using information theory (United States)

    Weijs, S. V.; Schoups, G.; van de Giesen, N.


    Probabilistic predictions are becoming increasingly popular in hydrology. Equally important are methods to test such predictions, given the topical debate on uncertainty analysis in hydrology. Also in the special case of hydrological forecasting, there is still discussion about which scores to use for their evaluation. In this paper, we propose to use information theory as the central framework to evaluate predictions. From this perspective, we hope to shed some light on what verification scores measure and should measure. We start from the ''divergence score'', a relative entropy measure that was recently found to be an appropriate measure for forecast quality. An interpretation of a decomposition of this measure provides insight in additive relations between climatological uncertainty, correct information, wrong information and remaining uncertainty. When the score is applied to deterministic forecasts, it follows that these increase uncertainty to infinity. In practice, however, deterministic forecasts tend to be judged far more mildly and are widely used. We resolve this paradoxical result by proposing that deterministic forecasts either are implicitly probabilistic or are implicitly evaluated with an underlying decision problem or utility in mind. We further propose that calibration of models representing a hydrological system should be the based on information-theoretical scores, because this allows extracting all information from the observations and avoids learning from information that is not there. Calibration based on maximizing utility for society trains an implicit decision model rather than the forecasting system itself. This inevitably results in a loss or distortion of information in the data and more risk of overfitting, possibly leading to less valuable and informative forecasts. We also show this in an example. The final conclusion is that models should preferably be explicitly probabilistic and calibrated to maximize the information they provide.

  6. Comparative Assessment of a New Hydrological Modelling Approach for Prediction of Runoff in Gauged and Ungauged Basins, and Climate Change Impacts Assessment: A Case Study from Benin. (United States)

    GABA, C. O. U.; Alamou, E.; Afouda, A.; Diekkrüger, B.


    Assessing water resources is still an important challenge especially in the context of climatic changes. Although numerous hydrological models exist, new approaches are still under investigation. In this context, we investigate a new modelling approach based on the Physics Principle of Least Action which was first applied to the Bétérou catchment in Benin and gave very good results. The study presents new hypotheses to go further in the model development with a view of widening its application. The improved version of the model MODHYPMA was applied to sixteen (16) subcatchments in Bénin, West Africa. Its performance was compared to two well-known lumped conceptual models, the GR4J and HBV models. The model was successfully calibrated and validated and showed a good performance in most catchments. The analysis revealed that the three models have similar performance and timing errors. But in contrary to other models, MODHYMA is subject to a less loss of performance from calibration to validation. In order to evaluate the usefulness of our model for the prediction of runoff in ungauged basins, model parameters were estimated from the physical catchments characteristics. We relied on statistical methods applied on calibrated model parameters to deduce relationships between parameters and physical catchments characteristics. These relationships were further tested and validated on gauged basins that were considered ungauged. This regionalization was also performed for GR4J model.We obtained NSE values greater than 0.7 for MODHYPMA while the NSE values for GR4J were inferior to 0.5. In the presented study, the effects of climate change on water resources in the Ouémé catchment at the outlet of Savè (about 23 500 km2) are quantified. The output of a regional climate model was used as input to the hydrological models.Computed within the GLOWA-IMPETUS project, the future climate projections (describing a rainfall reduction of up to 15%) are derived from the regional

  7. Verification of precipitation forecasts from two numerical weather prediction models in the Middle Atlantic Region of the USA: A precursory analysis to hydrologic forecasting (United States)

    Siddique, Ridwan; Mejia, Alfonso; Brown, James; Reed, Seann; Ahnert, Peter


    Accurate precipitation forecasts are required for accurate flood forecasting. The structures of different precipitation forecasting systems are constantly evolving, with improvements in forecasting techniques, increases in spatial and temporal resolution, improvements in model physics and numerical techniques, and better understanding of, and accounting for, predictive uncertainty. Hence, routine verification is necessary to understand the quality of forecasts as inputs to hydrologic modeling. In this study, we verify precipitation forecasts from the National Centers for Environmental Prediction (NCEP) 11-member Global Ensemble Forecast System Reforecast version 2 (GEFSRv2), as well as the 21-member Short Range Ensemble Forecast (SREF) system. Specifically, basin averaged precipitation forecasts are verified for different basin sizes (spatial scales) in the operating domain of the Middle Atlantic River Forecast Center (MARFC), using multi-sensor precipitation estimates (MPEs) as the observed data. The quality of the ensemble forecasts is evaluated conditionally upon precipitation amounts, forecast lead times, accumulation periods, and seasonality using different verification metrics. Overall, both GEFSRv2 and SREF tend to overforecast light to moderate precipitation and underforecast heavy precipitation. In addition, precipitation forecasts from both systems become increasingly reliable with increasing basin size and decreasing precipitation threshold, and the 24-hourly forecasts show slightly better skill than the 6-hourly forecasts. Both systems show a strong seasonal trend, characterized by better skill during the cool season than the warm season. Ultimately, the verification results lead to guidance on the expected quality of the precipitation forecasts, together with an assessment of their relative quality and unique information content, which is useful and necessary for their application in hydrologic forecasting.

  8. Impact of geological model uncertainty on integrated catchment hydrological modeling (United States)

    He, Xin; Jørgensen, Flemming; Refsgaard, Jens Christian


    Various types of uncertainty can influence hydrological model performance. Among them, uncertainty originated from geological model may play an important role in process-based integrated hydrological modeling, if the model is used outside the calibration base. In the present study, we try to assess the hydrological model predictive uncertainty caused by uncertainty of the geology using an ensemble of geological models with equal plausibility. The study is carried out in the 101 km2 Norsminde catchment in western Denmark. Geostatistical software TProGS is used to generate 20 stochastic geological realizations for the west side the of study area. This process is done while incorporating the borehole log data from 108 wells and high resolution airborne transient electromagnetic (AEM) data for conditioning. As a result, 10 geological models are generated based solely on borehole data, and another 10 geological models are based on both borehole and AEM data. Distributed surface water - groundwater models are developed using MIKE SHE code for each of the 20 geological models. The models are then calibrated using field data collected from stream discharge and groundwater head observations. The model simulation results are evaluated based on the same two types of field data. The results show that the differences between simulated discharge flows caused by using different geological models are relatively small. The model calibration is shown to be able to account for the systematic bias in different geological realizations and hence varies the calibrated model parameters. This results in an increase in the variance between the hydrological realizations compared to the uncalibrated models that uses the same parameter values in all 20 models. Furthermore, borehole based hydrological models in general show more variance between simulations than the AEM based models; however, the combined total uncertainty, bias plus variance, is not necessarily higher.

  9. Snow multivariable data assimilation for hydrological predictions in Alpine sites (United States)

    Piazzi, Gaia; Thirel, Guillaume; Campo, Lorenzo; Gabellani, Simone; Stevenin, Hervè


    Snowpack dynamics (snow accumulation and ablation) strongly impacts on hydrological processes in Alpine areas. During the winter season the presence of snow cover (snow accumulation) reduces the drainage in the basin with a resulting lower watershed time of concentration in case of possible rainfall events. Moreover, the release of the significant water volume stored in winter (snowmelt) considerably contributes to the total discharge during the melting period. Therefore when modeling hydrological processes in snow-dominated catchments the quality of predictions deeply depends on how the model succeeds in catching snowpack dynamics. The integration of a hydrological model with a snow module allows improving predictions of river discharges. Besides the well-known modeling limitations (uncertainty in parameterizations; possible errors affecting both meteorological forcing data and initial conditions; approximations in boundary conditions), there are physical factors that make an exhaustive reconstruction of snow dynamics complicated: snow intermittence in space and time, stratification and slow phenomena like metamorphism processes, uncertainty in snowfall evaluation, wind transportation, etc. Data Assimilation (DA) techniques provide an objective methodology to combine several independent snow-related data sources (model simulations, ground-based measurements and remote sensed observations) in order to obtain the most likely estimate of snowpack state. This study presents SMASH (Snow Multidata Assimilation System for Hydrology), a multi-layer snow dynamic model strengthened by a multivariable DA framework for hydrological purposes. The model is physically based on mass and energy balances and can be used to reproduce the main physical processes occurring within the snowpack: accumulation, density dynamics, melting, sublimation, radiative balance, heat and mass exchanges. The model is driven by observed forcing meteorological data (air temperature, wind velocity

  10. Hydrologic Predictions in the Anthropocene: A Research Framework Based on a Co-evolutionary Socio-hydrologic Perspective (United States)

    Sivapalan, M.; Bloeschl, G.


    The world is facing a water management crisis, in the context of fast rising demand for water due to growth of human populations and changing lifestyles, and depletion of freshwater resources. In many parts of the world, poor distribution of freshwater in relation to demand is already the cause of serious water scarcity, exacerbated by climate change. Cumulatively, these result in increased human appropriation of water resources, significant modification of landscapes, and a strong human imprint on water cycle dynamics from local to global scales. Hydrologic predictions in such a fast changing environment face significant challenges. Traditional models for predictions treat the hydrologic system as a simple input-output system, and propagate variability of external inputs or disturbances through the various hydrologic subsystems, but assuming stationarity. However, in a fast changing world, none of the subsystems can be assumed to be stationary, but as co-evolving parts of a complex system. The role of humans takes on an important role, which can no longer be assumed to independent of the natural system. We need new socio-hydrologic frameworks to observe, monitor, understand and predict the co-evolution of coupled human-natural systems. In this talk, using examples from one or more real-world settings (from Australia and Europe) involving human interactions with hydrologic systems, we will present new theoretical frameworks that should be adopted to advance the emergent new sub-discipline of socio-hydrology. The proposed research agenda is organized under (i) process socio-hydrology, (ii) comparative socio-hydrology, and (iii) historical socio-hydrology.

  11. Evaluating spatial patterns in hydrological modelling

    DEFF Research Database (Denmark)

    Koch, Julian

    with respect to their capability to mimic human evaluations. This PhD thesis aims at expanding the standard toolbox of spatial model evaluation with innovative metrics that adequately compare spatial patterns. Driven by the rise of more complex model structures and the increase of suitable remote sensing......The objective of this PhD study is to investigate possible ways towards a better integration of spatial observations into the modelling process via spatial pattern evaluation. It is widely recognized by the modelling community that the grand potential of readily available spatial observations...... is not fully exploited by current modelling frameworks due to the lack of suitable spatial performance metrics. Furthermore, the traditional model evaluation using discharge is found unsuitable to lay confidence on the predicted catchment inherent spatial variability of hydrological processes in a fully...

  12. The Central Valley Hydrologic Model (United States)

    Faunt, C.; Belitz, K.; Hanson, R. T.


    Historically, California’s Central Valley has been one of the most productive agricultural regions in the world. The Central Valley also is rapidly becoming an important area for California’s expanding urban population. In response to this competition for water, a number of water-related issues have gained prominence: conjunctive use, artificial recharge, hydrologic implications of land-use change, subsidence, and effects of climate variability. To provide information to stakeholders addressing these issues, the USGS made a detailed assessment of the Central Valley aquifer system that includes the present status of water resources and how these resources have changed over time. The principal product of this assessment is a tool, referred to as the Central Valley Hydrologic Model (CVHM), that simulates surface-water flows, groundwater flows, and land subsidence in response to stresses from human uses and from climate variability throughout the entire Central Valley. The CVHM utilizes MODFLOW combined with a new tool called “Farm Process” to simulate groundwater and surface-water flow, irrigated agriculture, land subsidence, and other key processes in the Central Valley on a monthly basis. This model was discretized horizontally into 20,000 1-mi2 cells and vertically into 10 layers ranging in thickness from 50 feet at the land surface to 750 feet at depth. A texture model constructed by using data from more than 8,500 drillers’ logs was used to estimate hydraulic properties. Unmetered pumpage and surface-water deliveries for 21 water-balance regions were simulated with the Farm Process. Model results indicate that human activities, predominately surface-water deliveries and groundwater pumping for irrigated agriculture, have dramatically influenced the hydrology of the Central Valley. These human activities have increased flow though the aquifer system by about a factor of six compared to pre-development conditions. The simulated hydrology reflects spatial

  13. Estimating real-time predictive hydrological uncertainty

    NARCIS (Netherlands)

    Verkade, J.S.


    Flood early warning systems provide a potentially highly effective flood risk reduction measure. The effectiveness of early warning, however, is affected by forecasting uncertainty: the impossibility of knowing, in advance, the exact future state of hydrological systems. Early warning systems

  14. Quantifying and Predicting Hydrologic Pathways in Subtropical Depressional Isolated Wetlands (United States)

    Min, J.; Perkins, D. B.; Jawitz, J. W.


    Depressional isolated wetlands exhibit highly transient hydrologic characteristics, which complicates assessment of the hydrologic connection between these systems and uplands. Compared to boundary-fixed water bodies, it is more difficult to measure or estimate each hydrologic pathway because the wetland flooded area changes dramatically in over short time periods. Here, we report a water budget analysis based on routinely collected hydrometeorological monitoring data. Monitoring was carried out over three years in four ditch-linked depressional wetlands of about 1 to 6 ha in the Lake Okeechobee basin, FL. The main objectives of this study were to quantify hydrologic pathways in these subtropical wetlands, which have rarely been tried, and examine how raising ditch outlet elevation would affect the hydrology and phosphorus retention capacity using a mass balance model developed based on the hydrologic quantification. Volume-based water budget components were measured or estimated independently. Rainfall, wetland stage, and upland groundwater level were measured on a daily basis and wetland stage-flooded area relationships were developed from bathymetric surveys. Daily evapotranspiration was estimated using the FAO Penman-Monteith method; ditch outflow was estimated using Manning’s roughness equation; direct runoff was estimated using the NRCS runoff curve number method; indirect runoff, defined as rainfall-induced flow from upland to wetland due to low soil water storage capacity of the unsaturated soil at the wetland-upland border, was estimated using the average capillary rising depth; and groundwater exchange was estimated with average hydraulic conductivity derived using the modified Dupuit equation under a constrained water budget framework. Runoff contributed between 34% and 144% as much water as rainfall at individual wetlands and groundwater inflow was less than 5% of total inflow. Ditch outflow from the systems was highly variable ranging from less than

  15. Covariance Models for Hydrological Applications (United States)

    Hristopulos, Dionissios


    This methodological contribution aims to present some new covariance models with applications in the stochastic analysis of hydrological processes. More specifically, we present explicit expressions for radially symmetric, non-differentiable, Spartan covariance functions in one, two, and three dimensions. The Spartan covariance parameters include a characteristic length, an amplitude coefficient, and a rigidity coefficient which determines the shape of the covariance function. Different expressions are obtained depending on the value of the rigidity coefficient and the dimensionality. If the value of the rigidity coefficient is much larger than one, the Spartan covariance function exhibits multiscaling. Spartan covariance models are more flexible than the classical geostatatistical models (e.g., spherical, exponential). Their non-differentiability makes them suitable for modelling the properties of geological media. We also present a family of radially symmetric, infinitely differentiable Bessel-Lommel covariance functions which are valid in any dimension. These models involve combinations of Bessel and Lommel functions. They provide a generalization of the J-Bessel covariance function, and they can be used to model smooth processes with an oscillatory decay of correlations. We discuss the dependence of the integral range of the Spartan and Bessel-Lommel covariance functions on the parameters. We point out that the dependence is not uniquely specified by the characteristic length, unlike the classical geostatistical models. Finally, we define and discuss the use of the generalized spectrum for characterizing different correlation length scales; the spectrum is defined in terms of an exponent α. We show that the spectrum values obtained for exponent values less than one can be used to discriminate between mean-square continuous but non-differentiable random fields. References [1] D. T. Hristopulos and S. Elogne, 2007. Analytic properties and covariance functions of

  16. Clustering of hydrological data: a review of methods for runoff predictions in ungauged basins (United States)

    Dogulu, Nilay; Kentel, Elcin


    There is a great body of research that has looked into the challenge of hydrological predictions in ungauged basins as driven by the Prediction in Ungauged Basins (PUB) initiative of the International Association of Hydrological Sciences (IAHS). Transfer of hydrological information (e.g. model parameters, flow signatures) from gauged to ungauged catchment, often referred as "regionalization", is the main objective and benefits from identification of hydrologically homogenous regions. Within this context, indirect representation of hydrologic similarity for ungauged catchments, which is not a straightforward task due to absence of streamflow measurements and insufficient knowledge of hydrologic behavior, has been explored in the literature. To this aim, clustering methods have been widely adopted. While most of the studies employ hard clustering techniques such as hierarchical (divisive or agglomerative) clustering, there have been more recent attempts taking advantage of fuzzy set theory (fuzzy clustering) and nonlinear methods (e.g. self-organizing maps). The relevant research findings from this fundamental task of hydrologic sciences have revealed the value of different clustering methods for improved understanding of catchment hydrology. However, despite advancements there still remains challenges and yet opportunities for research on clustering for regionalization purposes. The present work provides an overview of clustering techniques and their applications in hydrology with focus on regionalization for the PUB problem. Identifying their advantages and disadvantages, we discuss the potential of innovative clustering methods and reflect on future challenges in view of the research objectives of the PUB initiative.

  17. Genetic Programming for Automatic Hydrological Modelling (United States)

    Chadalawada, Jayashree; Babovic, Vladan


    One of the recent challenges for the hydrologic research community is the need for the development of coupled systems that involves the integration of hydrologic, atmospheric and socio-economic relationships. This poses a requirement for novel modelling frameworks that can accurately represent complex systems, given, the limited understanding of underlying processes, increasing volume of data and high levels of uncertainity. Each of the existing hydrological models vary in terms of conceptualization and process representation and is the best suited to capture the environmental dynamics of a particular hydrological system. Data driven approaches can be used in the integration of alternative process hypotheses in order to achieve a unified theory at catchment scale. The key steps in the implementation of integrated modelling framework that is influenced by prior understanding and data, include, choice of the technique for the induction of knowledge from data, identification of alternative structural hypotheses, definition of rules, constraints for meaningful, intelligent combination of model component hypotheses and definition of evaluation metrics. This study aims at defining a Genetic Programming based modelling framework that test different conceptual model constructs based on wide range of objective functions and evolves accurate and parsimonious models that capture dominant hydrological processes at catchment scale. In this paper, GP initializes the evolutionary process using the modelling decisions inspired from the Superflex framework [Fenicia et al., 2011] and automatically combines them into model structures that are scrutinized against observed data using statistical, hydrological and flow duration curve based performance metrics. The collaboration between data driven and physical, conceptual modelling paradigms improves the ability to model and manage hydrologic systems. Fenicia, F., D. Kavetski, and H. H. Savenije (2011), Elements of a flexible approach

  18. The transferability of hydrological models under nonstationary climatic conditions

    Directory of Open Access Journals (Sweden)

    C. Z. Li


    Full Text Available This paper investigates issues involved in calibrating hydrological models against observed data when the aim of the modelling is to predict future runoff under different climatic conditions. To achieve this objective, we tested two hydrological models, DWBM and SIMHYD, using data from 30 unimpaired catchments in Australia which had at least 60 yr of daily precipitation, potential evapotranspiration (PET, and streamflow data. Nash-Sutcliffe efficiency (NSE, modified index of agreement (d1 and water balance error (WBE were used as performance criteria. We used a differential split-sample test to split up the data into 120 sub-periods and 4 different climatic sub-periods in order to assess how well the calibrated model could be transferred different periods. For each catchment, the models were calibrated for one sub-period and validated on the other three. Monte Carlo simulation was used to explore parameter stability compared to historic climatic variability. The chi-square test was used to measure the relationship between the distribution of the parameters and hydroclimatic variability. The results showed that the performance of the two hydrological models differed and depended on the model calibration. We found that if a hydrological model is set up to simulate runoff for a wet climate scenario then it should be calibrated on a wet segment of the historic record, and similarly a dry segment should be used for a dry climate scenario. The Monte Carlo simulation provides an effective and pragmatic approach to explore uncertainty and equifinality in hydrological model parameters. Some parameters of the hydrological models are shown to be significantly more sensitive to the choice of calibration periods. Our findings support the idea that when using conceptual hydrological models to assess future climate change impacts, a differential split-sample test and Monte Carlo simulation should be used to quantify uncertainties due to

  19. An approach to measure parameter sensitivity in watershed hydrologic modeling (United States)

    U.S. Environmental Protection Agency — Abstract Hydrologic responses vary spatially and temporally according to watershed characteristics. In this study, the hydrologic models that we developed earlier...

  20. Putting hydrological modelling practice to the test

    NARCIS (Netherlands)

    Melsen, Lieke Anna


    Six steps can be distinguished in the process of hydrological modelling: the perceptual model (deciding on the processes), the conceptual model (deciding on the equations), the procedural model (get the code to run on a computer), calibration (identify the parameters), evaluation (confronting output

  1. Hydrological and hydraulic modelling of the Nyl River floodplain Part ...

    African Journals Online (AJOL)

    Catchment land-use and water resource developments may threaten the ecological integrity of the Nyl River floodplain, a world-renowned conservation area. The effect of developments on the water supply regime to the floodplain can be predicted by hydrological modelling, but assessing their ecological consequences ...

  2. Hydrological Modelling of Ganga River basin. (United States)

    Anand, J.; Gosain, A. K.; Khosa, R.


    Application of a hydrological model, Soil and Water Assessment Tool (SWAT) to the Ganga basin having a total drainage area of around 1.08 M sq. km extending over Tibet, Nepal, India and Bangladesh has been made. The model is calibrated to determine the spatial deviations in runoff at sub-basin level, and to capture the water balance of the river basin. Manual calibration approach was used for calibrating the SWAT model by following multi-step procedure to get to the realistic present situation as close as possible. Simulations were then further made with and without proposed future projects to obtain various scenarios. The various statistical parameters used for the evaluation of the monthly runoff simulation showed that SWAT performed well in mimicking the monthly stream flow for Ganga River basin. The model under predicted the flows in the non-perennial region during non-monsoon season, due to low rainfall and regulated flows and seepage taking place from the reservoirs. The impacts of the interventions, both existing as well as proposed, on the water balance of the basin were evaluated and quantified. The derived results suggest that there is a substantial reduction in overall water resources availability in the study basin on account of the current level of development and further, future developments, as are being proposed, may require a careful study of their potential impact on currently sanctioned water use. The present study showcases that efficacy of the model for simulating the stream flow is admirable.

  3. Committee of machine learning predictors of hydrological models uncertainty (United States)

    Kayastha, Nagendra; Solomatine, Dimitri


    In prediction of uncertainty based on machine learning methods, the results of various sampling schemes namely, Monte Carlo sampling (MCS), generalized likelihood uncertainty estimation (GLUE), Markov chain Monte Carlo (MCMC), shuffled complex evolution metropolis algorithm (SCEMUA), differential evolution adaptive metropolis (DREAM), particle swarm optimization (PSO) and adaptive cluster covering (ACCO)[1] used to build a predictive models. These models predict the uncertainty (quantiles of pdf) of a deterministic output from hydrological model [2]. Inputs to these models are the specially identified representative variables (past events precipitation and flows). The trained machine learning models are then employed to predict the model output uncertainty which is specific for the new input data. For each sampling scheme three machine learning methods namely, artificial neural networks, model tree, locally weighted regression are applied to predict output uncertainties. The problem here is that different sampling algorithms result in different data sets used to train different machine learning models which leads to several models (21 predictive uncertainty models). There is no clear evidence which model is the best since there is no basis for comparison. A solution could be to form a committee of all models and to sue a dynamic averaging scheme to generate the final output [3]. This approach is applied to estimate uncertainty of streamflows simulation from a conceptual hydrological model HBV in the Nzoia catchment in Kenya. [1] N. Kayastha, D. L. Shrestha and D. P. Solomatine. Experiments with several methods of parameter uncertainty estimation in hydrological modeling. Proc. 9th Intern. Conf. on Hydroinformatics, Tianjin, China, September 2010. [2] D. L. Shrestha, N. Kayastha, and D. P. Solomatine, and R. Price. Encapsulation of parameteric uncertainty statistics by various predictive machine learning models: MLUE method, Journal of Hydroinformatic, in press

  4. On the Use of Models in Hydrology. (United States)

    de Marsily, G.


    This discussion article addresses the nature of models used in hydrology. It proposes a minimalist classification of models into two categories: models built on data from observations of the processes involved, and those for which there are no observation data on any of these processes, at the scale of interest. (LZ)

  5. Development of a coupled hydrological-geotechnical framework for rainfall-induced landslides prediction (United States)

    He, Xiaogang; Hong, Yang; Vergara, Humberto; Zhang, Ke; Kirstetter, Pierre-Emmanuel; Gourley, Jonathan J.; Zhang, Yu; Qiao, Gang; Liu, Chun


    In this paper, we propose a new coupled hydrological-geotechnical model called CRESLIDE (Coupled Routing and Excess Storage and SLope-Infiltration-Distributed Equilibrium), which can alleviate the chronic flaws of landslides simulation and prediction. CRESLIDE is designed to improve the original landslides model (SLIDE) through the coupling of hydrological model (CREST) and to deliver an integrated system for predicting storm-triggered landslides. This coupled system is implemented and evaluated in Macon County, North Carolina, where Hurricane Ivan triggered widespread landslides in September 2004 during the hurricane season. Model simulations from CRESLIDE show its reliability to predict landslides occurrence (location and timing). Receiver Operating Characteristic (ROC) analysis demonstrates that the coupled system (CRESLIDE) has higher specificity (94.10%) and higher sensitivity (11.36%) compared to the original SLIDE model (specificity = 93.32%, sensitivity = 10.23%) and a well-known landslide model (TRIGRS, whose sensitivity is 6.98%). This improved predictive performance demonstrates the advantage of coupling hydrological and geotechnical models with a more realistic representation of infiltration. It warrants a better depiction of the spatial and temporal dependence of hydrological and geotechnical processes in the course of the rainfall-triggered landslide event. This kind of model integration is useful for landslides prediction and early warning.

  6. Hydrologic modeling in a marsh-mangrove ecotone: Predicting wetland surface water and salinity response to restoration in the Ten Thousand Islands region of Florida, USA (United States)

    Michot, B.D.; Meselhe, E.A.; Krauss, Ken W.; Shrestha, Surendra; From, Andrew S.; Patino, Eduardo


    At the fringe of Everglades National Park in southwest Florida, United States, the Ten Thousand Islands National Wildlife Refuge (TTINWR) habitat has been heavily affected by the disruption of natural freshwater flow across the Tamiami Trail (U.S. Highway 41). As the Comprehensive Everglades Restoration Plan (CERP) proposes to restore the natural sheet flow from the Picayune Strand Restoration Project area north of the highway, the impact of planned measures on the hydrology in the refuge needs to be taken into account. The objective of this study was to develop a simple, computationally efficient mass balance model to simulate the spatial and temporal patterns of water level and salinity within the area of interest. This model could be used to assess the effects of the proposed management decisions on the surface water hydrological characteristics of the refuge. Surface water variations are critical to the maintenance of wetland processes. The model domain is divided into 10 compartments on the basis of their shared topography, vegetation, and hydrologic characteristics. A diversion of +10% of the discharge recorded during the modeling period was simulated in the primary canal draining the Picayune Strand forest north of the Tamiami Trail (Faka Union Canal) and this discharge was distributed as overland flow through the refuge area. Water depths were affected only modestly. However, in the northern part of the refuge, the hydroperiod, i.e., the duration of seasonal flooding, was increased by 21 days (from 115 to 136 days) for the simulation during the 2008 wet season, with an average water level rise of 0.06 m. The average salinity over a two-year period in the model area just south of Tamiami Trail was reduced by approximately 8 practical salinity units (psu) (from 18 to 10 psu), whereas the peak dry season average was reduced from 35 to 29 psu (by 17%). These salinity reductions were even larger with greater flow diversions (+20%). Naturally, the reduction

  7. Grey Box Modelling of Hydrological Systems

    DEFF Research Database (Denmark)

    Thordarson, Fannar Ørn

    The main topic of the thesis is grey box modelling of hydrologic systems, as well as formulation and assessment of their embedded uncertainties. Grey box model is a combination of a white box model, a physically-based model that is traditionally formulated using deterministic ordinary differential...... represent a stochastic state space model. In the grey box model the total noise is divided into a measurement noise and a process noise. The process noise is due to model approximations, undiscovered input and uncertainties in the input series. Estimates of the process noise can be used to highlight...... in the model, or formulation of process noise can be considered so that it meets the physical limits of the hydrological system and give an adequate description of the embedded uncertainty in model structure. The thesis consists of two parts: a summary report and a part which contains six scientific papers...

  8. Hydrological Modeling and Repeatability with Brokering (United States)

    Easton, Z. M.; Collick, A.; Srinivasan, R.; Braeckel, A.; Nativi, S.; McAlister, C.; Wright, D. J.; Khalsa, S. J. S.; Fuka, D.


    Data brokering aims to provide those in the hydrological sciences with access to relevant data to represent physical, biological, and chemical characteristics researchers need to accelerate discovery in their domain. Environmental models are useful tools to understand the behavior of hydrological systems. Unfortunately, parameterization of these models requires many different data sources from different disciplines (e.g., atmospheric, geoscience, ecology). In hydrological modeling, the traditional procedure for model initialization starts with obtaining elevation models, land-use characterizations, soils maps, and weather data. It is often the researcher's past experience with these datasets that determines which datasets will be used in a study, and often newer, more suitable data products exist. An added complexity is that various science communities have differing data formats, storage protocols and manipulation methods, which makes use by a non domain scientist difficult and time consuming. We propose data brokering as a means to address several of these challenges. We present two test case scenarios in which researchers attempt to reproduce hydrological model results using 1) general internet based data gathering techniques, and 2) a scientific data brokering interface. We show that data brokering increases the efficiency with which data are collected, models are initialized, and results are analyzed. As an added benefit, it appears brokering significantly increases the repeatability of a study.

  9. Modeling Hydrological Extremes in the Anthropocene (United States)

    Di Baldassarre, Giuliano; Martinez, Fabian; Kalantari, Zahra; Viglione, Alberto


    Hydrological studies have investigated human impacts on hydrological extremes, i.e. droughts and floods, while social studies have explored human responses and adaptation to them. Yet, there is still little understanding about the dynamics resulting from two-way feedbacks, i.e. both impacts and responses. Traditional risk assessment methods therefore fail to assess future dynamics, and thus risk reduction strategies built on these methods can lead to unintended consequences in the medium-long term. Here we review the dynamics resulting from the reciprocal links between society and hydrological extremes, and describe initial efforts to model floods and droughts in the Anthropocene. In particular, we first discuss the need for a novel approach to explicitly account for human interactions with both hydrological extremes, and then present a stylized model simulating the reciprocal effects between droughts, foods and reservoir operation rules. Unprecedented opportunities offered by the growing availability of global data and worldwide archives to uncover the mutual shaping of hydrological extremes and society across places and scales are also discussed.

  10. Global Sensitivity Analysis of the WASIM hydrological model using VARS (United States)

    Rehan Anis, Muhammad; Haghnegahdar, Amin; Razavi, Saman; Wheater, Howard


    Sensitivity analysis (SA) aims to identify the key parameters that affect model performance and it plays an important role in model understanding, calibration, and uncertainty quantification. The increasing complexity of physically-based hydrological models warrants application of comprehensive SA methods for an improved and effective application of hydrological modeling. This study aims to provide a comprehensive sensitivity assessment of WaSiM (Richards version 9.03) hydrological model using a novel and efficient global SA technique Variogram Analysis of Response Surface (VARS), at the experimental Schaefertal catchment (1.44 Km2) in lower Harz Mountains Germany. WaSiM is a distributed hydrological model that can simulate surface and sub-surface flows at various spatial and temporal scales. VARS is a variogram-based framework for global SA that can characterize the full spectrum of sensitivity-related information, thereby providing a comprehensive set of "global" sensitivity metrics with minimal computational cost. Our preliminary SA results show that simulated streamflows in WaSim-ETH are most sensitive to precipitation correction factor followed by parameters related to the snowmelt and flow density. We aim to expand this sensitivity assessment by conducting a more comprehensive global SA with more than 70 parameters from various model components corresponding to interception, infiltration, evapotranspiration, snowmelt, and runoff. This will enable us to provide an enhanced understanding of WaSiM structure and identify dominant controls of its behavior that can be utilized to reduce model prediction uncertainty and reduce parameters needed for calibration.

  11. Should the landscape or the modeler define hydrological model structure? (Invited) (United States)

    Weiler, M.


    In most applications of hydrological models the same model structure is applied everywhere even though the model is unable to provide a faithful description of all occurring hydrological processes. Insights gained from experimental hydrology are rarely used directly to define the structure of hydrological models. Instead, more complex, distributed physically-based models use simple look-up tables to relate the parameters of each structural model element to soil and land-cover information without sufficiently evaluating these relationships. Still, the models are expected to generate the correct processes pattern within the landscape based on the fixed model structure with local parameterization. However, as for example the generation of surface runoff shows, the resulting pattern of the process is often incorrect because the model fails to predict the variable dynamics of soil saturation correctly. Another approach could be to have the landscape and climate define the model structure and hence directly guide selection and description of relevant hydrological processes. From our long experience in experimental hydrology we have collected a wealth of knowledge and data to predict, for example, if a specific hillslope that has developed over a known geologic formation within a specific climate generates surface or subsurface runoff during a storm. If we are able to predict the location of dominating hydrological processes based on landscape information, we could use this “map” of hydrological processes to define or adjust the model structure representing a specific process. This approach would be particularly powerful in ungauged basins. This contribution will compare the two approaches, introduce different methods how landscape can define model structure, and discuss strategies to identify regional differences in perceptual models and to determine the suitability of different model structures in different regions.

  12. Data Assimilation in Integrated and Distributed Hydrological Models

    DEFF Research Database (Denmark)

    Zhang, Donghua

    Integrated hydrological models are frequently used in water-related environmental resource management. With our better understanding of the hydrological processes and the improved computational power, hydrological models are becoming increasingly more complex as they integrate multiple hydrological...... processes and provide simulations in refined temporal and spatial resolutions. Recent developments in measurement and sensor technologies have significantly improved the coverage, quality, frequency and diversity of hydrological observations. Data assimilation provides a great potential in relation...


    Directory of Open Access Journals (Sweden)



    Full Text Available The water has an essential role in the functioning of ecosystems by integrating the complex physical, chemical, and biological processes that sustain life. Water is a key factor in determining the productivity of ecosystems, biodiversity and species composition. Water is also essential for humanity: water supply systems for population, agriculture, fisheries, industries, and hydroelectric power depend on water supplies. The modelling of hydrological processes is an important activity for water resources management, especially now, when the climate change is one of the major challenges of our century, with strong influence on hydrological processes dynamics. Climate change and needs for more knowledge in water resources require the use of advanced hydroinformatic tools in hydrological processes modelling. The rationale and purpose of advanced hydroinformatic tools is to develop a new relationship between the stakeholders and the users and suppliers of the systems: to offer the basis (systems which supply useable results, the validity of which cannot be put in reasonable doubt by any of the stakeholders involved. For a successful modelling of hydrological processes also need specialists well trained and able to use advanced hydro-informatics tools. Results of modelling can be a useful tool for decision makers to taking efficient measures in social, economical and ecological domain regarding water resources, for an integrated water resources management.

  14. Data assimilation in integrated hydrological modelling

    DEFF Research Database (Denmark)

    Rasmussen, Jørn

    Integrated hydrological models are useful tools for water resource management and research, and advances in computational power and the advent of new observation types has resulted in the models generally becoming more complex and distributed. However, the models are often characterized by a high...... using both synthetic data and real observations. Groundwater head and stream discharge observations are assimilated in an integrated hydrological model, with the aim of updating the groundwater head, stream discharge and water level, and model parameters. When synthetically generated observations......, two bias-aware data assimilation algorithms are tested and were shown to successfully estimate the bias of most observations. The data assimilation framework was applied to real observations and an improvement in stream discharge was obtained compared to a deterministic model without data assimilation...

  15. Modeling the hydrological cycle on Mars

    Directory of Open Access Journals (Sweden)

    Ghada Machtoub


    Full Text Available The study provides a detailed analysis of the hydrological cycle on Mars simulated with a newly developed microphysical model, incorporated in a spectral Mars General Circulation Model. The modeled hydrological cycle is compared well with simulations of other global climate models. The simulated seasonal migration ofwater vapor, circulation instability, and the high degree of temporal variability of localized water vapor outbursts are shown closely consistent with recent observations. The microphysical parameterization provides a significant improvement in the modeling of ice clouds evolved over the tropics and major ancient volcanoes on Mars. The most significant difference between the simulations presented here and other GCM results is the level at which the water ice clouds are found. The model findings also support interpretation of observed thermal anomalies in the Martian tropics during northern spring and summer seasons.

  16. Optimal combinations of specialized conceptual hydrological models (United States)

    Kayastha, Nagendra; Lal Shrestha, Durga; Solomatine, Dimitri


    In hydrological modelling it is a usual practice to use a single lumped conceptual model for hydrological simulations at all regimes. However often the simplicity of the modelling paradigm leads to errors in represent all the complexity of the physical processes in the catchment. A solution could be to model various hydrological processes separately by differently parameterized models, and to combine them. Different hydrological models have varying performance in reproducing catchment response. Generally it cannot be represented precisely in different segments of the hydrograph: some models performed well in simulating the peak flows, while others do well in capturing the low flows. Better performance can be achieved if a model being applied to the catchment using different model parameters that are calibrated using criteria favoring high or low flows. In this work we use a modular approach to simulate hydrology of a catchment, wherein multiple models are applied to replicate the catchment responses and each "specialist" model is calibrated according to a specific objective function which is chosen in a way that forces the model to capture certain aspects of the hydrograph, and outputs of models are combined using so-called "fuzzy committee". Such multi-model approach has been already previously implemented in the development of data driven and conceptual models (Fenicia et al., 2007), but its perfomance was considered only during the calibration period. In this study we tested an application to conceptual models in both calibration and verification period. In addition, we tested the sensitivity of the result to the use of different weightings used in the objective functions formulations, and memberbship functions used in the committee. The study was carried out for Bagamati catchment in Nepal and Brue catchment in United Kingdoms with the MATLAB-based implementation of HBV model. Multi-objective evolutionary optimization genetic algorithm (Deb, 2001) was used to

  17. eWaterCycle: A global operational hydrological forecasting model (United States)

    van de Giesen, Nick; Bierkens, Marc; Donchyts, Gennadii; Drost, Niels; Hut, Rolf; Sutanudjaja, Edwin


    Development of an operational hyper-resolution hydrological global model is a central goal of the eWaterCycle project ( This operational model includes ensemble forecasts (14 days) to predict water related stress around the globe. Assimilation of near-real time satellite data is part of the intended product that will be launched at EGU 2015. The challenges come from several directions. First, there are challenges that are mainly computer science oriented but have direct practical hydrological implications. For example, we aim to make use as much as possible of existing standards and open-source software. For example, different parts of our system are coupled through the Basic Model Interface (BMI) developed in the framework of the Community Surface Dynamics Modeling System (CSDMS). The PCR-GLOBWB model, built by Utrecht University, is the basic hydrological model that is the engine of the eWaterCycle project. Re-engineering of parts of the software was needed for it to run efficiently in a High Performance Computing (HPC) environment, and to be able to interface using BMI, and run on multiple compute nodes in parallel. The final aim is to have a spatial resolution of 1km x 1km, which is currently 10 x 10km. This high resolution is computationally not too demanding but very memory intensive. The memory bottleneck becomes especially apparent for data assimilation, for which we use OpenDA. OpenDa allows for different data assimilation techniques without the need to build these from scratch. We have developed a BMI adaptor for OpenDA, allowing OpenDA to use any BMI compatible model. To circumvent memory shortages which would result from standard applications of the Ensemble Kalman Filter, we have developed a variant that does not need to keep all ensemble members in working memory. At EGU, we will present this variant and how it fits well in HPC environments. An important step in the eWaterCycle project was the coupling between the hydrological and

  18. Regional review: the hydrology of the Okavango Delta, Botswana-processes, data and modelling

    DEFF Research Database (Denmark)

    Milzow, C.; Kgotlhang, L.; Bauer-Gottwein, Peter


    . For the global community, the wetlands retain a tremendous pool of biodiversity. As the upstream states Angola and Namibia are developing, however, changes in the use of the water of the Okavango River and in the ecological status of the wetlands are to be expected. To predict these impacts, the hydrology...... of the Delta has to be understood. This article reviews scientific work done for that purpose, focussing on the hydrological modelling of surface water and groundwater. Research providing input data to hydrological models is also presented. It relies heavily on all types of remote sensing. The history...... of hydrologic models of the Delta is retraced from the early box models to state-of-the-art distributed hydrological models. The knowledge gained from hydrological models and its relevance for the management of the Delta are discussed....

  19. On science versus engineering in hydrological modelling (United States)

    Melsen, Lieke


    It is always stressed that hydrological modelling is very important, to prevent floods, to mitigate droughts, to ensure food production or nature conservation. All very true, but I believe that focussing so much on the application of our knowledge (which I call `the engineering approach'), does not stimulate thorough system understanding (which I call `the scientific approach'). In many studies, science and engineering approaches are mixed, which results in large uncertainty e.g. due to a lack of system understanding. To what extent engineering and science approached are mixed depends on the Philosophy of Science of the researcher; verificationism seems to be closer related to engineering, than falsificationism or Bayesianism. In order to grow our scientific knowledge, which means increasing our understanding of the system, we need to be more critical towards the models that we use, but also recognize all the processes that influence the hydrological cycle. In an era called 'The Anthropocene' the influence of humans on the water system can no longer be neglected, and if we choose a scientific approach we have to account for human-induced processes. Summarizing, I believe that we have to account for human impact on the hydrological system, but we have to resist the temptation to directly quantify the hydrological impact on the human system.

  20. Impact of multicollinearity on small sample hydrologic regression models (United States)

    Kroll, Charles N.; Song, Peter


    Often hydrologic regression models are developed with ordinary least squares (OLS) procedures. The use of OLS with highly correlated explanatory variables produces multicollinearity, which creates highly sensitive parameter estimators with inflated variances and improper model selection. It is not clear how to best address multicollinearity in hydrologic regression models. Here a Monte Carlo simulation is developed to compare four techniques to address multicollinearity: OLS, OLS with variance inflation factor screening (VIF), principal component regression (PCR), and partial least squares regression (PLS). The performance of these four techniques was observed for varying sample sizes, correlation coefficients between the explanatory variables, and model error variances consistent with hydrologic regional regression models. The negative effects of multicollinearity are magnified at smaller sample sizes, higher correlations between the variables, and larger model error variances (smaller R2). The Monte Carlo simulation indicates that if the true model is known, multicollinearity is present, and the estimation and statistical testing of regression parameters are of interest, then PCR or PLS should be employed. If the model is unknown, or if the interest is solely on model predictions, is it recommended that OLS be employed since using more complicated techniques did not produce any improvement in model performance. A leave-one-out cross-validation case study was also performed using low-streamflow data sets from the eastern United States. Results indicate that OLS with stepwise selection generally produces models across study regions with varying levels of multicollinearity that are as good as biased regression techniques such as PCR and PLS.

  1. Combined effects of climate models, hydrological model structures and land use scenarios on hydrological impacts of climate change

    DEFF Research Database (Denmark)

    Karlsson, Ida B.; Sonnenborg, Torben O.; Refsgaard, Jens Christian


    to cause little change in mean hydrological responses and little variation between hydrological models. Differences in hydrological model responses to land use were, however, significant for extremes due to dissimilarities in hydrological model structure and process equations. The climate model choice......Impact studies of the hydrological response of future climate change are important for the water authorities when risk assessment, management and adaptation to a changing climate are carried out. The objective of this study was to model the combined effect of land use and climate changes...... on hydrology for a 486 km2 catchment in Denmark and to evaluate the sensitivity of the results to the choice of hydrological model. Three hydrological models, NAM, SWAT and MIKE SHE, were constructed and calibrated using similar methods. Each model was forced with results from four climate models and four land...

  2. Identification of the HYPE hydrological model over the Indian subcontinent (United States)

    Pechlivanidis, Ilias; Gustafsson, David; Arheimer, Berit


    Large-scale hydrological modelling has the potential to encompass many river basins, cross regional and international boundaries and represent a number of different geophysical and climatic zones. However the performance of this type of model is subject to several sources of uncertainty/error which may be caused by, among others, the imperfectness of driving inputs, i.e. regional and global databases. This uncertainty further leads to wrong model parameterisation and incomplete process understanding. Data assimilation aims to utilize both hydrological process knowledge (as embodied in a hydrologic model) and information that can be gained from observations; hence information from model predictions and observations is synergistically used to improve performance. This study presents a methodology, drawn on experience from modelling with the HYPE model in the Indian subcontinent (covering a modelled area of 4.9 million km2), to enhance identification of highly parameterised large-scale hydrological models. The model was set up using available large-scale datasets on topography, land use, soil, precipitation, temperature, lakes, reservoirs, crop types, irrigation, evaporation, snow and discharge. A stepwise automatic calibration is carried out to avoid, to a certain extent, errors incurring in some model processes and being compensated by introducing errors in other parts of the model. In addition, information from remote sensing data is assimilated in the model to drive identification of parameters that control the spatial distribution of potential evapotranspiration. Results show that despite the strong hydro-climatic gradient over the domain, the model can adequately describe the hydrological process in the Indian subcontinent. Overall, the median Kling-Gupta Efficiency (KGE) increased from 0.08 to 0.64 during the calibration process using 43 stations of monthly discharge series over the period 1971 to 1979. Finally, decomposition of the KGE (i.e. into terms

  3. Land-surface modelling in hydrological perspective

    DEFF Research Database (Denmark)

    Overgaard, Jesper; Rosbjerg, Dan; Butts, M.B.


    The purpose of this paper is to provide a review of the different types of energy-based land-surface models (LSMs) and discuss some of the new possibilities that will arise when energy-based LSMs are combined with distributed hydrological modelling. We choose to focus on energy-based approaches......, because in comparison to the traditional potential evapotranspiration models, these approaches allow for a stronger link to remote sensing and atmospheric modelling. New opportunities for evaluation of distributed land-surface models through application of remote sensing are discussed in detail...

  4. Reducing equifinality of hydrological models by integrating Functional Streamflow Disaggregation (United States)

    Lüdtke, Stefan; Apel, Heiko; Nied, Manuela; Carl, Peter; Merz, Bruno


    A universal problem of the calibration of hydrological models is the equifinality of different parameter sets derived from the calibration of models against total runoff values. This is an intrinsic problem stemming from the quality of the calibration data and the simplified process representation by the model. However, discharge data contains additional information which can be extracted by signal processing methods. An analysis specifically developed for the disaggregation of runoff time series into flow components is the Functional Streamflow Disaggregation (FSD; Carl & Behrendt, 2008). This method is used in the calibration of an implementation of the hydrological model SWIM in a medium sized watershed in Thailand. FSD is applied to disaggregate the discharge time series into three flow components which are interpreted as base flow, inter-flow and surface runoff. In addition to total runoff, the model is calibrated against these three components in a modified GLUE analysis, with the aim to identify structural model deficiencies, assess the internal process representation and to tackle equifinality. We developed a model dependent (MDA) approach calibrating the model runoff components against the FSD components, and a model independent (MIA) approach comparing the FSD of the model results and the FSD of calibration data. The results indicate, that the decomposition provides valuable information for the calibration. Particularly MDA highlights and discards a number of standard GLUE behavioural models underestimating the contribution of soil water to river discharge. Both, MDA and MIA yield to a reduction of the parameter ranges by a factor up to 3 in comparison to standard GLUE. Based on these results, we conclude that the developed calibration approach is able to reduce the equifinality of hydrological model parameterizations. The effect on the uncertainty of the model predictions is strongest by applying MDA and shows only minor reductions for MIA. Besides

  5. Monthly Water Balance Model Hydrology Futures (United States)

    Bock, Andy; Hay, Lauren E.; Markstrom, Steven; Atkinson, R. Dwight


    A monthly water balance model (MWBM) was driven with precipitation and temperature using a station-based dataset for current conditions (1950 to 2010) and selected statistically-downscaled general circulation models (GCMs) for current and future conditions (1950 to 2099) across the conterminous United States (CONUS) using hydrologic response units from the Geospatial Fabric for National Hydrologic Modeling ( Six MWBM output variables (actual evapotranspiration (AET), potential evapotranspiration (PET), runoff (RO), streamflow (STRM), soil moisture storage (SOIL), and snow water equivalent (SWE)) and the two MWBM input variables (atmospheric temperature (TAVE) and precipitation (PPT)) were summarized for hydrologic response units and aggregated at points of interest on a stream network. Results were then organized into the Monthly Water Balance Hydrology Futures database, an open-access database using netCDF format (  Methods used to calibrate and parameterize the MWBM are detailed in the Hydrology and Earth System Sciences (HESS)  paper "Parameter regionalization of a monthly water balance model for the conterminous United States" by Bock and others (2016).  See the discussion paper link in the "Related External Resources" section for access.  Supplemental data files related to the plots and data analysis in Bock and others (2016) can be found in the folder in the "Attached Files" section.  Detailed information on the files and data can be found in the ReadMe.txt contained within the zipped folder. Recommended citation of discussion paper:Bock, A.R., Hay, L.E., McCabe, G.J., Markstrom, S.L., and Atkinson, R.D., 2016, Parameter regionalization of a monthly water balance model for the conterminous United States: Hydrology and Earth System Sciences, v. 20, 2861-2876, doi:10.5194/hess-20-2861-2016, 2016

  6. Delineating wetland catchments and modeling hydrologic ... (United States)

    In traditional watershed delineation and topographic modeling, surface depressions are generally treated as spurious features and simply removed from a digital elevation model (DEM) to enforce flow continuity of water across the topographic surface to the watershed outlets. In reality, however, many depressions in the DEM are actual wetland landscape features with seasonal to permanent inundation patterning characterized by nested hierarchical structures and dynamic filling–spilling–merging surface-water hydrological processes. Differentiating and appropriately processing such ecohydrologically meaningful features remains a major technical terrain-processing challenge, particularly as high-resolution spatial data are increasingly used to support modeling and geographic analysis needs. The objectives of this study were to delineate hierarchical wetland catchments and model their hydrologic connectivity using high-resolution lidar data and aerial imagery. The graph-theory-based contour tree method was used to delineate the hierarchical wetland catchments and characterize their geometric and topological properties. Potential hydrologic connectivity between wetlands and streams were simulated using the least-cost-path algorithm. The resulting flow network delineated potential flow paths connecting wetland depressions to each other or to the river network on scales finer than those available through the National Hydrography Dataset. The results demonstrated that

  7. Spatial resolution considerations for urban hydrological modelling (United States)

    Krebs, G.; Kokkonen, T.; Valtanen, M.; Setälä, H.; Koivusalo, H.


    Hydrological model simulations can be applied to evaluate the performance of low impact development (LID) tools in urban areas. However, the assessment for large-scale urban areas remains a challenge due to the required high spatial resolution and limited availability of field measurements for model calibration. This study proposes a methodology to parameterize a hydrological model (SWMM) with sufficiently high spatial resolution and direct accessibility of model parameters for LID performance simulation applicable to a large-scale ungauged urban area. Based on calibrated high-resolution models for three small-scale study catchments (6-12 ha), we evaluated how constraints implied by large-scale urban modelling, such as data limitations, affect the model results. The high-resolution surface representation, resulting in subcatchments of uniform surface types, reduced the number of calibration parameters. Calibration conducted independently for all catchments yielded similar parameter values for same surface types in each study catchment. These results suggest the applicability of the parameter values calibrated for high resolution models to be regionalized to larger, ungauged urban areas. The accessibility of surface specific model parameters for LID simulation is then also retained. Conducted perturbations in spatial resolution through sewer network truncation showed that while the runoff volume was mostly unaffected by resolution perturbations, lower resolutions resulted in over-simulation of peak flows due to excessively rapid catchment response to storm events. Our results suggest that a hydrological model where parameter values are adopted from high-resolution models and that is developed based on a minimum conduit diameter of 300 mm provides good simulation performance and is applicable to large-scale urban areas with reasonable effort.

  8. Extending data worth methods to select multiple observations targeting specific hydrological predictions of interest (United States)

    Vilhelmsen, Troels N.; Ferré, Ty P. A.


    Hydrological models are often developed to forecasting future behavior in response due to natural or human induced changes in stresses affecting hydrologic systems. Commonly, these models are conceptualized and calibrated based on existing data/information about the hydrological conditions. However, most hydrologic systems lack sufficient data to constrain models with adequate certainty to support robust decision making. Therefore, a key element of a hydrologic study is the selection of additional data to improve model performance. Given the nature of hydrologic investigations, it is not practical to select data sequentially, i.e. to choose the next observation, collect it, refine the model, and then repeat the process. Rather, for timing and financial reasons, measurement campaigns include multiple wells or sampling points. There is a growing body of literature aimed at defining the expected data worth based on existing models. However, these are almost all limited to identifying single additional observations. In this study, we present a methodology for simultaneously selecting multiple potential new observations based on their expected ability to reduce the uncertainty of the forecasts of interest. This methodology is based on linear estimates of the predictive uncertainty, and it can be used to determine the optimal combinations of measurements (location and number) established to reduce the uncertainty of multiple predictions. The outcome of the analysis is an estimate of the optimal sampling locations; the optimal number of samples; as well as a probability map showing the locations within the investigated area that are most likely to provide useful information about the forecasting of interest.

  9. Representing northern peatland microtopography and hydrology within the Community Land Model (United States)

    X. Shi; P.E. Thornton; D.M. Ricciuto; P J. Hanson; J. Mao; Stephen Sebestyen; N.A. Griffiths; G. Bisht


    Predictive understanding of northern peatland hydrology is a necessary precursor to understanding the fate of massive carbon stores in these systems under the influence of present and future climate change. Current models have begun to address microtopographic controls on peatland hydrology, but none have included a prognostic calculation of peatland water table depth...

  10. On noice in data assimilation schemes for improved flood forecasting using distributed hydrological models

    NARCIS (Netherlands)

    Noh, S.J.; Rakovec, O.; Weerts, A.H.; Tachikawa, Y.


    We investigate the effects of noise specification on the quality of hydrological forecasts via an advanced data assimilation (DA) procedure using a distributed hydrological model driven by numerical weather predictions. The sequential DA procedure is based on (1) a multivariate rainfall ensemble

  11. Time Varying Parameterization of Hydrological Models (United States)

    Bardossy, A.; Singh, S. K.


    Hydrological models are frequently used for forecasting, water management or design to provide information for decision making. Due to the simplification of the complex natural processes and the limited availability of observations the parameters of these models cannot be identified perfectly. Usually the parameters of the models are assumed to be time independent. However some properties of the catchments might change in from one event to another in an unpredictable manner. The purpose of this paper is to develop a methodology to estimate selected model parameters as random variables changing in time. The distribution of the model parameter is assessed in calibration phase using different assumptions. During the application of the model these distributions are used to estimate the expected hydrological behavior and the uncertainty too. The methodology will be demonstrated on mezo-scale catchments in the Neckar basin in South-West Germany. The systematic differences between model behavior and observations are demonstrated using a set of selected events. Calibration and uncertainty estimation are demonstrated by an example application to a distributed HBV model. The model residual distributions are presented and compared to a standard calibration method. Further, it is shown that the new methodology leads to more realistic confidence intervals for model simulations.

  12. Proving the ecosystem value through hydrological modelling (United States)

    Dorner, W.; Spachinger, K.; Porter, M.; Metzka, R.


    Ecosystems provide valuable functions. Also natural floodplains and river structures offer different types of ecosystem functions such as habitat function, recreational area and natural detention. From an economic stand point the loss (or rehabilitation) of these natural systems and their provided natural services can be valued as a damage (or benefit). Consequently these natural goods and services must be economically valued in project assessments e.g. cost-benefit-analysis or cost comparison. Especially in smaller catchments and river systems exists significant evidence that natural flood detention reduces flood risk and contributes to flood protection. Several research projects evaluated the mitigating effect of land use, river training and the loss of natural flood plains on development, peak and volume of floods. The presented project analysis the hypothesis that ignoring natural detention and hydrological ecosystem services could result in economically inefficient solutions for flood protection and mitigation. In test areas, subcatchments of the Danube in Germany, a combination of hydrological and hydrodynamic models with economic evaluation techniques was applied. Different forms of land use, river structure and flood protection measures were assed and compared from a hydrological and economic point of view. A hydrodynamic model was used to simulate flows to assess the extent of flood affected areas and damages to buildings and infrastructure as well as to investigate the impacts of levees and river structure on a local scale. These model results provided the basis for an economic assessment. Different economic valuation techniques, such as flood damage functions, cost comparison method and substation-approach were used to compare the outcomes of different hydrological scenarios from an economic point of view and value the ecosystem service. The results give significant evidence that natural detention must be evaluated as part of flood mitigation projects

  13. Documentation for the hydrological discharge model

    Energy Technology Data Exchange (ETDEWEB)

    Hagemann, S.; Duemenil, L. [Max-Planck-Institut fuer Meteorologie, Hamburg (Germany)


    To improve the representation of hydrological land surface processes, which has so far been treated inadequately in global models of the atmospheric general circulation (GCMs), a model for the lateral waterflows from the continents into the ocean on the global scale was developed. The model describes the translation and retention of the lateral discharge as a function of the spatially distributed land surface characteristics that are globally available. Here, global scale refers to the resolution of 0.5 and lower, corresponding to a typical GCM gridbox area of about 2500 km{sup 2}. This model is called the Hydrological Discharge model or HD model. The HD model computes the discharge only at 0.5 resolution. A model input fields (runoff and drainage, see Sect. 3.1.) from the various GCM resolutions are interpolated to the same 0.5 grid. Thus, input fields may be used from any available resolution, if the corresponding interpolation routine to the 0.5 degree grid is provided. Since the HD model uses a time step of one day, a temporal resolution of one day is sufficient for the input fields. (orig.)

  14. A new eco-hydrological distributed model for the predictions of the climate change impact on water resources of Mediterranean water-limited basins: the Mulargia basin case study in Sardinia. (United States)

    Sarigu, Alessio; Montaldo, Nicola


    In the last three decades, climate change and human activities increased desertification process in Mediterranean regions, with dramatic consequences for agriculture and water availability. For instance in the main reservoir systems in Sardinia the average annual runoff in the latter part of the 20th century decreased of more than 50% compared with the previous period, while the precipitation over the Sardinia basin has decreased, but not at such a drastic rate as the discharge, with an high precipitation elasticity to streamflow, highlighting the key role of the rainfall seasonality on runoff production. IPCC climate change scenarios predict a further decrease of winter rainfall, which is the key term for runoff production in these typical Mediterranean climate basins, and air temperature increase, which can potentially impact on evapotranspiration, soil moisture and runoff. Only the use of an accurate ecohydrological physically based distributed model allow to well predict the impact of the climate change scenarios on the basin water resources. A new eco-hydrological model is developed that couples a distributed hydrological model of and a vegetation dynamic model (VDM). The hydrological model estimates the soil water balance of each basin cell using the force-restore method, the Philips model for infiltration estimate and the Penman-Monteith equation for evapotranspiration estimate. The VDM evaluates the changes in biomass over time for each cell and provides the leaf area index (LAI), which is then used by the hydrological model for evapotranspiration and rainfall interception estimates. Case study is the Mulargia basin (Sardinia, basin area of about 70 km2), where an extended field campaign started from 2003, with rain and discharge data observed at the basin outlet, periodic field measurements of soil moisture and LAI all over the basin, and evapotraspiration estimates using an eddy correlation based tower. The Mulargia basin case study is a very interesting

  15. An integrated crop and hydrologic modeling system to estimate hydrologic impacts of crop irrigation demands (United States)

    R.T. McNider; C. Handyside; K. Doty; W.L. Ellenburg; J.F. Cruise; J.R. Christy; D. Moss; V. Sharda; G. Hoogenboom; Peter Caldwell


    The present paper discusses a coupled gridded crop modeling and hydrologic modeling system that can examine the benefits of irrigation and costs of irrigation and the coincident impact of the irrigation water withdrawals on surface water hydrology. The system is applied to the Southeastern U.S. The system tools to be discussed include a gridded version (GriDSSAT) of...

  16. Skill and relative economic value of medium-range hydrological ensemble predictions

    Directory of Open Access Journals (Sweden)

    E. Roulin


    Full Text Available A hydrological ensemble prediction system, integrating a water balance model with ensemble precipitation forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF Ensemble Prediction System (EPS, is evaluated for two Belgian catchments using verification methods borrowed from meteorology. The skill of the probability forecast that the streamflow exceeds a given level is measured with the Brier Skill Score. Then the value of the system is assessed using a cost-loss decision model. The verification results of the hydrological ensemble predictions are compared with the corresponding results obtained for simpler alternatives as the one obtained by using of the deterministic forecast of ECMWF which is characterized by a higher spatial resolution or by using of the EPS ensemble mean.

  17. Flood forecasting in Blue Nile basin using a process-based hydrological model

    Directory of Open Access Journals (Sweden)

    Osama R Abdel-Aziz


    Full Text Available Predictions of variations in global and regional hydrological cycles and their response to changes in climate and the environment are key problems for future human life. Therefore, basin-scale hydrological forecasts, along with predictions regarding future climate change, are needed in areas with high flood potential. This study forecasts hydrological process scenarios in Blue Nile basin using a distributed hydrological model (DHM and predicted scenarios of precipitation from two general circulation models, CCSM3 model and Miroc3.2-hires. Firstly, river discharge was simulated by the DHM using the observed rainfall from 1976 to 1979 and then, simulating future precipitations from 2011 to 2040, discharge scenarios were predicted. DOI: International Journal of Environment Vol.3(1 2014: 10-21

  18. Improving the realism of hydrologic model through multivariate parameter estimation (United States)

    Rakovec, Oldrich; Kumar, Rohini; Attinger, Sabine; Samaniego, Luis


    Increased availability and quality of near real-time observations should improve understanding of predictive skills of hydrological models. Recent studies have shown the limited capability of river discharge data alone to adequately constrain different components of distributed model parameterizations. In this study, the GRACE satellite-based total water storage (TWS) anomaly is used to complement the discharge data with an aim to improve the fidelity of mesoscale hydrologic model (mHM) through multivariate parameter estimation. The study is conducted in 83 European basins covering a wide range of hydro-climatic regimes. The model parameterization complemented with the TWS anomalies leads to statistically significant improvements in (1) discharge simulations during low-flow period, and (2) evapotranspiration estimates which are evaluated against independent (FLUXNET) data. Overall, there is no significant deterioration in model performance for the discharge simulations when complemented by information from the TWS anomalies. However, considerable changes in the partitioning of precipitation into runoff components are noticed by in-/exclusion of TWS during the parameter estimation. A cross-validation test carried out to assess the transferability and robustness of the calibrated parameters to other locations further confirms the benefit of complementary TWS data. In particular, the evapotranspiration estimates show more robust performance when TWS data are incorporated during the parameter estimation, in comparison with the benchmark model constrained against discharge only. This study highlights the value for incorporating multiple data sources during parameter estimation to improve the overall realism of hydrologic model and its applications over large domains. Rakovec, O., Kumar, R., Attinger, S. and Samaniego, L. (2016): Improving the realism of hydrologic model functioning through multivariate parameter estimation. Water Resour. Res., 52,

  19. Remote sensing applications in hydrological modeling (United States)

    Whitelaw, Alan S.; Howes, Sally; Fletcher, Peter; Rast, Michael


    Hydrological modeling is important for a wide range of operational forecasting activities in water resource management. The aim of this paper is to assess the capabilities of Earth observation sensors in relation to modeling data requirements in order to identify future areas of development in both model and sensor specifications. Models range from simple black boxes to distributed physically based models. There is significant variation in the data required and the ways in which these data are used. This range of requirements is compared with the capabilities of existing Earth observation sensors in order to define the current situation. Progress requires the coordinated development of both the sensors and the models, together with a greater understanding of the relationship between measurement and process scales. As a result, existing obstacles to progress in both areas are reviewed with the aid of specific case studies. This analysis leads to a set of recommendations on how to develop the use of sensor data in models.

  20. Xanthos – A Global Hydrologic Model

    Energy Technology Data Exchange (ETDEWEB)

    Li, Xinya; Vernon, Chris R.; Hejazi, Mohamad I.; Link, Robert P.; Feng, Leyang; Liu, Yaling; Rauchenstein, Lynn T.


    Xanthos is a Python model designed to quantify and analyze global water availability historically and in the future at 0.5° × 0.5° spatial resolution and a monthly time step. Its performance and functionality was tested through real-world applications. It is open-source, extensible and accessible for researchers who work on long-term climate data for studies of global water supply, and the Global Change Assessment Model (GCAM). This package integrates inherent global gridded data maps, I/O modules, hydrologic processes and diagnostics modules parameterized by a user-defined configuration file.

  1. An evaluation of the Canadian global meteorological ensemble prediction system for short-term hydrological forecasting

    Directory of Open Access Journals (Sweden)

    F. Anctil


    Full Text Available Hydrological forecasting consists in the assessment of future streamflow. Current deterministic forecasts do not give any information concerning the uncertainty, which might be limiting in a decision-making process. Ensemble forecasts are expected to fill this gap.

    In July 2007, the Meteorological Service of Canada has improved its ensemble prediction system, which has been operational since 1998. It uses the GEM model to generate a 20-member ensemble on a 100 km grid, at mid-latitudes. This improved system is used for the first time for hydrological ensemble predictions. Five watersheds in Quebec (Canada are studied: Chaudière, Châteauguay, Du Nord, Kénogami and Du Lièvre. An interesting 17-day rainfall event has been selected in October 2007. Forecasts are produced in a 3 h time step for a 3-day forecast horizon. The deterministic forecast is also available and it is compared with the ensemble ones. In order to correct the bias of the ensemble, an updating procedure has been applied to the output data. Results showed that ensemble forecasts are more skilful than the deterministic ones, as measured by the Continuous Ranked Probability Score (CRPS, especially for 72 h forecasts. However, the hydrological ensemble forecasts are under dispersed: a situation that improves with the increasing length of the prediction horizons. We conjecture that this is due in part to the fact that uncertainty in the initial conditions of the hydrological model is not taken into account.

  2. Groundwater modelling in conceptual hydrological models - introducing space (United States)

    Boje, Søren; Skaugen, Thomas; Møen, Knut; Myrabø, Steinar


    The tiny Sæternbekken Minifelt (Muren) catchment (7500 m2) in Bærumsmarka, Norway, was during the 1990s, densely instrumented with more than a 100 observation points for measuring groundwater levels. The aim was to investigate the link between shallow groundwater dynamics and runoff. The DDD (Distance Distribution Dynamics) model is a newly developed rainfall-runoff model used operationally by the Norwegian Flood-Forecasting service at NVE. The model estimates the capacity of the subsurface reservoir at different levels of saturation and predicts overland flow. The subsurface in the DDD model has a 2-D representation that calculates the saturated and unsaturated soil moisture along a hillslope representing the entire catchment in question. The groundwater observations from more than two decades ago are used to verify assumptions of the subsurface reservoir in the DDD model and to validate its spatial representation of the subsurface reservoir. The Muren catchment will, during 2017, be re-instrumented in order to continue the work to bridge the gap between conceptual hydrological models, with typically single value or 0-dimension representation of the subsurface, and models with more realistic 2- or 3-dimension representation of the subsurface.

  3. Can the super model (SUMO) method improve hydrological simulations? Exploratory tests with the GR hydrological models (United States)

    Santos, Léonard; Thirel, Guillaume; Perrin, Charles


    Errors made by hydrological models may come from a problem in parameter estimation, uncertainty on observed measurements, numerical problems and from the model conceptualization that simplifies the reality. Here we focus on this last issue of hydrological modeling. One of the solutions to reduce structural uncertainty is to use a multimodel method, taking advantage of the great number and the variability of existing hydrological models. In particular, because different models are not similarly good in all situations, using multimodel approaches can improve the robustness of modeled outputs. Traditionally, in hydrology, multimodel methods are based on the output of the model (the simulated flow series). The aim of this poster is to introduce a different approach based on the internal variables of the models. The method is inspired by the SUper MOdel (SUMO, van den Berge et al., 2011) developed for climatology. The idea of the SUMO method is to correct the internal variables of a model taking into account the values of the internal variables of (an)other model(s). This correction is made bilaterally between the different models. The ensemble of the different models constitutes a super model in which all the models exchange information on their internal variables with each other at each time step. Due to this continuity in the exchanges, this multimodel algorithm is more dynamic than traditional multimodel methods. The method will be first tested using two GR4J models (in a state-space representation) with different parameterizations. The results will be presented and compared to traditional multimodel methods that will serve as benchmarks. In the future, other rainfall-runoff models will be used in the super model. References van den Berge, L. A., Selten, F. M., Wiegerinck, W., and Duane, G. S. (2011). A multi-model ensemble method that combines imperfect models through learning. Earth System Dynamics, 2(1) :161-177.

  4. Chapman Conference on Spatial Variability in Hydrologic Modeling (United States)

    Woolhiser, D. A.; Morel-Seytoux, H. J.

    The AGU Chapman Conference on Spatial Variability in Hydrologic Modeling was held July 21-23, 1981, at the Colorado State University Pingree Park Campus, located in the mountains some 88.5 km (55 miles) west of Fort Collins, Colorado. The conference was attended by experimentalists and theoreticians from a wide range of disciplines, including geology, hydrology, civil engineering, watershed science, chemical engineering, geography, statistics, mathematics, meteorology, and soil science. The attendees included researchers at various levels of research experience, including a large contingent of graduate students and many senior scientists.The conference goal was to review progress and discuss research approaches to the spatial variability of catchment surface and subsurface properties in a distributed modeling context. Mathematical models of water movement dynamics within a catchment consist of linked partial differential equations that describe free surface flow and unsaturated and saturated flow in porous media. Such models are utilized extensively in attempts to understand and predict the environmental consequences of human activities such as agricultural land management, waste disposal, urbanization, etc. We are concerned with the spatial structure of the parameters in such models, the precipitation input, and the geometric complexity of the system boundaries. The emphasis of this conference was on surface and subsurface hydrological process and their interactions.

  5. Scale effect challenges in urban hydrology highlighted with a distributed hydrological model

    Directory of Open Access Journals (Sweden)

    A. Ichiba


    Full Text Available Hydrological models are extensively used in urban water management, development and evaluation of future scenarios and research activities. There is a growing interest in the development of fully distributed and grid-based models. However, some complex questions related to scale effects are not yet fully understood and still remain open issues in urban hydrology. In this paper we propose a two-step investigation framework to illustrate the extent of scale effects in urban hydrology. First, fractal tools are used to highlight the scale dependence observed within distributed data input into urban hydrological models. Then an intensive multi-scale modelling work is carried out to understand scale effects on hydrological model performance. Investigations are conducted using a fully distributed and physically based model, Multi-Hydro, developed at Ecole des Ponts ParisTech. The model is implemented at 17 spatial resolutions ranging from 100 to 5 m. Results clearly exhibit scale effect challenges in urban hydrology modelling. The applicability of fractal concepts highlights the scale dependence observed within distributed data. Patterns of geophysical data change when the size of the observation pixel changes. The multi-scale modelling investigation confirms scale effects on hydrological model performance. Results are analysed over three ranges of scales identified in the fractal analysis and confirmed through modelling. This work also discusses some remaining issues in urban hydrology modelling related to the availability of high-quality data at high resolutions, and model numerical instabilities as well as the computation time requirements. The main findings of this paper enable a replacement of traditional methods of model calibration by innovative methods of model resolution alteration based on the spatial data variability and scaling of flows in urban hydrology.

  6. Hydrological states and fluxes in terrestrial systems: from observation to prediction (John Dalton Medal Lecture) (United States)

    Vereecken, Harry


    Quantification and prediction of hydrological processes requires information on the spatial and temporal distribution of soil water fluxes and soil water content. The access to spatially and temporally highly resolved soil water content and fluxes is needed to adequately test hydrological hypotheses and to validate hydrological models. In this presentation we will discuss new developments for the determination of soil water content and quantification and prediction of hydrological fluxes based on hydrogeophysical measurement techniques and novel ground- and satellite based sensing platforms. At the field scale, ground penetrating radar and passive microwave methods are presently being developed which provide the possibility to map soil water content with a high spatial and temporal resolution, also in the subsurface environment. Recent developments show that the application of full wave form inversion methods is a unique technique to derive soil water and soil hydraulic parameters from on- and off-ground systems with high spatial resolution. At the small catchment scale, wireless sensor networks are presently being developed providing soil moisture content values with a high spatial and temporal resolution. Stochastic theories have been used to interpret the relationship between average soil water content and its standard deviation. Cosmic ray sensors are presently being deployed within the TERENO observatories. These sensors provide soil moisture content values with a high temporal resolution at a scale of one to two hundred meters, thereby bridging the gap between local scale measurements and remote sensing platforms. Cosmic ray probes are extremely valuable for the determination of soil water content in agriculturally managed soils. Data assimilation methods provide a unique approach to fully exploit the value of spatially and temporally highly resolved soil water content measurements and states of the terrestrial system for the prediction of hydrological fluxes

  7. Modeled hydrologic metrics show links between hydrology and the functional composition of stream assemblages. (United States)

    Patrick, Christopher J; Yuan, Lester L


    Flow alteration is widespread in streams, but current understanding of the effects of differences in flow characteristics on stream biological communities is incomplete. We tested hypotheses about the effect of variation in hydrology on stream communities by using generalized additive models to relate watershed information to the values of different flow metrics at gauged sites. Flow models accounted for 54-80% of the spatial variation in flow metric values among gauged sites. We then used these models to predict flow metrics in 842 ungauged stream sites in the mid-Atlantic United States that were sampled for fish, macroinvertebrates, and environmental covariates. Fish and macroinvertebrate assemblages were characterized in terms of a suite of metrics that quantified aspects of community composition, diversity, and functional traits that were expected to be associated with differences in flow characteristics. We related modeled flow metrics to biological metrics in a series of stressor-response models. Our analyses identified both drying and base flow instability as explaining 30-50% of the observed variability in fish and invertebrate community composition. Variations in community composition were related to variations in the prevalence of dispersal traits in invertebrates and trophic guilds in fish. The results demonstrate that we can use statistical models to predict hydrologic conditions at bioassessment sites, which, in turn, we can use to estimate relationships between flow conditions and biological characteristics. This analysis provides an approach to quantify the effects of spatial variation in flow metrics using readily available biomonitoring data. © 2017 by the Ecological Society of America.

  8. Hydrology under change: an evaluation protocol to investigate how hydrological models deal with changing catchments (United States)

    G. Thirel; V. Andreassian; C. Perrin; J.-N. Audouy; L. Berthet; Pamela Edwards; N. Folton; C. Furusho; A. Kuentz; J. Lerat; G. Lindstrom; E. Martin; T. Mathevet; R. Merz; J. Parajka; D. Ruelland; J. Vaze


    Testing hydrological models under changing conditions is essential to evaluate their ability to cope with changing catchments and their suitability for impact studies. With this perspective in mind, a workshop dedicated to this issue was held at the 2013 General Assembly of the International Association of Hydrological Sciences (IAHS) in Göteborg, Sweden, in July 2013...

  9. Xanthos – A Global Hydrologic Model

    Directory of Open Access Journals (Sweden)

    Xinya Li


    Full Text Available Xanthos is an open-source hydrologic model, written in Python, designed to quantify and analyse global water availability. Xanthos simulates historical and future global water availability on a monthly time step at a spatial resolution of 0.5 geographic degrees. Xanthos was designed to be extensible and used by scientists that study global water supply and work with the Global Change Assessment Model (GCAM. Xanthos uses a user-defined configuration file to specify model inputs, outputs and parameters. Xanthos has been tested using actual global data sets and the model is able to provide historical observations and future estimates of renewable freshwater resources in the form of total runoff. Funding statement: PNNL is operated for DOE by Battelle Memorial Institute under contract DE-AC05-76RL01830.

  10. Assessing climate change impact by integrated hydrological modelling (United States)

    Lajer Hojberg, Anker; Jørgen Henriksen, Hans; Olsen, Martin; der Keur Peter, van; Seaby, Lauren Paige; Troldborg, Lars; Sonnenborg, Torben; Refsgaard, Jens Christian


    Future climate may have a profound effect on the freshwater cycle, which must be taken into consideration by water management for future planning. Developments in the future climate are nevertheless uncertain, thus adding to the challenge of managing an uncertain system. To support the water managers at various levels in Denmark, the national water resources model (DK-model) (Højberg et al., 2012; Stisen et al., 2012) was used to propagate future climate to hydrological response under considerations of the main sources of uncertainty. The DK-model is a physically based and fully distributed model constructed on the basis of the MIKE SHE/MIKE11 model system describing groundwater and surface water systems and the interaction between the domains. The model has been constructed for the entire 43.000 km2 land area of Denmark only excluding minor islands. Future climate from General Circulation Models (GCM) was downscaled by Regional Climate Models (RCM) by a distribution-based scaling method (Seaby et al., 2012). The same dataset was used to train all combinations of GCM-RCMs and they were found to represent the mean and variance at the seasonal basis equally well. Changes in hydrological response were computed by comparing the short term development from the period 1990 - 2010 to 2021 - 2050, which is the time span relevant for water management. To account for uncertainty in future climate predictions, hydrological response from the DK-model using nine combinations of GCMs and RCMs was analysed for two catchments representing the various hydrogeological conditions in Denmark. Three GCM-RCM combinations displaying high, mean and low future impacts were selected as representative climate models for which climate impact studies were carried out for the entire country. Parameter uncertainty was addressed by sensitivity analysis and was generally found to be of less importance compared to the uncertainty spanned by the GCM-RCM combinations. Analysis of the simulations

  11. Evaluation of the TRMM real time Multi-satellite Precipitation Analysis for global hydrologic prediction (United States)

    Gao, H.; Voisin, N.; Minihane, M.; Huffman, G. J.; Sheffield, J.; Lettenmaier, D. P.


    The applicability of satellite precipitation products like the TRMM multi-satellite precipitation analysis (TMPA) products has been limited in its applicability to real-time hydrologic prediction (e.g., of floods and droughts) by the need for retrospective gauge-based adjustments to correct for biases. However, recent advances in the TMPA algorithms and data streams now offer encouragement regarding their potential use for real-time hydrologic prediction without gauge adjustment. This potential is of particular interest in regions like Africa where in situ gauge networks are sparse. We evaluate how changes in the TMPA real-time (TMPA-RT) precipitation retrieval algorithms have affected the products in the context of flood and drought prediction, and quantify the uncertainty in streamflow predictions resulting from TMPA real-time errors with respect to the TMPA research (gauge corrected) product (TMPA-RP). We conduct hydrologic simulations using the Variable Infiltration Capacity (VIC) model over 11 global river basins within the TMPA domain for the period 2003 to 2011. For evaluation purposes, the model is forced by the newly available TMPA-RP Version 7 TMPA-RT, , and a bias corrected TMPA-RT (adjusted in real-time to correct biases relative to TMPA-RP at the University of Washington). Other meteorological forcings for VIC are taken from an independent global data set. The daily VIC model output is routed to the main river outlet for each basin using a one quarter degree routing network. We evaluate the results both in terms of the evolution of the RT algorithms and the uncertainty of hydrologic prediction associated with the latest (V7) algorithm.

  12. Multi-model assessment of hydrologic impacts of climate change in a small Mediterranean basin (United States)

    Perra, Enrica; Piras, Monica; Deidda, Roberto; Paniconi, Claudio; Mascaro, Giuseppe; Vivoni, Enrique R.; Cau, Pierluigi; Marras, Pier Andrea; Meyer, Swen; Ludwig, Ralf


    Assessing the hydrologic impacts of climate change is of great importance in the Mediterranean region, which is characterized by high precipitation variablitity and complex interactions within the water cycle. In this work we focus on the hydrological response of the Rio Mannu catchment, a small basin located in southern Sardinia (Italy) and characterized by a semi-arid climate. Specifically, we investigate inter-model variability and uncertainty by comparing the results of five distributed hydrologic models, namely CATchment HYdrology (CATHY), Soil and Water Assessment Tool (SWAT), TOPographic Kinematic APproximation and Integration eXtended (TOPKAPI-X), TIN-based Real time Integrated Basin Simulator (tRIBS), and WAter flow and balance SIMulation (WASIM), that differ greatly in their representation of terrain features, physical processes, and numerical complexity. The hydrological models were independently calibrated and validated on observed meteorological and hydrological time series, and then forced by the output of four combinations of global and regional climate models (properly bias-corrected and downscaled) in order to evaluate the effects of climate change for a reference (1971-2000) and a future (2041-2070) period. Notwithstanding their differences, the five hydrologic models responded similarly to the reduced precipitation and increased temperatures predicted by the climate models, and lend strong support to a future scenario of increased water shortages. The multi-model framework allows estimation of the uncertainty associated with these hydrologic simulations and this aspect will also be discussed.

  13. Performance Assessment of Hydrological Models Considering Acceptable Forecast Error Threshold

    Directory of Open Access Journals (Sweden)

    Qianjin Dong


    Full Text Available It is essential to consider the acceptable threshold in the assessment of a hydrological model because of the scarcity of research in the hydrology community and errors do not necessarily cause risk. Two forecast errors, including rainfall forecast error and peak flood forecast error, have been studied based on the reliability theory. The first order second moment (FOSM and bound methods are used to identify the reliability. Through the case study of the Dahuofang (DHF Reservoir, it is shown that the correlation between these two errors has great influence on the reliability index of hydrological model. In particular, the reliability index of the DHF hydrological model decreases with the increasing correlation. Based on the reliability theory, the proposed performance evaluation framework incorporating the acceptable forecast error threshold and correlation among the multiple errors can be used to evaluate the performance of a hydrological model and to quantify the uncertainties of a hydrological model output.

  14. Plant adaptive behaviour in hydrological models (Invited) (United States)

    van der Ploeg, M. J.; Teuling, R.


    Models that will be able to cope with future precipitation and evaporation regimes need a solid base that describes the essence of the processes involved [1]. Micro-behaviour in the soil-vegetation-atmosphere system may have a large impact on patterns emerging at larger scales. A complicating factor in the micro-behaviour is the constant interaction between vegetation and geology in which water plays a key role. The resilience of the coupled vegetation-soil system critically depends on its sensitivity to environmental changes. As a result of environmental changes vegetation may wither and die, but such environmental changes may also trigger gene adaptation. Constant exposure to environmental stresses, biotic or abiotic, influences plant physiology, gene adaptations, and flexibility in gene adaptation [2-6]. Gene expression as a result of different environmental conditions may profoundly impact drought responses across the same plant species. Differences in response to an environmental stress, has consequences for the way species are currently being treated in models (single plant to global scale). In particular, model parameters that control root water uptake and plant transpiration are generally assumed to be a property of the plant functional type. Assigning plant functional types does not allow for local plant adaptation to be reflected in the model parameters, nor does it allow for correlations that might exist between root parameters and soil type. Models potentially provide a means to link root water uptake and transport to large scale processes (e.g. Rosnay and Polcher 1998, Feddes et al. 2001, Jung 2010), especially when powered with an integrated hydrological, ecological and physiological base. We explore the experimental evidence from natural vegetation to formulate possible alternative modeling concepts. [1] Seibert, J. 2000. Multi-criteria calibration of a conceptual runoff model using a genetic algorithm. Hydrology and Earth System Sciences 4(2): 215

  15. Distributed Hydrologic Modeling Apps for Decision Support in the Cloud (United States)

    Swain, N. R.; Latu, K.; Christiensen, S.; Jones, N.; Nelson, J.


    Advances in computation resources and greater availability of water resources data represent an untapped resource for addressing hydrologic uncertainties in water resources decision-making. The current practice of water authorities relies on empirical, lumped hydrologic models to estimate watershed response. These models are not capable of taking advantage of many of the spatial datasets that are now available. Physically-based, distributed hydrologic models are capable of using these data resources and providing better predictions through stochastic analysis. However, there exists a digital divide that discourages many science-minded decision makers from using distributed models. This divide can be spanned using a combination of existing web technologies. The purpose of this presentation is to present a cloud-based environment that will offer hydrologic modeling tools or 'apps' for decision support and the web technologies that have been selected to aid in its implementation. Compared to the more commonly used lumped-parameter models, distributed models, while being more intuitive, are still data intensive, computationally expensive, and difficult to modify for scenario exploration. However, web technologies such as web GIS, web services, and cloud computing have made the data more accessible, provided an inexpensive means of high-performance computing, and created an environment for developing user-friendly apps for distributed modeling. Since many water authorities are primarily interested in the scenario exploration exercises with hydrologic models, we are creating a toolkit that facilitates the development of a series of apps for manipulating existing distributed models. There are a number of hurdles that cloud-based hydrologic modeling developers face. One of these is how to work with the geospatial data inherent with this class of models in a web environment. Supporting geospatial data in a website is beyond the capabilities of standard web frameworks and it

  16. Landfilling: Hydrology

    DEFF Research Database (Denmark)

    Kjeldsen, Peter; Beaven, R.


    Landfill hydrology deals with the presence and movement of water through a landfill. The main objective in landfill hydrology is usually to predict leachate generation, but the presence and movement of water in a landfill also affect the degradation of the waste, the leaching of pollutants...... and the geotechnical stability of the fill. Understanding landfill hydrology is thus important for many aspects of landfill, in particular siting, design and operation. The objective of this chapter is to give a basic understanding of the hydrology of landfills, and to present ways to estimate leachate quantities......-circuiting. In the final section different existing hydrological models for landfills are presented with a special focus on the HELP model. This model is the most widely used tool for the prediction of leachate quantities in landfills, and for the sizing of leachate control and management infrastructure....

  17. Improvements of Physically-Based Hydrological Modelling using the ACRU Agro-Hydrological Modelling System (United States)

    Bonifacio, C. M. T.; Kienzle, S. W.; Xu, W.; Zhang, J.


    The uncertainty of future water availability due to climate change in the Upper Oldman River Basin in Alberta, Canada, and downstream users is considered in this study. A changing climate can significantly perturb hydrological response within a region, thereby affecting the available water resources within southern Alberta. The ACRU agro-hydrological modelling system is applied to simulate historical (1950-2010) and future (2041-2070) streamflows and volumes of a major irrigation reservoir. Like many highly complex, process-based distributed models, major limitations include the data availability and data quality at finer spatial resolutions. With the use of a scripting language, certain limitations can be greatly reduced. Three phases of the project will be emphasized. First, the assimilation of solar radiation, relative humidity, sunshine hours and wind speed daily data into the Canadian 10KM daily climate data that contains daily precipitation, maximum and minimum temperature data for the period 1950-2010, so as to enable potential evapotranspiration calculations using the Penman-Monteith equation. Second, the downscaling of five regional climate model (RCM) data to match the 10KM spatial resolution was undertaken. Third, a total of 1722 hydrological response units (HRUs) were delineated within the 4403 km2 large upper Oldman River Basin. In all phases of model input data parameterization and calibration, the automation of known external procedures greatly decreased erroneous model inputs and increased the efficiency of validating the quality of input data to be used within the ACRU model.

  18. Coupled hydrologic and hydraulic modeling of Upper Niger River Basin (United States)

    Fleischmann, Ayan; Siqueira, Vinícius; Paris, Adrien; Collischonn, Walter; Paiva, Rodrigo; Gossett, Marielle; Pontes, Paulo; Calmant, Stephane; Biancamaria, Sylvain; Crétaux, Jean-François; Tanimoune, Bachir


    The Upper Niger Basin is located in Western Africa, flowing from Guinea Highlands towards the Sahel region. In this area lies the seasonally inundated Niger Inland Delta, which supports important environmental services such as habitats for wildlife, climate and flood regulation, as well as large fishery and agricultural areas. In this study, we present the application of MGB-IPH large scale hydrologic and hydrodynamic model for the Upper Niger Basin, totaling c.a. 650,000 km2 and set up until the city of Niamey in Niger. The model couples hydrological vertical balance and runoff generation with hydrodynamic flood wave propagation, by allowing infiltration from floodplains into soil column as well as representing backwater effects and floodplain storage throughout flat areas such as the Inland Delta. The model is forced with TRMM 3B42 daily precipitation and Climate Research Unit (CRU) climatology for the period 2000-2010, and was calibrated against in-situ discharge gauges and validated with in-situ water level, remotely sensed estimations of flooded areas (classification of MODIS imagery) and satellite altimetry (JASON-2 mission). Model results show good predictions for calibrated daily discharge and validated water level and altimetry at stations both upstream and downstream of the delta (Nash-Sutcliffe Efficiency>0.7 for all stations), as well as for flooded areas within the delta region (ENS=0.5; r2=0.8), allowing a good representation of flooding dynamics basinwide and simulation of flooding behavior of both perennial (e.g., Niger main stem) and ephemeral rivers (e.g., Niger Red Flood tributaries in Sahel). Coupling between hydrology and hydrodynamic processes indicates an important feedback between floodplain and soil water storage that allows high evapotranspiration rates even after the flood passage around the inner delta area. Also, representation of water retention in floodplain channels and distributaries in the inner delta (e.g., Diaka river

  19. Developing predictive insight into changing water systems: use-inspired hydrologic science for the Anthropocene

    National Research Council Canada - National Science Library

    Thompson, S. E; Sivapalan, M; Harman, C. J; Srinivasan, V; Hipsey, M. R; Reed, P; Montanari, A; Blöschl, G


    ... to address internal and exogenous changes in the properties of hydrologic systems. To do this, new hydrologic research must identify, describe and model feedbacks between water and other changing, coupled environmental subsystems...

  20. A hydrological model of New Zealand (United States)

    Woods, R. A.; Tarboton, D. G.; Ibbitt, R. P.; Wild, M.; Henderson, R. D.; Turner, R.


    We present initial results from a hydrological model of New Zealand, using Topnet, a variant of TOPMODEL, linked to a kinematic wave channel network routing algorithm. This model run uses daily timesteps for the period 1985-2001, and subdivides the country into approximately 35,000 sub-catchments of 7-10 sq km each. The sub-catchments are linked by 55,000 river reaches, which route sub-catchment runoff. The model subcatchments and reaches are defined automatically by DEM analyses, and initial estimates of model parameters are defined by GIS overlay, coupled with purpose-built model assembly code, and lookup tables for model parameters. A daily simulation for 1 year over New Zealand takes two hours on a standard desktop computer. The model is forced by gridded daily rainfall and temperature data, and it calculates daily water balance for each of the sub-catchments (rain, evaporation, throughfall, infiltration, soil drainage, surface runoff, subsurface runoff, and changes in storage in the canopy, root zone, and saturated storage), as well as daily flows in each river reach. The model as currently implemented does not include snow, glaciers, or deep groundwater flow (i.e. across sub-catchment boundaries). The first applications of the model are for developing an annual water balance of New Zealand for the period 1994-2001, at the regional scale, and for driving a high-spatial resolution, daily time-stepping national erosion model. We are moving to further applications for water resource modeling (e.g. impact of abstraction and/or storage), and for flood forecasting, using hourly rainfall from a mesoscale atmospheric model.

  1. Implementation of evapotranspiration data assimilation with catchment scale distributed hydrological model via an ensemble Kalman Filter (United States)

    Zou, Lei; Zhan, Chesheng; Xia, Jun; Wang, Tiejun; Gippel, Christopher J.


    Terrestrial actual evapotranspiration (ETa) is a crucial component of terrestrial water cycles. The most common methods of estimating catchment-scale ETa are remote sensing and hydrological models. These methods have limitations when applied at the catchment scale due to coarse resolutions of data and uncertainties in model predictions. Data assimilation techniques that combine complementary information from hydrological models and observed data can overcome some of the limitations. These techniques have been used in many hydrological modeling studies, but few have applied data assimilation to ETa within a distributed precipitation-runoff catchment modeling framework. This paper proposes a catchment scale ETa data assimilation technique (termed ET-DA) that assimilates remotely sensed ETa data into a distributed time-variant gain hydrological model (DTVGM-ET) for improving hydrological model simulations. The DTVGM-ET improved the ETa computation on the basis of a nonlinear soil water availability function to establish an explicit time response relationship between ETa and soil moisture for implementing the ETa assimilation. The proposed ET-DA system was tested in the Upper Huai River Basin (UHRB), China using data from 2000 to 2012. Through synthetic simulation experiments, the capability of ET-DA for obtaining accurate, continuous time series of ETa estimates and achieving assimilation feedback on soil moisture and streamflow was examined. The results demonstrated that ET-DA provided improved regional ETa monitoring capability, and assimilation of ETa into the hydrological model led to improved model predictions of soil moisture and streamflow.

  2. Modelling the effect of land use change on hydrological model ...

    African Journals Online (AJOL)

    Conceptual rainfall–runoff models have become a basic tool for evaluating effects of land use/cover changes on the hydrologic processes in small-scale as well as large watersheds. The runoff-producing mechanism is influenced by land use/cover changes. In this study, we analysed the effect of land use change on ...

  3. Towards the development of a multimodel hydrological ensemble prediction system for La Mojana, Colombia (United States)

    Brochero, D.; Peña, J.; Anctil, F.; Boucher, M. A.; Nogales, J.; Reyes, N.


    The impacts of floods in Colombia during 2010 and 2011 as a result of ENSO in its cold phase (La Niña) marked a milestone in Colombian politics. In La Mojana region the balance was around 100,000 homeless and 3 km2 of flooded crops. We model the upstream basin of La Mojana (3600 km2 and a mean annual precipitation from 1000mm in valleys to 4500 mm in mountains). A forecasting system of at least three days in advance was judged prudent. This basin receives an streamflow highly regulated by multiple reservoirs that we model with a recurrent neural networks from 1 to 3-days ahead. For hydrological modeling purposes we use the GR4J, HBV, and SIMHYD models, records of daily precipitation, temperature, and streamflows, and 110 prediction scenarios of precipitation and temperature from Canada, USA, Brazil, and Europe extracted from the TIGGE database (MEPS). Calibration period is between January 2004 and August 2011. Validation from September to December 2011, taking as meteorological input the MEPS. We analised four alternative for the 3-day Hydrological Ensemble Prediction System (HEPS) Calibration: 1) only the GR4J model and observed values, 2). as 1 but HBV and SIMHYD are included, 3). Simultaneous optimization of the three hydrological models based on the reliability maximisation and the CRPS minimisation using the multiobjective calibration, observed and forecasted temperature and precipitation from the MEPS and, 4). as 3 but adding the daily streamflow data assimilation. Results show that the use of multiple hydrological models is clearly advantageous but even more performing the simultaneous optimization of hydrological models in the probabilistic context directly. The results evolution of the MAE on the reliability diagram (MAE-RD) are 43%, 27%, 17% and 15% respectively for the four alternatives. Regarding CRPS, MAE results show that the probabilistic prediction improves the deterministic estimate based on the daily mean HEPS scenario, despite the improvement in

  4. Improving hydrological simulations by incorporating GRACE data for model calibration (United States)

    Bai, Peng; Liu, Xiaomang; Liu, Changming


    Hydrological model parameters are typically calibrated by observed streamflow data. This calibration strategy is questioned when the simulated hydrological variables of interest are not limited to streamflow. Well-performed streamflow simulations do not guarantee the reliable reproduction of other hydrological variables. One of the reasons is that hydrological model parameters are not reasonably identified. The Gravity Recovery and Climate Experiment (GRACE)-derived total water storage change (TWSC) data provide an opportunity to constrain hydrological model parameterizations in combination with streamflow observations. In this study, a multi-objective calibration scheme based on GRACE-derived TWSC and streamflow observations was compared with the traditional single-objective calibration scheme based on only streamflow simulations. Two hydrological models were employed on 22 catchments in China with different climatic conditions. The model evaluations were performed using observed streamflows, GRACE-derived TWSC, and actual evapotranspiration (ET) estimates from flux towers and from the water balance approach. Results showed that the multi-objective calibration scheme provided more reliable TWSC and ET simulations without significant deterioration in the accuracy of streamflow simulations than the single-objective calibration. The improvement in TWSC and ET simulations was more significant in relatively dry catchments than in relatively wet catchments. In addition, hydrological models calibrated using GRACE-derived TWSC data alone cannot obtain accurate runoff simulations in ungauged catchments. This study highlights the importance of including additional constraints in addition to streamflow observations to improve performances of hydrological models.

  5. An Educational Model for Hands-On Hydrology Education (United States)

    AghaKouchak, A.; Nakhjiri, N.; Habib, E. H.


    This presentation provides an overview of a hands-on modeling tool developed for students in civil engineering and earth science disciplines to help them learn the fundamentals of hydrologic processes, model calibration, sensitivity analysis, uncertainty assessment, and practice conceptual thinking in solving engineering problems. The toolbox includes two simplified hydrologic models, namely HBV-EDU and HBV-Ensemble, designed as a complement to theoretical hydrology lectures. The models provide an interdisciplinary application-oriented learning environment that introduces the hydrologic phenomena through the use of a simplified conceptual hydrologic model. The toolbox can be used for in-class lab practices and homework assignments, and assessment of students' understanding of hydrological processes. Using this modeling toolbox, students can gain more insights into how hydrological processes (e.g., precipitation, snowmelt and snow accumulation, soil moisture, evapotranspiration and runoff generation) are interconnected. The educational toolbox includes a MATLAB Graphical User Interface (GUI) and an ensemble simulation scheme that can be used for teaching more advanced topics including uncertainty analysis, and ensemble simulation. Both models have been administered in a class for both in-class instruction and a final project, and students submitted their feedback about the toolbox. The results indicate that this educational software had a positive impact on students understanding and knowledge of hydrology.

  6. Statistical Modeling to Predict N2O Production Within the Hyporheic Zone by Coupling Denitrifying Microbial Community Abundance to Geochemical and Hydrological Parameters (United States)

    Farrell, T. B.; Quick, A. M.; Reeder, W. J.; Benner, S. G.; Tonina, D.; Feris, K. P.


    The hyporheic zone (HZ) of streams may be a significant source of nitrous oxide (N2O). However, the biogeochemical processes controlling N2O emissions remain poorly constrained due to difficulties in obtaining high-resolution chemical, physical, and biological data from streams. Our research elucidates specific controls on N2O production within the HZ by coupling the distribution of denitrifying microbial communities to flow dynamics (i.e. hydraulics and streambed morphology) and biogeochemical processes. We conducted a large-scale flume experiment that allowed us to constrain streambed morphology, flow rate, organic carbon loading, grain size distribution, and exogenous nitrate loading while enabling regular monitoring of dissolved oxygen, pH, alkalinity, nitrogen species, and elemental concentrations in the HZ. We also employed real-time PCR (qPCR) to quantify the distribution of denitrifying functional genes (nirS and nosZ, nitrite reductase and nitrous oxide reductase genes, respectively) in HZ sediment cores as a measure of denitrifying microorganism abundance. A steady increase in N2O was observed after 8 hours of residence time with a peak in concentration (9.5 μg-N/L) recorded at hour 18. Abundance of nosZ increased an order of magnitude between hours 8 and 18 (2.6x106 to 2.1x107 gene copy #/g dry sediment). nirS abundance remained within the same order of magnitude between hours 8 and 18 (1.7x107 to 3.8x107). Linear and nonlinear mixed-effects models were used to investigate N2O production in the HZ as a function of total nitrogen, nirS, nosZ, residence time, and dissolved oxygen. N2O production was localized at redox-controlled hotspots within the subsurface and concentrations were strongly correlated with the availability of nitrogen when an interaction with nosZ abundance was considered. On-going analysis will provide predictions of N2O production and support for conditions under which the HZ could be a significant contributor of N2O emissions. These

  7. Evaluation of a monthly hydrological model for Integrated Assessment Models (United States)

    Liu, Y.; Hejazi, M. I.; Li, H. Y.; Zhang, X.; Leng, G.


    The Integrated Assessment modeling (IAM) community, which generated the four representative concentration pathways (RCPs), is actively moving toward including endogenous representations of water supply and demand in their economic modeling frameworks. Toward integrating the water supply module, we build an efficient object-oriented and open-source hydrologic model (HM) to be embedded in IAMs - Global Change Assessment Model (GCAM). The main objective for this new HM is to strike a balance between model complexity and computational efficiency; i.e., possessing sufficient fidelity to capture both the annual and the seasonal signals of water fluxes and pools and being highly computationally efficient so that it can be used for large number of simulations or uncertainty quantification analyses. To this end, we build a monthly gridded hydrological model based on the ABCD model with some additional features such as a snow scheme and the effects of land use and land cover change (LULCC) on the hydrological cycle. In this framework, we mainly simulate the pools of soil moisture, snowpack and groundwater storage, and the fluxes of evapotranspiration, recharge to groundwater, direct runoff and groundwater discharge. We assess the performance of the model by comparing the model results against runoff simulation from the model of Variable Infiltration Capacity (VIC) as well as historical streamflow observations at various gauge stations. We will present results on the model performance, the gains of adding different model components (e.g., snow scheme, effects of LULCC), and the variations of hydrological cycle globally over the historical period of 1901-2010.

  8. Patterns of Hydrologic Sensitivity to Climate in the Western US: Implications for Future Predictions (United States)

    Safeeq, M.; Grant, G.


    A key challenge for resource and land managers is predicting the consequences of climate warming on streamflow and water resources. During the last century in the western United States, significant reductions in snowpack and earlier snowmelt have led to an increase in the fraction of annual streamflow during winter and a decline in the summer. However, this increase and decrease in streamflow is mediated by the climate and landscape. Here we explore key landscape and climate metrics for interpreting hydrologic sensitivity to climate using observed flow from a range of watersheds across the western United States. Our results indicate that the recession constant and fraction of precipitation falling as snow are the two primary controls on hydrologic sensitivity to climate in this region. Dry season flows in watersheds that drain slowly from deep groundwater and receive precipitation as snow are most sensitive to climate warming. In terms of peak flow, watersheds are most sensitivity to the consistency (i.e. signal-to-noise ratio) in fraction of precipitation falling as snow. Our results also indicate that not all trends in western United States are associated with changes in snowpack dynamics; we observe declining flow in late fall and winter in rain-dominated watersheds as well. These empirical findings support both theory and hydrologic modeling and have implications for how hydrologic sensitivity to climate change is evaluated and interpreted across broad regions.

  9. Effects of modeling decisions on cold region hydrological model performance: snow, soil and streamflow (United States)

    Musselman, Keith; Clark, Martyn; Endalamaw, Abraham; Bolton, W. Robert; Nijssen, Bart; Arnold, Jeffrey


    Cold regions are characterized by intense spatial gradients in climate, vegetation and soil properties that determine the complex spatiotemporal patterns of snowpack evolution, frozen soil dynamics, catchment connectivity, and streamflow. These spatial gradients pose unique challenges for hydrological models, including: 1) how the spatial variability of the physical processes are best represented across a hierarchy of scales, and 2) what algorithms and parameter sets best describe the biophysical and hydrological processes at the spatial scale of interest. To address these topics, we apply the Structure for Unifying Multiple Modeling Alternatives (SUMMA) to simulate hydrological processes at the Caribou - Poker Creeks Research Watershed in the Alaskan sub-arctic Boreal forest. The site is characterized by numerous gauged headwater catchments ranging in size from 5 sq. km to 106 sq. km with varying extents (3% to 53%) of discontinuous permafrost that permits a multi-scale paired watershed analysis of the hydrological impacts of frozen soils. We evaluate the effects of model decisions on the skill of SUMMA to simulate observed snow and soil dynamics, and the spatial integration of these processes as catchment streamflow. Decisions such as the number of soil layers, total soil column depth, and vertical soil discretization are shown to have profound impacts on the simulation of seasonal active layer dynamics. Decisions on the spatial organization (lateral connectivity, representation of riparian response units, and the spatial discretization of the hydrological landscape) are shown to be as important as accurate snowpack and soil process representation in the simulation of streamflow. The work serves to better inform hydrological model decisions for cold region hydrologic evaluation and to improve predictive capacity for water resource planning.

  10. Elements of a flexible approach for conceptual hydrological modeling: 2. Application and experimental insights (United States)

    Kavetski, Dmitri; Fenicia, Fabrizio


    In this article's companion paper, flexible approaches for conceptual hydrological modeling at the catchment scale were motivated, and the SUPERFLEX framework, based on generic model components, was introduced. In this article, the SUPERFLEX framework and the "fixed structure" GR4H model (an hourly version of the popular GR4J model) are applied to four hydrologically distinct experimental catchments in Europe and New Zealand. The estimated models are scrutinized using several diagnostic measures, ranging from statistical metrics, such as the statistical reliability and precision of the predictive distribution of streamflow, to more process-oriented diagnostics based on flow-duration curves and the correspondence between model states and groundwater piezometers. Model performance was clearly catchment specific, with a single fixed structure unable to accommodate intercatchment differences in hydrological behavior, including seasonality and thresholds. This highlights an important limitation of any "fixed" model structure. In the experimental catchments, the ability of competing model hypotheses to reproduce hydrological signatures of interest could be interpreted on the basis of independent fieldwork insights. The potential of flexible frameworks such as SUPERFLEX is then examined with respect to systematic and stringent hypothesis-testing in hydrological modeling, for characterizing catchment diversity, and, more generally, for aiding progress toward a more unified formulation of hydrological theory at the catchment scale. When interpreted in physical process-oriented terms, the flexible approach can also serve as a language for dialogue between modeler and experimentalist, facilitating the understanding, representation, and interpretation of catchment behavior.

  11. Synchronising data sources and filling gaps by global hydrological modelling (United States)

    Pimentel, Rafael; Crochemore, Louise; Hasan, Abdulghani; Pineda, Luis; Isberg, Kristina; Arheimer, Berit


    The advances in remote sensing in the last decades combined with the creation of different open hydrological databases have generated a very large amount of useful information for global hydrological modelling. Working with this huge number of datasets to set up a global hydrological model can constitute challenges such as multiple data formats and big heterogeneity on spatial and temporal resolutions. Different initiatives have made effort to homogenize some of these data sources, i.e. GRDC (Global Runoff Data Center), HYDROSHEDS (SHuttle Elevation Derivatives at multiple Scales), GLWD (Global Lake and Wetland Database) for runoff, watershed delineation and water bodies respectively. However, not all the related issues are covered or homogenously solved at the global scale and new information is continuously available to complete the current ones. This work presents synchronising efforts to make use of different global data sources needed to set up the semi-distributed hydrological model HYPE (Hydrological Predictions for the Environment) at the global scale. These data sources included: topography for watershed delineation, gauging stations of river flow, and extention of lakes, flood plains and land cover classes. A new database with approximately 100 000 subbasins, with an average area of 1000 km2, was created. Subbasin delineation was done combining Global Width Database for Large River (GWD-LR), SRTM high-resolution elevation data and a number of forced points of interest (gauging station of river flow, lakes, reservoirs, urban areas, nuclear plants and areas with high risk of flooding). Regarding flow data, the locations of GRDC stations were checked or placed along the river network when necessary, and completed with available information from national water services in data-sparse regions. A screening of doublet stations and associated time series was necessary to efficiently combine the two types of data sources. A total number about 21 000 stations were

  12. Data Mining of Hydrological Model Performances (United States)

    Vitolo, Claudia; Buytaert, Wouter


    Multi-objective criteria have long been used to infer hydrological simulations and fit the natural world. On the other hand, modelling frameworks are also becoming more and more popular as identification of the processes occurring in a catchment is still a very uncertain matter. In theory, multi-objective criteria and multi-model frameworks should be used in combination so that the 'representation' of the catchment is fitted to the observations, not only the simulated results. In practise those approaches are highly computationally demanding. The modeller is often obliged to find a compromise reducing either the number of objective functions or model structures taken into consideration. This compromise is becoming obsolete using parallel computing. In the present study we investigate the extend to which model selection algorithms and regionalisation techniques can be improved by such facilities and highlight the challenges that still need to be addressed. The model simulations are obtained using an ensemble of conceptual lumped models (FUSE by Clark et al. 2008), but techniques and suggestions are of general use and applicable to any modelling frameworks. In particular we developed a novel model selection algorithm tuned to drastically reduce the subjectivity in the analysis. The procedure was automated and coupled with redundancy reduction techniques such as PCA and Cluster Analysis. Results show that the actual model 'representation' has the shape of a set of complementing model structures. It is also possible to capture intra-annum dynamics of the response as the algorithm recognises subtle variations in the selected model structures in different seasons. Similar variations can be found analysing different catchments. This suggests the same methodology would be suitable for analysing spatial patterns in the distribution of suitable model structures and maybe long term dynamics in relation with expedited climate modifications. Although the mentioned methodology

  13. Development of a "Hydrologic Equivalent Wetland" Concept for Modeling Cumulative Effects of Wetlands on Watershed Hydrology (United States)

    Wang, X.; Liu, T.; Li, R.; Yang, X.; Duan, L.; Luo, Y.


    and wetland characteristics (e.g., size and morphology) to be accurately represented in the models. The loss of the first 10 to 20% of the wetlands in the Minnesota study area would drastically increase the peak discharge and loadings of sediment, total phosphorus (TP), and total nitrogen (TN). On the other hand, the justifiable reductions of the peak discharge and loadings of sediment, TP, and TN in the Manitoba study area may require that 50 to 80% of the lost wetlands be restored. Further, the comparison between the predicted restoration and conservation effects revealed that wetland conservation seems to deserve a higher priority while both wetland conservation and restoration may be equally important. Moreover, although SWAT was used in this study, the HEW concept is generic and can also be applied with any other hydrologic models.

  14. Genetic Algorithm Optimization of Artificial Neural Networks for Hydrological Modelling (United States)

    Abrahart, R. J.


    This paper will consider the case for genetic algorithm optimization in the development of an artificial neural network model. It will provide a methodological evaluation of reported investigations with respect to hydrological forecasting and prediction. The intention in such operations is to develop a superior modelling solution that will be: \\begin{itemize} more accurate in terms of output precision and model estimation skill; more tractable in terms of personal requirements and end-user control; and/or more robust in terms of conceptual and mechanical power with respect to adverse conditions. The genetic algorithm optimization toolbox could be used to perform a number of specific roles or purposes and it is the harmonious and supportive relationship between neural networks and genetic algorithms that will be highlighted and assessed. There are several neural network mechanisms and procedures that could be enhanced and potential benefits are possible at different stages in the design and construction of an operational hydrological model e.g. division of inputs; identification of structure; initialization of connection weights; calibration of connection weights; breeding operations between successful models; and output fusion associated with the development of ensemble solutions. Each set of opportunities will be discussed and evaluated. Two strategic questions will also be considered: [i] should optimization be conducted as a set of small individual procedures or as one large holistic operation; [ii] what specific function or set of weighted vectors should be optimized in a complex software product e.g. timings, volumes, or quintessential hydrological attributes related to the 'problem situation' - that might require the development flood forecasting, drought estimation, or record infilling applications. The paper will conclude with a consideration of hydrological forecasting solutions developed on the combined methodologies of co-operative co-evolution and

  15. Macroscale hydrologic modeling of ecologically relevant flow metrics (United States)

    Seth J. Wenger; Charles H. Luce; Alan F. Hamlet; Daniel J. Isaak; Helen M. Neville


    Stream hydrology strongly affects the structure of aquatic communities. Changes to air temperature and precipitation driven by increased greenhouse gas concentrations are shifting timing and volume of streamflows potentially affecting these communities. The variable infiltration capacity (VIC) macroscale hydrologic model has been employed at regional scales to describe...

  16. Catchment-scale hydrological modeling and data assimilation

    NARCIS (Netherlands)

    Troch, P.A.A.; Paniconi, C.; McLaughlin, D.


    This special issue of Advances in Water Resources presents recent progress in the application of DA (data assimilation) for distributed hydrological modeling and in the use of in situ and remote sensing datasets for hydrological analysis and parameter estimation. The papers were presented at the De

  17. ZONE package of the Central Valley Hydrologic Model (United States)

    U.S. Geological Survey, Department of the Interior — This digital dataset defines the model grid, active cells in model layers 2 and 3, and geologic province arrays of the ZONE package used in the transient hydrologic...

  18. Pursuing the method of multiple working hypotheses for hydrological modeling

    NARCIS (Netherlands)

    Clark, M.P.; Kavetski, D.; Fenicia, F.


    Ambiguities in the representation of environmental processes have manifested themselves in a plethora of hydrological models, differing in almost every aspect of their conceptualization and implementation. The current overabundance of models is symptomatic of an insufficient scientific understanding

  19. From local hydrological process analysis to regional hydrological model application in Benin: Concept, results and perspectives (United States)

    Bormann, H.; Faß, T.; Giertz, S.; Junge, B.; Diekkrüger, B.; Reichert, B.; Skowronek, A.

    This paper presents the concept, first results and perspectives of the hydrological sub-project of the IMPETUS-Benin project which is part of the GLOWA program funded by the German ministry of education and research. In addition to the research concept, first results on field hydrology, pedology, hydrogeology and hydrological modelling are presented, focusing on the understanding of the actual hydrological processes. For analysing the processes a 30 km 2 catchment acting as a super test site was chosen which is assumed to be representative for the entire catchment of about 15,000 km 2. First results of the field investigations show that infiltration, runoff generation and soil erosion strongly depend on land cover and land use which again influence the soil properties significantly. A conceptual hydrogeological model has been developed summarising the process knowledge on runoff generation and subsurface hydrological processes. This concept model shows a dominance of fast runoff components (surface runoff and interflow), a groundwater recharge along preferential flow paths, temporary interaction between surface and groundwater and separate groundwater systems on different scales (shallow, temporary groundwater on local scale and permanent, deep groundwater on regional scale). The findings of intensive measurement campaigns on soil hydrology, groundwater dynamics and soil erosion have been integrated into different, scale-dependent hydrological modelling concepts applied at different scales in the target region (upper Ouémé catchment in Benin, about 15,000 km 2). The models have been applied and successfully validated. They will be used for integrated scenario analyses in the forthcoming project phase to assess the impacts of global change on the regional water cycle and on typical problem complexes such as food security in West African countries.

  20. Computer-assisted mesh generation based on hydrological response units for distributed hydrological modeling (United States)

    Sanzana, P.; Jankowfsky, S.; Branger, F.; Braud, I.; Vargas, X.; Hitschfeld, N.; Gironás, J.


    Distributed hydrological models rely on a spatial discretization composed of homogeneous units representing different areas within the catchment. Hydrological Response Units (HRUs) typically form the basis of such a discretization. HRUs are generally obtained by intersecting raster or vector layers of land uses, soil types, geology and sub-catchments. Polylines maps representing ditches and river drainage networks can also be used. However this overlapping may result in a mesh with numerical and topological problems not highly representative of the terrain. Thus, a pre-processing is needed to improve the mesh in order to avoid negative effects on the performance of the hydrological model. This paper proposes computer-assisted mesh generation tools to obtain a more regular and physically meaningful mesh of HRUs suitable for hydrologic modeling. We combined existing tools with newly developed scripts implemented in GRASS GIS. The developed scripts address the following problems: (1) high heterogeneity in Digital Elevation Model derived properties within the HRUs, (2) correction of concave polygons or polygons with holes inside, (3) segmentation of very large polygons, and (4) bad estimations of units' perimeter and distances among them. The improvement process was applied and tested using two small catchments in France. The improvement of the spatial discretization was further assessed by comparing the representation and arrangement of overland flow paths in the original and improved meshes. Overall, a more realistic physical representation was obtained with the improved meshes, which should enhance the computation of surface and sub-surface flows in a hydrologic model.

  1. An approach to predict water quality in data-sparse catchments using hydrological catchment similarity (United States)

    Pohle, Ina; Glendell, Miriam; Stutter, Marc I.; Helliwell, Rachel C.


    An understanding of catchment response to climate and land use change at a regional scale is necessary for the assessment of mitigation and adaptation options addressing diffuse nutrient pollution. It is well documented that the physicochemical properties of a river ecosystem respond to change in a non-linear fashion. This is particularly important when threshold water concentrations, relevant to national and EU legislation, are exceeded. Large scale (regional) model assessments required for regulatory purposes must represent the key processes and mechanisms that are more readily understood in catchments with water quantity and water quality data monitored at high spatial and temporal resolution. While daily discharge data are available for most catchments in Scotland, nitrate and phosphorus are mostly available on a monthly basis only, as typified by regulatory monitoring. However, high resolution (hourly to daily) water quantity and water quality data exist for a limited number of research catchments. To successfully implement adaptation measures across Scotland, an upscaling from data-rich to data-sparse catchments is required. In addition, the widespread availability of spatial datasets affecting hydrological and biogeochemical responses (e.g. soils, topography/geomorphology, land use, vegetation etc.) provide an opportunity to transfer predictions between data-rich and data-sparse areas by linking processes and responses to catchment attributes. Here, we develop a framework of catchment typologies as a prerequisite for transferring information from data-rich to data-sparse catchments by focusing on how hydrological catchment similarity can be used as an indicator of grouped behaviours in water quality response. As indicators of hydrological catchment similarity we use flow indices derived from observed discharge data across Scotland as well as hydrological model parameters. For the latter, we calibrated the lumped rainfall-runoff model TUWModel using multiple

  2. Multi-Model Combination techniques for Hydrological Forecasting: Application to Distributed Model Intercomparison Project Results

    Energy Technology Data Exchange (ETDEWEB)

    Ajami, N K; Duan, Q; Gao, X; Sorooshian, S


    This paper examines several multi-model combination techniques: the Simple Multi-model Average (SMA), the Multi-Model Super Ensemble (MMSE), Modified Multi-Model Super Ensemble (M3SE) and the Weighted Average Method (WAM). These model combination techniques were evaluated using the results from the Distributed Model Intercomparison Project (DMIP), an international project sponsored by the National Weather Service (NWS) Office of Hydrologic Development (OHD). All of the multi-model combination results were obtained using uncalibrated DMIP model outputs and were compared against the best uncalibrated as well as the best calibrated individual model results. The purpose of this study is to understand how different combination techniques affect the skill levels of the multi-model predictions. This study revealed that the multi-model predictions obtained from uncalibrated single model predictions are generally better than any single member model predictions, even the best calibrated single model predictions. Furthermore, more sophisticated multi-model combination techniques that incorporated bias correction steps work better than simple multi-model average predictions or multi-model predictions without bias correction.

  3. Advancements in Hydrology and Erosion Process Understanding and Post-Fire Hydrologic and Erosion Model Development for Semi-Arid Landscapes (United States)

    Williams, C. Jason; Pierson, Frederick B.; Al-Hamdan, Osama Z.; Robichaud, Peter R.; Nearing, Mark A.; Hernandez, Mariano; Weltz, Mark A.; Spaeth, Kenneth E.; Goodrich, David C.


    Fire activity continues to increase in semi-arid regions around the globe. Private and governmental land management entities are challenged with predicting and mitigating post-fire hydrologic and erosion responses on these landscapes. For more than a decade, a team of scientists with the US Department of Agriculture has collaborated on extensive post-fire hydrologic field research and the application of field research to development of post-fire hydrology and erosion predictive technologies. Experiments funded through this research investigated the impacts of fire on vegetation and soils and the effects of these fire-induced changes on infiltration, runoff generation, erodibility, and soil erosion processes. The distribution of study sites spans diverse topography across grassland, shrubland, and woodland landscapes throughout the western United States. Knowledge gleaned from the extensive field experiments was applied to develop and enhance physically-based models for hillslope- to watershed-scale runoff and erosion prediction. Our field research and subsequent data syntheses have identified key knowledge gaps and challenges regarding post-fire hydrology and erosion modeling. Our presentation details some consistent trends across a diverse domain and varying landscape conditions based on our extensive field campaigns. We demonstrate how field data have advanced our understanding of post-fire hydrology and erosion for semi-arid landscapes and highlight remaining key knowledge gaps. Lastly, we briefly show how our well-replicated experimental methodologies have contributed to advancements in hydrologic and erosion model development for the post-fire environment.

  4. Using models for the optimization of hydrologic monitoring (United States)

    Fienen, Michael N.; Hunt, Randall J.; Doherty, John E.; Reeves, Howard W.


    Hydrologists are often asked what kind of monitoring network can most effectively support science-based water-resources management decisions. Currently (2011), hydrologic monitoring locations often are selected by addressing observation gaps in the existing network or non-science issues such as site access. A model might then be calibrated to available data and applied to a prediction of interest (regardless of how well-suited that model is for the prediction). However, modeling tools are available that can inform which locations and types of data provide the most 'bang for the buck' for a specified prediction. Put another way, the hydrologist can determine which observation data most reduce the model uncertainty around a specified prediction. An advantage of such an approach is the maximization of limited monitoring resources because it focuses on the difference in prediction uncertainty with or without additional collection of field data. Data worth can be calculated either through the addition of new data or subtraction of existing information by reducing monitoring efforts (Beven, 1993). The latter generally is not widely requested as there is explicit recognition that the worth calculated is fundamentally dependent on the prediction specified. If a water manager needs a new prediction, the benefits of reducing the scope of a monitoring effort, based on an old prediction, may be erased by the loss of information important for the new prediction. This fact sheet focuses on the worth or value of new data collection by quantifying the reduction in prediction uncertainty achieved be adding a monitoring observation. This calculation of worth can be performed for multiple potential locations (and types) of observations, which then can be ranked for their effectiveness for reducing uncertainty around the specified prediction. This is implemented using a Bayesian approach with the PREDUNC utility in the parameter estimation software suite PEST (Doherty, 2010). The

  5. Medium-term hydrologic forecasting in mountain basins using forecasting of a mesoscale numerical weather model (United States)

    Castro Heredia, L. M.; Suarez, F. I.; Fernandez, B.; Maass, T.


    For forecasting of water resources, weather outputs provide a valuable source of information which is available online. Compared to traditional ground-based meteorological gauges, weather forecasts data offer spatially and temporally continuous data not yet evaluated and used in the forecasting of water resources in mountainous regions in Chile. Nevertheless, the use of this non-conventional data has been limited or null in developing countries, basically because of the spatial resolution, despite the high potential in the management of water resources. The adequate incorporation of these data in hydrological models requires its evaluation while taking into account the features of river basins in mountainous regions. This work presents an integrated forecasting system which represents a radical change in the way of making the streamflow forecasts in Chile, where the snowmelt forecast is the principal component of water resources management. The integrated system is composed of a physically based hydrological model, which is the prediction tool itself, together with a methodology for remote sensing data gathering that allows feed the hydrological model in real time, and meteorological forecasts from NCEP-CFSv2. Previous to incorporation of meteorological forecasts into the hydrological model, the weather outputs were evaluated and downscaling using statistical downscaling methods. The hydrological forecasts were evaluated in two mountain basins in Chile for a term of six months for the snowmelt period. In every month an assimilation process was performed, and the hydrological forecast was improved. Each month, the snow cover area (from remote sensing) and the streamflow observed were used to assimilate the model parameters in order to improve the next hydrological forecast using meteorological forecasts. The operation of the system in real time shows a good agreement between the streamflow and the snow cover area observed. The hydrological model and the weather

  6. Revisiting an interdisciplinary hydrological modelling project. A socio-hydrology (?) example from the early 2000s (United States)

    Seidl, Roman; Barthel, Roland


    Interdisciplinary scientific and societal knowledge plays an increasingly important role in global change research. Also, in the field of water resources interdisciplinarity as well as cooperation with stakeholders from outside academia have been recognized as important. In this contribution, we revisit an integrated regional modelling system (DANUBIA), which was developed by an interdisciplinary team of researchers and relied on stakeholder participation in the framework of the GLOWA-Danube project from 2001 to 2011 (Mauser and Prasch 2016). As the model was developed before the current increase in literature on participatory modelling and interdisciplinarity, we ask how a socio-hydrology approach would have helped and in what way it would have made the work different. The present contribution firstly presents the interdisciplinary concept of DANUBIA, mainly with focus on the integration of human behaviour in a spatially explicit, process-based numerical modelling system (Roland Barthel, Janisch, Schwarz, Trifkovic, Nickel, Schulz, and Mauser 2008; R. Barthel, Nickel, Meleg, Trifkovic, and Braun 2005). Secondly, we compare the approaches to interdisciplinarity in GLOWA-Danube with concepts and ideas presented by socio-hydrology. Thirdly, we frame DANUBIA and a review of key literature on socio-hydrology in the context of a survey among hydrologists (N = 184). This discussion is used to highlight gaps and opportunities of the socio-hydrology approach. We show that the interdisciplinary aspect of the project and the participatory process of stakeholder integration in DANUBIA were not entirely successful. However, important insights were gained and important lessons were learnt. Against the background of these experiences we feel that in its current state, socio-hydrology is still lacking a plan for knowledge integration. Moreover, we consider necessary that socio-hydrology takes into account the lessons learnt from these earlier examples of knowledge integration

  7. Hydrological modeling of the Jiaoyi watershed (China) using HSPF model. (United States)

    Yan, Chang-An; Zhang, Wanchang; Zhang, Zhijie


    A watershed hydrological model, hydrological simulation program-Fortran (HSPF), was applied to simulate the spatial and temporal variation of hydrological processes in the Jiaoyi watershed of Huaihe River Basin, the heaviest shortage of water resources and polluted area in China. The model was calibrated using the years 2001-2004 and validated with data from 2005 to 2006. Calibration and validation results showed that the model generally simulated mean monthly and daily runoff precisely due to the close matching hydrographs between simulated and observed runoff, as well as the excellent evaluation indicators such as Nash-Sutcliffe efficiency (NSE), coefficient of correlation (R (2)), and the relative error (RE). The similar simulation results between calibration and validation period showed that all the calibrated parameters had a certain representation in Jiaoyi watershed. Additionally, the simulation in rainy months was more accurate than the drought months. Another result in this paper was that HSPF was also capable of estimating the water balance components reasonably and realistically in space through the whole watershed. The calibrated model can be used to explore the effects of climate change scenarios and various watershed management practices on the water resources and water environment in the basin.

  8. Hydrologi

    DEFF Research Database (Denmark)

    Burcharth, Hans F.

    Hydro1ogi er den videnskab, der omhand1er jordens vand, dets forekomst, cirku1ation og forde1ing, dets kemiske og fysiske egenskaber samt indvirkning på omgivelserne, herunder dets relation ti1 alt liv på jorden. Således lyder en b1andt mange definitioner på begrebet hydrologi, og som man kan se...

  9. Multi-Model Combination Techniques for Hydrological Forecasting: Application to Distributed Model Intercomparison Project Results

    Energy Technology Data Exchange (ETDEWEB)

    Ajami, N; Duan, Q; Gao, X; Sorooshian, S


    This paper examines several multi-model combination techniques: the Simple Multimodel Average (SMA), the Multi-Model Super Ensemble (MMSE), Modified Multi-Model Super Ensemble (M3SE) and the Weighted Average Method (WAM). These model combination techniques were evaluated using the results from the Distributed Model Intercomparison Project (DMIP), an international project sponsored by the National Weather Service (NWS) Office of Hydrologic Development (OHD). All of the multi-model combination results were obtained using uncalibrated DMIP model outputs and were compared against the best uncalibrated as well as the best calibrated individual model results. The purpose of this study is to understand how different combination techniques affect the skill levels of the multi-model predictions. This study revealed that the multi-model predictions obtained from uncalibrated single model predictions are generally better than any single member model predictions, even the best calibrated single model predictions. Furthermore, more sophisticated multi-model combination techniques that incorporated bias correction steps work better than simple multi-model average predictions or multi-model predictions without bias correction.

  10. A double continuum hydrological model for glacier applications

    Directory of Open Access Journals (Sweden)

    B. de Fleurian


    Full Text Available The flow of glaciers and ice streams is strongly influenced by the presence of water at the interface between ice and bed. In this paper, a hydrological model evaluating the subglacial water pressure is developed with the final aim of estimating the sliding velocities of glaciers. The global model fully couples the subglacial hydrology and the ice dynamics through a water-dependent friction law. The hydrological part of the model follows a double continuum approach which relies on the use of porous layers to compute water heads in inefficient and efficient drainage systems. This method has the advantage of a relatively low computational cost that would allow its application to large ice bodies such as Greenland or Antarctica ice streams. The hydrological model has been implemented in the finite element code Elmer/Ice, which simultaneously computes the ice flow. Herein, we present an application to the Haut Glacier d'Arolla for which we have a large number of observations, making it well suited to the purpose of validating both the hydrology and ice flow model components. The selection of hydrological, under-determined parameters from a wide range of values is guided by comparison of the model results with available glacier observations. Once this selection has been performed, the coupling between subglacial hydrology and ice dynamics is undertaken throughout a melt season. Results indicate that this new modelling approach for subglacial hydrology is able to reproduce the broad temporal and spatial patterns of the observed subglacial hydrological system. Furthermore, the coupling with the ice dynamics shows good agreement with the observed spring speed-up.

  11. An integrated model of soil, hydrology, and vegetation for carbon dynamics in wetland ecosystems (United States)

    Yu Zhang; Changsheng Li; Carl C. Trettin; Harbin Li; Ge Sun


    Wetland ecosystems are an important component in global carbon (C) cycles and may exert a large influence on global clinlate change. Predictions of C dynamics require us to consider interactions among many critical factors of soil, hydrology, and vegetation. However, few such integrated C models exist for wetland ecosystems. In this paper, we report a simulation model...

  12. Modeling summer month hydrological drought probabilities in the United States using antecedent flow conditions (United States)

    Austin, Samuel H.; Nelms, David L.


    Climate change raises concern that risks of hydrological drought may be increasing. We estimate hydrological drought probabilities for rivers and streams in the United States (U.S.) using maximum likelihood logistic regression (MLLR). Streamflow data from winter months are used to estimate the chance of hydrological drought during summer months. Daily streamflow data collected from 9,144 stream gages from January 1, 1884 through January 9, 2014 provide hydrological drought streamflow probabilities for July, August, and September as functions of streamflows during October, November, December, January, and February, estimating outcomes 5-11 months ahead of their occurrence. Few drought prediction methods exploit temporal links among streamflows. We find MLLR modeling of drought streamflow probabilities exploits the explanatory power of temporally linked water flows. MLLR models with strong correct classification rates were produced for streams throughout the U.S. One ad hoc test of correct prediction rates of September 2013 hydrological droughts exceeded 90% correct classification. Some of the best-performing models coincide with areas of high concern including the West, the Midwest, Texas, the Southeast, and the Mid-Atlantic. Using hydrological drought MLLR probability estimates in a water management context can inform understanding of drought streamflow conditions, provide warning of future drought conditions, and aid water management decision making.

  13. Regional review: the hydrology of the Okavango Delta, Botswana—processes, data and modelling (United States)

    Milzow, Christian; Kgotlhang, Lesego; Bauer-Gottwein, Peter; Meier, Philipp; Kinzelbach, Wolfgang


    The wetlands of the Okavango Delta accommodate a multitude of ecosystems with a large diversity in fauna and flora. They not only provide the traditional livelihood of the local communities but are also the basis of a tourism industry that generates substantial revenue for the whole of Botswana. For the global community, the wetlands retain a tremendous pool of biodiversity. As the upstream states Angola and Namibia are developing, however, changes in the use of the water of the Okavango River and in the ecological status of the wetlands are to be expected. To predict these impacts, the hydrology of the Delta has to be understood. This article reviews scientific work done for that purpose, focussing on the hydrological modelling of surface water and groundwater. Research providing input data to hydrological models is also presented. It relies heavily on all types of remote sensing. The history of hydrologic models of the Delta is retraced from the early box models to state-of-the-art distributed hydrological models. The knowledge gained from hydrological models and its relevance for the management of the Delta are discussed.

  14. Probabilistic hydrological nowcasting using radar based nowcasting techniques and distributed hydrological models: application in the Mediterranean area (United States)

    Poletti, Maria Laura; Pignone, Flavio; Rebora, Nicola; Silvestro, Francesco


    The exposure of the urban areas to flash-floods is particularly significant to Mediterranean coastal cities, generally densely-inhabited. Severe rainfall events often associated to intense and organized thunderstorms produced, during the last century, flash-floods and landslides causing serious damages to urban areas and in the worst events led to human losses. The temporal scale of these events has been observed strictly linked to the size of the catchments involved: in the Mediterranean area a great number of catchments that pass through coastal cities have a small drainage area (less than 100 km2) and a corresponding hydrologic response timescale in the order of a few hours. A suitable nowcasting chain is essential for the on time forecast of this kind of events. In fact meteorological forecast systems are unable to predict precipitation at the scale of these events, small both at spatial (few km) and temporal (hourly) scales. Nowcasting models, covering the time interval of the following two hours starting from the observation try to extend the predictability limits of the forecasting models in support of real-time flood alert system operations. This work aims to present the use of hydrological models coupled with nowcasting techniques. The nowcasting model PhaSt furnishes an ensemble of equi-probable future precipitation scenarios on time horizons of 1-3 h starting from the most recent radar observations. The coupling of the nowcasting model PhaSt with the hydrological model Continuum allows to forecast the flood with a few hours in advance. In this way it is possible to generate different discharge prediction for the following hours and associated return period maps: these maps can be used as a support in the decisional process for the warning system.

  15. Modeling the hydrological patterns on Pantanal wetlands, Brazil (United States)

    Castro, A. A.; Cuartas, A.; Coe, M. T.; Koumrouyan, A.; Panday, P. K.; Lefebvre, P.; Padovani, C.; Costa, M. H.; de Oliveira, G. S.


    The Pantanal of Brazil is one of the world's largest wetland regions. It is located within the 370,000 km2 Alto Paraguai Basin (BAP). In wet years almost 15% of the total area of the basin can be flooded (approximately 53,000 km2). The hydrological cycle is particularly important in the Pantanal in the transport of materials, and the transfer of energy between atmospheric, aquatic, and terrestrial systems. The INLAND (Integrated Land Surface Model) terrestrial ecosystem model is coupled with the THMB hydrological model to examine the hydrological balance and water dynamics for this region. The INLAND model is based on the IBIS dynamic vegetation model, while THMB represents the river, wetland and lake dynamics of the land surface. The modeled hydrological components are validated with surface and satellite-based estimates of precipitation (gridded observations from CRU v. 3.21, reanalysis data from ERA-interim, and TRMM estimates), evapotranspiration (MODIS and Land Flux-Eval dataset), total runoff (discharge data from ANA-Agência Nacional das Águas - Brazil), and terrestrial water storage (GRACE). Results show that the coupled hydrological model adequately represents the water cycle components, the river discharge and flooded areas. Model simulations are further used to study the influences of climatic variations on the hydrological components, river network, and the inundated areas in the Pantanal.

  16. Exploiting remote sensing land surface temperature in distributed hydrological modelling: the example of the Continuum model

    Directory of Open Access Journals (Sweden)

    F. Silvestro


    Full Text Available Full process description and distributed hydrological models are very useful tools in hydrology as they can be applied in different contexts and for a wide range of aims such as flood and drought forecasting, water management, and prediction of impact on the hydrologic cycle due to natural and human-induced changes. Since they must mimic a variety of physical processes, they can be very complex and with a high degree of parameterization. This complexity can be increased by necessity of augmenting the number of observable state variables in order to improve model validation or to allow data assimilation.

    In this work a model, aiming at balancing the need to reproduce the physical processes with the practical goal of avoiding over-parameterization, is presented. The model is designed to be implemented in different contexts with a special focus on data-scarce environments, e.g. with no streamflow data.

    All the main hydrological phenomena are modelled in a distributed way. Mass and energy balance are solved explicitly. Land surface temperature (LST, which is particularly suited to being extensively observed and assimilated, is an explicit state variable.

    A performance evaluation, based on both traditional and satellite derived data, is presented with a specific reference to the application in an Italian catchment. The model has been firstly calibrated and validated following a standard approach based on streamflow data. The capability of the model in reproducing both the streamflow measurements and the land surface temperature from satellites has been investigated.

    The model has been then calibrated using satellite data and geomorphologic characteristics of the basin in order to test its application on a basin where standard hydrologic observations (e.g. streamflow data are not available. The results have been compared with those obtained by the standard calibration strategy based on streamflow data.

  17. Evapotranspiration Input Data for the Central Valley Hydrologic Model (CVHM) (United States)

    U.S. Geological Survey, Department of the Interior — This digital dataset contains monthly reference evapotranspiration (ETo) data for the Central Valley Hydrologic Model (CVHM). The Central Valley encompasses an...

  18. California Basin Characterization Model Downscaled Climate and Hydrology (United States)

    U.S. Geological Survey, Department of the Interior — The California Basin Characterization Model (CA-BCM 2014) dataset provides historical and projected climate and hydrologic surfaces for the region that encompasses...

  19. Does model performance improve with complexity? A case study with three hydrological models (United States)

    Orth, Rene; Staudinger, Maria; Seneviratne, Sonia I.; Seibert, Jan; Zappa, Massimiliano


    In recent decades considerable progress has been made in climate model development. Following the massive increase in computational power, models became more sophisticated. At the same time also simple conceptual models have advanced. In this study we validate and compare three hydrological models of different complexity to investigate whether their performance varies accordingly. For this purpose we use runoff and also soil moisture measurements, which allow a truly independent validation, from several sites across Switzerland. The models are calibrated in similar ways with the same runoff data. Our results show that the more complex models HBV and PREVAH outperform the simple water balance model (SWBM) in case of runoff but not for soil moisture. Furthermore the most sophisticated PREVAH model shows an added value compared to the HBV model only in case of soil moisture. Focusing on extreme events we find generally improved performance of the SWBM during drought conditions and degraded agreement with observations during wet extremes. For the more complex models we find the opposite behavior, probably because they were primarily developed for prediction of runoff extremes. As expected given their complexity, HBV and PREVAH have more problems with over-fitting. All models show a tendency towards better performance in lower altitudes as opposed to (pre-) alpine sites. The results vary considerably across the investigated sites. In contrast, the different metrics we consider to estimate the agreement between models and observations lead to similar conclusions, indicating that the performance of the considered models is similar at different time scales as well as for anomalies and long-term means. We conclude that added complexity does not necessarily lead to improved performance of hydrological models, and that performance can vary greatly depending on the considered hydrological variable (e.g. runoff vs. soil moisture) or hydrological conditions (floods vs. droughts).

  20. Pursuing realistic hydrologic model under SUPERFLEX framework in a semi-humid catchment in China (United States)

    Wei, Lingna; Savenije, Hubert H. G.; Gao, Hongkai; Chen, Xi


    Model realism is pursued perpetually by hydrologists for flood and drought prediction, integrated water resources management and decision support of water security. "Physical-based" distributed hydrologic models are speedily developed but they also encounter unneglectable challenges, for instance, computational time with low efficiency and parameters uncertainty. This study step-wisely tested four conceptual hydrologic models under the framework of SUPERFLEX in a small semi-humid catchment in southern Huai River basin of China. The original lumped FLEXL has hypothesized model structure of four reservoirs to represent canopy interception, unsaturated zone, subsurface flow of fast and slow components and base flow storage. Considering the uneven rainfall in space, the second model (FLEXD) is developed with same parameter set for different rain gauge controlling units. To reveal the effect of topography, terrain descriptor of height above the nearest drainage (HAND) combined with slope is applied to classify the experimental catchment into two landscapes. Then the third one (FLEXTOPO) builds different model blocks in consideration of the dominant hydrologic process corresponding to the topographical condition. The fourth one named FLEXTOPOD integrating the parallel framework of FLEXTOPO in four controlled units is designed to interpret spatial variability of rainfall patterns and topographic features. Through pairwise comparison, our results suggest that: (1) semi-distributed models (FLEXD and FLEXTOPOD) taking precipitation spatial heterogeneity into account has improved model performance with parsimonious parameter set, and (2) hydrologic model architecture with flexibility to reflect perceived dominant hydrologic processes can include the local terrain circumstances for each landscape. Hence, the modeling actions are coincided with the catchment behaviour and close to the "reality". The presented methodology is regarding hydrologic model as a tool to test our

  1. A Four-Stage Hybrid Model for Hydrological Time Series Forecasting (United States)

    Di, Chongli; Yang, Xiaohua; Wang, Xiaochao


    Hydrological time series forecasting remains a difficult task due to its complicated nonlinear, non-stationary and multi-scale characteristics. To solve this difficulty and improve the prediction accuracy, a novel four-stage hybrid model is proposed for hydrological time series forecasting based on the principle of ‘denoising, decomposition and ensemble’. The proposed model has four stages, i.e., denoising, decomposition, components prediction and ensemble. In the denoising stage, the empirical mode decomposition (EMD) method is utilized to reduce the noises in the hydrological time series. Then, an improved method of EMD, the ensemble empirical mode decomposition (EEMD), is applied to decompose the denoised series into a number of intrinsic mode function (IMF) components and one residual component. Next, the radial basis function neural network (RBFNN) is adopted to predict the trend of all of the components obtained in the decomposition stage. In the final ensemble prediction stage, the forecasting results of all of the IMF and residual components obtained in the third stage are combined to generate the final prediction results, using a linear neural network (LNN) model. For illustration and verification, six hydrological cases with different characteristics are used to test the effectiveness of the proposed model. The proposed hybrid model performs better than conventional single models, the hybrid models without denoising or decomposition and the hybrid models based on other methods, such as the wavelet analysis (WA)-based hybrid models. In addition, the denoising and decomposition strategies decrease the complexity of the series and reduce the difficulties of the forecasting. With its effective denoising and accurate decomposition ability, high prediction precision and wide applicability, the new model is very promising for complex time series forecasting. This new forecast model is an extension of nonlinear prediction models. PMID:25111782

  2. Landscape-based hydrological modelling : Understanding the influence of climate, topography, and vegetation on catchment hydrology

    NARCIS (Netherlands)

    Gao, H.


    In this thesis, a novel landscape-based hydrological model is presented that was developed and tested in numerous catchments around the world with various landscapes and climate conditions. A landscape is considered to consist of a topography and an ecosystem living on it. Firstly, the influence of

  3. Application of a global hydrologic prediction system to the Zambezi River Basin (Invited) (United States)

    Voisin, N.; Pappenberger, F.; Buizza, R.; Lettenmaier, D. P.


    We evaluate a 10-day globally applicable flood prediction scheme over the Zambezi River basin for the period 2003-2007. The hydrological core of the scheme is the Variable Infiltration Capacity (VIC) hydrology model, which we forced with the European Centre for Medium Range Weather Forecasts (ECMWF) temperature and wind analyses, and the near real-time Tropical Rainfall Monitoring Mission (TRMM) precipitation product (3B42RT) up to the day of forecast. During the forecast period, the VIC model was forced with calibrated and downscaled 10-day forecasts from the ECMWF ensemble prediction system (EPS). We also tested a parallel setup where the EPS ensemble forecasts were interpolated to the 0.25 degree spatial resolution of the hydrology model. Each set of forecasts was extended by 5 days using monthly mean climatological variables and zero precipitation in order to account for the effect of initial conditions (the EPS was extended to 15 days only in 2006). The 15-day spatially distributed ensemble runoff forecasts were then routed to several locations in the basin. Surrogates for observed daily runoff and streamflow were provided by the reference run, i.e. the VIC simulations forced with ECMWF analysis fields and TRMM precipitation. Mean forecast errors and skills for the two sets of ensemble forecasts are evaluated with respect to the reference on a seasonal basis, and are compared to previous results from a similarly designed study over the Ohio River Basin. The influence on forecast accuracy of basin drainage area, hydroclimatic diversity within the basin, and storm type on forecast skill scores is evaluated.

  4. Calibration of hydrological models using flow-duration curves

    Directory of Open Access Journals (Sweden)

    I. K. Westerberg


    Full Text Available The degree of belief we have in predictions from hydrologic models will normally depend on how well they can reproduce observations. Calibrations with traditional performance measures, such as the Nash-Sutcliffe model efficiency, are challenged by problems including: (1 uncertain discharge data, (2 variable sensitivity of different performance measures to different flow magnitudes, (3 influence of unknown input/output errors and (4 inability to evaluate model performance when observation time periods for discharge and model input data do not overlap. This paper explores a calibration method using flow-duration curves (FDCs to address these problems. The method focuses on reproducing the observed discharge frequency distribution rather than the exact hydrograph. It consists of applying limits of acceptability for selected evaluation points (EPs on the observed uncertain FDC in the extended GLUE approach. Two ways of selecting the EPs were tested – based on equal intervals of discharge and of volume of water. The method was tested and compared to a calibration using the traditional model efficiency for the daily four-parameter WASMOD model in the Paso La Ceiba catchment in Honduras and for Dynamic TOPMODEL evaluated at an hourly time scale for the Brue catchment in Great Britain. The volume method of selecting EPs gave the best results in both catchments with better calibrated slow flow, recession and evaporation than the other criteria. Observed and simulated time series of uncertain discharges agreed better for this method both in calibration and prediction in both catchments. An advantage with the method is that the rejection criterion is based on an estimation of the uncertainty in discharge data and that the EPs of the FDC can be chosen to reflect the aims of the modelling application, e.g. using more/less EPs at high/low flows. While the method appears less sensitive to epistemic input/output errors than previous use of limits of

  5. Everglades Landscape Model: Integrated Assessment of Hydrology, Biogeochemistry, and Biology (United States)

    Fitz, H. C.; Wang, N.; Sklar, F. H.


    Water management infrastructure and operations have fragmented the greater Everglades into separate, impounded basins, altering flows and hydropatterns. A significant area of this managed system has experienced anthropogenic eutrophication. This combination of altered hydrology and water quality has interacted to degrade vegetative habitats and other ecological characteristics of the Everglades. One of the modeling tools to be used in developing restoration alternatives is the Everglades Landscape Model (ELM), a process-based, spatially explicit simulation of ecosystem dynamics across a heterogeneous, 10,000 km2 region. The model has been calibrated to capture hydrologic and surface water quality dynamics across most of the Everglades landscape over decadal time scales. We evaluated phosphorus loading throughout the Everglades system under two base scenarios. The 1995 base case assumed current management operations, with phosphorus inflow concentrations fixed at their long term, historical average. The 2050 base case assumed future modifications in water and nutrient management, with all managed inflows to the Everglades having reduced phosphorus concentrations. In an example indicator subregion that currently is highly eutrophic, the 31-yr simulations predicted that desirable periphyton and macrophyte communities were maintained under the 2050 base case, whereas in the 1995 base case, periphyton biomass and production decreased to negligible levels and macrophytes became extremely dense. The negative periphyton response in the 1995 base case was due to high phosphorus loads and rapid macrophyte growth that shaded this algal community. Along an existing 11 km eutrophication gradient, the model indicated that the 2050 base case had ecologically significant reductions in phosphorus accumulation compared to the 1995 base case. Indicator regions (in Everglades National Park) distant from phosphorus inflow points also exhibited reductions in phosphorus accumulation

  6. Impact of microwave derived soil moisture on hydrologic simulations using a spatially distributed water balance model (United States)

    Lin, D. S.; Wood, E. F.; Famiglietti, J. S.; Mancini, M.


    Spatial distributions of soil moisture over an agricultural watershed with a drainage area of 60 ha were derived from two NASA microwave remote sensors, and then used as a feedback to determine the initial condition for a distributed water balance model. Simulated hydrologic fluxes over a period of twelve days were compared with field observations and with model predictions based on a streamflow derived initial condition. The results indicated that even the low resolution remotely sensed data can improve the hydrologic model's performance in simulating the dynamics of unsaturated zone soil moisture. For the particular watershed under study, the simulated water budget was not sensitive to the resolutions of the microwave sensors.

  7. A comparison of hydrologic models for ecological flows and water availability (United States)

    Caldwell, Peter V; Kennen, Jonathan G.; Sun, Gee; Kiang, Julie E.; Butcher, John B; Eddy, Michelle C; Hay, Lauren E.; LaFontaine, Jacob H.; Hain, Ernie F.; Nelson, Stacy C; McNulty, Steve G


    Robust hydrologic models are needed to help manage water resources for healthy aquatic ecosystems and reliable water supplies for people, but there is a lack of comprehensive model comparison studies that quantify differences in streamflow predictions among model applications developed to answer management questions. We assessed differences in daily streamflow predictions by four fine-scale models and two regional-scale monthly time step models by comparing model fit statistics and bias in ecologically relevant flow statistics (ERFSs) at five sites in the Southeastern USA. Models were calibrated to different extents, including uncalibrated (level A), calibrated to a downstream site (level B), calibrated specifically for the site (level C) and calibrated for the site with adjusted precipitation and temperature inputs (level D). All models generally captured the magnitude and variability of observed streamflows at the five study sites, and increasing level of model calibration generally improved performance. All models had at least 1 of 14 ERFSs falling outside a +/−30% range of hydrologic uncertainty at every site, and ERFSs related to low flows were frequently over-predicted. Our results do not indicate that any specific hydrologic model is superior to the others evaluated at all sites and for all measures of model performance. Instead, we provide evidence that (1) model performance is as likely to be related to calibration strategy as it is to model structure and (2) simple, regional-scale models have comparable performance to the more complex, fine-scale models at a monthly time step.

  8. Climate noise effect on uncertainty of hydrological extremes: numerical experiments with hydrological and climate models

    Directory of Open Access Journals (Sweden)

    A. N. Gelfan


    Full Text Available An approach has been proposed to analyze the simulated hydrological extreme uncertainty related to the internal variability of the atmosphere ("climate noise", which is inherent to the climate system and considered as the lowest level of uncertainty achievable in climate impact studies. To assess the climate noise effect, numerical experiments were made with climate model ECHAM5 and hydrological model ECOMAG. The case study was carried out to Northern Dvina River basin (catchment area is 360 000 km2, whose hydrological regime is characterised by extreme freshets during spring-summer snowmelt period. The climate noise was represented by ensemble ECHAM5 simulations (45 ensemble members with identical historical boundary forcing and varying initial conditions. An ensemble of the ECHAM5-outputs for the period of 1979–2012 was used (after bias correction post-processing as the hydrological model inputs, and the corresponding ensemble of 45 multi-year hydrographs was simulated. From this ensemble, we derived flood statistic uncertainty caused by the internal variability of the atmosphere.

  9. A coupled energy transport and hydrological model for urban canopies (United States)

    Wang, Z.; Bou-Zeid, E.; Smith, J. A.


    Urban land-atmosphere interaction has been attracting more research efforts in order to understand the complex physics of flow and mass and heat transport in urban surfaces and the lower urban atmosphere. In this work, we developed and implemented a new physically-based single-layer urban canopy model, coupling the surface exchange of energy and the subsurface transport of water/soil moisture. The new model incorporates sub-facet heterogeneity for each urban surface (roof, wall or ground). This better simulates the energy transport in urban canopy layers, especially over low-intensity built (suburban type) terrains that include a significant fraction of vegetated surfaces. We implemented detailed urban hydrological models for both natural terrains (bare soil and vegetation) and porous engineered materials with water-holding capacity (concrete, gravel, etc). The skill of the new scheme was tested against experimental data collected through a wireless sensor network deployed over the campus of Princeton University. The model performance was found to be robust and insensitive to changes in weather conditions or seasonal variability. Predictions of the volumetric soil water content were also in good agreement with field measurements, highlighting the model capability of capturing subsurface water transport for urban lawns. The new model was also applied to a case study assessing different strategies, i.e. white versus green roofs, in the mitigation of urban heat island effect.

  10. Impact of vegetation dynamics on hydrological processes in a semi-arid basin by using a land surface-hydrology coupled model (United States)

    Jiao, Yang; Lei, Huimin; Yang, Dawen; Huang, Maoyi; Liu, Dengfeng; Yuan, Xing


    Land surface models (LSMs) are widely used to understand the interactions between hydrological processes and vegetation dynamics, which is important for the attribution and prediction of regional hydrological variations. However, most LSMs have large uncertainties in their representations of eco-hydrological processes due to deficiencies in hydrological parameterizations. In this study, the Community Land Model version 4 (CLM4) LSM was modified with an advanced runoff generation and flow routing scheme, resulting in a new land surface-hydrology coupled model, CLM-GBHM. Both models were implemented in the Wudinghe River Basin (WRB), which is a semi-arid basin located in the middle reaches of the Yellow River, China. Compared with CLM, CLM-GBHM increased the Nash Sutcliffe efficiency for daily river discharge simulation (1965-1969) from -0.03 to 0.23 and reduced the relative bias in water table depth simulations (2010-2012) from 32.4% to 13.4%. The CLM-GBHM simulations with static, remotely sensed and model-predicted vegetation conditions showed that the vegetation in the WRB began to recover in the 2000s due to the Grain for Green Program but had not reached the same level of vegetation cover as regions in natural eco-hydrological equilibrium. Compared with a simulation using remotely sensed vegetation cover, the simulation with a dynamic vegetation model that considers only climate-induced change showed a 10.3% increase in evapotranspiration, a 47.8% decrease in runoff, and a 62.7% and 71.3% deceleration in changing trend of the outlet river discharge before and after the year 2000, respectively. This result suggests that both natural and anthropogenic factors should be incorporated in dynamic vegetation models to better simulate the eco-hydrological cycle.

  11. Reduction of uncertainty of hydrological modelling using different precipitation inputs (United States)

    Pluntke, T.; Pavlik, D.; Bernhofer, C.


    models was evaluated with the Nash-Sutcliff-Efficiency coefficient (NSE) and the R2 between observed and modelled runoff. The model Stations performed better (R2/NSE: 0.66/0.61) than CCLM and Regionalized (0.54/0.54 and 0.57/0.53). Uncertainty of the hydrologic modelling (POC and d-factor) could not be reduced applying the alternative models. A promising method to improve the model performance and reduce the uncertainty is model averaging. Two model averaging methods were tested: arithmetic mean of the ensemble and a weighted mean (depending on NSE). The results show that the model performance could be improved (R2/NSE: 0.67/0.67) and the uncertainty reduced. Differences between the applied model averaging methods were marginal. Although not all observations could be reproduced, neither by the single models nor the ensemble averages, it was illustrated that combining different precipitation inputs improved the hydrologic predictions. Further calibration runs as well as the application of Bayesian Model Averaging are envisaged as next steps. Reference: Abbaspour, K. C., Johnson, C., & van Genuchten, M. T. (2004). Estimating uncertain flow and transport parameters using a sequential uncertainty fitting procedure. Vadose Zone Journal, (3), 1340-1352.

  12. Soil Systems for Upscaling Saturated Hydraulic Conductivity (Ksat) for Hydrological Modeling in the Critical Zone (United States)

    Successful hydrological model predictions depend on appropriate framing of scale and the spatial-temporal accuracy of input parameters describing soil hydraulic properties. Saturated soil hydraulic conductivity (Ksat) is one of the most important properties influencing water movement through soil un...

  13. airGRteaching: an R-package designed for teaching hydrology with lumped hydrological models (United States)

    Thirel, Guillaume; Delaigue, Olivier; Coron, Laurent; Andréassian, Vazken; Brigode, Pierre


    Lumped hydrological models are useful and convenient tools for research, engineering and educational purposes. They propose catchment-scale representations of the precipitation-discharge relationship. Thanks to their limited data requirements, they can be easily implemented and run. With such models, it is possible to simulate a number of hydrological key processes over the catchment with limited structural and parametric complexity, typically evapotranspiration, runoff, underground losses, etc. The Hydrology Group at Irstea (Antony) has been developing a suite of rainfall-runoff models over the past 30 years. This resulted in a suite of models running at different time steps (from hourly to annual) applicable for various issues including water balance estimation, forecasting, simulation of impacts and scenario testing. Recently, Irstea has developed an easy-to-use R-package (R Core Team, 2016), called airGR (Coron et al., 2016, 2017), to make these models widely available. Although its initial target public was hydrological modellers, the package is already used for educational purposes. Indeed, simple models allow for rapidly visualising the effects of parameterizations and model components on flows hydrographs. In order to avoid the difficulties that students may have when manipulating R and datasets, we developed (Delaigue and Coron, 2016): - Three simplified functions to prepare data, calibrate a model and run a simulation - Simplified and dynamic plot functions - A shiny (Chang et al., 2016) interface that connects this R-package to a browser-based visualisation tool. On this interface, the students can use different hydrological models (including the possibility to use a snow-accounting model), manually modify their parameters and automatically calibrate their parameters with diverse objective functions. One of the visualisation tabs of the interface includes observed precipitation and temperature, simulated snowpack (if any), observed and simulated

  14. Modeling conditional covariance between meteorological and hydrological drought (United States)

    Modarres, R.


    This study introduces a bivariate Generalized Autoregressive Conditional Heteroscedasticity (GARCH) approach to model the time varying second order moment or conditional variance-covariance link of hydrologic and meteorological drought. The standardized streamflow and rainfall time series are selected as drought indices and the bivariate diagonal BEKK model is applied to estimate the conditional variance-covariance structure between hydrologic and meteorological drought. Results of diagonal BEKK(1,1) model indicated that the conditional variance of meteorological drought is weak and much smaller than that for hydrological drought which shows a strong volatility effect. However both drought indices show a weak memory in the conditional variance. It is also observed that the conditional covariance between two drought indices is also weak and only shows a slight short run volatility effect. This may suggest the effect of basin features such as groundwater storage and physical characteristics which attenuate and modify the effect of meteorological drought on hydrologic drought in the basin scale. conditional correlation time series between meteorological and hydrologic drought at two selected stations monthly variation of conditional correlation between meteorological and hydrologic drought at two selected stations

  15. Plug-and-Play Hydrologic Modeling: Is That Really Possible? (United States)

    Peckham, S. D.


    The vision of a community of modelers that shares reusable and well-tested process components that can easily be linked together to create new models is very appealing. In this vision, trying a new method for modeling a physical process, comparing two methods from different groups or coupling two models together to do something new is painless and straightforward. Scientists get to spend more time on understanding the natural world, making predictions and analyzing model results. Students quickly learn how different approaches differ and how sensitive models are to various input parameters. They begin to understand how the whole system works instead of just one part of it. Believe it or not, this vision is on the verge of becoming a reality but we aren't quite there yet. In order for the hydrologic modeling community to achieve this vision and work together in this way it isn't necessary for us to drastically change the way we do things. However, we do need to agree on some minimum set of standards and these have mostly to do with providing standardized metadata decriptions of our models and our data sets. We already have great software tools for accommodating differences between models that allow them to be coupled and work together. These include tools for spatial regridding, time interpolation, unit conversion, format conversion and even computer language interoperability. But in order to write software that automatically invokes these tools when needed, we need standardized machine and human-readable metadata descriptions of our models and data sets. The purpose of this talk is to review some of the technical problems that have already been solved, including the tools mentioned above, and then explain why we need standardized metadata in order to achieve the vision of seamless model integration. A new standard called the CSDMS Standard Names that is being developed for the Community Surface Dynamics Modeling System (CSDMS) project to address this problem will

  16. Advancing Collaboration through Hydrologic Data and Model Sharing (United States)

    Tarboton, D. G.; Idaszak, R.; Horsburgh, J. S.; Ames, D. P.; Goodall, J. L.; Band, L. E.; Merwade, V.; Couch, A.; Hooper, R. P.; Maidment, D. R.; Dash, P. K.; Stealey, M.; Yi, H.; Gan, T.; Castronova, A. M.; Miles, B.; Li, Z.; Morsy, M. M.


    HydroShare is an online, collaborative system for open sharing of hydrologic data, analytical tools, and models. It supports the sharing of and collaboration around "resources" which are defined primarily by standardized metadata, content data models for each resource type, and an overarching resource data model based on the Open Archives Initiative's Object Reuse and Exchange (OAI-ORE) standard and a hierarchical file packaging system called "BagIt". HydroShare expands the data sharing capability of the CUAHSI Hydrologic Information System by broadening the classes of data accommodated to include geospatial and multidimensional space-time datasets commonly used in hydrology. HydroShare also includes new capability for sharing models, model components, and analytical tools and will take advantage of emerging social media functionality to enhance information about and collaboration around hydrologic data and models. It also supports web services and server/cloud based computation operating on resources for the execution of hydrologic models and analysis and visualization of hydrologic data. HydroShare uses iRODS as a network file system for underlying storage of datasets and models. Collaboration is enabled by casting datasets and models as "social objects". Social functions include both private and public sharing, formation of collaborative groups of users, and value-added annotation of shared datasets and models. The HydroShare web interface and social media functions were developed using the Django web application framework coupled to iRODS. Data visualization and analysis is supported through the Tethys Platform web GIS software stack. Links to external systems are supported by RESTful web service interfaces to HydroShare's content. This presentation will introduce the HydroShare functionality developed to date and describe ongoing development of functionality to support collaboration and integration of data and models.

  17. Value of medium range weather forecasts in the improvement of seasonal hydrologic prediction skill

    Directory of Open Access Journals (Sweden)

    S. Shukla


    Full Text Available We investigated the contribution of medium range weather forecasts with lead times of up to 14 days to seasonal hydrologic prediction skill over the conterminous United States (CONUS. Three different Ensemble Streamflow Prediction (ESP based experiments were performed for the period 1980–2003 using the Variable Infiltration Capacity (VIC hydrology model to generate forecasts of monthly runoff and soil moisture (SM at lead-1 (first month of the forecast period to lead-3. The first experiment (ESP used a resampling from the retrospective period 1980–2003 and represented full climatological uncertainty for the entire forecast period. In the second and third experiments, the first 14 days of each ESP ensemble member were replaced by either observations (perfect 14-day forecast or by a deterministic 14-day weather forecast. We used Spearman rank correlations of forecasts and observations as the forecast skill score. We estimated the potential and actual improvement in baseline skill as the difference between the skill of experiments 2 and 3 relative to ESP, respectively. We found that useful runoff and SM forecast skill at lead-1 to -3 months can be obtained by exploiting medium range weather forecast skill in conjunction with the skill derived by the knowledge of initial hydrologic conditions. Potential improvement in baseline skill by using medium range weather forecasts for runoff [SM] forecasts generally varies from 0 to 0.8 [0 to 0.5] as measured by differences in correlations, with actual improvement generally from 0 to 0.8 of the potential improvement. With some exceptions, most of the improvement in runoff is for lead-1 forecasts, although some improvement in SM was achieved at lead-2.

  18. Hydrological Evaluation of Lake Chad Basin Using Space Borne and Hydrological Model Observations

    Directory of Open Access Journals (Sweden)

    Willibroad Gabila Buma


    Full Text Available Sustainable water resource management requires the assessment of hydrological changes in response to climate fluctuations and anthropogenic activities in any given area. A quantitative estimation of water balance entities is important to understand the variations within a basin. Water resources in remote areas with little infrastructure and technological knowhow suffer from poor documentation, rendering water management difficult and unreliable. This study analyzes the changes in the hydrological behavior of the Lake Chad basin with extreme climatic and environmental conditions that hinder the collection of field observations. Total water storage (TWS from the Gravity Recovery and Climate Experiment (GRACE, lake level variations from satellite altimetry, and water fluxes and soil moisture from Global Land Data Assimilation System (GLDAS were used to study the spatiotemporal variability of the hydrological parameters of the Lake Chad basin. The estimated TWS varies in a similar pattern as the lake water level. TWS in the basin area is governed by the lake’s surface water. The subsurface water volume changes were derived by combining the altimetric lake volume with the TWS over the drainage basin. The results were compared with groundwater outputs from WaterGAP Global Hydrology Model (WGHM, with both showing a somewhat similar pattern. These results could provide an insight to the availability of water resources in the Lake Chad basin for current and future management purposes.

  19. Incorporating modelled subglacial hydrology into inversions for basal drag

    Directory of Open Access Journals (Sweden)

    C. P. Koziol


    Full Text Available A key challenge in modelling coupled ice-flow–subglacial hydrology is initializing the state and parameters of the system. We address this problem by presenting a workflow for initializing these values at the start of a summer melt season. The workflow depends on running a subglacial hydrology model for the winter season, when the system is not forced by meltwater inputs, and ice velocities can be assumed constant. Key parameters of the winter run of the subglacial hydrology model are determined from an initial inversion for basal drag using a linear sliding law. The state of the subglacial hydrology model at the end of winter is incorporated into an inversion of basal drag using a non-linear sliding law which is a function of water pressure. We demonstrate this procedure in the Russell Glacier area and compare the output of the linear sliding law with two non-linear sliding laws. Additionally, we compare the modelled winter hydrological state to radar observations and find that it is in line with summer rather than winter observations.

  20. Accounting for the uncertainties in radar-raingauge rainfall estimation and the parametric uncertainties of the hydrological model in the prediction of flash floods in the Cévennes-Vivarais region, France (United States)

    Navas, Rafael; Delrieu, Guy


    The Cévennes-Vivarais is a Mediterranean medium-elevation mountainous region of about 32000 km2 located in the south-east of France, prone to heavy precipitation events and subsequent flash floods and floods occurring mainly during the autumn season. Due to this vulnerability, it is a well instrumented region in terms of rainfall (4 weather radars of the French ARAMIS radar network, 250 hourly raingauges) and river discharge (45 stations) observations. A high-resolution (1 km2, 1 hour) radar-raingauge rainfall re-analysis has been established for the period 2007-2014 by using the kriging with external drift (KED) technique (Delrieu et al. 2014; Boudevillain et al. 2016). In the present communication, we present first a geostatistical method aimed at generating radar-raingauge rainfall ensembles based on the KED error standard deviations and the space-time structure of the residuals to the drift. The method is implemented over the four main watersheds of the Cévennes-Vivarais region by considering a spatial segmentation in hydrological meshes of variable sizes from 10 to 300 km2. A distributed hydrological model based on the SCS curve number and unit hydrograph concepts is then implemented in continuous mode for these watersheds. A sensitivity analysis allows us to identify the most sensitive parameters and to generate ensembles of "acceptable" hydrological simulations by using 16 discharge time series. Several results of this simulation framework will be highlighted: (1) the overall quality of the hydrological simulations as a function of the gauged watershed characteristics, (2) the transferability of the acceptable parameter sets from one year to another, (3) the effect of the space and time resolution of rainfall estimations on the hydrological simulations for gauged watersheds, (4) the respective impact of rainfall and model parametric uncertainties over a range of spatial and temporal scales for ungauged watersheds. References: Delrieu, G., A. Wijbrans, B

  1. Nitrogen Risk Assessment Model for Scotland: II. Hydrological transport and model testing

    Directory of Open Access Journals (Sweden)

    S. M. Dunn


    Full Text Available The amount and concentration of N in catchment runoff is strongly controlled by a number of hydrological influences, such as leaching rates and the rate of transport of N from the land to surface water bodies. This paper describes how the principal hydrological controls at a catchment scale have been represented within the Nitrogen Risk Assessment Model for Scotland (NIRAMS; it demonstrates their influence through application of the model to eight Scottish catchments, contrasting in terms of their land use, climate and topography. Calculation of N leaching rates, described in the preceding paper (Dunn et al., 2004, is based on soil water content determined by application of a weekly water balance model. This model uses national scale datasets and has been developed and applied to the whole of Scotland using five years of historical meteorological data. A catchment scale transport model, constructed from a 50m digital elevation model, routes flows of N through the sub-surface and groundwater to the stream system. The results of the simulations carried out for eight different catchments demonstrate that the NIRAMS model is capable of predicting time-series of weekly stream flows and N concentrations, to an acceptable degree of accuracy. The model provides an appropriate framework for risk assessment applications requiring predictions in ungauged catchments and at a national scale. Analysis of the model behaviour shows that streamwater N concentrations are controlled both by the rate of supply of N from leaching as well as the rate of transport of N from the land to the water. Keywords: nitrogen, diffuse pollution, hydrology, model, transport, catchment

  2. Modelling hydrological processes at different scales across Russian permafrost domain (United States)

    Makarieva, Olga; Lebedeva, Lyudmila; Nesterova, Natalia; Vinogradova, Tatyana


    The project aims to study the interactions between permafrost and runoff generation processes across Russian Arctic domain based on hydrological modelling. The uniqueness of the approach is a unified modelling framework which allows for coupled simulations of upper permafrost dynamics and streamflow generation at different scales (from soil column to large watersheds). The base of the project is hydrological model Hydrograph (Vinogradov et al. 2011, Semenova et al. 2013, 2015; Lebedeva et al., 2015). The model algorithms combine physically-based and conceptual approaches for the description of land hydrological cycle processes, which allows for maintaining a balance between the complexity of model design and the use of limited input information. The method for modeling heat dynamics in soil is integrated into the model. Main parameters of the model are the physical properties of landscapes that may be measured (observed) in nature and are classified according to the types of soil, vegetation and other characteristics. A set of parameters specified in the studied catchments (basins analog) can be transferred to ungauged basins with similar types of the underlying surface without calibration. The results of modelling from small research watersheds to large poorly gauged river basins in different climate and landscape settings of Russian Arctic (within the Yenisey, Lena, Yana, Indigirka, Kolyma rivers basins) will be presented. Based on gained experience methodological aspects of hydrological modelling approaches in permafrost environment will be discussed. The study is partially supported by Russian Foundation for Basic Research, projects 16-35-50151 and 17-05-01138.

  3. The added value of remote sensing products in constraining hydrological models (United States)

    Nijzink, Remko C.; Almeida, Susana; Pechlivanidis, Ilias; Capell, René; Gustafsson, David; Arheimer, Berit; Freer, Jim; Han, Dawei; Wagener, Thorsten; Sleziak, Patrik; Parajka, Juraj; Savenije, Hubert; Hrachowitz, Markus


    The calibration of a hydrological model still depends on the availability of streamflow data, even though more additional sources of information (i.e. remote sensed data products) have become more widely available. In this research, the model parameters of four different conceptual hydrological models (HYPE, HYMOD, TUW, FLEX) were constrained with remotely sensed products. The models were applied over 27 catchments across Europe to cover a wide range of climates, vegetation and landscapes. The fluxes and states of the models were correlated with the relevant products (e.g. MOD10A snow with modelled snow states), after which new a-posteriori parameter distributions were determined based on a weighting procedure using conditional probabilities. Briefly, each parameter was weighted with the coefficient of determination of the relevant regression between modelled states/fluxes and products. In this way, final feasible parameter sets were derived without the use of discharge time series. Initial results show that improvements in model performance, with regard to streamflow simulations, are obtained when the models are constrained with a set of remotely sensed products simultaneously. In addition, we present a more extensive analysis to assess a model's ability to reproduce a set of hydrological signatures, such as rising limb density or peak distribution. Eventually, this research will enhance our understanding and recommendations in the use of remotely sensed products for constraining conceptual hydrological modelling and improving predictive capability, especially for data sparse regions.

  4. How to handle spatial heterogeneity in hydrological models. (United States)

    Loritz, Ralf; Neuper, Malte; Gupta, Hoshin; Zehe, Erwin


    The amount of data we observe in our environmental systems is larger than ever. This leads to a new kind of problem where hydrological modelers can have access to large datasets with various quantitative and qualitative observations but are uncertain about the information content with respect to the hydrological functioning of a landscape. For example digital elevation models obviously contain plenty of information about the topography of a landscape; however the question of relevance for Hydrology is how much of this information is important for the hydrological functioning of a landscape. This kind of question is not limited to topography and we can ask similar questions when handling distributed rainfall data or geophysical images. In this study we would like to show how one can separate dominant patterns in the landscape from idiosyncratic system details. We use a 2D numerical hillslope model in combination with an extensive research data set to test a variety of different model setups that are built upon different landscape characteristics and run by different rainfalls measurements. With the help of information theory based measures we can identify and learn how much heterogeneity is really necessary for successful hydrological simulations and how much of it we can neglect.

  5. Calibration of a Hydrological Model using Ensemble Satellite Rainfall Inputs (United States)

    Skinner, Christopher; Bellerby, Timothy


    A combination of satellite rainfall estimates (SRFE) and hydrological models can provide useful information for many remote areas of the planet. However, each component contains its own uncertainties and these uncertainties will interact when SRFE are used as inputs for hydrological models. For any assessment of a coupled system such as this there is a requirement for a comprehensive analysis of all sources of uncertainty, with full consideration of both facets. SRFE have been shown to be useful in many areas that lack the infrastructure to make timely and accurate estimations of rainfall from the ground. Sub-Saharan Africa is typical of this, where a paucity of rain recording radar and sparse gauging networks combine with a highly variable climate and a reliance on rain-fed agriculture. When operating at higher spatial and temporal resolutions, SRFE contain large uncertainties which will propagate through a hydrological model if used as a driving input. This study used a sequential method to produce ensemble SRFE based around the full conditional distribution of recorded rainfall from a sparse, historic raingauge network. The TAMSIM method (introduced by Teo, 2006) was used to produce 200 unique yet equiprobable SRFE, each used as a driver to a downstream hydrological model. Traditional hydrological modelling uses the adjustment of variable parameters within the model to reduce the error between a recorded record of discharge and the modelled one, and many automatic procedures have been produced to refine this calibration process. When SRFE have been used as a driver, little consideration has been paid to this process and often a calibration using the raingauge data has been used, without any consideration to the resulting uncertainty within the hydrological model and its calibration. A similar issue arises when ensemble inputs are used to a hydrological model that has been calibrated using a deterministic estimate of rainfall. This study has shown that such

  6. Understanding uncertainty in process-based hydrological models (United States)

    Clark, M. P.; Kavetski, D.; Slater, A. G.; Newman, A. J.; Marks, D. G.; Landry, C.; Lundquist, J. D.; Rupp, D. E.; Nijssen, B.


    Building an environmental model requires making a series of decisions regarding the appropriate representation of natural processes. While some of these decisions can already be based on well-established physical understanding, gaps in our current understanding of environmental dynamics, combined with incomplete knowledge of properties and boundary conditions of most environmental systems, make many important modeling decisions far more ambiguous. There is consequently little agreement regarding what a 'correct' model structure is, especially at relatively larger spatial scales such as catchments and beyond. In current practice, faced with such a range of decisions, different modelers will generally make different modeling decisions, often on an ad hoc basis, based on their balancing of process understanding, the data available to evaluate the model, the purpose of the modeling exercise, and their familiarity with or investment in an existing model infrastructure. This presentation describes development and application of multiple-hypothesis models to evaluate process-based hydrologic models. Our numerical model uses robust solutions of the hydrology and thermodynamic governing equations as the structural core, and incorporates multiple options to represent the impact of different modeling decisions, including multiple options for model parameterizations (e.g., below-canopy wind speed, thermal conductivity, storage and transmission of liquid water through soil, etc.), as well as multiple options for model architecture, that is, the coupling and organization of different model components (e.g., representations of sub-grid variability and hydrologic connectivity, coupling with groundwater, etc.). Application of this modeling framework across a collection of different research basins demonstrates that differences among model parameterizations are often overwhelmed by differences among equally-plausible model parameter sets, while differences in model architecture lead

  7. Use of remote sensing data in distributed hydrological models: Applications in the Senegal river basin

    DEFF Research Database (Denmark)

    Sandholt, Inge; Andersen, Jens; Dybkjær, Gorm Ibsen


    Earth observation, remote sensing, hydrology, distributed hydrological modelling, West Africa, Senegal river basin, land cover, soil moisture, NOAA AVHRR, SPOT, Mike-she......Earth observation, remote sensing, hydrology, distributed hydrological modelling, West Africa, Senegal river basin, land cover, soil moisture, NOAA AVHRR, SPOT, Mike-she...

  8. Hydrological Modelling of Small Scale Processes in a Wetland Habitat

    DEFF Research Database (Denmark)

    Johansen, Ole; Jensen, Jacob Birk; Pedersen, Morten Lauge


    Numerical modelling of the hydrology in a Danish rich fen area has been conducted. By collecting various data in the field the model has been successfully calibrated and the flow paths as well as the groundwater discharge distribution have been simulated in details. The results of this work have ...

  9. Hydrologic and water quality terminology as applied to modeling (United States)

    A survey of literature and examination in particular of terminology use in a previous special collection of modeling calibration and validation papers has been conducted to arrive at a list of consistent terminology recommended for writing about hydrologic and water quality model calibration and val...

  10. Performance measures and criteria for hydrologic and water quality models (United States)

    Performance measures and criteria are essential for model calibration and validation. This presentation will include a summary of one of the papers that will be included in the 2014 Hydrologic and Water Quality Model Calibration & Validation Guidelines Special Collection of the ASABE Transactions. T...

  11. Impact of vegetation dynamics on hydrological processes in a semi-arid basin by using a land surface-hydrology coupled model

    Energy Technology Data Exchange (ETDEWEB)

    Jiao, Yang; Lei, Huimin; Yang, Dawen; Huang, Maoyi; Liu, Dengfeng; Yuan, Xing


    Land surface models (LSMs) are widely used to understand the interactions between hydrological processes and vegetation dynamics, which is important for the attribution and prediction of regional hydrological variations. However, most LSMs have large uncertainties in their representations of ecohydrological processes due to deficiencies in hydrological parameterizations. In this study, the Community Land Model version 4 (CLM4) LSM was modified with an advanced runoff generation and flow routing scheme, resulting in a new land surface-hydrology coupled model, CLM-GBHM. Both models were implemented in the Wudinghe River Basin (WRB), which is a semi-arid basin located in the middle reaches of the Yellow River, China. Compared with CLM, CLM-GBHM increased the Nash Sutcliffe efficiency for daily river discharge simulation (1965–1969) from 0.03 to 0.23 and reduced the relative bias in water table depth simulations (2010–2012) from 32.4% to 13.4%. The CLM-GBHM simulations with static, remotely sensed and model-predicted vegetation conditions showed that the vegetation in the WRB began to recover in the 2000s due to the Grain for Green Program but had not reached the same level of vegetation cover as regions in natural eco-hydrological equilibrium. Compared with a simulation using remotely sensed vegetation cover, the simulation with a dynamic vegetation model that considers only climate-induced change showed a 10.3% increase in evapotranspiration, a 47.8% decrease in runoff, and a 62.7% and 71.3% deceleration in changing trend of the outlet river discharge before and after the year 2000, respectively. This result suggests that both natural and anthropogenic factors should be incorporated in dynamic vegetation models to better simulate the eco-hydrological cycle.

  12. Hydrologic and Water Quality Model Development Using Simulink

    Directory of Open Access Journals (Sweden)

    James D. Bowen


    Full Text Available A stormwater runoff model based on the Soil Conservation Service (SCS method and a finite-volume based water quality model have been developed to investigate the use of Simulink for use in teaching and research. Simulink, a MATLAB extension, is a graphically based model development environment for system modeling and simulation. Widely used for mechanical and electrical systems, Simulink has had less use for modeling of hydrologic systems. The watershed model is being considered for use in teaching graduate-level courses in hydrology and/or stormwater modeling. Simulink’s block (data process and arrow (data transfer object model, the copy and paste user interface, the large number of existing blocks, and the absence of computer code allows students to become model developers almost immediately. The visual depiction of systems, their component subsystems, and the flow of data through the systems are ideal attributes for hands-on teaching of hydrologic and mass balance processes to today’s computer-savvy visual learners. Model development with Simulink for research purposes is also investigated. A finite volume, multi-layer pond model using the water quality kinetics present in CE-QUAL-W2 has been developed using Simulink. The model is one of the first uses of Simulink for modeling eutrophication dynamics in stratified natural systems. The model structure and a test case are presented. One use of the model for teaching a graduate-level water quality modeling class is also described.

  13. Improving flash flood forecasting with distributed hydrological model by parameter optimization (United States)

    Chen, Yangbo


    In China, flash food is usually regarded as flood occured in small and medium sized watersheds with drainage area less than 200 km2, and is mainly induced by heavy rains, and occurs in where hydrological observation is lacked. Flash flood is widely observed in China, and is the flood causing the most casualties nowadays in China. Due to hydrological data scarcity, lumped hydrological model is difficult to be employed for flash flood forecasting which requires lots of observed hydrological data to calibrate model parameters. Physically based distributed hydrological model discrete the terrain of the whole watershed into a number of grid cells at fine resolution, assimilate different terrain data and precipitation to different cells, and derive model parameteris from the terrain properties, thus having the potential to be used in flash flood forecasting and improving flash flood prediction capability. In this study, the Liuxihe Model, a physically based distributed hydrological model mainly proposed for watershed flood forecasting is employed to simulate flash floods in the Ganzhou area in southeast China, and models have been set up in 5 watersheds. Model parameters have been derived from the terrain properties including the DEM, the soil type and land use type, but the result shows that the flood simulation uncertainty is high, which may be caused by parameter uncertainty, and some kind of uncertainty control is needed before the model could be used in real-time flash flood forecastin. Considering currently many Chinese small and medium sized watersheds has set up hydrological observation network, and a few flood events could be collected, it may be used for model parameter optimization. For this reason, an automatic model parameter optimization algorithm using Particle Swam Optimization(PSO) is developed to optimize the model parameters, and it has been found that model parameters optimized even only with one observed flood events could largely reduce the flood

  14. Eco-hydrologic model cascades: Simulating land use and climate change impacts on hydrology, hydraulics and habitats for fish and macroinvertebrates. (United States)

    Guse, Björn; Kail, Jochem; Radinger, Johannes; Schröder, Maria; Kiesel, Jens; Hering, Daniel; Wolter, Christian; Fohrer, Nicola


    Climate and land use changes affect the hydro- and biosphere at different spatial scales. These changes alter hydrological processes at the catchment scale, which impact hydrodynamics and habitat conditions for biota at the river reach scale. In order to investigate the impact of large-scale changes on biota, a cascade of models at different scales is required. Using scenario simulations, the impact of climate and land use change can be compared along the model cascade. Such a cascade of consecutively coupled models was applied in this study. Discharge and water quality are predicted with a hydrological model at the catchment scale. The hydraulic flow conditions are predicted by hydrodynamic models. The habitat suitability under these hydraulic and water quality conditions is assessed based on habitat models for fish and macroinvertebrates. This modelling cascade was applied to predict and compare the impacts of climate- and land use changes at different scales to finally assess their effects on fish and macroinvertebrates. Model simulations revealed that magnitude and direction of change differed along the modelling cascade. Whilst the hydrological model predicted a relevant decrease of discharge due to climate change, the hydraulic conditions changed less. Generally, the habitat suitability for fish decreased but this was strongly species-specific and suitability even increased for some species. In contrast to climate change, the effect of land use change on discharge was negligible. However, land use change had a stronger impact on the modelled nitrate concentrations affecting the abundances of macroinvertebrates. The scenario simulations for the two organism groups illustrated that direction and intensity of changes in habitat suitability are highly species-dependent. Thus, a joined model analysis of different organism groups combined with the results of hydrological and hydrodynamic models is recommended to assess the impact of climate and land use changes on

  15. How far can we go in distributed hydrological modelling?

    Directory of Open Access Journals (Sweden)

    K. Beven*


    Full Text Available This paper considers distributed hydrological models in hydrology as an expression of a pragmatic realism. Some of the problems of distributed modelling are discussed including the problem of nonlinearity, the problem of scale, the problem of equifinality, the problem of uniqueness and the problem of uncertainty. A structure for the application of distributed modelling is suggested based on an uncertain or fuzzy landscape space to model space mapping. This is suggested as the basis for an Alternative Blueprint for distributed modelling in the form of an application methodology. This Alternative Blueprint is scientific in that it allows for the formulation of testable hypotheses. It focuses attention on the prior evaluation of models in terms of physical realism and on the value of data in model rejection. Finally, some unresolved questions that distributed modelling must address in the future are outlined, together with a vision for distributed modelling as a means of learning about places.

  16. Use of hydrologic and hydrodynamic modeling for ecosystem restoration (United States)

    Obeysekera, J.; Kuebler, L.; Ahmed, S.; Chang, M.-L.; Engel, V.; Langevin, C.; Swain, E.; Wan, Y.


    Planning and implementation of unprecedented projects for restoring the greater Everglades ecosystem are underway and the hydrologic and hydrodynamic modeling of restoration alternatives has become essential for success of restoration efforts. In view of the complex nature of the South Florida water resources system, regional-scale (system-wide) hydrologic models have been developed and used extensively for the development of the Comprehensive Everglades Restoration Plan. In addition, numerous subregional-scale hydrologic and hydrodynamic models have been developed and are being used for evaluating project-scale water management plans associated with urban, agricultural, and inland costal ecosystems. The authors provide a comprehensive summary of models of all scales, as well as the next generation models under development to meet the future needs of ecosystem restoration efforts in South Florida. The multiagency efforts to develop and apply models have allowed the agencies to understand the complex hydrologic interactions, quantify appropriate performance measures, and use new technologies in simulation algorithms, software development, and GIS/database techniques to meet the future modeling needs of the ecosystem restoration programs. Copyright ?? 2011 Taylor & Francis Group, LLC.

  17. Brokering as a framework for hydrological model repeatability (United States)

    Fuka, Daniel; Collick, Amy; MacAlister, Charlotte; Braeckel, Aaron; Wright, Dawn; Jodha Khalsa, Siri; Boldrini, Enrico; Easton, Zachary


    Data brokering aims to provide those in the the sciences with quick and repeatable access to data that represents physical, biological, and chemical characteristics; specifically to accelerate scientific discovery. Environmental models are useful tools to understand the behavior of hydrological systems. Unfortunately, parameterization of these hydrological models requires many different data, from different sources, and from different disciplines (e.g., atmospheric, geoscience, ecology). In basin scale hydrological modeling, the traditional procedure for model initialization starts with obtaining elevation models, land-use characterizations, soils maps, and weather data. It is often the researcher's past experience with these datasets that determines which datasets will be used in a study, and often newer, or more suitable data products will exist. An added complexity is that various science communities have differing data formats, storage protocols, and manipulation methods, which makes use by a non native user exceedingly difficult and time consuming. We demonstrate data brokering as a means to address several of these challenges. We present two test case scenarios in which researchers attempt to reproduce hydrological model results using 1) general internet based data gathering techniques, and 2) a scientific data brokering interface. We show that data brokering can increase the efficiency with which data are obtained, models are initialized, and results are analyzed. As an added benefit, it appears brokering can significantly increase the repeatability of a given study.

  18. Multi-objective Optimization Based Calibration of Hydrologic Model and Ensemble Hydrologic Forecast for Java Island, Indonesia (United States)

    Yanto, M.; Kasprzyk, J. R.; Rajagopalan, B.; Livneh, B.


    This study explores the benefits of multi-objective optimization of Variable Infiltration Capacity (VIC) model for five watersheds in Java, the most populous island in Indonesia. Six objective functions: Nash Sutcliffe Efficiency (NSE), percent bias (PBIAS), logarithmic function of root mean square error (Log-RMSE), predictive efficiency (Pe), percent errors in peak (PEP) and slope of flow duration curve error (SFDCE) were selected as evaluation metrics. These metrics were optimized by tuning four VIC model parameters: infiltration shape parameter (b), fraction of maximum baseflow where nonlinear baseflow begin (Ds), thickness of soil layer 2 (thick2) and thickness of soil layer 3 (thick3). We employed Borg Multiobjective Evolutionary Algorithm (Borg MOEA), an automatic simulation-optimization algorithm, to search for non-dominated solutions. We identified the redundancy between NSE and Log-RMSE, Pe, and PEP through visual inspection of their sensitivity to parameters b and Ds of VIC model and to baseflow index (BFI). Accordingly, we proposed NSE, PBIAS and SFDCE as critical objective functions to represent hydrologic processes in tropical region of Java, Indonesia. Using these three objective functions, we culled the objective functions based on at least - NSE > 0.75, PBIAS time window when the seasonal climate forecasts and observed streamflow records overlaps. We measured the skill of this seasonal forecast by computing the rank probability skill score (RPSS) of seasonal total flows and extremes at three different thresholds, for the dry and wet seasons. We showed that the RPSS of seasonal flows and the extremes are very good for both seasons. This study, for the first time, demonstrates the utility of the multiobjective based calibration of hydrologic model in tropical regions and its applications in generating skillful seasonal ensemble hydrologic forecasts which are important for short and long term water resources planning and management.

  19. Flood Modelling of Banjir Kanal Barat (Integration of Hydrology Model and GIS

    Directory of Open Access Journals (Sweden)

    Muhammad Aris Marfai


    Full Text Available Hydrological modelling has an advantage on river flood study. Hydrological factors can be easily determined and calculated using hydrological model. HEC-RAS (Hydrological Engineering Centre-River Analysis System software is well known as hydrological modelling software for flood simulation and encroachment analysis of the floodplain area. For spatial performance and analysis of flood, the integration of the Geographic Information Systems (GIS and hydrological model is needed. The aims of this research are 1 to perform a flood encroachment using HEC-RAS software, and 2 to generate a flood hazard map. The methodology for this research omprise of 1 generating geometric data as a requirement of the data input on HEC-RAS hydrological model, 2 Hydrological data inputting, 3 generating of the flood encroachment analysis, and 4 transformation of flood encroachment into flood hazard map. The spatial pattern of the flood hazard is illustrated in a map. The result shows that hydrological model as integration with GIS can be used for flood hazard map generation. This method has advantages on the calculation of the hydrological factors of flood and spatial performance of the flood hazard map. For further analysis, the landuse map can be used on the overlay operation with the flood hazard map in order to obtain the impact of the flood on the landuse.

  20. Tuning hydrological models for ecological modeling - improving simulations of low flows critical to stream ecology

    DEFF Research Database (Denmark)

    Olsen, Martin; Troldborg, Lars; Boegh, Eva


    The consequences of using simulated discharge from a conventional hydrological model as input in stream physical habitat modelling was investigated using output from the Danish national hydrological model and a physical habitat model of three small streams. It was found that low flow simulation e...

  1. Elements of a flexible approach for conceptual hydrological modeling : 1. Motivation and theoretical development

    NARCIS (Netherlands)

    Fenicia, F.; Kavetski, D.; Savenije, H.H.G.


    This paper introduces a flexible framework for conceptual hydrological modeling, with two related objectives: (1) generalize and systematize the currently fragmented field of conceptual models and (2) provide a robust platform for understanding and modeling hydrological systems. In contrast to

  2. Modelling the effect of land use change on hydrological model ...

    African Journals Online (AJOL)


    Apr 2, 2017 ... Keywords: land use/cover change; parameter calibration; linearized; upper Huaihe River Basin ...... programming for modelling coastal algal blooms. ... prediction of reference evapotranspiration with climate change in.

  3. Development and evaluation of a watershed-scale hybrid hydrologic model


    Cho, Younghyun


    A watershed-scale hybrid hydrologic model (Distributed-Clark), which is a lumped conceptual and distributed feature model, was developed to predict spatially distributed short- and long-term rainfall runoff generation and routing using relatively simple methodologies and state-of-the-art spatial data in a GIS environment. In Distributed-Clark, spatially distributed excess rainfall estimated with the SCS curve number method and a GIS-based set of separated unit hydrographs (spatially distribut...


    African Journals Online (AJOL)


    Jul 2, 2012 ... Discussions on some of the design techniques based on. MPC and their .... is then calculated using the receding horizon concept, since the prediction ...... of interior point methods to model predictive control,. Journal of ...

  5. Legacy model integration for enhancing hydrologic interdisciplinary research (United States)

    Dozier, A.; Arabi, M.; David, O.


    Many challenges are introduced to interdisciplinary research in and around the hydrologic science community due to advances in computing technology and modeling capabilities in different programming languages, across different platforms and frameworks by researchers in a variety of fields with a variety of experience in computer programming. Many new hydrologic models as well as optimization, parameter estimation, and uncertainty characterization techniques are developed in scripting languages such as Matlab, R, Python, or in newer languages such as Java and the .Net languages, whereas many legacy models have been written in FORTRAN and C, which complicates inter-model communication for two-way feedbacks. However, most hydrologic researchers and industry personnel have little knowledge of the computing technologies that are available to address the model integration process. Therefore, the goal of this study is to address these new challenges by utilizing a novel approach based on a publish-subscribe-type system to enhance modeling capabilities of legacy socio-economic, hydrologic, and ecologic software. Enhancements include massive parallelization of executions and access to legacy model variables at any point during the simulation process by another program without having to compile all the models together into an inseparable 'super-model'. Thus, this study provides two-way feedback mechanisms between multiple different process models that can be written in various programming languages and can run on different machines and operating systems. Additionally, a level of abstraction is given to the model integration process that allows researchers and other technical personnel to perform more detailed and interactive modeling, visualization, optimization, calibration, and uncertainty analysis without requiring deep understanding of inter-process communication. To be compatible, a program must be written in a programming language with bindings to a common

  6. A surface hydrology model for regional vector borne disease models (United States)

    Tompkins, Adrian; Asare, Ernest; Bomblies, Arne; Amekudzi, Leonard


    Small, sun-lit temporary pools that form during the rainy season are important breeding sites for many key mosquito vectors responsible for the transmission of malaria and other diseases. The representation of this surface hydrology in mathematical disease models is challenging, due to their small-scale, dependence on the terrain and the difficulty of setting soil parameters. Here we introduce a model that represents the temporal evolution of the aggregate statistics of breeding sites in a single pond fractional coverage parameter. The model is based on a simple, geometrical assumption concerning the terrain, and accounts for the processes of surface runoff, pond overflow, infiltration and evaporation. Soil moisture, soil properties and large-scale terrain slope are accounted for using a calibration parameter that sets the equivalent catchment fraction. The model is calibrated and then evaluated using in situ pond measurements in Ghana and ultra-high (10m) resolution explicit simulations for a village in Niger. Despite the model's simplicity, it is shown to reproduce the variability and mean of the pond aggregate water coverage well for both locations and validation techniques. Example malaria simulations for Uganda will be shown using this new scheme with a generic calibration setting, evaluated using district malaria case data. Possible methods for implementing regional calibration will be briefly discussed.

  7. Description of the National Hydrologic Model for use with the Precipitation-Runoff Modeling System (PRMS) (United States)

    Regan, R. Steven; Markstrom, Steven L.; Hay, Lauren E.; Viger, Roland J.; Norton, Parker A.; Driscoll, Jessica M.; LaFontaine, Jacob H.


    This report documents several components of the U.S. Geological Survey National Hydrologic Model of the conterminous United States for use with the Precipitation-Runoff Modeling System (PRMS). It provides descriptions of the (1) National Hydrologic Model, (2) Geospatial Fabric for National Hydrologic Modeling, (3) PRMS hydrologic simulation code, (4) parameters and estimation methods used to compute spatially and temporally distributed default values as required by PRMS, (5) National Hydrologic Model Parameter Database, and (6) model extraction tool named Bandit. The National Hydrologic Model Parameter Database contains values for all PRMS parameters used in the National Hydrologic Model. The methods and national datasets used to estimate all the PRMS parameters are described. Some parameter values are derived from characteristics of topography, land cover, soils, geology, and hydrography using traditional Geographic Information System methods. Other parameters are set to long-established default values and computation of initial values. Additionally, methods (statistical, sensitivity, calibration, and algebraic) were developed to compute parameter values on the basis of a variety of nationally-consistent datasets. Values in the National Hydrologic Model Parameter Database can periodically be updated on the basis of new parameter estimation methods and as additional national datasets become available. A companion ScienceBase resource provides a set of static parameter values as well as images of spatially-distributed parameters associated with PRMS states and fluxes for each Hydrologic Response Unit across the conterminuous United States.

  8. On the use of three hydrological models as hypotheses to investigate the behaviour of a small Mediterranean catchment (United States)

    Ruiz Pérez, Guiomar; Latron, Jérôme; Llorens, Pilar; Gallart, Francesc; Francés, Félix


    Selecting an adequate hydrological model is the first step to carry out a rainfall-runoff modelling exercise. A hydrological model is a hypothesis of catchment functioning, encompassing a description of dominant hydrological processes and predicting how these processes interact to produce the catchment's response to external forcing. Current research lines emphasize the importance of multiple working hypotheses for hydrological modelling instead of only using a single model. In line with this philosophy, here different hypotheses were considered and analysed to simulate the nonlinear response of a small Mediterranean catchment and to progress in the analysis of its hydrological behaviour. In particular, three hydrological models were considered representing different potential hypotheses: two lumped models called LU3 and LU4, and one distributed model called TETIS. To determine how well each specific model performed and to assess whether a model was more adequate than another, we raised three complementary tests: one based on the analysis of residual errors series, another based on a sensitivity analysis and the last one based on using multiple evaluation criteria associated to the concept of Pareto frontier. This modelling approach, based on multiple working hypotheses, helped to improve our perceptual model of the catchment behaviour and, furthermore, could be used as a guidance to improve the performance of other environmental models.

  9. Modeling the Hydrologic Processes of a Permeable Pavement System (United States)

    A permeable pavement system can capture stormwater to reduce runoff volume and flow rate, improve onsite groundwater recharge, and enhance pollutant controls within the site. A new unit process model for evaluating the hydrologic performance of a permeable pavement system has be...

  10. A simple, dynamic, hydrological model of a mesotidal salt marsh (United States)

    Salt marsh hydrology presents many difficulties from a modeling standpoint: the bi-directional flows of tidal waters, variable water densities due to mixing of fresh and salt water, significant influences from vegetation, and complex stream morphologies. Because of these difficu...

  11. Uncertainty propagation in urban hydrology water quality modelling

    NARCIS (Netherlands)

    Torres Matallana, Arturo; Leopold, U.; Heuvelink, G.B.M.


    Uncertainty is often ignored in urban hydrology modelling. Engineering practice typically ignores uncertainties and uncertainty propagation. This can have large impacts, such as the wrong dimensioning of urban drainage systems and the inaccurate estimation of pollution in the environment caused

  12. GIS-Based Hydrological Modelling Using Swat: Case Study of ...

    African Journals Online (AJOL)

    Hydrological modeling tools have been increasingly used worldwide in the management of water resources at watershed level. The application of these tools have been improved in recent time through the advent of remote sensing and Geographical Information System (GIS) techniques which enhance the use of spatially ...

  13. Application of GIS-Based Spatially Distributed Hydrologic Model in ...

    African Journals Online (AJOL)

    Application of GIS-Based Spatially Distributed Hydrologic Model in Integrated Watershed Management:A Case Study of Nzoia Basin, Kenya. ... 1986 and 2000 also revealed increased peaks in resulting hydrographs as a result of increased acreage under crops and reduced forest cover for same storm characteristics.

  14. Integrated landscape/hydrologic modeling tool for semiarid watersheds (United States)

    Mariano Hernandez; Scott N. Miller


    An integrated hydrologic modeling/watershed assessment tool is being developed to aid in determining the susceptibility of semiarid landscapes to natural and human-induced changes across a range of scales. Watershed processes are by definition spatially distributed and are highly variable through time, and this approach is designed to account for their spatial and...

  15. Hydrologic and water quality modeling: spatial and temporal considerations (United States)

    Hydrologic and water quality models are used to help manage water resources by investigating the effects of climate, land use, land management, and water management on water resources. Each water-related issue is better investigated at a specific scale, which can vary spatially from point to watersh...

  16. Hydrologic and water quality models: Use, calibration, and validation (United States)

    This paper introduces a special collection of 22 research articles that present and discuss calibration and validation concepts in detail for hydrologic and water quality models by their developers and presents a broad framework for developing the American Society of Agricultural and Biological Engi...

  17. Hydrologic and water quality models: Performance measures and evaluation criteria (United States)

    Performance measures and corresponding criteria constitute an important aspect of calibration and validation of any hydrological and water quality (H/WQ) model. As new and improved methods and information are developed, it is essential that performance measures and criteria be updated. Therefore, th...

  18. Using Modeling Tools to Better Understand Permafrost Hydrology

    Directory of Open Access Journals (Sweden)

    Clément Fabre


    Full Text Available Modification of the hydrological cycle and, subsequently, of other global cycles is expected in Arctic watersheds owing to global change. Future climate scenarios imply widespread permafrost degradation caused by an increase in air temperature, and the expected effect on permafrost hydrology is immense. This study aims at analyzing, and quantifying the daily water transfer in the largest Arctic river system, the Yenisei River in central Siberia, Russia, partially underlain by permafrost. The semi-distributed SWAT (Soil and Water Assessment Tool hydrological model has been calibrated and validated at a daily time step in historical discharge simulations for the 2003–2014 period. The model parameters have been adjusted to embrace the hydrological features of permafrost. SWAT is shown capable to estimate water fluxes at a daily time step, especially during unfrozen periods, once are considered specific climatic and soils conditions adapted to a permafrost watershed. The model simulates average annual contribution to runoff of 263 millimeters per year (mm yr−1 distributed as 152 mm yr−1 (58% of surface runoff, 103 mm yr−1 (39% of lateral flow and 8 mm yr−1 (3% of return flow from the aquifer. These results are integrated on a reduced basin area downstream from large dams and are closer to observations than previous modeling exercises.

  19. Modelling of green roof hydrological performance for urban drainage applications

    DEFF Research Database (Denmark)

    Locatelli, Luca; Mark, Ole; Mikkelsen, Peter Steen


    , the model was used to evaluate the variation of the average annual runoff from green roofs as a function of the total available storage and vegetation type. The results show that even a few millimeters of storage can reduce the mean annual runoff by up to 20% when compared to a traditional roof......Green roofs are being widely implemented for stormwater management and their impact on the urban hydrological cycle can be evaluated by incorporating them into urban drainage models. This paper presents a model of green roof long term and single event hydrological performance. The model includes...... surface and subsurface storage components representing the overall retention capacity of the green roof which is continuously re-established by evapotranspiration. The runoff from the model is described through a non-linear reservoir approach. The model was calibrated and validated using measurement data...

  20. Modeling of hydrological processes in arid agricultural regions

    Directory of Open Access Journals (Sweden)

    Jiang LI,Xiaomin MAO,Shaozhong KANG,David A. BARRY


    Full Text Available Understanding of hydrological processes, including consideration of interactions between vegetation growth and water transfer in the root zone, underpins efficient use of water resources in arid-zone agriculture. Water transfers take place in the soil-plant-atmosphere continuum, and include groundwater dynamics, unsaturated zone flow, evaporation/transpiration from vegetated/bare soil and surface water, agricultural canal/surface water flow and seepage, and well pumping. Models can be categorized into three classes: (1 regional distributed hydrological models with various land uses, (2 groundwater-soil-plant-atmosphere continuum models that neglect lateral water fluxes, and (3 coupled models with groundwater flow and unsaturated zone water dynamics. This review highlights, in addition, future research challenges in modeling arid-zone agricultural systems, e.g., to effectively assimilate data from remote sensing, and to fully reflect climate change effects at various model scales.

  1. Hydrologic modelling for climate change impacts analysis of shifts in future hydrologic regimes: implications for stream temperature and salmon habitat (United States)

    Bennett, K. E.; Werner, A. T.; Schnorbus, M.; Salathé, E. P.; Nelitz, M.


    The challenges faced by climate change impact analysts must be solved through interdisciplinary collaboration between research scientists, institutions and stakeholders. In particular, hydrologic modelers, climate scientists, biologists, ecologists, engineers and water resource managers must interact to pool expertise and provide tools to address the complex issues associated with future climate change. The current study examines the results of an application of the VIC macro-scale hydrologic model to predict future changes to soil moisture, snowpack, evapo-transpiration, and streamflow in the Fraser Basin of British Columbia - and then apply these results to stream temperature and fish habitat models to predict future impacts on freshwater ecosystems. The results of this work will be presented to fisheries managers to provide them with the information needed to develop adaptation strategies that will help mitigate the adverse effects of climate change. This presentation will focus on the hydrologic modelling results of a number of downscaled scenarios to examine the projected differences for the 2050s (2041 - 2070) as compared to the historical baseline (1961- 1990). By the 2050s, although the magnitude of change varies by GCM and emissions scenarios, overall precipitation and temperature is projected to increase, particularly in the winter, which leads to increased winter time runoff for many basins. However, this is combined with declines in snow water equivalent (SWE) for many sites, which coupled with lower early season soil moisture, leads to declines in summer runoff and baseflow. SWE increases in some basins under the cgcm3 A1B and echam5 A1B scenarios at high elevations. A similar result was found in this region with the Canadian Regional Climate Model (CRCM) 4, driven with run 4 of the CGCM3 under the A2 emissions scenario. Lack of water availability during the summer time periods appears to limit evaporation, causing declines in summer ET across most

  2. Testing the Transferability of Hydrological Water Quality Model between two Catchments in Central Germany (United States)

    Jomaa, S.; Jiang, S.; Rode, M.


    Several indications showed that changes in land use/cover can influence the hydrological regimes and in consequence river water quality. Hydrological water quality modelling has proven to be an efficient tool to predict how the changes in land cover can affect the discharge of river catchment and its water quality (such as nitrogen and phosphorus) using different land use scenarios. The aim of this study was to test the tranferability of a hydrological water quality model between two catchments with different physiographical charcatctreristics. The HYPE model (HYdrological Predictions for the Environment) was setup in two mesoscale catchments in central Germany. The selected catchments are Selke (463 km2) and Weida (99.5 km2), which are two small tributaries of Elbe river basin and are located in Saxony-Anhalt and Thuringian states, respectively. The predominant land use classes of the Selke catchment are arable land (≈ 50%) located mainly in the lowland area and forest (35%), which is situated in low montain area. Howover, the dominating land use classes of the Weida catchment are agricultural land (40%), forest (29%) and grassland (26%), which are all located in low-montain range (elevation between 357-552m). First, The HYPE model was setup for the Selke catchment. Second, the model was used to predict the measured discharge and nutrient concentration of the Weida catchment using the same corresponding optimized paramter values obtained from calibration in the Selke catchment. Therefore, the feasability of HYPE model-parameter transferability between catchments with different physiographic characteristics and new regionalization schemes were investigated. The HYPE model was then used to predict the impact of different bionergy scanarios on the river discharge and nutrient emission. The preliminary results of this study will be presented and discussed.

  3. Geographically Isolated Wetlands and Catchment Hydrology: A Modified Model Analyses (United States)

    Evenson, G.; Golden, H. E.; Lane, C.; D'Amico, E.


    Geographically isolated wetlands (GIWs), typically defined as depressional wetlands surrounded by uplands, support an array of hydrological and ecological processes. However, key research questions concerning the hydrological connectivity of GIWs and their impacts on downgradient surface waters remain unanswered. This is particularly important for regulation and management of these systems. For example, in the past decade United States Supreme Court decisions suggest that GIWs can be afforded protection if significant connectivity exists between these waters and traditional navigable waters. Here we developed a simulation procedure to quantify the effects of various spatial distributions of GIWs across the landscape on the downgradient hydrograph using a refined version of the Soil and Water Assessment Tool (SWAT), a catchment-scale hydrological simulation model. We modified the SWAT FORTRAN source code and employed an alternative hydrologic response unit (HRU) definition to facilitate an improved representation of GIW hydrologic processes and connectivity relationships to other surface waters, and to quantify their downgradient hydrological effects. We applied the modified SWAT model to an ~ 202 km2 catchment in the Coastal Plain of North Carolina, USA, exhibiting a substantial population of mapped GIWs. Results from our series of GIW distribution scenarios suggest that: (1) Our representation of GIWs within SWAT conforms to field-based characterizations of regional GIWs in most respects; (2) GIWs exhibit substantial seasonally-dependent effects upon downgradient base flow; (3) GIWs mitigate peak flows, particularly following high rainfall events; and (4) The presence of GIWs on the landscape impacts the catchment water balance (e.g., by increasing groundwater outflows). Our outcomes support the hypothesis that GIWs have an important catchment-scale effect on downgradient streamflow.

  4. Study of Parameters And Methods of LL-Ⅳ Distributed Hydrological Model in DMIP2 (United States)

    Li, L.; Wu, J.; Wang, X.; Yang, C.; Zhao, Y.; Zhou, H.


    : The Physics-based distributed hydrological model is considered as an important developing period from the traditional experience-hydrology to the physical hydrology. The Hydrology Laboratory of the NOAA National Weather Service proposes the first and second phase of the Distributed Model Intercomparison Project (DMIP),that it is a great epoch-making work. LL distributed hydrological model has been developed to the fourth generation since it was established in 1997 on the Fengman-I district reservoir area (11000 km2).The LL-I distributed hydrological model was born with the applications of flood control system in the Fengman-I in China. LL-II was developed under the DMIP-I support, it is combined with GIS, RS, GPS, radar rainfall measurement.LL-III was established along with Applications of LL Distributed Model on Water Resources which was supported by the 973-projects of The Ministry of Science and Technology of the People's Republic of China. LL-Ⅳ was developed to face China's water problem. Combined with Blue River and the Baron Fork River basin of DMIP-II, the convection-diffusion equation of non-saturated and saturated seepage was derived from the soil water dynamics and continuous equation. In view of the technical characteristics of the model, the advantage of using convection-diffusion equation to compute confluence overall is longer period of predictable, saving memory space, fast budgeting, clear physical concepts, etc. The determination of parameters of hydrological model is the key, including experience coefficients and parameters of physical parameters. There are methods of experience, inversion, and the optimization to determine the model parameters, and each has advantages and disadvantages. This paper briefly introduces the LL-Ⅳ distribution hydrological model equations, and particularly introduces methods of parameters determination and simulation results on Blue River and Baron Fork River basin for DMIP-II. The soil moisture diffusion

  5. Global quantifiction of vegetation rooting depth for hydrological modelling (United States)

    Yuting, Yuting; Donohue, Randall; McVicar, Tim


    Plant rooting depth (Zr) is a key parameter in hydrological and biogeochemical models, yet the global spatial distribution of Zr is largely unknown due to the difficulties in its direct measurement. Moreover, Zr observations are usually only representative of a single plant or several plants, which can differ greatly from the effective Zr over a modelling unit (e.g., catchment or grid-box). Here, we provide a global parameterization of an analytical Zr model that balances the marginal carbon cost and benefit of deeper roots, and produce a climatological (i.e., 1982-2010 average) global Zr map. To test the Zr estimates, we apply the estimated Zr in a highly transparent hydrological model (i.e., the Budyko-Choudhury-Porporato (BCP) model) to estimate mean annual actual evapotranspiration (E) across the globe. We then compare the estimated E with both water balance-based E observations at 32 major catchments and satellite grid-box retrievals across the globe. Our results show that the BCP model, when implemented with Zr estimated herein, optimally reproduced the spatial pattern of E at both scales and provides improved model outputs when compared to BCP model results from two already existing global Zr datasets. These results suggest that our Zr estimates can be effectively used in state-of-the-art hydrological models, and potentially biogeochemical models, where the determination of Zr currently largely relies on biome type-based look-up tables.

  6. Improving statistical forecasts of seasonal streamflows using hydrological model output

    Directory of Open Access Journals (Sweden)

    D. E. Robertson


    Full Text Available Statistical methods traditionally applied for seasonal streamflow forecasting use predictors that represent the initial catchment condition and future climate influences on future streamflows. Observations of antecedent streamflows or rainfall commonly used to represent the initial catchment conditions are surrogates for the true source of predictability and can potentially have limitations. This study investigates a hybrid seasonal forecasting system that uses the simulations from a dynamic hydrological model as a predictor to represent the initial catchment condition in a statistical seasonal forecasting method. We compare the skill and reliability of forecasts made using the hybrid forecasting approach to those made using the existing operational practice of the Australian Bureau of Meteorology for 21 catchments in eastern Australia. We investigate the reasons for differences. In general, the hybrid forecasting system produces forecasts that are more skilful than the existing operational practice and as reliable. The greatest increases in forecast skill tend to be (1 when the catchment is wetting up but antecedent streamflows have not responded to antecedent rainfall, (2 when the catchment is drying and the dominant source of antecedent streamflow is in transition between surface runoff and base flow, and (3 when the initial catchment condition is near saturation intermittently throughout the historical record.

  7. Improving statistical forecasts of seasonal streamflows using hydrological model output (United States)

    Robertson, D. E.; Pokhrel, P.; Wang, Q. J.


    Statistical methods traditionally applied for seasonal streamflow forecasting use predictors that represent the initial catchment condition and future climate influences on future streamflows. Observations of antecedent streamflows or rainfall commonly used to represent the initial catchment conditions are surrogates for the true source of predictability and can potentially have limitations. This study investigates a hybrid seasonal forecasting system that uses the simulations from a dynamic hydrological model as a predictor to represent the initial catchment condition in a statistical seasonal forecasting method. We compare the skill and reliability of forecasts made using the hybrid forecasting approach to those made using the existing operational practice of the Australian Bureau of Meteorology for 21 catchments in eastern Australia. We investigate the reasons for differences. In general, the hybrid forecasting system produces forecasts that are more skilful than the existing operational practice and as reliable. The greatest increases in forecast skill tend to be (1) when the catchment is wetting up but antecedent streamflows have not responded to antecedent rainfall, (2) when the catchment is drying and the dominant source of antecedent streamflow is in transition between surface runoff and base flow, and (3) when the initial catchment condition is near saturation intermittently throughout the historical record.

  8. Altitudes of the top of model layers in the Central Valley Hydrologic Model (CVHM) (United States)

    U.S. Geological Survey, Department of the Interior — This digital dataset defines the model grid and altitudes of the top of the 10 model layers and base of the model simulated in the transient hydrologic model of the...

  9. Detecting Human Hydrologic Alteration from Diversion Hydropower Requires Universal Flow Prediction Tools: A Proposed Framework for Flow Prediction in Poorly-gauged, Regulated Rivers (United States)

    Kibler, K. M.; Alipour, M.


    Achieving the universal energy access Sustainable Development Goal will require great investment in renewable energy infrastructure in the developing world. Much growth in the renewable sector will come from new hydropower projects, including small and diversion hydropower in remote and mountainous regions. Yet, human impacts to hydrological systems from diversion hydropower are poorly described. Diversion hydropower is often implemented in ungauged rivers, thus detection of impact requires flow analysis tools suited to prediction in poorly-gauged and human-altered catchments. We conduct a comprehensive analysis of hydrologic alteration in 32 rivers developed with diversion hydropower in southwestern China. As flow data are sparse, we devise an approach for estimating streamflow during pre- and post-development periods, drawing upon a decade of research into prediction in ungauged basins. We apply a rainfall-runoff model, parameterized and forced exclusively with global-scale data, in hydrologically-similar gauged and ungauged catchments. Uncertain "soft" data are incorporated through fuzzy numbers and confidence-based weighting, and a multi-criteria objective function is applied to evaluate model performance. Testing indicates that the proposed framework returns superior performance (NSE = 0.77) as compared to models parameterized by rote calibration (NSE = 0.62). Confident that the models are providing `the right answer for the right reasons', our analysis of hydrologic alteration based on simulated flows indicates statistically significant hydrologic effects of diversion hydropower across many rivers. Mean annual flows, 7-day minimum and 7-day maximum flows decreased. Frequency and duration of flow exceeding Q25 decreased while duration of flows sustained below the Q75 increased substantially. Hydrograph rise and fall rates and flow constancy increased. The proposed methodology may be applied to improve diversion hydropower design in data-limited regions.

  10. Future Projections for Southern High Plains Agriculture Using Coupled Economic and Hydrologic Models and Climate Variability (United States)

    Rainwater, K.; Tewari, R.; Willis, D.; Stovall, J.; Hayhoe, K.; Hernandez, A.; Mauget, S. A.; Leiker, G.; Johnson, J.


    The objective of the project was to evaluate the hypothesis that predicted climate change will affect the useful life of the Ogallala aquifer in the Southern High Plains (SHP) through its impact on the amount of irrigation withdrawals, and thus affect the yields and economic costs and net income. A ninety-year time frame has been considered, although the research team recognizes that long-term predictions of crop prices and selections are perhaps even more uncertain than long-term weather projections. Previous work by the research team recently demonstrated the development of regionally downscaled climate projections for the SHP. Quantitative projections of precipitation, potential evaporation, and temperature trends for the 90-yr duration were selected from a downscaled set of high-resolution (one-eighth degree) daily climate and hydrological simulations covering the entire Great Plains region, driven by the latest IPCC AR4 climate model outputs. These projections were used as input to the Ogallala Ag Tool software developed by the USDA-ARS to predict daily and seasonal values of those variables, which directly affect irrigation, at different locations in the study area. Results from the Ogallala Ag Tool were then used to drive future projected crop production functions for cotton, corn, wheat, and sorghum using the DSSAT crop model. These production functions were then included in an integrated economic-hydrologic modeling approach that coupled an economic optimization model with a groundwater hydrological model. The groundwater model was based on the Texas Water Development Board's Southern Ogallala Groundwater Availability Model, which has been recalibrated by the research team for previous applications. The coupling of the two models allowed better recognition of spatial heterogeneity across the SHP, such that irrigation water availability was better represented through the spatial variations in pumping demands and saturated thickness. With this hydrologic

  11. Different methods for spatial interpolation of rainfall data for operational hydrology and hydrological modeling at watershed scale: a review

    Directory of Open Access Journals (Sweden)

    Ly, S.


    Full Text Available Watershed management and hydrological modeling require data related to the very important matter of precipitation, often measured using raingages or weather stations. Hydrological models often require a preliminary spatial interpolation as part of the modeling process. The success of spatial interpolation varies according to the type of model chosen, its mode of geographical management and the resolution used. The quality of a result is determined by the quality of the continuous spatial rainfall, which ensues from the interpolation method used. The objective of this article is to review the existing methods for interpolation of rainfall data that are usually required in hydrological modeling. We review the basis for the application of certain common methods and geostatistical approaches used in interpolation of rainfall. Previous studies have highlighted the need for new research to investigate ways of improving the quality of rainfall data and ultimately, the quality of hydrological modeling.

  12. Long Memory Models to Generate Synthetic Hydrological Series

    Directory of Open Access Journals (Sweden)

    Guilherme Armando de Almeida Pereira


    Full Text Available In Brazil, much of the energy production comes from hydroelectric plants whose planning is not trivial due to the strong dependence on rainfall regimes. This planning is accomplished through optimization models that use inputs such as synthetic hydrologic series generated from the statistical model PAR(p (periodic autoregressive. Recently, Brazil began the search for alternative models able to capture the effects that the traditional model PAR(p does not incorporate, such as long memory effects. Long memory in a time series can be defined as a significant dependence between lags separated by a long period of time. Thus, this research develops a study of the effects of long dependence in the series of streamflow natural energy in the South subsystem, in order to estimate a long memory model capable of generating synthetic hydrologic series.

  13. Testing the Hydrological Landscape Unit Classification System and Other Terrain Analysis Measures for Predicting Low-Flow Nitrate and Chloride in Watersheds (United States)

    Poor, Cara J.; McDonnell, Jeffrey J.; Bolte, John


    Elevated nitrate concentrations in streamwater are a major environmental management problem. While land use exerts a large control on stream nitrate, hydrology often plays an equally important role. To date, predictions of low-flow nitrate in ungauged watersheds have been poor because of the difficulty in describing the uniqueness of watershed hydrology over large areas. Clearly, hydrologic response varies depending on the states and stocks of water, flow pathways, and residence times. How to capture the dominant hydrological controls that combine with land use to define streamwater nitrate concentration is a major research challenge. This paper tests the new Hydrologic Landscape Regions (HLRs) watershed classification scheme of Wolock and others (Environmental Management 34:S71-S88, 2004) to address the question: Can HLRs be used as a way to predict low-flow nitrate? We also test a number of other indexes including inverse-distance weighting of land use and the well-known topographic index (TI) to address the question: How do other terrain and land use measures compare to HLR in terms of their ability to predict low-flow nitrate concentration? We test this for 76 watersheds in western Oregon using the U.S. Environmental Protection Agency’s Environmental Monitoring and Assessment Program and Regional Environmental Monitoring and Assessment Program data. We found that HLRs did not significantly improve nitrate predictions beyond the standard TI and land-use metrics. Using TI and inverse-distance weighting did not improve nitrate predictions; the best models were the percentage land use—elevation models. We did, however, see an improvement of chloride predictions using HLRs, TI, and inverse-distance weighting; adding HLRs and TI significantly improved model predictions and the best models used inverse-distance weighting and elevation. One interesting result of this study is elevation consistently predicted nitrate better than TI or the hydrologic classification

  14. Hydrology in a Mediterranean mountain environment, the Vallcebre Research basins (North Eastern Spain). IV. Testing hydrological and erosion models

    Energy Technology Data Exchange (ETDEWEB)

    Gallart, F.; Latron, J.; Llorens, P.; Martinez-Carreras, N.


    Three modelling exercises were carried out in the Vallcebre research basins in order to both improve the understanding of the hydrological processes and test the adequate of some models in such Mediterranean mountain conditions. These exercises consisted of i) the analysis of the hydrological role of the agricultural terraces using the TOPMODEL topographic index, ii) the parametrisation of TOPMODEL using internal basin information, and iii) a test of the erosion model KINEROS2 for simulating badlands erosion. (Author) 13 refs.

  15. Flash flood modeling with the MARINE hydrological distributed model (United States)

    Estupina-Borrell, V.; Dartus, D.; Ababou, R.


    Flash floods are characterized by their violence and the rapidity of their occurrence. Because these events are rare and unpredictable, but also fast and intense, their anticipation with sufficient lead time for warning and broadcasting is a primary subject of research. Because of the heterogeneities of the rain and of the behavior of the surface, spatially distributed hydrological models can lead to a better understanding of the processes and so on they can contribute to a better forecasting of flash flood. Our main goal here is to develop an operational and robust methodology for flash flood forecasting. This methodology should provide relevant data (information) about flood evolution on short time scales, and should be applicable even in locations where direct observations are sparse (e.g. absence of historical and modern rainfalls and streamflows in small mountainous watersheds). The flash flood forecast is obtained by the physically based, space-time distributed hydrological model "MARINE'' (Model of Anticipation of Runoff and INondations for Extreme events). This model is presented and tested in this paper for a real flash flood event. The model consists in two steps, or two components: the first component is a "basin'' flood module which generates flood runoff in the upstream part of the watershed, and the second component is the "stream network'' module, which propagates the flood in the main river and its subsidiaries. The basin flash flood generation model is a rainfall-runoff model that can integrate remotely sensed data. Surface hydraulics equations are solved with enough simplifying hypotheses to allow real time exploitation. The minimum data required by the model are: (i) the Digital Elevation Model, used to calculate slopes that generate runoff, it can be issued from satellite imagery (SPOT) or from French Geographical Institute (IGN); (ii) the rainfall data from meteorological radar, observed or anticipated by the French Meteorological Service (M

  16. Use of remotely sensed precipitation and leaf area index in a distributed hydrological model

    DEFF Research Database (Denmark)

    Andersen, Jens; Dybkjær, Gorm Ibsen; Jensen, Karsten Høgh


    distributed hydrological modelling, remote sensing, precipitation, leaf area index, NOAA AVHRR, cold cloud duration......distributed hydrological modelling, remote sensing, precipitation, leaf area index, NOAA AVHRR, cold cloud duration...

  17. Perspectives in using a remotely sensed dryness index in distributed hydrological models at river basin scale

    DEFF Research Database (Denmark)

    Andersen, J.; Sandholt, Inge; Jensen, Karsten Høgh


    Remote Sensing, hydrological modelling, dryness index, surface temperature, vegetation index, Africa, Senegal, soil moisture......Remote Sensing, hydrological modelling, dryness index, surface temperature, vegetation index, Africa, Senegal, soil moisture...

  18. Multi-Model Grand Ensemble Hydrologic Forecasting in the Fu River Basin Using Bayesian Model Averaging

    Directory of Open Access Journals (Sweden)

    Bo Qu


    Full Text Available Statistical post-processing for multi-model grand ensemble (GE hydrologic predictions is necessary, in order to achieve more accurate and reliable probabilistic forecasts. This paper presents a case study which applies Bayesian model averaging (BMA to statistically post-process raw GE runoff forecasts in the Fu River basin in China, at lead times ranging from 6 to 120 h. The raw forecasts were generated by running the Xinanjiang hydrologic model with ensemble forecasts (164 forecast members, using seven different “THORPEX Interactive Grand Global Ensemble” (TIGGE weather centres as forcing inputs. Some measures, such as data transformation and high-dimensional optimization, were included in the experiment after considering the practical water regime and data conditions. The results indicate that the BMA post-processing method is capable of improving the performance of raw GE runoff forecasts, yielding more calibrated and sharp predictive probability density functions (PDFs, over a range of lead times from 24 to 120 h. The analysis of percentile forecasts in two different flood events illustrates the great potential and prospects of BMA GE probabilistic river discharge forecasts, for taking precautions against severe flooding events.

  19. Estimating predictive hydrological uncertainty by dressing deterministic and ensemble forecasts; a comparison, with application to Meuse and Rhine (United States)

    Verkade, J. S.; Brown, J. D.; Davids, F.; Reggiani, P.; Weerts, A. H.


    Two statistical post-processing approaches for estimation of predictive hydrological uncertainty are compared: (i) 'dressing' of a deterministic forecast by adding a single, combined estimate of both hydrological and meteorological uncertainty and (ii) 'dressing' of an ensemble streamflow forecast by adding an estimate of hydrological uncertainty to each individual streamflow ensemble member. Both approaches aim to produce an estimate of the 'total uncertainty' that captures both the meteorological and hydrological uncertainties. They differ in the degree to which they make use of statistical post-processing techniques. In the 'lumped' approach, both sources of uncertainty are lumped by post-processing deterministic forecasts using their verifying observations. In the 'source-specific' approach, the meteorological uncertainties are estimated by an ensemble of weather forecasts. These ensemble members are routed through a hydrological model and a realization of the probability distribution of hydrological uncertainties (only) is then added to each ensemble member to arrive at an estimate of the total uncertainty. The techniques are applied to one location in the Meuse basin and three locations in the Rhine basin. Resulting forecasts are assessed for their reliability and sharpness, as well as compared in terms of multiple verification scores including the relative mean error, Brier Skill Score, Mean Continuous Ranked Probability Skill Score, Relative Operating Characteristic Score and Relative Economic Value. The dressed deterministic forecasts are generally more reliable than the dressed ensemble forecasts, but the latter are sharper. On balance, however, they show similar quality across a range of verification metrics, with the dressed ensembles coming out slightly better. Some additional analyses are suggested. Notably, these include statistical post-processing of the meteorological forecasts in order to increase their reliability, thus increasing the reliability

  20. An energy balance climate model with hydrological cycle. 1. Model description and sensitivity to internal parameters (United States)

    Jentsch, Volker


    A thermodynamical model designed to illustrate the effect of a hydrological cycle on climate sensitivity is presented. The model contains three climatic variables: two temperatures referring to an idealized atmosphere and ocean, respectively, and atmospheric humidity. The independent variables are time and latitude. Atmosphere and ocean are coupled by radiation and convection at their interface. Some structure of the atmospheric circulation is retained by differentiating between the dynamics of a low latitude zone (0° - ϕH) and that of a high latitude zone (ϕH-90°), where ϕH ≈ 30° is the intersection of meridional temperature gradient and critical gradient for baroclinic instability. The atmospheric transport is split into an advective and a diffusive part, while the oceanic transport is approximated by pure diffusion. The coefficients associated with horizontal and vertical motion are modelled in terms of temperature gradients. The predicted water vapor gives rise to precipitation and clouds and influences (via cloud cover and greenhouse effect) the radiation balance of the system. The model is integrated for annual mean conditions until an asymptotic equilibrium is reached. The free (internal) parameters of the system are determined by optimization methods so that simulated temperature, heat flux and hydrological cycle are in close agreement with observations. The sensitivity of the model is governed by radiation parameters. Of these, the cloud albedo is the most sensitive quantity. By contrast, the model is relatively little affected by parameters associated with horizontal and vertical transport of heat.

  1. Gravitational and capillary soil moisture dynamics for distributed hydrologic models

    Directory of Open Access Journals (Sweden)

    A. Castillo


    Full Text Available Distributed and continuous catchment models are used to simulate water and energy balance and fluxes across varied topography and landscape. The landscape is discretized into computational plan elements at resolutions of 101–103 m, and soil moisture is the hydrologic state variable. At the local scale, the vertical soil moisture dynamics link hydrologic fluxes and provide continuity in time. In catchment models these local-scale processes are modeled using 1-D soil columns that are discretized into layers that are usually 10−3–10−1 m in thickness. This creates a mismatch between the horizontal and vertical scales. For applications across large domains and in ensemble mode, this treatment can be a limiting factor due to its high computational demand. This study compares continuous multi-year simulations of soil moisture at the local scale using (i a 1-pixel version of a distributed catchment hydrologic model and (ii a benchmark detailed soil water physics solver. The distributed model uses a single soil layer with a novel dual-pore structure and employs linear parameterization of infiltration and some other fluxes. The detailed solver uses multiple soil layers and employs nonlinear soil physics relations to model flow in unsaturated soils. Using two sites with different climates (semiarid and sub-humid, it is shown that the efficient parameterization in the distributed model captures the essential dynamics of the detailed solver.

  2. Hydrologic behavior of model slopes with synthetic water repellent soils (United States)

    Zheng, Shuang; Lourenço, Sérgio D. N.; Cleall, Peter J.; Chui, Ting Fong May; Ng, Angel K. Y.; Millis, Stuart W.


    In the natural environment, soil water repellency decreases infiltration, increases runoff, and increases erosion in slopes. In the built environment, soil water repellency offers the opportunity to develop granular materials with controllable wettability for slope stabilization. In this paper, the influence of soil water repellency on the hydrological response of slopes is investigated. Twenty-four flume tests were carried out in model slopes under artificial rainfall; soils with various wettability levels were tested, including wettable (Contact Angle, CA 90°). Various rainfall intensities (30 mm/h and 70 mm/h), slope angles (20° and 40°) and relative compactions (70% and 90%) were applied to model the response of natural and man-made slopes to rainfall. To quantitatively assess the hydrological response, a number of measurements were made: runoff rate, effective rainfall rate, time to ponding, time to steady state, runoff acceleration, total water storage and wetting front rate. Overall, an increase in soil water repellency reduces infiltration and shortens the time for runoff generation, with the effects amplified for high rainfall intensity. Comparatively, the slope angle and relative compaction had only a minor contribution to the slope hydrology. The subcritical water repellent soils sustained infiltration for longer than both the wettable and water repellent soils, which presents an added advantage if they are to be used in the built environment as barriers. This study revealed substantial impacts of man-made or synthetically induced soil water repellency on the hydrological behavior of model slopes in controlled conditions. The results shed light on our understanding of hydrological processes in environments where the occurrence of natural soil water repellency is likely, such as slopes subjected to wildfires and in agricultural and forested slopes.

  3. On the role of model structure in hydrological modeling : Understanding models

    NARCIS (Netherlands)

    Gharari, S.


    Modeling is an essential part of the science of hydrology. Models enable us to formulate what we know and perceive from the real world into a neat package. Rainfall-runoff models are abstract simplifications of how a catchment works. Within the research field of scientific rainfall-runoff modeling,


    African Journals Online (AJOL)


    Jul 2, 2012 ... written to simulate an example of a randomly generated system. This paper can serve as tutorial to anyone interested in this area of research. Keywords: model predictive control, linear systems, discrete-time systems, constraints, quadratic programming. 1. Introduction. Model Predictive Control (MPC), also ...

  5. Archaeological predictive model set. (United States)


    This report is the documentation for Task 7 of the Statewide Archaeological Predictive Model Set. The goal of this project is to : develop a set of statewide predictive models to assist the planning of transportation projects. PennDOT is developing t...

  6. Hydrologic Evaluation of Landfill Performance (HELP) Model (United States)

    The program models rainfall, runoff, infiltration, and other water pathways to estimate how much water builds up above each landfill liner. It can incorporate data on vegetation, soil types, geosynthetic materials, initial moisture conditions, slopes, etc.

  7. The Chena River Watershed Hydrology Model (United States)


    during the season as the albedo and density of the snow change. During rainy condi- tions, snow melts at a faster rate because heat from the liquid...values for evapotranspiration and the air temperature lapse rate were estimated using the available data. A temperature index snow model was developed...and calibrated with existing snow water equivalent data. The HEC- HMS model was calibrated based on 3 years of continuous simulation between 1 April

  8. Evaluation of drought propagation in an ensemble mean of large-scale hydrological models

    NARCIS (Netherlands)

    Loon, van A.F.; Huijgevoort, van M.H.J.; Lanen, van H.A.J.


    Hydrological drought is increasingly studied using large-scale models. It is, however, not sure whether large-scale models reproduce the development of hydrological drought correctly. The pressing question is how well do large-scale models simulate the propagation from meteorological to hydrological

  9. Integrated hydrological modelling of the North China Plain

    DEFF Research Database (Denmark)

    Shu, Yunqiao; Villholth, Karen G.; Jensen, Karsten Høgh


    The integrated hydrological model MIKE SHE was applied to a part of the North China Plain to examine the dynamics of the hydrological system and to assess water management options to restore depleted groundwater resources. The model simulates the spatio-temporal distribution of recharge...... for scenario analysis of the effect of different cropping rotations, irrigation intensity, and other water management options, like the implementation of the South to North Water Transfer (SNWT) project. The model analysis verified that groundwater tables in the region are subject to steep declines (up to 1 m....../yr) due to decades of intensive exploitation of the groundwater resources for crop irrigation, primarily the widespread crop rotation of irrigated winter wheat and mostly rainfed summer maize. The SNWT project mitigates water stress in Shijiazhuang city and areas adjacent to wastewater canals but cannot...

  10. A conceptual glacio-hydrological model for high mountainous catchments

    Directory of Open Access Journals (Sweden)

    B. Schaefli


    Full Text Available In high mountainous catchments, the spatial precipitation and therefore the overall water balance is generally difficult to estimate. The present paper describes the structure and calibration of a semi-lumped conceptual glacio-hydrological model for the joint simulation of daily discharge and annual glacier mass balance that represents a better integrator of the water balance. The model has been developed for climate change impact studies and has therefore a parsimonious structure; it requires three input times series - precipitation, temperature and potential evapotranspiration - and has 7 parameters to calibrate. A multi-signal approach considering daily discharge and - if available - annual glacier mass balance has been developed for the calibration of these parameters. The model has been calibrated for three different catchments in the Swiss Alps having glaciation rates between 37% and 52%. It simulates well the observed daily discharge, the hydrological regime and some basic glaciological features, such as the annual mass balance.

  11. Modelling floods in the Ammer catchment: limitations and challenges with a coupled meteo-hydrological model approach

    Directory of Open Access Journals (Sweden)

    R. Ludwig


    Full Text Available Numerous applications of hydrological models have shown their capability to simulate hydrological processes with a reasonable degree of certainty. For flood modelling, the quality of precipitation data — the key input parameter — is very important but often remains questionable. This paper presents a critical review of experience in the EU-funded RAPHAEL project. Different meteorological data sources were evaluated to assess their applicability for flood modelling and forecasting in the Bavarian pre-alpine catchment of the Ammer river (709 km2, for which the hydrological aspects of runoff production are described as well as the complex nature of floods. Apart from conventional rain gauge data, forecasts from several Numerical Weather Prediction Models (NWP as well as rain radar data are examined, scaled and applied within the framework of a GIS-structured and physically based hydrological model. Multi-scenario results are compared and analysed. The synergetic approach leads to promising results under certain meteorological conditions but emphasises various drawbacks. At present, NWPs are the only source of rainfall forecasts (up to 96 hours with large spatial coverage and high temporal resolution. On the other hand, the coarse spatial resolution of NWP grids cannot yet address, adequately, the heterogeneous structures of orographic rainfields in complex convective situations; hence, a major downscaling problem for mountain catchment applications is introduced. As shown for two selected Ammer flood events, a high variability in prediction accuracy has still to be accepted at present. Sensitivity analysis of both meteo-data input and hydrological model performance in terms of process description are discussed and positive conclusions have been drawn for future applications of an advanced meteo-hydro model synergy. Keywords: RAPHAEL, modelling, forecasting, model coupling, PROMET-D, TOPMODEL

  12. Impact of uncertainty description on assimilating hydraulic head in the MIKE SHE distributed hydrological model

    DEFF Research Database (Denmark)

    Zhang, Donghua; Madsen, Henrik; Ridler, Marc E.


    The ensemble Kalman filter (EnKF) is a popular data assimilation (DA) technique that has been extensively used in environmental sciences for combining complementary information from model predictions and observations. One of the major challenges in EnKF applications is the description of model...... uncertainty. In most hydrological EnKF applications, an ad hoc model uncertainty is defined with the aim of avoiding a collapse of the filter. The present work provides a systematic assessment of model uncertainty in DA applications based on combinations of forcing, model parameters, and state uncertainties...

  13. A double-layer hydrological model dedicated to glacier sliding (United States)

    de Fleurian, B.; Gagliardini, O.; Lemeur, E.; Durand, G.


    Field observations show that subglacial hydrology and glacier dynamics are tightly linked. The basal friction law that controls sliding velocities via subglacial water-pressure has been developed but, unfortunately, subglacial water pressure cannot be easily assessed. In the existing physically-based hydrological models, the effective pressure is even set to zero, which prevents from using these models to accurately compute the basal water pressure. In the proposed approach, the water pressure is computed from Darcy's equations for a confined aquifer. These equations are applied to two different layers. The first one features a classical sediment drainage system. The second one, with an appropriate equivalent conductivity, consist of an efficient channel-type drainage system. This second layer is activated when the effective pressure tends toward zero and allows the drainage of the excess of water from the sediment layer. This hydrological model is coupled with a full Stokes ice flow model including a water-pressure dependant friction law used to compute the basal boundary condition. This modelling attempt is first carried out over a synthetic bedrock which is consistent with the specific characteristics of an Antarctic test outlet glacier. These characteristics result from a preliminary survey carried out during the 2007-2009 field seasons on the Astrolabe glacier (Terre Adélie French sector) in the framework of the DACOTA programme.

  14. Mid-Holocene Hydrologic Model of the Shingobee Watershed, Minnesota (United States)

    Filby, Sheryl K.; Locke, Sharon M.; Person, Mark A.; Winter, Thomas C.; Rosenberry, Donald O.; Nieber, John L.; Gutowski, William J.; Ito, Emi


    A hydrologic model of the Shingobee Watershed in north-central Minnesota was developed to reconstruct mid-Holocene paleo-lake levels for Williams Lake, a surface-water body located in the southern portion of the watershed. Hydrologic parameters for the model were first estimated in a calibration exercise using a 9-yr historical record (1990-1998) of climatic and hydrologic stresses. The model reproduced observed temporal and spatial trends in surface/groundwater levels across the watershed. Mid-Holocene aquifer and lake levels were then reconstructed using two paleoclimatic data sets: CCM1 atmospheric general circulation model output and pollen-transfer functions using sediment core data from Williams Lake. Calculated paleo-lake levels based on pollen-derived paleoclimatic reconstructions indicated a 3.5-m drop in simulated lake levels and were in good agreement with the position of mid-Holocene beach sands observed in a Williams Lake sediment core transect. However, calculated paleolake levels based on CCM1 climate forcing produced only a 0.05-m drop in lake levels. We found that decreases in winter precipitation rather than temperature increases had the largest effect on simulated mid-Holocene lake levels. The study illustrates how watershed models can be used to critically evaluate paleoclimatic reconstructions by integrating geologic, climatic, limnologic, and hydrogeologic data sets.

  15. eWaterCycle: A high resolution global hydrological model (United States)

    van de Giesen, Nick; Bierkens, Marc; Drost, Niels; Hut, Rolf; Sutanudjaja, Edwin


    In 2013, the eWaterCycle project was started, which has the ambitious goal to run a high resolution global hydrological model. Starting point was the PCR-GLOBWB built by Utrecht University. The software behind this model will partially be re-engineered in order to enable to run it in a High Performance Computing (HPC) environment. The aim is to have a spatial resolution of 1km x 1km. The idea is also to run the model in real-time and forecasting mode, using data assimilation. An on-demand hydraulic model will be available for detailed flow and flood forecasting in support of navigation and disaster management. The project faces a set of scientific challenges. First, to enable the model to run in a HPC environment, model runs were analyzed to examine on which parts of the program most CPU time was spent. These parts were re-coded in Open MPI to allow for parallel processing. Different parallelization strategies are thinkable. In our case, it was decided to use watershed logic as a first step to distribute the analysis. There is rather limited recent experience with HPC in hydrology and there is much to be learned and adjusted, both on the hydrological modeling side and the computer science side. For example, an interesting early observation was that hydrological models are, due to their localized parameterization, much more memory intensive than models of sister-disciplines such as meteorology and oceanography. Because it would be deadly to have to swap information between CPU and hard drive, memory management becomes crucial. A standard Ensemble Kalman Filter (enKF) would, for example, have excessive memory demands. To circumvent these problems, an alternative to the enKF was developed that produces equivalent results. This presentation shows the most recent results from the model, including a 5km x 5km simulation and a proof of concept for the new data assimilation approach. Finally, some early ideas about financial sustainability of an operational global

  16. Wind power prediction models (United States)

    Levy, R.; Mcginness, H.


    Investigations were performed to predict the power available from the wind at the Goldstone, California, antenna site complex. The background for power prediction was derived from a statistical evaluation of available wind speed data records at this location and at nearby locations similarly situated within the Mojave desert. In addition to a model for power prediction over relatively long periods of time, an interim simulation model that produces sample wind speeds is described. The interim model furnishes uncorrelated sample speeds at hourly intervals that reproduce the statistical wind distribution at Goldstone. A stochastic simulation model to provide speed samples representative of both the statistical speed distributions and correlations is also discussed.

  17. Watershed Models for Predicting Nitrogen Loads from Artificially Drained Lands (United States)

    R. Wayne Skaggs; George M. Chescheir; Glenn Fernandez; Devendra M. Amatya


    Non-point sources of pollutants originate at the field scale but water quality problems usually occur at the watershed or basin scale. This paper describes a series of models developed for poorly drained watersheds. The models use DRAINMOD to predict hydrology at the field scale and a range of methods to predict channel hydraulics and nitrogen transport. In-stream...

  18. Assessment of biophysical and hydrological variables in semiarid West Africa based on MSG data and numerical modelling

    DEFF Research Database (Denmark)

    Rasmussen, Michael Schultz; Sandholt, Inge; Rasmussen, Kjeld


    Remote Sensing, Senegal, SEVIRI, MSG (Metrosat Second Generation), vegetation, hydrological model......Remote Sensing, Senegal, SEVIRI, MSG (Metrosat Second Generation), vegetation, hydrological model...

  19. Application of soft computing based hybrid models in hydrological variables modeling: a comprehensive review (United States)

    Fahimi, Farzad; Yaseen, Zaher Mundher; El-shafie, Ahmed


    Since the middle of the twentieth century, artificial intelligence (AI) models have been used widely in engineering and science problems. Water resource variable modeling and prediction are the most challenging issues in water engineering. Artificial neural network (ANN) is a common approach used to tackle this problem by using viable and efficient models. Numerous ANN models have been successfully developed to achieve more accurate results. In the current review, different ANN models in water resource applications and hydrological variable predictions are reviewed and outlined. In addition, recent hybrid models and their structures, input preprocessing, and optimization techniques are discussed and the results are compared with similar previous studies. Moreover, to achieve a comprehensive view of the literature, many articles that applied ANN models together with other techniques are included. Consequently, coupling procedure, model evaluation, and performance comparison of hybrid models with conventional ANN models are assessed, as well as, taxonomy and hybrid ANN models structures. Finally, current challenges and recommendations for future researches are indicated and new hybrid approaches are proposed.

  20. An integrated modelling framework for regulated river systems in Land Surface Hydrological Models (United States)

    Rehan Anis, Muhammad; razavi, Saman; Wheater, Howard


    Many of the large river systems around the world are highly regulated with numerous physical flow control and storage structures as well as a range of water abstraction rules and regulations. Most existing Land Surface Models (LSM) do not represent the modifications to the hydrological regimes introduced by water management (reservoirs, irrigation diversions, etc.). The interactions between natural hydrological processes and changes in water and energy fluxes and storage due to human interventions are important to the understanding of how these systems may respond to climate change amongst other drivers for change as well as to the assessment of their feedbacks to the climate system at regional and global scales. This study presents an integrated modelling approach to include human interventions within natural hydrological systems using a fully coupled modelling platform. The Bow River Basin in Alberta (26,200 km2), one of the most managed Canadian rivers, is used to demonstrate the approach. We have dynamically linked the MESH modelling system, which embeds the Canadian Land Surface Scheme (CLASS), with the MODSIM-DSS water management modelling tool. MESH models the natural hydrology while MODSIM optimizes the reservoir operation of 4 simulated reservoirs to satisfy demands within the study basin. MESH was calibrated for the catchments upstream the reservoirs and gave good performance (NSE = 0.81) while BIAS was only 2.3% at the catchment outlet. Without coupling with MODSIM (i.e. no regulation), simulated hydrographs at the catchment outlet were in complete disagreement with observations (NSE = 0.28). The coupled model simulated the optimization introduced by the operation of the multi-reservoir system in the Bow river basin and shows excellent agreement between observed and simulated hourly flows (NSE = 0.98). Irrigation demands are fully satisfied during summer, however, there are some shortages in winter demand from industries, which can be rectified by

  1. Airborne laser scanning and usefulness for hydrological models

    Directory of Open Access Journals (Sweden)

    M. Hollaus


    Full Text Available Digital terrain models form the basis for distributed hydrologic models as well as for two-dimensional hydraulic river flood models. The technique used for generating high accuracy digital terrain models has shifted from stereoscopic aerial-photography to airborne laser scanning during the last years. Since the disastrous floods 2002 in Austria, large airborne laser-scanning flight campaigns have been carried out for several river basins. Additionally to the topographic information, laser scanner data offer also the possibility to estimate object heights (vegetation, buildings. Detailed land cover maps can be derived in conjunction with the complementary information provided by high-resolution colour-infrared orthophotos. As already shown in several studies, the potential of airborne laser scanning to provide data for hydrologic/hydraulic applications is high. These studies were mostly constraint to small test sites. To overcome this spatial limitation, the current paper summarises the experiences to process airborne laser scanner data for large mountainous regions, thereby demonstrating the applicability of this technique in real-world hydrological applications.

  2. Eco-hydrological Modeling in the Framework of Climate Change (United States)

    Fatichi, Simone; Ivanov, Valeriy Y.; Caporali, Enrica


    A blueprint methodology for studying climate change impacts, as inferred from climate models, on eco-hydrological dynamics at the plot and small catchment scale is presented. Input hydro-meteorological variables for hydrological and eco-hydrological models for present and future climates are reproduced using a stochastic downscaling technique and a weather generator, "AWE-GEN". The generated time series of meteorological variables for the present climate and an ensemble of possible future climates serve as input to a newly developed physically-based eco-hydrological model "Tethys-Chloris". An application of the proposed methodology is realized reproducing the current (1961-2000) and multiple future (2081-2100) climates for the location of Tucson (Arizona). A general reduction of precipitation and a significant increase of air temperature are inferred. The eco-hydrological model is successively applied to detect changes in water recharge and vegetation dynamics for a desert shrub ecosystem, typical of the semi-arid climate of south Arizona. Results for the future climate account for uncertainties in the downscaling and are produced in terms of probability density functions. A comparison of control and future scenarios is discussed in terms of changes in the hydrological balance components, energy fluxes, and indices of vegetation productivity. An appreciable effect of climate change can be observed in metrics of vegetation performance. The negative impact on vegetation due to amplification of water stress in a warmer and dryer climate is offset by a positive effect of carbon dioxide augment. This implies a positive shift in plant capabilities to exploit water. Consequently, the plant water use efficiency and rain use efficiency are expected to increase. Interesting differences in the long-term vegetation productivity are also observed for the ensemble of future climates. The reduction of precipitation and the substantial maintenance of vegetation cover ultimately

  3. Effect of citizen engagement levels in flood forecasting by assimilating crowdsourced observations in hydrological models (United States)

    Mazzoleni, Maurizio; Cortes Arevalo, Juliette; Alfonso, Leonardo; Wehn, Uta; Norbiato, Daniele; Monego, Martina; Ferri, Michele; Solomatine, Dimitri


    In the past years, a number of methods have been proposed to reduce uncertainty in flood prediction by means of model updating techniques. Traditional physical observations are usually integrated into hydrological and hydraulic models to improve model performances and consequent flood predictions. Nowadays, low-cost sensors can be used for crowdsourced observations. Different type of social sensors can measure, in a more distributed way, physical variables such as precipitation and water level. However, these crowdsourced observations are not integrated into a real-time fashion into water-system models due to their varying accuracy and random spatial-temporal coverage. We assess the effect in model performance due to the assimilation of crowdsourced observations of water level. Our method consists in (1) implementing a Kalman filter into a cascade of hydrological and hydraulic models. (2) defining observation errors depending on the type of sensor either physical or social. Randomly distributed errors are based on accuracy ranges that slightly improve according to the citizens' expertise level. (3) Using a simplified social model to realistically represent citizen engagement levels based on population density and citizens' motivation scenarios. To test our method, we synthetically derive crowdsourced observations for different citizen engagement levels from a distributed network of physical and social sensors. The observations are assimilated during a particular flood event occurred in the Bacchiglione catchment, Italy. The results of this study demonstrate that sharing crowdsourced water level observations (often motivated by a feeling of belonging to a community of friends) can help in improving flood prediction. On the other hand, a growing participation of individual citizens or weather enthusiasts sharing hydrological observations in cities can help to improve model performance. This study is a first step to assess the effects of crowdsourced observations in

  4. Use of output from high-resolution atmospheric models in landscape-scale hydrologic models: An assessment (United States)

    Hostetler, S.W.; Giorgi, F.


    In this paper we investigate the feasibility of coupling regional climate models (RCMs) with landscape-scale hydrologic models (LSHMs) for studies of the effects of climate on hydrologic systems. The RCM used is the National Center for Atmospheric Research/Pennsylvania State University mesoscale model (MM4). Output from two year-round simulations (1983 and 1988) over the western United States is used to drive a lake model for Pyramid Lake in Nevada and a streamfiow model for Steamboat Creek in Oregon. Comparisons with observed data indicate that MM4 is able to produce meteorologic data sets that can be used to drive hydrologic models. Results from the lake model simulations indicate that the use of MM4 output produces reasonably good predictions of surface temperature and evaporation. Results from the streamflow simulations indicate that the use of MM4 output results in good simulations of the seasonal cycle of streamflow, but deficiencies in simulated wintertime precipitation resulted in underestimates of streamflow and soil moisture. Further work with climate (multiyear) simulations is necessary to achieve a complete analysis, but the results from this study indicate that coupling of LSHMs and RCMs may be a useful approach for evaluating the effects of climate change on hydrologic systems.

  5. Diagnosis of the hydrology of a small Arctic basin at the tundra-taiga transition using a physically based hydrological model (United States)

    Krogh, Sebastian A.; Pomeroy, John W.; Marsh, Philip


    A better understanding of cold regions hydrological processes and regimes in transitional environments is critical for predicting future Arctic freshwater fluxes under climate and vegetation change. A physically based hydrological model using the Cold Regions Hydrological Model platform was created for a small Arctic basin in the tundra-taiga transition region. The model represents snow redistribution and sublimation by wind and vegetation, snowmelt energy budget, evapotranspiration, subsurface flow through organic terrain, infiltration to frozen soils, freezing and thawing of soils, permafrost and streamflow routing. The model was used to reconstruct the basin water cycle over 28 years to understand and quantify the mass fluxes controlling its hydrological regime. Model structure and parameters were set from the current understanding of Arctic hydrology, remote sensing, field research in the basin and region, and calibration against streamflow observations. Calibration was restricted to subsurface hydraulic and storage parameters. Multi-objective evaluation of the model using observed streamflow, snow accumulation and ground freeze/thaw state showed adequate simulation. Significant spatial variability in the winter mass fluxes was found between tundra, shrubs and forested sites, particularly due to the substantial blowing snow redistribution and sublimation from the wind-swept upper basin, as well as sublimation of canopy intercepted snow from the forest (about 17% of snowfall). At the basin scale, the model showed that evapotranspiration is the largest loss of water (47%), followed by streamflow (39%) and sublimation (14%). The models streamflow performance sensitivity to a set of parameter was analysed, as well as the mean annual mass balance uncertainty associated with these parameters.

  6. Advancing reservoir operation description in physically based hydrological models (United States)

    Anghileri, Daniela; Giudici, Federico; Castelletti, Andrea; Burlando, Paolo


    Last decades have seen significant advances in our capacity of characterizing and reproducing hydrological processes within physically based models. Yet, when the human component is considered (e.g. reservoirs, water distribution systems), the associated decisions are generally modeled with very simplistic rules, which might underperform in reproducing the actual operators' behaviour on a daily or sub-daily basis. For example, reservoir operations are usually described by a target-level rule curve, which represents the level that the reservoir should track during normal operating conditions. The associated release decision is determined by the current state of the reservoir relative to the rule curve. This modeling approach can reasonably reproduce the seasonal water volume shift due to reservoir operation. Still, it cannot capture more complex decision making processes in response, e.g., to the fluctuations of energy prices and demands, the temporal unavailability of power plants or varying amount of snow accumulated in the basin. In this work, we link a physically explicit hydrological model with detailed hydropower behavioural models describing the decision making process by the dam operator. In particular, we consider two categories of behavioural models: explicit or rule-based behavioural models, where reservoir operating rules are empirically inferred from observational data, and implicit or optimization based behavioural models, where, following a normative economic approach, the decision maker is represented as a rational agent maximising a utility function. We compare these two alternate modelling approaches on the real-world water system of Lake Como catchment in the Italian Alps. The water system is characterized by the presence of 18 artificial hydropower reservoirs generating almost 13% of the Italian hydropower production. Results show to which extent the hydrological regime in the catchment is affected by different behavioural models and reservoir

  7. Dynamical forecast vs Ensemble Streamflow Prediction (ESP): how sensitive are monthly and seasonal hydrological forecasts to the quality of rainfall drivers? (United States)

    Tanguy, Maliko; Prudhomme, Christel; Harrigan, Shaun; Smith, Katie


    Seasonal forecasting of hydrological extremes is challenging for the hydro-meteorological modelling community, and the performance of hydrological forecasts at lead times over 1 month is still poor especially for catchments with limited hydrological memory. A considerable amount of effort is being invested within the meteorological community to improve dynamic meteorological forecasting which can then be used to drive hydrological models to produce physically-driven hydrological forecasts. However, currently for the UK, these meteorological forecasts are being produced at 1 month or seasonal time-step, whereas hydrological models often require daily or sub-daily time-steps. A simpler way to get seasonal forecasts is to use historical climate data to drive hydrological models using Ensemble Streamflow Prediction (ESP). This gives a range of possible future hydrological status given known initial conditions, but it does not contain any information on the future dynamic of the atmosphere. The error is highly dependent on the type of catchment, but ESP is an improvement compared to simply using climatology of river flows, especially in groundwater dominated catchments. The objective of this study is to find out how accurate the seasonal rainfall forecast has to be (in terms of total rainfall and temporal distribution) for the dynamical seasonal forecast to beat ESP. To this aim, we have looked at the sensitivity of hydrological models to the quality of driving rainfall input, proxy of 'best possible' forecasts. Study catchments representative of the range of UK's hydro-climatic conditions were selected. For these catchments, synthetic rainfall time series derived from observed data were created by increasingly degrading the data. The number of rainy days, their intensity and their sequencing were artificially modified to analyse which of these characteristics is most important to get a better hydrological forecast using a simple lumped hydrological model (GR4J), and

  8. Calibration process of highly parameterized semi-distributed hydrological model (United States)

    Vidmar, Andrej; Brilly, Mitja


    Hydrological phenomena take place in the hydrological system, which is governed by nature, and are essentially stochastic. These phenomena are unique, non-recurring, and changeable across space and time. Since any river basin with its own natural characteristics and any hydrological event therein, are unique, this is a complex process that is not researched enough. Calibration is a procedure of determining the parameters of a model that are not known well enough. Input and output variables and mathematical model expressions are known, while only some parameters are unknown, which are determined by calibrating the model. The software used for hydrological modelling nowadays is equipped with sophisticated algorithms for calibration purposes without possibility to manage process by modeler. The results are not the best. We develop procedure for expert driven process of calibration. We use HBV-light-CLI hydrological model which has command line interface and coupling it with PEST. PEST is parameter estimation tool which is used widely in ground water modeling and can be used also on surface waters. Process of calibration managed by expert directly, and proportionally to the expert knowledge, affects the outcome of the inversion procedure and achieves better results than if the procedure had been left to the selected optimization algorithm. First step is to properly define spatial characteristic and structural design of semi-distributed model including all morphological and hydrological phenomena, like karstic area, alluvial area and forest area. This step includes and requires geological, meteorological, hydraulic and hydrological knowledge of modeler. Second step is to set initial parameter values at their preferred values based on expert knowledge. In this step we also define all parameter and observation groups. Peak data are essential in process of calibration if we are mainly interested in flood events. Each Sub Catchment in the model has own observations group

  9. Effect of Baseflow Separation on Uncertainty of Hydrological Modeling in the Xinanjiang Model

    Directory of Open Access Journals (Sweden)

    Kairong Lin


    Full Text Available Based on the idea of inputting more available useful information for evaluation to gain less uncertainty, this study focuses on how well the uncertainty can be reduced by considering the baseflow estimation information obtained from the smoothed minima method (SMM. The Xinanjiang model and the generalized likelihood uncertainty estimation (GLUE method with the shuffled complex evolution Metropolis (SCEM-UA sampling algorithm were used for hydrological modeling and uncertainty analysis, respectively. The Jiangkou basin, located in the upper of the Hanjiang River, was selected as case study. It was found that the number and standard deviation of behavioral parameter sets both decreased when the threshold value for the baseflow efficiency index increased, and the high Nash-Sutcliffe efficiency coefficients correspond well with the high baseflow efficiency coefficients. The results also showed that uncertainty interval width decreased significantly, while containing ratio did not decrease by much and the simulated runoff with the behavioral parameter sets can fit better to the observed runoff, when threshold for the baseflow efficiency index was taken into consideration. These implied that using the baseflow estimation information can reduce the uncertainty in hydrological modeling to some degree and gain more reasonable prediction bounds.

  10. Hydrological modelling with TOPMODEL of Chingaza páramo, Colombia

    Directory of Open Access Journals (Sweden)

    Eydith Girleza Gil Morales


    Full Text Available Páramo ecosystems are located on the upper parts of the tropical mountains, below the snow line areas or in isolated areas where no glacier ecosystems occur. These ecosystems are considered important for their biodiversity, but mainly because they are permanent source of water for populations located at the upper and middle parts of the Andes. Recent studies indicate that ecosystems located at high altitudes, are more vulnerable to climate change and to changes in land use, which threatens the ecosystem services derived from them. There are very few studies in these ecosystems, within which, studies on the hydrological functioning are even scarcer, which seems to be related to their position in the top of the mountains and difficulties associated with the access to them. This implies that there is a need to create tools that allow us to study these ecosystems, overcoming the current difficulties. Hydrological TOPMODEL is used to investigate the hydrological functioning of the páramo of Chingaza, through a case study in la Chucua basin. For this, we calibrate and validate the model using two data sets of climate and the hydrology of the basin (climate and discharge from 2008 and 2009, respectively. Through the calibration procedure we obtain a high efficiency value of 0.76 model (coefficient Nash - Sutcliffe, which adequately represents the hydrological behavior of the páramo. Simulations with better adjustment between measured and predicted values of discharge, have low values of surface infiltration excess runoff, indicating high water storage capacity on the soils. This agrees with the predominance of subsurface flow in studied ecosystem, given the special characteristics of soils. Results also show the large influence of factors represented in the model (topography and soils, on water basin response to rainfall events. This is significant evidence of exceptional hydrological behavior of the páramos, mainly related to the presence of soil

  11. Hydrological modelling of the west coast of India

    Digital Repository Service at National Institute of Oceanography (India)

    Suprit, K.

    pleasure. I am thankful to our system administrators Dattaram, Kaushik, Krupesh, Ashok and Sarvesh for providing hassle-free computer and peripheral support. After passing M. Sc., I was looking for a research position and NIO was not on my radar. Roxy, my..., and evaporation. The framework is based on Terrestrial Hydrologic Model with Biogeochemistry (THMB) 2, a numerical model developed by Coe [2000]. THMB model provides a reliable water balance of a river system. Figure 1.7 The Mandovi and Zuari (all rivers digitized...

  12. A confined-unconfined aquifer model for subglacial hydrology (United States)

    Beyer, Sebastian; Kleiner, Thomas; Humbert, Angelika


    Modeling the evolution of subglacial channels underneath ice sheets is an urgent need for ice sheet modellers, as channels affect sliding velocities and hence ice discharge. Owing to very limited observations of the subglacial hydraulic system, the development of physical models is quite restricted. Subglacial hydrology models are currently taking two different approaches: either modeling the development of a network of individual channels or modeling an equivalent porous layer where the channels are not resolved individually but modeled as a diffusive process, adjusted to reproduce the characteristic of an efficient system. Here, we use the latter approach, improving it by using a confined-unconfined aquifer model (CUAS), that allows the system to run dry in absence of sufficient water input. This ensures physical values for the water pressure. Channels are represented by adjusting the permeability and storage of the system according to projected locations of channels. The evolution of channel positions is governed by a reduced complexity model that computes channel growths according to simple rules (weighted random walks descending the hydraulic potential). As a proof of concept we present the results of the evolution of the hydrological system over time for a simple artificial glacier geometry.

  13. Inverse and Predictive Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Syracuse, Ellen Marie [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)


    The LANL Seismo-Acoustic team has a strong capability in developing data-driven models that accurately predict a variety of observations. These models range from the simple – one-dimensional models that are constrained by a single dataset and can be used for quick and efficient predictions – to the complex – multidimensional models that are constrained by several types of data and result in more accurate predictions. Team members typically build models of geophysical characteristics of Earth and source distributions at scales of 1 to 1000s of km, the techniques used are applicable for other types of physical characteristics at an even greater range of scales. The following cases provide a snapshot of some of the modeling work done by the Seismo- Acoustic team at LANL.

  14. Integrated hydrological SVAT model for climate change studies in Denmark (United States)

    Mollerup, M.; Refsgaard, J.; Sonnenborg, T. O.


    In a major Danish funded research project ( a coupling is being established between the HIRHAM regional climate model code from Danish Meteorological Institute and the MIKE SHE distributed hydrological model code from DHI. The linkage between those two codes is a soil vegetation atmosphere transfer scheme, which is a module of MIKE SHE. The coupled model will be established for the entire country of Denmark (43,000 km2 land area) where a MIKE SHE based hydrological model already exists (Henriksen et al., 2003, 2008). The present paper presents the MIKE SHE SVAT module and the methodology used for parameterising and calibrating the MIKE SHE SVAT module for use throughout the country. As SVAT models previously typically have been tested for research field sites with comprehensive data on energy fluxes, soil and vegetation data, the major challenge lies in parameterisation of the model when only ordinary data exist. For this purpose annual variations of vegetation characteristics (Leaf Area Index (LAI), Crop height, Root depth and the surface albedo) for different combinations of soil profiles and vegetation types have been simulated by use of the soil plant atmosphere model Daisy (Hansen et al., 1990; Abrahamsen and Hansen, 2000) has been applied. The MIKE SHE SVAT using Daisy generated surface/soil properties model has been calibrated against existing data on groundwater heads and river discharges. Simulation results in form of evapotranspiration and percolation are compared to the existing MIKE SHE model and to observations. To analyse the use of the SVAT model in climate change impact assessments data from the ENSEMBLES project ( have been analysed to assess the impacts on reference evapotranspiration (calculated by the Makkink and the Penmann-Monteith equations) as well as on the individual elements in the Penmann-Monteith equation (radiation, wind speed, humidity and temperature). The differences on the

  15. Parallelization of a hydrological model using the message passing interface (United States)

    Wu, Yiping; Li, Tiejian; Sun, Liqun; Chen, Ji


    With the increasing knowledge about the natural processes, hydrological models such as the Soil and Water Assessment Tool (SWAT) are becoming larger and more complex with increasing computation time. Additionally, other procedures such as model calibration, which may require thousands of model iterations, can increase running time and thus further reduce rapid modeling and analysis. Using the widely-applied SWAT as an example, this study demonstrates how to parallelize a serial hydrological model in a Windows® environment using a parallel programing technology—Message Passing Interface (MPI). With a case study, we derived the optimal values for the two parameters (the number of processes and the corresponding percentage of work to be distributed to the master process) of the parallel SWAT (P-SWAT) on an ordinary personal computer and a work station. Our study indicates that model execution time can be reduced by 42%–70% (or a speedup of 1.74–3.36) using multiple processes (two to five) with a proper task-distribution scheme (between the master and slave processes). Although the computation time cost becomes lower with an increasing number of processes (from two to five), this enhancement becomes less due to the accompanied increase in demand for message passing procedures between the master and all slave processes. Our case study demonstrates that the P-SWAT with a five-process run may reach the maximum speedup, and the performance can be quite stable (fairly independent of a project size). Overall, the P-SWAT can help reduce the computation time substantially for an individual model run, manual and automatic calibration procedures, and optimization of best management practices. In particular, the parallelization method we used and the scheme for deriving the optimal parameters in this study can be valuable and easily applied to other hydrological or environmental models.

  16. Modeling the Hydrologic Processes of a Permeable Pavement ... (United States)

    A permeable pavement system can capture stormwater to reduce runoff volume and flow rate, improve onsite groundwater recharge, and enhance pollutant controls within the site. A new unit process model for evaluating the hydrologic performance of a permeable pavement system has been developed in this study. The developed model can continuously simulate infiltration through the permeable pavement surface, exfiltration from the storage to the surrounding in situ soils, and clogging impacts on infiltration/exfiltration capacity at the pavement surface and the bottom of the subsurface storage unit. The exfiltration modeling component simulates vertical and horizontal exfiltration independently based on Darcy’s formula with the Green-Ampt approximation. The developed model can be arranged with physically-based modeling parameters, such as hydraulic conductivity, Manning’s friction flow parameters, saturated and field capacity volumetric water contents, porosity, density, etc. The developed model was calibrated using high-frequency observed data. The modeled water depths are well matched with the observed values (R2 = 0.90). The modeling results show that horizontal exfiltration through the side walls of the subsurface storage unit is a prevailing factor in determining the hydrologic performance of the system, especially where the storage unit is developed in a long, narrow shape; or with a high risk of bottom compaction and clogging. This paper presents unit

  17. Hydrologic modeling of Guinale River Basin using HEC-HMS and synthetic aperture radar (United States)

    Bien, Ferdinand E.; Plopenio, Joanaviva C.


    This paper presents the methods and results of hydrologic modeling of Guinale river basin through the use of HEC-HMS software and Synthetic Aperture Radar Digital Elevation Model (SAR DEM). Guinale River Basin is located in the province of Albay, Philippines which is one of the river basins covered by the Ateneo de Naga University (ADNU) Phil-LiDAR 1. This research project was funded by the Department of Science and Technology (DOST) through the Philippine Council for Industry, Energy and Emerging Technology Research and Development (PCIEERD). Its objectives are to simulate the hydrologic model of Guinale River basin using HEC-HMS software and SAR DEM. Its basin covers an area of 165.395 and the hydrologic model was calibrated using the storm event typhoon Nona (international name Melor). Its parameter had undergone a series of optimization processes of HEC-HMS software in order to produce an acceptable level of model efficiency. The Nash-Sutcliffe (E), Percent Bias and Standard Deviation Ratio were used to measure the model efficiency, giving values of 0.880, 0.260 and 0.346 respectively which resulted to a "very good" performance rating of the model. The flood inundation model was simulated using Legazpi Rainfall Intensity Duration Frequency Curves (RIDF) and HEC-RAS software developed by the US Army corps of Engineers (USACE). This hydrologic model will provide the Municipal Disaster Risk Reduction Management Office (MDRRMO), Local Government units (LGUs) and the community a tool for the prediction of runoff in the area.

  18. Towards improved parameterization of a macroscale hydrologic model in a discontinuous permafrost boreal forest ecosystem (United States)

    Endalamaw, Abraham; Bolton, W. Robert; Young-Robertson, Jessica M.; Morton, Don; Hinzman, Larry; Nijssen, Bart


    Modeling hydrological processes in the Alaskan sub-arctic is challenging because of the extreme spatial heterogeneity in soil properties and vegetation communities. Nevertheless, modeling and predicting hydrological processes is critical in this region due to its vulnerability to the effects of climate change. Coarse-spatial-resolution datasets used in land surface modeling pose a new challenge in simulating the spatially distributed and basin-integrated processes since these datasets do not adequately represent the small-scale hydrological, thermal, and ecological heterogeneity. The goal of this study is to improve the prediction capacity of mesoscale to large-scale hydrological models by introducing a small-scale parameterization scheme, which better represents the spatial heterogeneity of soil properties and vegetation cover in the Alaskan sub-arctic. The small-scale parameterization schemes are derived from observations and a sub-grid parameterization method in the two contrasting sub-basins of the Caribou Poker Creek Research Watershed (CPCRW) in Interior Alaska: one nearly permafrost-free (LowP) sub-basin and one permafrost-dominated (HighP) sub-basin. The sub-grid parameterization method used in the small-scale parameterization scheme is derived from the watershed topography. We found that observed soil thermal and hydraulic properties - including the distribution of permafrost and vegetation cover heterogeneity - are better represented in the sub-grid parameterization method than the coarse-resolution datasets. Parameters derived from the coarse-resolution datasets and from the sub-grid parameterization method are implemented into the variable infiltration capacity (VIC) mesoscale hydrological model to simulate runoff, evapotranspiration (ET), and soil moisture in the two sub-basins of the CPCRW. Simulated hydrographs based on the small-scale parameterization capture most of the peak and low flows, with similar accuracy in both sub-basins, compared to

  19. Towards improved parameterization of a macroscale hydrologic model in a discontinuous permafrost boreal forest ecosystem

    Directory of Open Access Journals (Sweden)

    A. Endalamaw


    Full Text Available Modeling hydrological processes in the Alaskan sub-arctic is challenging because of the extreme spatial heterogeneity in soil properties and vegetation communities. Nevertheless, modeling and predicting hydrological processes is critical in this region due to its vulnerability to the effects of climate change. Coarse-spatial-resolution datasets used in land surface modeling pose a new challenge in simulating the spatially distributed and basin-integrated processes since these datasets do not adequately represent the small-scale hydrological, thermal, and ecological heterogeneity. The goal of this study is to improve the prediction capacity of mesoscale to large-scale hydrological models by introducing a small-scale parameterization scheme, which better represents the spatial heterogeneity of soil properties and vegetation cover in the Alaskan sub-arctic. The small-scale parameterization schemes are derived from observations and a sub-grid parameterization method in the two contrasting sub-basins of the Caribou Poker Creek Research Watershed (CPCRW in Interior Alaska: one nearly permafrost-free (LowP sub-basin and one permafrost-dominated (HighP sub-basin. The sub-grid parameterization method used in the small-scale parameterization scheme is derived from the watershed topography. We found that observed soil thermal and hydraulic properties – including the distribution of permafrost and vegetation cover heterogeneity – are better represented in the sub-grid parameterization method than the coarse-resolution datasets. Parameters derived from the coarse-resolution datasets and from the sub-grid parameterization method are implemented into the variable infiltration capacity (VIC mesoscale hydrological model to simulate runoff, evapotranspiration (ET, and soil moisture in the two sub-basins of the CPCRW. Simulated hydrographs based on the small-scale parameterization capture most of the peak and low flows, with similar accuracy in both sub

  20. The IAHS Decade on Prediction in Ungauged Basins (PUB) as a key U.S. Contribution to International Hydrology (United States)

    McDonnell, J. J.; Sivapalan, M.; Bloschl, G.


    The IAHS Decade on Prediction in Ungauged Basins (PUB) is a 10 year effort by the international research community to change fundamentally, the practice of hydrology: to focus on uncertainty reduction in all its forms and shift hydrology from the use of calibration reliant models to schemes that can be used without the aid of calibration data. Over the past 5 years, U.S. scientists have helped lead the six main science themes of PUB: development of watershed classification measures, conceptualization of process heterogeneity, development of model uncertainty diagnostics, development and use of new data collection approaches, development of new hydrological theory and development of new model approaches. The PUB science plan has served as a community science exemplar for CUAHSI and the recent USA PUB Workshop has influenced programmatic thinking at NSF. PUB is now formally linked to other international programs where U.S. scientists are playing leadership roles (e.g. UNESCO's HELP and FRIEND programs). PUB has a Secretariat funded by the International Water Management Institute, located in Colombo Sri Lanka. PUB has also launched the Blue Nile initiative where U.S. scientists now have a vehicle for participation in coordinated hydrological science in developing world. Several U.S.-based PUB Working Groups are now underway, including the Slope Intercomparison Experiment, the Low Flow Working Group, the Model Diagnostics Working Group and the Watershed Classification Working Group, among others. This presentation is designed to bring attention to these activities for AGU members who are not aware of them and to foster even greater participation by the U.S. community in this multi-national program.

  1. Impact of precipitation spatial resolution on the hydrological response of an integrated distributed water resources model

    DEFF Research Database (Denmark)

    Fu, Suhua; Sonnenborg, Torben; Jensen, Karsten Høgh


    Precipitation is a key input variable to hydrological models, and the spatial variability of the input is expected to impact the hydrological response predicted by a distributed model. In this study, the effect of spatial resolution of precipitation on runoff , recharge and groundwater head...... of the total catchment and runoff discharge hydrograph at watershed outlet. On the other hand, groundwater recharge and groundwater head were both aff ected. The impact of the spatial resolution of precipitation input is reduced with increasing catchment size. The effect on stream discharge is relatively low......, groundwater recharge, and groundwater head were also affected by the method for correction of systematic errors in precipitation measurements. The results underscored the importance of using a spatial resolution of the precipitation input that captures the overall precipitation characteristics...

  2. Impact of model structure on flow simulation and hydrological realism: from a lumped to a semi-distributed approach (United States)

    Garavaglia, Federico; Le Lay, Matthieu; Gottardi, Fréderic; Garçon, Rémy; Gailhard, Joël; Paquet, Emmanuel; Mathevet, Thibault


    Model intercomparison experiments are widely used to investigate and improve hydrological model performance. However, a study based only on runoff simulation is not sufficient to discriminate between different model structures. Hence, there is a need to improve hydrological models for specific streamflow signatures (e.g., low and high flow) and multi-variable predictions (e.g., soil moisture, snow and groundwater). This study assesses the impact of model structure on flow simulation and hydrological realism using three versions of a hydrological model called MORDOR: the historical lumped structure and a revisited formulation available in both lumped and semi-distributed structures. In particular, the main goal of this paper is to investigate the relative impact of model equations and spatial discretization on flow simulation, snowpack representation and evapotranspiration estimation. Comparison of the models is based on an extensive dataset composed of 50 catchments located in French mountainous regions. The evaluation framework is founded on a multi-criterion split-sample strategy. All models were calibrated using an automatic optimization method based on an efficient genetic algorithm. The evaluation framework is enriched by the assessment of snow and evapotranspiration modeling against in situ and satellite data. The results showed that the new model formulations perform significantly better than the initial one in terms of the various streamflow signatures, snow and evapotranspiration predictions. The semi-distributed approach provides better calibration-validation performance for the snow cover area, snow water equivalent and runoff simulation, especially for nival catchments.

  3. Hierarchical mixture of experts and diagnostic modeling approach to reduce hydrologic model structural uncertainty: STRUCTURAL UNCERTAINTY DIAGNOSTICS

    Energy Technology Data Exchange (ETDEWEB)

    Moges, Edom [Civil and Environmental Engineering Department, Washington State University, Richland Washington USA; Demissie, Yonas [Civil and Environmental Engineering Department, Washington State University, Richland Washington USA; Li, Hong-Yi [Hydrology Group, Pacific Northwest National Laboratory, Richland Washington USA


    In most water resources applications, a single model structure might be inadequate to capture the dynamic multi-scale interactions among different hydrological processes. Calibrating single models for dynamic catchments, where multiple dominant processes exist, can result in displacement of errors from structure to parameters, which in turn leads to over-correction and biased predictions. An alternative to a single model structure is to develop local expert structures that are effective in representing the dominant components of the hydrologic process and adaptively integrate them based on an indicator variable. In this study, the Hierarchical Mixture of Experts (HME) framework is applied to integrate expert model structures representing the different components of the hydrologic process. Various signature diagnostic analyses are used to assess the presence of multiple dominant processes and the adequacy of a single model, as well as to identify the structures of the expert models. The approaches are applied for two distinct catchments, the Guadalupe River (Texas) and the French Broad River (North Carolina) from the Model Parameter Estimation Experiment (MOPEX), using different structures of the HBV model. The results show that the HME approach has a better performance over the single model for the Guadalupe catchment, where multiple dominant processes are witnessed through diagnostic measures. Whereas, the diagnostics and aggregated performance measures prove that French Broad has a homogeneous catchment response, making the single model adequate to capture the response.

  4. Communication of uncertainty in hydrological predictions: a user-driven example web service for Europe (United States)

    Fry, Matt; Smith, Katie; Sheffield, Justin; Watts, Glenn; Wood, Eric; Cooper, Jon; Prudhomme, Christel; Rees, Gwyn


    Water is fundamental to society as it impacts on all facets of life, the economy and the environment. But whilst it creates opportunities for growth and life, it can also cause serious damages to society and infrastructure through extreme hydro-meteorological events such as floods or droughts. Anticipation of future water availability and extreme event risks would both help optimise growth and limit damage through better preparedness and planning, hence providing huge societal benefits. Recent scientific research advances make it now possible to provide hydrological outlooks at monthly to seasonal lead time, and future projections up to the end of the century accounting for climatic changes. However, high uncertainty remains in the predictions, which varies depending on location, time of the year, prediction range and hydrological variable. It is essential that this uncertainty is fully understood by decision makers so they can account for it in their planning. Hence, the challenge is to finds ways to communicate such uncertainty for a range of stakeholders with different technical background and environmental science knowledge. The project EDgE (End-to end Demonstrator for improved decision making in the water sector for Europe) funded by the Copernicus programme (C3S) is a proof-of-concept project that develops a unique service to support decision making for the water sector at monthly to seasonal and to multi-decadal lead times. It is a mutual effort of co-production between hydrologists and environmental modellers, computer scientists and stakeholders representative of key decision makers in Europe for the water sector. This talk will present the iterative co-production process of a web service that serves the need of the user community. Through a series of Focus Group meetings in Spain, Norway and the UK, options for visualising the hydrological predictions and associated uncertainties are presented and discussed first as mock-up dash boards, off-line tools

  5. A Hydrological Modeling Framework for Flood Risk Assessment for Japan (United States)

    Ashouri, H.; Chinnayakanahalli, K.; Chowdhary, H.; Sen Gupta, A.


    Flooding has been the most frequent natural disaster that claims lives and imposes significant economic losses to human societies worldwide. Japan, with an annual rainfall of up to approximately 4000 mm is extremely vulnerable to flooding. The focus of this research is to develop a macroscale hydrologic model for simulating flooding toward an improved understanding and assessment of flood risk across Japan. The framework employs a conceptual hydrological model, known as the Probability Distributed Model (PDM), as well as the Muskingum-Cunge flood routing procedure for simulating streamflow. In addition, a Temperature-Index model is incorporated to account for snowmelt and its contribution to streamflow. For an efficient calibration of the model, in terms of computational timing and convergence of the parameters, a set of A Priori parameters is obtained based on the relationships between the model parameters and the physical properties of watersheds. In this regard, we have implemented a particle tracking algorithm and a statistical model which use high resolution Digital Terrain Models to estimate different time related parameters of the model such as time to peak of the unit hydrograph. In addition, global soil moisture and depth data are used to generate A Priori estimation of maximum soil moisture capacity, an important parameter of the PDM model. Once the model is calibrated, its performance is examined during the Typhoon Nabi which struck Japan in September 2005 and caused severe flooding throughout the country. The model is also validated for the extreme precipitation event in 2012 which affected Kyushu. In both cases, quantitative measures show that simulated streamflow depicts good agreement with gauge-based observations. The model is employed to simulate thousands of possible flood events for the entire Japan which makes a basis for a comprehensive flood risk assessment and loss estimation for the flood insurance industry.

  6. Impact of wetlands mapping on parameterization of hydrologic simulation models (United States)

    Viger, R.


    Wetlands and other surface depressions can impact hydrologic response within the landscape in a number of ways, such as intercepting runoff and near-surface flows or changing the potential for evaporation and seepage into the soil. The role of these features is increasingly being integrated into hydrological simulation models, such as the USGS Precipitation-Runoff Modeling System (PRMS) and the Soil Water Assessment Tool (SWAT), and applied to landscapes where wetlands are dominating features. Because the extent of these features varies widely through time, many modeling applications rely on delineations of the maximum possible extent to define total capacity of a model's spatial response unit. This poster presents an evaluation of several wetland map delineations for the Pipestem River basin in the North Dakota Prairie-pothole region. The featured data sets include the US Fish and Wildlife Service National Wetlands Inventory (NWI), surface water bodies extracted from the US Geological Survey National Hydrography Dataset (NHD), and elevation depressions extracted from 1 meter LiDAR data for the area. In addition to characterizing differences in the quality of these datasets, the poster will assess the impact of these differences when parameters are derived from them for the spatial response units of the PRMS model.

  7. Enhanced Identification of hydrologic models using streamflow and satellite water storage data: a multi-objective calibration approach (United States)

    Yassin, F. A.; Razavi, S.; Sapriza, G.; Wheater, H. S.


    The conventional procedure for parameter identification of hydrological processes through conditioning only to streamflow data is challenging in physically based distributed hydrologic modelling. The challenge increases for modeling the landscapes where vertical processes dominate horizontal processes, leading to high uncertainties in modelled state variables, vertical fluxes and hence parameter estimates. Such behavior is common in modeling the prairie region of the Saskatchewan River Basin (SaskRB, our case study), Canada, where hydrologic connectivity and vertical fluxes are mainly controlled by surface and sub-surface water storage. To address this challenge, we developed a novel multi-criteria framework that utilizes total column water storage derived from the GRACE satellite, in addition to streamflows. We used a multi-objective optimization algorithm (Borg) and a recently-developed global sensitivity analysis approach (VARS) to effectively identify the model parameters and characterize their significance in model performance. We applied this framework in the calibration of a Land Surface Scheme-Hydrology model, MESH (Modélisation Environmentale Communautaire - Surface and Hydrology) to a sub-watershed of SaskRB. Results showed that the developed framework is superior to the conventional approach of calibration to streamflows. The new framework allowed us to find optimal solutions that effectively constrain the posterior parameter space and are representative of storage and streamflow performance criteria, yielding more credible prediction with reduced uncertainty of modeled storage and evaporation.

  8. The state of the art of flood forecasting - Hydrological Ensemble Prediction Systems (United States)

    Thielen-Del Pozo, J.; Pappenberger, F.; Salamon, P.; Bogner, K.; Burek, P.; de Roo, A.


    Flood forecasting systems form a key part of ‘preparedness' strategies for disastrous floods and provide hydrological services, civil protection authorities and the public with information of upcoming events. Provided the warning leadtime is sufficiently long, adequate preparatory actions can be taken to efficiently reduce the impacts of the flooding. Because of the specific characteristics of each catchment, varying data availability and end-user demands, the design of the best flood forecasting system may differ from catchment to catchment. However, despite the differences in concept and data needs, there is one underlying issue that spans across all systems. There has been an growing awareness and acceptance that uncertainty is a fundamental issue of flood forecasting and needs to be dealt with at the different spatial and temporal scales as well as the different stages of the flood generating processes. Today, operational flood forecasting centres change increasingly from single deterministic forecasts to probabilistic forecasts with various representations of the different contributions of uncertainty. The move towards these so-called Hydrological Ensemble Prediction Systems (HEPS) in flood forecasting represents the state of the art in forecasting science, following on the success of the use of ensembles for weather forecasting (Buizza et al., 2005) and paralleling the move towards ensemble forecasting in other related disciplines such as climate change predictions. The use of HEPS has been internationally fostered by initiatives such as "The Hydrologic Ensemble Prediction Experiment" (HEPEX), created with the aim to investigate how best to produce, communicate and use hydrologic ensemble forecasts in hydrological short-, medium- und long term prediction of hydrological processes. The advantages of quantifying the different contributions of uncertainty as well as the overall uncertainty to obtain reliable and useful flood forecasts also for extreme events

  9. Modeling Hydraulic Properties and Hydrologic Processes in Shrink-swell Clay Soils (United States)

    Stewart, R. D.; Rupp, D. E.; Abou Najm, M. R.; Selker, J. S.


    Recognizing the need for tractable models that accurately describe the hydrologic behaviors of shrink-swell soils, we propose a new conceptual model that identifies up to five porosity domains based on morphological and hydrological distinctions. We provide governing equations that predict the porosity distribution as a function of soil water content and six additional parameters, all of which can be determined using laboratory measurements conducted on individual soil samples. We next derive new expressions for the hydraulic properties of such soils, which can be used to model infiltration at the plot scale. Finally, we incorporate these expressions into new models that can be used to predict and quantify surface runoff (i.e., overland flow) thresholds, and which may be used to reveal the dominant mechanisms by which water moves through clayey soils. Altogether, these models successfully link small-scale shrinkage/swelling behaviors with large-scale processes, and can be applied to such practical applications as converting measurements between gravimetric and volumetric water contents, as well as to predicting field-scale processes such as the sealing of individual cracks.

  10. Development of Turbulent Diffusion Transfer Model to Estimate Hydrologic Budget of Upper Klamath Lake Oregon, USA (United States)

    Sahoo, G. B.; Schladow, G.


    Detailed and accurate hydrologic budgets of lake or reservoirs are essential for sustainable water supply and ecosystem managements due to increasing water demand and uncertainties related to climate change. Ensuring sustainable water allocation to stakeholders requires accurate heat and hydrologic budgets. A number of micrometeorological methods have been developed to approximate heat budget components, such as evaporative and sensible heat loss, that are not directly measurable. Although micrometeorological methods estimate the sensible and evaporative loss well for stationary (i.e. ideal) condition, these methods can rarely be approximated for non-idealized condition. We developed a turbulent diffusion transfer model and coupled to the dynamic lake model (DLM-WQ), developed at UC Davis, with the goal of correctly estimating the hydrologic budget of Upper Klamath Lake Oregon, USA. The measured and DLM-WQ estimated lake water temperatures and water elevation are in excellent agreement with correlation coefficient equals 0.95 and 0.99, respectively. Consistent with previous studies, the sensible and latent heat exchange coefficients were found to be site specific. Estimated lake mixing shows that the lake became strongly stratified during summer (between late April and the end of August). For the hypereutrophic shallow Upper Klamath Lake, longer stratification results in low dissolved oxygen (DO) concentration at the sediment surface causing DO sensitive habitat destruction and ecological problems. The updated DLM-WQ can provide quantitative estimates of hydrologic components and predict the effects of natural- or human-induced changes in one component of the hydrologic cycle on the lake supplies and associated consequences.

  11. Evaluation of SCaMPR Satellite QPEs for Operational Hydrologic Prediction (United States)

    LEE, H.; Zhang, Y.; Seo, D.; Kitzmiller, D. H.; Kuligowski, R. J.; Corby, R.


    National Weather Service (NWS) River Forecast Centers (RFCs) use rain gauge or radar-gauge multi-sensor quantitative precipitation estimates (QPEs) as the primary rainfall input to their operational hydrologic models. In areas with poor radar and rain gauge coverage, satellite-based QPEs are a potential alternative. In this work, we evaluated the utility of satellite-based QPEs produced via the Self-Calibrating Multivariate Precipitation Retrieval (SCaMPR) algorithm for operational hydrologic modeling for a set of basins in Texas and Louisiana for the period of 2000-7. First, we assessed the relative accuracy of two sets of SCaMPR QPEs versus gauge-only QPE, with operational multi-sensor QPEs as the reference. One set used only operational polar orbiting satellite microwave input as the predictors, the other included Tropical Rainfall Measuring Mission (TRMM) rain rates in the calibration process. We then performed hydrologic simulations using these QPEs and evaluated the simulations. Results indicated that a) SCaMPR QPEs showed better/worse skill than the gauge-only QPEs in resolving heavy precipitation at 1-h/24-h time intervals in terms of Critical Success Index (CSI); b) SCaMPR QPEs underperformed gauge-only QPEs in simulating flood events; and c) ingesting TRMM rainfall rates helped enhance the hydrologic utility of SCaMPR QPE, by mitigating the positive bias of SCaMPR QPEs, elevating the detection rates of heavy rainfall, and improving the simulation of flood discharge. Our findings suggest that the superior performance of gauge-only QPEs versus SCaMPR in hydrologic simulations is tied to its better accuracy at 24-h scale. The implication of the scale dependence in the relative performance of SCaMPR QPEs to their potential hydrologic utility is discussed.

  12. Hydrologic Modeling in the Kenai River Watershed using Event Based Calibration (United States)

    Wells, B.; Toniolo, H. A.; Stuefer, S. L.


    Understanding hydrologic changes is key for preparing for possible future scenarios. On the Kenai Peninsula in Alaska the yearly salmon runs provide a valuable stimulus to the economy. It is the focus of a large commercial fishing fleet, but also a prime tourist attraction. Modeling of anadromous waters provides a tool that assists in the prediction of future salmon run size. Beaver Creek, in Kenai, Alaska, is a lowlands stream that has been modeled using the Army Corps of Engineers event based modeling package HEC-HMS. With the use of historic precipitation and discharge data, the model was calibrated to observed discharge values. The hydrologic parameters were measured in the field or calculated, while soil parameters were estimated and adjusted during the calibration. With the calibrated parameter for HEC-HMS, discharge estimates can be used by other researches studying the area and help guide communities and officials to make better-educated decisions regarding the changing hydrology in the area and the tied economic drivers.

  13. Applying sequential Monte Carlo methods into a distributed hydrologic model: lagged particle filtering approach with regularization

    Directory of Open Access Journals (Sweden)

    S. J. Noh


    Full Text Available Data assimilation techniques have received growing attention due to their capability to improve prediction. Among various data assimilation techniques, sequential Monte Carlo (SMC methods, known as "particle filters", are a Bayesian learning process that has the capability to handle non-linear and non-Gaussian state-space models. In this paper, we propose an improved particle filtering approach to consider different response times of internal state variables in a hydrologic model. The proposed method adopts a lagged filtering approach to aggregate model response until the uncertainty of each hydrologic process is propagated. The regularization with an additional move step based on the Markov chain Monte Carlo (MCMC methods is also implemented to preserve sample diversity under the lagged filtering approach. A distributed hydrologic model, water and energy transfer processes (WEP, is implemented for the sequential data assimilation through the updating of state variables. The lagged regularized particle filter (LRPF and the sequential importance resampling (SIR particle filter are implemented for hindcasting of streamflow at the Katsura catchment, Japan. Control state variables for filtering are soil moisture content and overland flow. Streamflow measurements are used for data assimilation. LRPF shows consistent forecasts regardless of the process noise assumption, while SIR has different values of optimal process noise and shows sensitive variation of confidential intervals, depending on the process noise. Improvement of LRPF forecasts compared to SIR is particularly found for rapidly varied high flows due to preservation of sample diversity from the kernel, even if particle impoverishment takes place.

  14. Towards robust quantification and reduction of uncertainty in hydrologic predictions: Integration of particle Markov chain Monte Carlo and factorial polynomial chaos expansion (United States)

    Wang, S.; Huang, G. H.; Baetz, B. W.; Ancell, B. C.


    The particle filtering techniques have been receiving increasing attention from the hydrologic community due to its ability to properly estimate model parameters and states of nonlinear and non-Gaussian systems. To facilitate a robust quantification of uncertainty in hydrologic predictions, it is necessary to explicitly examine the forward propagation and evolution of parameter uncertainties and their interactions that affect the predictive performance. This paper presents a unified probabilistic framework that merges the strengths of particle Markov chain Monte Carlo (PMCMC) and factorial polynomial chaos expansion (FPCE) algorithms to robustly quantify and reduce uncertainties in hydrologic predictions. A Gaussian anamorphosis technique is used to establish a seamless bridge between the data assimilation using the PMCMC and the uncertainty propagation using the FPCE through a straightforward transformation of posterior distributions of model parameters. The unified probabilistic framework is applied to the Xiangxi River watershed of the Three Gorges Reservoir (TGR) region in China to demonstrate its validity and applicability. Results reveal that the degree of spatial variability of soil moisture capacity is the most identifiable model parameter with the fastest convergence through the streamflow assimilation process. The potential interaction between the spatial variability in soil moisture conditions and the maximum soil moisture capacity has the most significant effect on the performance of streamflow predictions. In addition, parameter sensitivities and interactions vary in magnitude and direction over time due to temporal and spatial dynamics of hydrologic processes.

  15. How far can we go in hydrological modelling without any knowledge of runoff formation processes? (United States)

    Ayzel, Georgy


    Hydrological modelling is a challenging scientific issue for the last 50 years and tend to be it further because of the highest level of runoff formation processes complexity at the different spatio-temporal scales. Enormous number of modelling-related papers have submitted to the top-ranked journals every year, but in this publication speed race authors have pay increasing attention to the models and data they use by itself rather than underlying watershed processes. Great community effort of the free and open-source models sharing with high availability of hydrometeorological data sources led to conceptual shifting paradigm of hydrological science to the technical-oriented direction. In the third-world countries this shifting is more clear by the reason of field studies absence and obligatory requirement of practical significance of the research supported by the government funds. As a result we get a state of hydrological modelling discipline closer to the aim of high Nash-Sutcliffe efficiency (NSE) achievement rather than watershed processes understanding. Both lumped physically-based land-surface model SWAP (Soil Water - Atmosphere - Plants) and SCE-UA (Shuffled Complex Evolution method developed at The University of Arizona) technique for robust model parameters search were used for the runoff modelling of 323 MOPEX watersheds. No one special data analysis and expert knowledge-based decisions were not performed. Median value of NSE is 0.652 and 90% of watersheds have efficiency bigger than 0.5. Thus without any information of particular features of each watershed satisfactory modelling results were obtained. To prove our conclusions we build cutting-edge conceptual rainfall-runoff model based on decision trees and adaptive boosting machine learning algorithms for the one small watershed in USA. No one special data analysis or feature engineering was not performed too. Obtained results demonstrate great model prediction power both for learning and testing

  16. Modeling of subglacial hydrological development following rapid supraglacial lake drainage (United States)

    Dow, C. F.; Kulessa, B.; Rutt, I. C.; Tsai, V. C.; Pimentel, S.; Doyle, S. H.; van As, D.; Lindbäck, K.; Pettersson, R.; Jones, G. A.; Hubbard, A.


    The rapid drainage of supraglacial lakes injects substantial volumes of water to the bed of the Greenland ice sheet over short timescales. The effect of these water pulses on the development of basal hydrological systems is largely unknown. To address this, we develop a lake drainage model incorporating both (1) a subglacial radial flux element driven by elastic hydraulic jacking and (2) downstream drainage through a linked channelized and distributed system. Here we present the model and examine whether substantial, efficient subglacial channels can form during or following lake drainage events and their effect on the water pressure in the surrounding distributed system. We force the model with field data from a lake drainage site, 70 km from the terminus of Russell Glacier in West Greenland. The model outputs suggest that efficient subglacial channels do not readily form in the vicinity of the lake during rapid drainage and instead water is evacuated primarily by a transient turbulent sheet and the distributed system. Following lake drainage, channels grow but are not large enough to reduce the water pressure in the surrounding distributed system, unless preexisting channels are present throughout the domain. Our results have implications for the analysis of subglacial hydrological systems in regions where rapid lake drainage provides the primary mechanism for surface-to-bed connections.

  17. Spatial interpolation schemes of daily precipitation for hydrologic modeling (United States)

    Hwang, Y.; Clark, M.R.; Rajagopalan, B.; Leavesley, G.


    Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. We compare and contrast the performance of regression-based statistical methods for the spatial estimation of precipitation in two hydrologically different basins and confirmed that widely used regression-based estimation schemes fail to describe the realistic spatial variability of daily precipitation field. The methods assessed are: (1) inverse distance weighted average; (2) multiple linear regression (MLR); (3) climatological MLR; and (4) locally weighted polynomial regression (LWP). In order to improve the performance of the interpolations, the authors propose a two-step regression technique for effective daily precipitation estimation. In this simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before estimate the amount of precipitation separately on wet days. This process generated the precipitation occurrence, amount, and spatial correlation effectively. A distributed hydrologic model (PRMS) was used for the impact analysis in daily time step simulation. Multiple simulations suggested noticeable differences between the input alternatives generated by three different interpolation schemes. Differences are shown in overall simulation error against the observations, degree of explained variability, and seasonal volumes. Simulated streamflows also showed different characteristics in mean, maximum, minimum, and peak flows. Given the same parameter optimization technique, LWP input showed least streamflow error in Alapaha basin and CMLR input showed least error (still very close to LWP) in Animas basin. All of the two-step interpolation inputs resulted in lower streamflow error compared to the directly interpolated inputs. ?? 2011 Springer-Verlag.

  18. Monitoring soil moisture through assimilation of active microwave remote sensing observation into a hydrologic model (United States)

    Liu, Qian; Zhao, Yingshi


    Soil moisture can be estimated from point measurements, hydrologic models, and remote sensing. Many researches indicated that the most promising approach for soil moisture is the integration of remote sensing surface soil moisture data and computational modeling. Although many researches were conducted using passive microwave remote sensing data in soil moisture assimilation with coarse spatial resolution, few researches were carried out using active microwave remote sensing observation. This research developed and tested an operational approach of assimilation for soil moisture prediction using active microwave remote sensing data ASAR (Advanced Synthetic Aperture Radar) in Heihe Watershed. The assimilation was based on ensemble Kalman filter (EnKF), a forward radiative transfer model and the Distributed Hydrology Soil Vegetation Model (DHSVM). The forward radiative transfer model, as a semi-empirical backscattering model, was used to eliminate the effect of surface roughness and vegetation cover on the backscatter coefficient. The impact of topography on soil water movement and the vertical and lateral exchange of soil water were considered. We conducted experiments to assimilate active microwave remote sensing data (ASAR) observation into a hydrologic model at two field sites, which had different underlying conditions. The soil moisture ground-truth data were collected through the field Time Domain Reflectometry (TDR) tools, and were used to assess the assimilation method. The temporal evolution of soil moisture measured at point-based monitoring locations were compared with EnKF based model predictions. The results indicated that the estimate of soil moisture was improved through assimilation with ASAR observation and the soil moisture based on data assimilation can be monitored in moderate spatial resolution.

  19. Impacts of Polarimetric CASA Radar Observations on a Distributed Hydrologic Model (United States)

    Chandrasekar, Venkatachalam; Chen, Haonan; Seo, Dong-Jun


    Radar can monitor the atmospheric conditions of a wide area very quickly and provide advanced observations and warnings for the precipitation systems at high spatial resolution. Over the past two decades, significant progress has been made in dual-polarization radar quantitative precipitation estimations (QPE). The polarimetric radar observations can provide more information on the drop size distribution and hydrometeor classifications over traditional Z-R methods. Among different rainfall algorithms, the Kdp-based QPE was proved to be immune to the partial beam blockage and hail contamination, and it is also less prone to the calibration errors. The networked Kdp-based QPE system developed by the U.S. National Science Foundation Engineering Research Center (NSF-ERC) for Collaborative Adaptive Sensing of the Atmosphere (CASA) has shown a great improvement compared with state-of-the-art. The high spatial and temporal resolution rainfall products from CASA QPE system can serve as a reliable data input for distributed hydrological models. The Research Distributed Hydrologic Model (RDHM) developed by the U.S. National Weather Service (NWS) Office of Hydrologic Development (OHD) is a promising tool for generating streamflow and other hydrological information such as soil moisture, etc. It can incorporate the heat transfer (HT) dynamics with the Sacramento soil moisture accounting model (SAC) to simulate rainfall-runoff and channel routing models for routing streamflow. In this research, the SAC-HT model was forced using hourly rainfall estimates produced by the CASA X-band dual-polarization radar network, for the purpose of predicting hydrological response and dealing with the flash flood issues. This paper will present a brief overview of the CASA QPE system and its various products. Then, the impacts of CASA QPE on SAC-HT model are mainly focused on, by using the networked polarimetric radar observations collected in IP-1 test bed in Southwestern Oklahoma. The "first

  20. Modeling watershed-scale solute transport using an integrated, process-based hydrologic model with applications to bacterial fate and transport (United States)

    Niu, Jie; Phanikumar, Mantha S.


    Distributed hydrologic models that simulate fate and transport processes at sub-daily timescales are useful tools for estimating pollutant loads exported from watersheds to lakes and oceans downstream. There has been considerable interest in the application of integrated process-based hydrologic models in recent years. While the models have been applied to address questions of water quantity and to better understand linkages between hydrology and land surface processes, routine applications of these models to address water quality issues are currently limited. In this paper, we first describe a general process-based watershed-scale solute transport modeling framework, based on an operator splitting strategy and a Lagrangian particle transport method combined with dispersion and reactions. The transport and the hydrologic modules are tightly coupled and the interactions among different hydrologic components are explicitly modeled. We test transport modules using data from plot-scale experiments and available analytical solutions for different hydrologic domains. The numerical solutions are also compared with an analytical solution for groundwater transit times with interactions between surface and subsurface flows. Finally, we demonstrate the application of the model to simulate bacterial fate and transport in the Red Cedar River watershed in Michigan and test hypotheses about sources and transport pathways. The watershed bacterial fate and transport model is expected to be useful for making near real-time predictions at marine and freshwater beaches.

  1. Role-play games, experiments, workshops, blog posts: how community activities in HEPEX contribute to advance hydrologic ensemble prediction (United States)

    Ramos, Maria-Helena; Wetterhall, Fredrik; Wood, Andy; Wang, Qj; Pappenberger, Florian; Verkade, Jan


    Since 2004, HEPEX (Hydrologic Ensemble Prediction Experiment) has been fostering a community of researchers and practitioners around the world. Through the years, it has contributed to establish a more integrative view of hydrological forecasting, where data assimilation, hydro-meteorological modelling chains, post-processing techniques, expert knowledge, and decision support systems are connected to enhance operational systems and water management applications. Here we present the community activities in HEPEX that have contributed to strengthening this unfunded/volunteer effort for more than a decade. It includes the organization of workshops, conference sessions, testbeds and inter-comparison experiments. More recently, HEPEX has also prompted the development of several publicly available role-play games and, since 2013, it has been running a blog portal (, which is used as an intersection point for members. Through this website, members can continuously share their research, make announcements, report on workshops, projects and meetings, and hear about related research and operational challenges. It also creates a platform for early career scientists to become increasingly involved in hydrological forecasting science and applications.

  2. Improved hydrological-model design by integrating nutrient and water flow (United States)

    Arheimer, B.; Lindstrom, G.


    The potential of integrating hydrologic and nutrient concentration data to better understand patterns of catchment response and to better design hydrological modeling was explored using a national multi-basin model system for Sweden, called ';S-HYPE'. The model system covers more than 450 000 km2 and produce daily values of nutrient concentration and water discharge in 37 000 catchments from 1961 and onwards. It is based on the processed-based and semi-distributed HYdrological Predictions for the Environment (HYPE) code. The model is used operationally for assessments of water status or climate change impacts and for forecasts by the national warning service of floods, droughts and fire. The first model was launched in 2008, but S-HYPE is continuously improved and released in new versions every second year. Observations are available in 400 sites for daily water discharge and some 900 sites for monthly grab samples of nutrient concentrations. The latest version (2012) has an average NSE for water discharge of 0.7 and an average relative error of 5%, including both regulated and unregulated rivers with catchments from ten to several thousands of km2 and various landuse. The daily relative errors of nutrient concentrations are on average 20% for total Nitrogen and 35% for total Phosphorus. This presentation will give practical examples of how the nutrient data has been used to trace errors or inadequate parameter values in the hydrological model. Since 2008 several parts of the model structure has been reconsidered both in the source code, parameter values and input data of catchment characteristics. In this process water quality has been guiding much of the overall model design of catchment hydrological functions and routing along the river network. The model structure has thus been developed iteratively when evaluating results and checking time-series. Examples of water quality driven improvements will be given for estimation of vertical flow paths, such as

  3. Evaluating uncertainty estimates in hydrologic models: borrowing measures from the forecast verification community

    Directory of Open Access Journals (Sweden)

    K. J. Franz


    Full Text Available The hydrologic community is generally moving towards the use of probabilistic estimates of streamflow, primarily through the implementation of Ensemble Streamflow Prediction (ESP systems, ensemble data assimilation methods, or multi-modeling platforms. However, evaluation of probabilistic outputs has not necessarily kept pace with ensemble generation. Much of the modeling community is still performing model evaluation using standard deterministic measures, such as error, correlation, or bias, typically applied to the ensemble mean or median. Probabilistic forecast verification methods have been well developed, particularly in the atmospheric sciences, yet few have been adopted for evaluating uncertainty estimates in hydrologic model simulations. In the current paper, we overview existing probabilistic forecast verification methods and apply the methods to evaluate and compare model ensembles produced from two different parameter uncertainty estimation methods: the Generalized Uncertainty Likelihood Estimator (GLUE, and the Shuffle Complex Evolution Metropolis (SCEM. Model ensembles are generated for the National Weather Service SACramento Soil Moisture Accounting (SAC-SMA model for 12 forecast basins located in the Southeastern United States. We evaluate the model ensembles using relevant metrics in the following categories: distribution, correlation, accuracy, conditional statistics, and categorical statistics. We show that the presented probabilistic metrics are easily adapted to model simulation ensembles and provide a robust analysis of model performance associated with parameter uncertainty. Application of these methods requires no information in addition to what is already available as part of traditional model validation methodology and considers the entire ensemble or uncertainty range in the approach.

  4. Evaluating uncertainty estimates in hydrologic models: borrowing measures from the forecast verification community (United States)

    Franz, K. J.; Hogue, T. S.


    The hydrologic community is generally moving towards the use of probabilistic estimates of streamflow, primarily through the implementation of Ensemble Streamflow Prediction (ESP) systems, ensemble data assimilation methods, or multi-modeling platforms. However, evaluation of probabilistic outputs has not necessarily kept pace with ensemble generation. Much of the modeling community is still performing model evaluation using standard deterministic measures, such as error, correlation, or bias, typically applied to the ensemble mean or median. Probabilistic forecast verification methods have been well developed, particularly in the atmospheric sciences, yet few have been adopted for evaluating uncertainty estimates in hydrologic model simulations. In the current paper, we overview existing probabilistic forecast verification methods and apply the methods to evaluate and compare model ensembles produced from two different parameter uncertainty estimation methods: the Generalized Uncertainty Likelihood Estimator (GLUE), and the Shuffle Complex Evolution Metropolis (SCEM). Model ensembles are generated for the National Weather Service SACramento Soil Moisture Accounting (SAC-SMA) model for 12 forecast basins located in the Southeastern United States. We evaluate the model ensembles using relevant metrics in the following categories: distribution, correlation, accuracy, conditional statistics, and categorical statistics. We show that the presented probabilistic metrics are easily adapted to model simulation ensembles and provide a robust analysis of model performance associated with parameter uncertainty. Application of these methods requires no information in addition to what is already available as part of traditional model validation methodology and considers the entire ensemble or uncertainty range in the approach.

  5. Dynamic Hydrological Modeling in Drylands with TRMM Based Rainfall

    Directory of Open Access Journals (Sweden)

    Elena Tarnavsky


    Full Text Available This paper introduces and evaluates DryMOD, a dynamic water balance model of the key hydrological process in drylands that is based on free, public-domain datasets. The rainfall model of DryMOD makes optimal use of spatially disaggregated Tropical Rainfall Measuring Mission (TRMM datasets to simulate hourly rainfall intensities at a spatial resolution of 1-km. Regional-scale applications of the model in seasonal catchments in Tunisia and Senegal characterize runoff and soil moisture distribution and dynamics in response to varying rainfall data inputs and soil properties. The results highlight the need for hourly-based rainfall simulation and for correcting TRMM 3B42 rainfall intensities for the fractional cover of rainfall (FCR. Without FCR correction and disaggregation to 1 km, TRMM 3B42 based rainfall intensities are too low to generate surface runoff and to induce substantial changes to soil moisture storage. The outcomes from the sensitivity analysis show that topsoil porosity is the most important soil property for simulation of runoff and soil moisture. Thus, we demonstrate the benefit of hydrological investigations at a scale, for which reliable information on soil profile characteristics exists and which is sufficiently fine to account for the heterogeneities of these. Where such information is available, application of DryMOD can assist in the spatial and temporal planning of water harvesting according to runoff-generating areas and the runoff ratio, as well as in the optimization of agricultural activities based on realistic representation of soil moisture conditions.

  6. Hydrological modeling of the Mun River basin in Thailand (United States)

    Akter, Aysha; Babel, Mukand S.


    SummarySources of pollution in river basins are increasing due to rapid changes in land uses and excessive nutrient application to crops which lead to degraded instream water quality. In this connection, the Mun River basin, one of the important and largest river basins in Thailand, has been studied. Comparative figures of nutrients in the Mun's water over a decade showed an increased total nitrogen (TN) and phosphorus (TP) ratio in the Lower Mun region (TN:TP > 14). Laboratory analysis of weekly water samples showed a realistic nutrient response when daily rainfall was compared to the seasonal water quality data collected by the Pollution Control Department (PCD). The Hydrologic Simulation Program - FORTRAN (HSPF) was calibrated and used to assess the effects of different land uses on river water quality. Model parameters related to hydrology and sediment were calibrated and validated using relevant measurements by the Royal Irrigation Department (RID). With a reasonable and acceptable model performance (r2 = 0.62), the highest simulated runoff was observed in urban areas. The trend of agricultural land (as a percentage of total area) - total nitrogen showed a linear relationship of a good correlation (i.e. r2 = 0.85). Based on the findings, it can be concluded that this model is expected to provide vital information for developing suitable land management policies and strategies to improve river water quality.

  7. Disaggregation, aggregation and spatial scaling in hydrological modelling (United States)

    Becker, Alfred; Braun, Peter


    A typical feature of the land surface is its heterogeneity in terms of the spatial variability of land surface characteristics and parameters controlling physical/hydrological, biological, and other related processes. Different forms and degrees of heterogeneity need to be taken into account in hydrological modelling. The first part of the article concerns the conditions under which a disaggregation of the land surface into subareas of uniform or "quasihomogeneous" behaviour (hydrotopes or hydrological response units - HRUs) is indispensable. In a case study in northern Germany, it is shown that forests in contrast to arable land, areas with shallow groundwater in contrast to those with deep, water surfaces and sealed areas should generally be distinguished (disaggregated) in modelling, whereas internal heterogeneities within these hydrotopes can be assessed statistically, e.g., by areal distribution functions (soil water holding capacity, hydraulic conductivity, etc.). Models with hydrotope-specific parameters can be applied to calculate the "vertical" processes (fluxes, storages, etc.), and this, moreover, for hydrotopes of different area, and even for groups of distributed hydrotopes in a reference area (hydrotope classes), provided that the meteorological conditions are similar. Thus, a scaling problem does not really exist in this process domain. The primary domain for the application of scaling laws is that of lateral flows in landscapes and river basins. This is illustrated in the second part of the article, where results of a case study in Bavaria/Germany are presented and discussed. It is shown that scaling laws can be applied efficiently for the determination of the Instantaneous Unit Hydrograph (IUH) of the surface runoff system in river basins: simple scaling for basins larger than 43 km 2, and multiple scaling for smaller basins. Surprisingly, only two parameters were identified as important in the derived relations: the drainage area and, in some

  8. One-Water Hydrologic Flow Model (MODFLOW-OWHM) (United States)

    Hanson, Randall T.; Boyce, Scott E.; Schmid, Wolfgang; Hughes, Joseph D.; Mehl, Steffen W.; Leake, Stanley A.; Maddock, Thomas; Niswonger, Richard G.


    The One-Water Hydrologic Flow Model (MF-OWHM) is a MODFLOW-based integrated hydrologic flow model (IHM) that is the most complete version, to date, of the MODFLOW family of hydrologic simulators needed for the analysis of a broad range of conjunctive-use issues. Conjunctive use is the combined use of groundwater and surface water. MF-OWHM allows the simulation, analysis, and management of nearly all components of human and natural water movement and use in a physically-based supply-and-demand framework. MF-OWHM is based on the Farm Process for MODFLOW-2005 (MF-FMP2) combined with Local Grid Refinement (LGR) for embedded models to allow use of the Farm Process (FMP) and Streamflow Routing (SFR) within embedded grids. MF-OWHM also includes new features such as the Surface-water Routing Process (SWR), Seawater Intrusion (SWI), and Riparian Evapotrasnpiration (RIP-ET), and new solvers such as Newton-Raphson (NWT) and nonlinear preconditioned conjugate gradient (PCGN). This IHM also includes new connectivities to expand the linkages for deformation-, flow-, and head-dependent flows. Deformation-dependent flows are simulated through the optional linkage to simulated land subsidence with a vertically deforming mesh. Flow-dependent flows now include linkages between the new SWR with SFR and FMP, as well as connectivity with embedded models for SFR and FMP through LGR. Head-dependent flows now include a modified Hydrologic Flow Barrier Package (HFB) that allows optional transient HFB capabilities, and the flow between any two layers that are adjacent along a depositional or erosional boundary or displaced along a fault. MF-OWHM represents a complete operational hydrologic model that fully links the movement and use of groundwater, surface water, and imported water for consumption by irrigated agriculture, but also of water used in urban areas and by natural vegetation. Supply and demand components of water use are analyzed under demand-driven and supply

  9. Informing a hydrological model of the Ogooué with multi-mission remote sensing data (United States)

    Kittel, Cecile; Bauer-Gottwein, Peter; Nielsen, Karina; Tøttrup, Christian


    Knowledge on hydrological regimes of river basins is crucial for water management. However, data requirements often limit the applicability of hydrological models in basins with scarce in-situ data. Remote sensing provides a unique possibility to acquire information on hydrological variables in these basins. This study explores how multi-mission remote sensing data can inform a hydrological model. The Ogooué basin in Gabon is used as study area. No previous modelling efforts have been conducted for the basin and only historical flow and precipitation observations are available. Publicly available remote sensing observations are used to parametrize, force, calibrate and validate a hydrological model of the Ogooué. The modelling framework used in the study, is a lumped conceptual rainfall-runoff model based on the Budyko framework coupled to a Muskingum routing scheme. Precipitation is a crucial driver of the land-surface water balance, therefore two satellite-based rainfall estimates, Tropical Rainfall Measuring Mission (TRMM) product 3B42 version 7 and Famine Early Warning System - Rainfall Estimate (FEWS-RFE), are compared. The comparison shows good seasonal and spatial agreement between the products; however, TRMM consistently predicts significantly more precipitation: 1726 mm on average per year against 1556 mm for FEWS-RFE. Best modeling results are obtained with the TRMM precipitation forcing. Model calibration combines historical in-situ flow observations and GRACE total water storage observations using the Jet Propulsion Laboratory (JPL) mascon solution in a multi-objective approach. The two models are calibrated using flow duration curves and climatology benchmarks to overcome the lack of simultaneity between simulated and observed discharge. The objectives are aggregated into a global objective function, and the models are calibrated using the Shuffled Complex Evolution Algorithm. Water height observations from drifting orbit altimetry missions are

  10. Adaptable Web Modules to Stimulate Active Learning in Engineering Hydrology using Data and Model Simulations of Three Regional Hydrologic Systems (United States)

    Habib, E. H.; Tarboton, D. G.; Lall, U.; Bodin, M.; Rahill-Marier, B.; Chimmula, S.; Meselhe, E. A.; Ali, A.; Williams, D.; Ma, Y.


    The hydrologic community has long recognized the need for broad reform in hydrologic education. A paradigm shift is critically sought in undergraduate hydrology and water resource education by adopting context-rich, student-centered, and active learning strategies. Hydrologists currently deal with intricate issues rooted in complex natural ecosystems containing a multitude of interconnected processes. Advances in the multi-disciplinary field include observational settings such as Critical Zone and Water, Sustainability and Climate Observatories, Hydrologic Information Systems, instrumentation and modeling methods. These research advances theory and practices call for similar efforts and improvements in hydrologic education. The typical, text-book based approach in hydrologic education has focused on specific applications and/or unit processes associated with the hydrologic cycle with idealizations, rather than the contextual relations in the physical processes and the spatial and temporal dynamics connecting climate and ecosystems. An appreciation of the natural variability of these processes will lead to graduates with the ability to develop independent learning skills and understanding. This appreciation cannot be gained in curricula where field components such as observational and experimental data are deficient. These types of data are also critical when using simulation models to create environments that support this type of learning. Additional sources of observations in conjunction with models and field data are key to students understanding of the challenges associated with using models to represent such complex systems. Recent advances in scientific visualization and web-based technologies provide new opportunities for the development of active learning techniques utilizing ongoing research. The overall goal of the current study is to develop visual, case-based, data and simulation driven learning experiences to instructors and students through a web

  11. Stream network geomorphology mediates predicted vulnerability of anadromous fish habitat to hydrologic change in southeast Alaska. (United States)

    Sloat, Matthew R; Reeves, Gordon H; Christiansen, Kelly R


    In rivers supporting Pacific salmon in southeast Alaska, USA, regional trends toward a warmer, wetter climate are predicted to increase mid- and late-21st-century mean annual flood size by 17% and 28%, respectively. Increased flood size could alter stream habitats used by Pacific salmon for reproduction, with negative consequences for the substantial economic, cultural, and ecosystem services these fish provide. We combined field measurements and model simulations to estimate the potential influence of future flood disturbance on geomorphic processes controlling the quality and extent of coho, chum, and pink salmon spawning habitat in over 800 southeast Alaska watersheds. Spawning habitat responses varied widely across watersheds and among salmon species. Little variation among watersheds in potential spawning habitat change was explained by predicted increases in mean annual flood size. Watershed response diversity was mediated primarily by topographic controls on stream channel confinement, reach-scale geomorphic associations with spawning habitat preferences, and complexity in the pace and mode of geomorphic channel responses to altered flood size. Potential spawning habitat loss was highest for coho salmon, which spawn over a wide range of geomorphic settings, including steeper, confined stream reaches that are more susceptible to streambed scour during high flows. We estimated that 9-10% and 13-16% of the spawning habitat for coho salmon could be lost by the 2040s and 2080s, respectively, with losses occurring primarily in confined, higher-gradient streams that provide only moderate-quality habitat. Estimated effects were lower for pink and chum salmon, which primarily spawn in unconfined floodplain streams. Our results illustrate the importance of accounting for valley and reach-scale geomorphic features in watershed assessments of climate vulnerability, especially in topographically complex regions. Failure to consider the geomorphic context of stream

  12. Does better rainfall interpolation improve hydrological model performance? (United States)

    Bàrdossy, Andràs; Kilsby, Chris; Lewis, Elisabeth


    High spatial variability of precipitation is one of the main sources of uncertainty in rainfall/runoff modelling. Spatially distributed models require detailed space time information on precipitation as input. In the past decades a lot of effort was spent on improving precipitation interpolation using point observations. Different geostatistical methods like Ordinary Kriging, External Drift Kriging or Copula based interpolation can be used to find the best estimators for unsampled locations. The purpose of this work is to investigate to what extents more sophisticated precipitation estimation methods can improve model performance. For this purpose the Wye catchment in Wales was selected. The physically-based spatially-distributed hydrological model SHETRAN is used to describe the hydrological processes in the catchment. 31 raingauges with 1 hourly temporal resolution are available for a time period of 6 years. In order to avoid the effect of model uncertainty model parameters were not altered in this study. Instead 100 random subsets consisting of 14 stations each were selected. For each of the configurations precipitation was interpolated for each time step using nearest neighbor (NN), inverse distance (ID) and Ordinary Kriging (OK). The variogram was obtained using the temporal correlation of the time series measured at different locations. The interpolated data were used as input for the spatially distributed model. Performance was evaluated for daily mean discharges using the Nash-Sutcliffe coefficient, temporal correlations, flow volumes and flow duration curves. The results show that the simplest NN and the sophisticated OK performances are practically equally good, while ID performed worse. NN was often better for high flows. The reason for this is that NN does not reduce the variance, while OK and ID yield smooth precipitation fields. The study points out the importance of precipitation variability and suggests the use of conditional spatial simulation as

  13. Model-based analysis of the influence of catchment properties on hydrologic partitioning across five mountain headwater subcatchments. (United States)

    Kelleher, Christa; Wagener, Thorsten; McGlynn, Brian


    Ungauged headwater basins are an abundant part of the river network, but dominant influences on headwater hydrologic response remain difficult to predict. To address this gap, we investigated the ability of a physically based watershed model (the Distributed Hydrology-Soil-Vegetation Model) to represent controls on metrics of hydrologic partitioning across five adjacent headwater subcatchments. The five study subcatchments, located in Tenderfoot Creek Experimental Forest in central Montana, have similar climate but variable topography and vegetation distribution. This facilitated a comparative hydrology approach to interpret how parameters that influence partitioning, detected via global sensitivity analysis, differ across catchments. Model parameters were constrained a priori using existing regional information and expert knowledge. Influential parameters were compared to perceptions of catchment functioning and its variability across subcatchments. Despite between-catchment differences in topography and vegetation, hydrologic partitioning across all metrics and all subcatchments was sensitive to a similar subset of snow, vegetation, and soil parameters. Results also highlighted one subcatchment with low certainty in parameter sensitivity, indicating that the model poorly represented some complexities in this subcatchment likely because an important process is missing or poorly characterized in the mechanistic model. For use in other basins, this method can assess parameter sensitivities as a function of the specific ungauged system to which it is applied. Overall, this approach can be employed to identify dominant modeled controls on catchment response and their agreement with system understanding.

  14. A novel approach to parameter uncertainty analysis of hydrological models using neural networks

    Directory of Open Access Journals (Sweden)

    D. P. Solomatine


    Full Text Available In this study, a methodology has been developed to emulate a time consuming Monte Carlo (MC simulation by using an Artificial Neural Network (ANN for the assessment of model parametric uncertainty. First, MC simulation of a given process model is run. Then an ANN is trained to approximate the functional relationships between the input variables of the process model and the synthetic uncertainty descriptors estimated from the MC realizations. The trained ANN model encapsulates the underlying characteristics of the parameter uncertainty and can be used to predict uncertainty descriptors for the new data vectors. This approach was validated by comparing the uncertainty descriptors in the verification data set with those obtained by the MC simulation. The method is applied to estimate the parameter uncertainty of a lumped conceptual hydrological model, HBV, for the Brue catchment in the United Kingdom. The results are quite promising as the prediction intervals estimated by the ANN are reasonably accurate. The proposed techniques could be useful in real time applications when it is not practicable to run a large number of simulations for complex hydrological models and when the forecast lead time is very short.

  15. New insight into unstable hillslopes hydrology from hydrogeochemical modelling. (United States)

    Bertrand, C.; Marc, V.; Malet, J.-P.


    In the black marl outcrops of the French South Alps, sub surface flow conditions are considered as the main triggering factor for initiation and reactivation of landslides. The problem is traditionally addressed in term of hydrological processes (how does percolation to the water table occur?) but in some cases the origin of water is also in question. Direct rainfall is generally assumed as the only water source for groundwater recharge in shallow hillslope aquifers. The bedrock is also supposed impervious and continuous. Yet the geological environment of the study area is very complex owing to the geological history of this alpine sector. The autochthonous callovo-oxfordian black marl bedrock is highly tectonized (Maquaire et al., 2003) and may be affected by large, possibly draining discontinuities. A deep water inflow at the slip surface may at least locally result in increase the pore pressure and decrease the effective shearing resistance of the landslide material. In the active slow-moving landslide of Super-Sauze (Malet and Maquaire, 2003), this question has been addressed using hydrochemical investigations. The groundwater was sampled during five field campaigns uniformly spread out over the year from a network of boreholes. Water chemistry data were completed by geochemical and mineralogical analyses of the marl material. The major hydro-geochemical processes over area proved (1) mixing processes, (2) pyrite alteration, (3) dissolution/precipitation of carbonates and (4) cations exchange (de Montety et al., 2007). A geochemical modelling was carried out using the model Phreeqc (Parkhurst and Appelo, version 2.15, 2008) to check how suitable was observed water chemistry with the reservoir characteristics. The modelling exercise was based on a kinetics approach of soil-water interactions. The model simulates the rock alteration by the dissolution of the primary minerals and the precipitation of new phases. Initial parameters were obtained from geochemical

  16. Techniques to Access Databases and Integrate Data for Hydrologic Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Whelan, Gene; Tenney, Nathan D.; Pelton, Mitchell A.; Coleman, Andre M.; Ward, Duane L.; Droppo, James G.; Meyer, Philip D.; Dorow, Kevin E.; Taira, Randal Y.


    This document addresses techniques to access and integrate data for defining site-specific conditions and behaviors associated with ground-water and surface-water radionuclide transport applicable to U.S. Nuclear Regulatory Commission reviews. Environmental models typically require input data from multiple internal and external sources that may include, but are not limited to, stream and rainfall gage data, meteorological data, hydrogeological data, habitat data, and biological data. These data may be retrieved from a variety of organizations (e.g., federal, state, and regional) and source types (e.g., HTTP, FTP, and databases). Available data sources relevant to hydrologic analyses for reactor licensing are identified and reviewed. The data sources described can be useful to define model inputs and parameters, including site features (e.g., watershed boundaries, stream locations, reservoirs, site topography), site properties (e.g., surface conditions, subsurface hydraulic properties, water quality), and site boundary conditions, input forcings, and extreme events (e.g., stream discharge, lake levels, precipitation, recharge, flood and drought characteristics). Available software tools for accessing established databases, retrieving the data, and integrating it with models were identified and reviewed. The emphasis in this review was on existing software products with minimal required modifications to enable their use with the FRAMES modeling framework. The ability of four of these tools to access and retrieve the identified data sources was reviewed. These four software tools were the Hydrologic Data Acquisition and Processing System (HDAPS), Integrated Water Resources Modeling System (IWRMS) External Data Harvester, Data for Environmental Modeling Environmental Data Download Tool (D4EM EDDT), and the FRAMES Internet Database Tools. The IWRMS External Data Harvester and the D4EM EDDT were identified as the most promising tools based on their ability to access and

  17. Uncertainty Precipitation Assessment in a Hydrological Model at the Combeima River Basin, Colombia (United States)

    Salgado, F., II


    Prediction and simulation of hydroclimatological events such as rain, have become an Absolute necessity in the management processes of watershed systems, particularly as it relates to the assessment of water resources and risk management. Precipitation is considered as a trigger to natural phenomena such as landslides, avalanches and floods, which occur as a result of the nonlinear interaction of hydrological dynamics. For the study and analysis of precipitation there are technological tools such as hydrological modeling, characterized by the transformation of input variables, such as precipitation and evapotranspiration rate. Therefore, precipitation is one of the most important variables because the quality and distribution of water resources depends upon it, thus a better understanding of the uncertainties associated with it is required. The precipitation in the tropics has a high variability at all spatial scales, from the microscale to the synoptic scale, as happens in the time scale (Poveda and Mejia 2004; Zawadzki, 1973). This space-time variability has implications for the modeling and simulation of storms, and in extreme flows. This fact, coupled with the hydrological models are calibrated setting, usually simulated flow against the flow observed using the recorded rainfall, which generates uncertainties. The main goal of this work was evaluate the uncertainty associated with the precipitation variable performing multiple simulations of synthetic events both in space and time, using the distributed hydrological model TETIS (Velez et al, 2002; Frances et al, 2007). A case study at the Watershed Andean high of Combeima River, in the city of Ibague (Colombia), was used to assess the uncertainty associated with the daily scale simulations.

  18. Characterizing Drought Events from a Hydrological Model Ensemble (United States)

    Smith, Katie; Parry, Simon; Prudhomme, Christel; Hannaford, Jamie; Tanguy, Maliko; Barker, Lucy; Svensson, Cecilia


    Hydrological droughts are a slow onset natural hazard that can affect large areas. Within the United Kingdom there have been eight major drought events over the last 50 years, with several events acting at the continental scale, and covering the entire nation. Many of these events have lasted several years and had significant impacts on agriculture, the environment and the economy. Generally in the UK, due to a northwest-southeast gradient in rainfall and relief, as well as varying underlying geology, droughts tend to be most severe in the southeast, which can threaten water supplies to the capital in London. With the impacts of climate change likely to increase the severity and duration of drought events worldwide, it is crucial that we gain an understanding of the characteristics of some of the longer and more extreme droughts of the 19th and 20th centuries, so we may utilize this information in planning for the future. Hydrological models are essential both for reconstructing such events that predate streamflow records, and for use in drought forecasting. However, whilst the uncertainties involved in modelling hydrological extremes on the flooding end of the flow regime have been studied in depth over the past few decades, the uncertainties in simulating droughts and low flow events have not yet received such rigorous academic attention. The "Cascade of Uncertainty" approach has been applied to explore uncertainty and coherence across simulations of notable drought events from the past 50 years using the airGR family of daily lumped catchment models. Parameter uncertainty has been addressed using a Latin Hypercube sampled experiment of 500,000 parameter sets per model (GR4J, GR5J and GR6J), over more than 200 catchments across the UK. The best performing model parameterisations, determined using a multi-objective function approach, have then been taken forward for use in the assessment of the impact of model parameters and model structure on drought event

  19. Development of efficient and cost-effective distributed hydrological modeling tool MWEasyDHM based on open-source MapWindow GIS (United States)

    Lei, Xiaohui; Wang, Yuhui; Liao, Weihong; Jiang, Yunzhong; Tian, Yu; Wang, Hao


    Many regions are still threatened with frequent floods and water resource shortage problems in China. Consequently, the task of reproducing and predicting the hydrological process in watersheds is hard and unavoidable for reducing the risks of damage and loss. Thus, it is necessary to develop an efficient and cost-effective hydrological tool in China as many areas should be modeled. Currently, developed hydrological tools such as Mike SHE and ArcSWAT (soil and water assessment tool based on ArcGIS) show significant power in improving the precision of hydrological modeling in China by considering spatial variability both in land cover and in soil type. However, adopting developed commercial tools in such a large developing country comes at a high cost. Commercial modeling tools usually contain large numbers of formulas, complicated data formats, and many preprocessing or postprocessing steps that may make it difficult for the user to carry out simulation, thus lowering the efficiency of the modeling process. Besides, commercial hydrological models usually cannot be modified or improved to be suitable for some special hydrological conditions in China. Some other hydrological models are open source, but integrated into commercial GIS systems. Therefore, by integrating hydrological simulation code EasyDHM, a hydrological simulation tool named MWEasyDHM was developed based on open-source MapWindow GIS, the purpose of which is to establish the first open-source GIS-based distributed hydrological model tool in China by integrating modules of preprocessing, model computation, parameter estimation, result display, and analysis. MWEasyDHM provides users with a friendly manipulating MapWindow GIS interface, selectable multifunctional hydrological processing modules, and, more importantly, an efficient and cost-effective hydrological simulation tool. The general construction of MWEasyDHM consists of four major parts: (1) a general GIS module for hydrological analysis, (2) a

  20. Testing the Spatio-temporal Transferability of a Hydrological Water Quality Model in Central Germany (United States)

    Jomaa, Seifeddine; Jiang, Sanyuan; Rode, Michael


    Numerous studies have shown that the changes in land cover/use affect significantly the hydrological regime, which in turn influence the surface water quality. It is known that, at the catchment scale, hydrological modelling is a favourable tool for discharge and nutrients transport (such as Nitrogen and Phosphorus) predictions. The semi-distributed hydrological water quality HYPE (Hydrological Predictions for the Environment) model, has been evaluated for different catchments, and has been shown to reliably reproduce the measured data. The aim of this study was to test the spatio-temporal transferability of the HYPE model in Central Germany. First, the spatial transferability of the HYPE model was tested using two mesoscale catchments with different physiographical characteristics. To achieve our gaols, the Selke (463 km²) and Weida (99.5 km²) catchments, which are two small tributaries of the Elbe river basin were utilized. Second, the temporal transferability of the HYPE model was tested in the Weida catchment using different periods, where different patterns of nitrogen leaching were measured due to two considerable shifts in land use intensities and fertilizers application rates in 1990 and 1997. For Selke, the HYPE model reproduced reasonably well the discharge and IN monthly loads (with lowest NSE of 0.86 and 0.69 for discharge and IN loads, respectively). Also, results showed that only a NSE of 0.30 was obtained for the Weida catchment, in situations where the same best-optimized values from Selke was utilized, reflecting the controlling factors of land use and topography on the runoff generation. However, when the physiographical characteristics of the Weida catchment were considered during the calibration and validation phases (1997-2000 and 2001-2004, respectively, daily data), the HYPE model could reasonably predict the measured discharge and IN concentrations with similar performance as the Selke. In addition, the temporal transferability of the HYPE

  1. Advances in Modeling of Coupled Hydrologic-Socioeconomic Systems (United States)

    Amadio, Mattia; Mysiak, Jaroslav; Pecora, Silvano; Agnetti, Alberto


    River flooding is the most common natural disaster in Europe, causing deaths and huge amount of economic losses. Disastrous flood events are often related to extreme meteorological conditions; therefore, climate change is expected to have an important influence over the intensity and frequency of major floods. While approximated large-scale assessments of flood risk scenarios have been carried out, the knowledge of the effects at smaller scales is poor or incomplete, with few localized studies. Also, the methods are still coarse and uneven. The approach of this study starts from the definition of the risk paradigm and the elaboration of local climatic scenarios to track a methodology aimed at elaborating and combining the three elements concurring to the determination of risk: hydrological hazard, value exposure and vulnerability. First, hydrological hazard scenarios are provided by hydrological and hydrodynamic models, used in to a flood forecasting system capable to define "what-if" scenario in a flexible way. These results are then integrated with land-use data (exposure) and depth-damage functions (vulnerability) in a GIS environment, to assess the final risk value (potential flood damage) and visualize it in form of risk maps. In this paper results from a pilot study in the Polesine area are presented, where four simulated levee breach scenarios are compared. The outcomes of the analysis may be instrumental to authorities to increase the knowledge of possible direct losses and guide decision making and planning processes also. As future perspective, the employed methodology can also be extended at the basin scale through integration with the existent flood warning system to gain a real-time estimate of floods direct costs.

  2. CEREF: A hybrid data-driven model for forecasting annual streamflow from a socio-hydrological system (United States)

    Zhang, Hongbo; Singh, Vijay P.; Wang, Bin; Yu, Yinghao


    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

  3. Improving rainfall representation for large-scale hydrological modelling of tropical mountain basins (United States)

    Zulkafli, Zed; Buytaert, Wouter; Onof, Christian; Lavado, Waldo; Guyot, Jean-Loup


    extended period) in multiple basins, and (2) a comparison of the outcome of hydrological modelling using the distributed JULES (Joint-UK Land Environment Simulator) land surface model. First results indicate an improvement in the water balance that directly translates into an increased hydrological performance. The more interesting aspect of the study, however, will be the insights into the nature of satellite precipitation errors in this extreme environment and the optimal means of improving the data to generate increased confidence in hydrological predictions.

  4. Assimilation of satellite altimetry data in hydrological models for improved inland surface water information: Case studies from the "Sentinel-3 Hydrologic Altimetry Processor prototypE" project (SHAPE) (United States)

    Gustafsson, David; Pimentel, Rafael; Fabry, Pierre; Bercher, Nicolas; Roca, Mónica; Garcia-Mondejar, Albert; Fernandes, Joana; Lázaro, Clara; Ambrózio, Américo; Restano, Marco; Benveniste, Jérôme


    This communication is about the Sentinel-3 Hydrologic Altimetry Processor prototypE (SHAPE) project, with a focus on the components dealing with assimilation of satellite altimetry data into hydrological models. The SHAPE research and development project started in September 2015, within the Scientific Exploitation of Operational Missions (SEOM) programme of the European Space Agency. The objectives of the project are to further develop and assess recent improvement in altimetry data, processing algorithms and methods for assimilation in hydrological models, with the overarching goal to support improved scientific use of altimetry data and improved inland water information. The objective is also to take scientific steps towards a future Inland Water dedicated processor on the Sentinel-3 ground segment. The study focuses on three main variables of interest in hydrology: river stage, river discharge and lake level. The improved altimetry data from the project is used to estimate river stage, river discharge and lake level information in a data assimilation framework using the hydrological dynamic and semi-distributed model HYPE (Hydrological Predictions for the Environment). This model has been developed by SMHI and includes data assimilation module based on the Ensemble Kalman filter method. The method will be developed and assessed for a number of case studies with available in situ reference data and satellite altimetry data based on mainly the CryoSat-2 mission on which the new processor will be run; Results will be presented from case studies on the Amazon and Danube rivers and Lake Vänern (Sweden). The production of alti-hydro products (water level time series) are improved thanks to the use of water masks. This eases the geo-selection of the CryoSat-2 altimetric measurements since there are acquired from a geodetic orbit and are thus spread along the river course in space and and time. The specific processing of data from this geodetic orbit space

  5. Using an integrated hydrological model to estimate the usefulness of meteorological drought indices in a changing climate

    Directory of Open Access Journals (Sweden)

    D. von Gunten


    Full Text Available Droughts are serious natural hazards, especially in semi-arid regions. They are also difficult to characterize. Various summary metrics representing the dryness level, denoted drought indices, have been developed to quantify droughts. They typically lump meteorological variables and can thus directly be computed from the outputs of regional climate models in climate-change assessments. While it is generally accepted that drought risks in semi-arid climates will increase in the future, quantifying this increase using climate model outputs is a complex process that depends on the choice and the accuracy of the drought indices, among other factors. In this study, we compare seven meteorological drought indices that are commonly used to predict future droughts. Our goal is to assess the reliability of these indices to predict hydrological impacts of droughts under changing climatic conditions at the annual timescale. We simulate the hydrological responses of a small catchment in northern Spain to droughts in present and future climate, using an integrated hydrological model calibrated for different irrigation scenarios. We compute the correlation of meteorological drought indices with the simulated hydrological time series (discharge, groundwater levels, and water deficit and compare changes in the relationships between hydrological variables and drought indices. While correlation coefficients linked with a specific drought index are similar for all tested land uses and climates, the relationship between drought indices and hydrological variables often differs between present and future climate. Drought indices based solely on precipitation often underestimate the hydrological impacts of future droughts, while drought indices that additionally include potential evapotranspiration sometimes overestimate the drought effects. In this study, the drought indices with the smallest bias were the rainfall anomaly index, the reconnaissance drought index, and

  6. Freeze Prediction Model (United States)

    Morrow, C. T. (Principal Investigator)


    Measurements of wind speed, net irradiation, and of air, soil, and dew point temperatures in an orchard at the Rock Springs Agricultural Research Center, as well as topographical and climatological data and a description of the major apple growing regions of Pennsylvania were supplied to the University of Florida for use in running the P-model, freeze prediction program. Results show that the P-model appears to have considerable applicability to conditions in Pennsylvania. Even though modifications may have to be made for use in the fruit growing regions, there are advantages for fruit growers with the model in its present form.

  7. European Continental Scale Hydrological Model, Limitations and Challenges (United States)

    Rouholahnejad, E.; Abbaspour, K.


    The pressures on water resources due to increasing levels of societal demand, increasing conflict of interest and uncertainties with regard to freshwater availability create challenges for water managers and policymakers in many parts of Europe. At the same time, climate change adds a new level of pressure and uncertainty with regard to freshwater supplies. On the other hand, the small-scale sectoral structure of water management is now reaching its limits. The integrated management of water in basins requires a new level of consideration where water bodies are to be viewed in the context of the whole river system and managed as a unit within their basins. In this research we present the limitations and challenges of modelling the hydrology of the continent Europe. The challenges include: data availability at continental scale and the use of globally available data, streamgauge data quality and their misleading impacts on model calibration, calibration of large-scale distributed model, uncertainty quantification, and computation time. We describe how to avoid over parameterization in calibration process and introduce a parallel processing scheme to overcome high computation time. We used Soil and Water Assessment Tool (SWAT) program as an integrated hydrology and crop growth simulator to model water resources of the Europe continent. Different components of water resources are simulated and crop yield and water quality are considered at the Hydrological Response Unit (HRU) level. The water resources are quantified at subbasin level with monthly time intervals for the period of 1970-2006. The use of a large-scale, high-resolution water resources models enables consistent and comprehensive examination of integrated system behavior through physically-based, data-driven simulation and provides the overall picture of water resources temporal and spatial distribution across the continent. The calibrated model and results provide information support to the European Water

  8. SWAT Modeling for Depression-Dominated Areas: How Do Depressions Manipulate Hydrologic Modeling?

    Directory of Open Access Journals (Sweden)

    Mohsen Tahmasebi Nasab


    Full Text Available Modeling hydrologic processes for depression-dominated areas such as the North American Prairie Pothole Region is complex and reliant on a clear understanding of dynamic filling-spilling-merging-splitting processes of numerous depressions over the surface. Puddles are spatially distributed over a watershed and their sizes, storages, and interactions vary over time. However, most hydrologic models fail to account for these dynamic processes. Like other traditional methods, depressions are filled as a required preprocessing step in the Soil and Water Assessment Tool (SWAT. The objective of this study was to facilitate hydrologic modeling for depression-dominated areas by coupling SWAT with a Puddle Delineation (PD algorithm. In the coupled PD-SWAT model, the PD algorithm was utilized to quantify topographic details, including the characteristics, distribution, and hierarchical relationships of depressions, which were incorporated into SWAT at the hydrologic response unit (HRU scale. The new PD-SWAT model was tested for a large watershed in North Dakota under real precipitation events. In addition, hydrologic modeling of a small watershed was conducted under two extreme high and low synthetic precipitation conditions. In particular, the PD-SWAT was compared against the regular SWAT based on depressionless DEMs. The impact of depressions on the hydrologic modeling of the large and small watersheds was evaluated. The simulation results for the large watershed indicated that SWAT systematically overestimated the outlet discharge, which can be attributed to the failure to account for the hydrologic effects of depressions. It was found from the PD-SWAT modeling results that at the HRU scale surface runoff initiation was significantly delayed due to the threshold control of depressions. Under the high precipitation scenario, depressions increased the surface runoff peak. However, the low precipitation scenario could not fully fill depressions to reach

  9. Neural Network Hydrological Modelling: Linear Output Activation Functions? (United States)

    Abrahart, R. J.; Dawson, C. W.


    The power to represent non-linear hydrological processes is of paramount importance in neural network hydrological modelling operations. The accepted wisdom requires non-polynomial activation functions to be incorporated in the hidden units such that a single tier of hidden units can thereafter be used to provide a 'universal approximation' to whatever particular hydrological mechanism or function is of interest to the modeller. The user can select from a set of default activation functions, or in certain software packages, is able to define their own function - the most popular options being logistic, sigmoid and hyperbolic tangent. If a unit does not transform its inputs it is said to possess a 'linear activation function' and a combination of linear activation functions will produce a linear solution; whereas the use of non-linear activation functions will produce non-linear solutions in which the principle of superposition does not hold. For hidden units, speed of learning and network complexities are important issues. For the output units, it is desirable to select an activation function that is suited to the distribution of the target values: e.g. binary targets (logistic); categorical targets (softmax); continuous-valued targets with a bounded range (logistic / tanh); positive target values with no known upper bound (exponential; but beware of overflow); continuous-valued targets with no known bounds (linear). It is also standard practice in most hydrological applications to use the default software settings and to insert a set of identical non-linear activation functions in the hidden layer and output layer processing units. Mixed combinations have nevertheless been reported in several hydrological modelling papers and the full ramifications of such activities requires further investigation and assessment i.e. non-linear activation functions in the hidden units connected to linear or clipped-linear activation functions in the output unit. There are two

  10. Quantile hydrologic model selection and model structure deficiency assessment : 2. Applications

    NARCIS (Netherlands)

    Pande, S.


    Quantile hydrologic model selection and structure deficiency assessment is applied in three case studies. The performance of quantile model selection problem is rigorously evaluated using a model structure on the French Broad river basin data set. The case study shows that quantile model selection

  11. Quantile hydrologic model selection and model structure deficiency assessment : 1. Theory

    NARCIS (Netherlands)

    Pande, S.


    A theory for quantile based hydrologic model selection and model structure deficiency assessment is presented. The paper demonstrates that the degree to which a model selection problem is constrained by the model structure (measured by the Lagrange multipliers of the constraints) quantifies

  12. An integrated modeling framework of socio-economic, biophysical, and hydrological processes in Midwest landscapes: Remote sensing data, agro-hydrological model, and agent-based model (United States)

    Ding, Deng

    Intensive human-environment interactions are taking place in Midwestern agricultural systems. An integrated modeling framework is suitable for predicting dynamics of key variables of the socio-economic, biophysical, hydrological processes as well as exploring the potential transitions of system states in response to changes of the driving factors. The purpose of this dissertation is to address issues concerning the interacting processes and consequent changes in land use, water balance, and water quality using an integrated modeling framework. This dissertation is composed of three studies in the same agricultural watershed, the Clear Creek watershed in East-Central Iowa. In the first study, a parsimonious hydrologic model, the Threshold-Exceedance-Lagrangian Model (TELM), is further developed into RS-TELM (Remote Sensing TELM) to integrate remote sensing vegetation data for estimating evapotranspiration. The goodness of fit of RS-TELM is comparable to a well-calibrated SWAT (Soil and Water Assessment Tool) and even slightly superior in capturing intra-seasonal variability of stream flow. The integration of RS LAI (Leaf Area Index) data improves the model's performance especially over the agriculture dominated landscapes. The input of rainfall datasets with spatially explicit information plays a critical role in increasing the model's goodness of fit. In the second study, an agent-based model is developed to simulate farmers' decisions on crop type and fertilizer application in response to commodity and biofuel crop prices. The comparison between simulated crop land percentage and crop rotations with satellite-based land cover data suggest that farmers may be underestimating the effects that continuous corn production has on yields (yield drag). The simulation results given alternative market scenarios based on a survey of agricultural land owners and operators in the Clear Creek Watershed show that, farmers see cellulosic biofuel feedstock production in the form

  13. On the calibration of hydrological models in ungauged basins : A framework for integrating hard and soft hydrological information

    NARCIS (Netherlands)

    Winsemius, H.C.; Schaefli, B.; Montanari, A.; Savenije, H.H.G.


    This paper presents a calibration framework based on the generalized likelihood uncertainty estimation (GLUE) that can be used to condition hydrological model parameter distributions in scarcely gauged river basins, where data is uncertain, intermittent or nonconcomitant. At the heart of this

  14. Radar altimetry assimilation in catchment-scale hydrological models (United States)

    Bauer-Gottwein, P.; Michailovsky, C. I. B.


    Satellite-borne radar altimeters provide time series of river and lake levels with global coverage and moderate temporal resolution. Current missions can detect rivers down to a minimum width of about 100m, depending on local conditions around the virtual station. Water level time series from space-borne radar altimeters are an important source of information in ungauged or poorly gauged basins. However, many water resources management applications require information on river discharge. Water levels can be converted into river discharge by means of a rating curve, if sufficient and accurate information on channel geometry, slope and roughness is available. Alternatively, altimetric river levels can be assimilated into catchment-scale hydrological models. The updated models can subsequently be used to produce improved discharge estimates. In this study, a Muskingum routing model for a river network is updated using multiple radar altimetry time series. The routing model is forced with runoff produced by lumped-parameter rainfall-runoff models in each subcatchment. Runoff is uncertain because of errors in the precipitation forcing, structural errors in the rainfall-runoff model as well as uncertain rainfall-runoff model parameters. Altimetric measurements are translated into river reach storage based on river geometry. The Muskingum routing model is forced with a runoff ensemble and storages in the river reaches are updated using a Kalman filter approach. The approach is applied to the Zambezi and Brahmaputra river basins. Assimilation of radar altimetry significantly improves the capability of the models to simulate river discharge.

  15. Myths about Mathematical Modeling in Hydrology and Geomorphology (United States)

    Bras, R. L.; Tucker, G. E.


    Models have always been essential in science. Unfortunately an artificial schism sometimes exists between modelers and experimentalist (or 'observationalists' ). On the one hand this schism is fueled by the abuse and misuse of readily available and commonly complicated mathematical models of modern days. On the other hand, it is also a result of lack of understanding of what lies behind models and of commonly polarized education, emphasizing one or another approach. In this paper we try to illustrate why we think mathematical models are useful and necessary in geomorphology and hydrology. We attempt to dispel myths that we believe hamper the appropriate use of mathematical models. First we argue that mechanistic rigor is not always possible or the best approach to problems. Second we discuss the meaning of 'verification' or 'confirmation' in a statistical, distributional, sense. Third we provide examples of how even 'unconfirmed' models can be useful tools and how 'failures' can lead to discoveries. Finally we show how complexity is not necessarily good or bad and how complex models commonly lead to simple solutions - or vice-versa. Mathematical modeling is a necessary tool of modern science, one that has expanded our horizons and ability to understand the natural world.

  16. Translating hydrologically-relevant variables from the ice sheet model SICOPOLIS to the Greenland Analog Project hydrologic modeling domain (United States)

    Vallot, Dorothée; Applegate, Patrick; Pettersson, Rickard


    Projecting future climate and ice sheet development requires sophisticated models and extensive field observations. Given the present state of our knowledge, it is very difficult to say what will happen with certainty. Despite the ongoing increase in atmospheric greenhouse gas concentrations, the possibility that a new ice sheet might form over Scandinavia in the far distant future cannot be excluded. The growth of a new Scandinavian Ice Sheet would have important consequences for buried nuclear waste repositories. The Greenland Analogue Project, initiated by the Swedish Nuclear Fuel and Waste Management Company (SKB), is working to assess the effects of a possible future ice sheet on groundwater flow by studying a constrained domain in Western Greenland by field measurements (including deep bedrock drilling in front of the ice sheet) combined with numerical modeling. To address the needs of the GAP project, we interpolated results from an ensemble of ice sheet model runs to the smaller and more finely resolved modeling domain used in the GAP project's hydrologic modeling. Three runs have been chosen with three fairly different positive degree-day factors among those that reproduced the modern ice margin at the borehole position. The interpolated results describe changes in hydrologically-relevant variables over two time periods, 115 ka to 80 ka, and 20 ka to 1 ka. In the first of these time periods, the ice margin advances over the model domain; in the second time period, the ice margin retreats over the model domain. The spatially-and temporally dependent variables that we treated include the ice thickness, basal melting rate, surface mass balance, basal temperature, basal thermal regime (frozen or thawed), surface temperature, and basal water pressure. The melt flux is also calculated.

  17. Testing calibration routines for LISFLOOD, a distributed hydrological model (United States)

    Pannemans, B.


    Traditionally hydrological models are considered as difficult to calibrate: their highly non-linearity results in rugged and rough response surfaces were calibration algorithms easily get stuck in local minima. For the calibration of distributed hydrological models two extra factors play an important role: on the one hand they are often costly on computation, thus restricting the feasible number of model runs; on the other hand their distributed nature smooths the response surface, thus facilitating the search for a global minimum. Lisflood is a distributed hydrological model currently used for the European Flood Alert System - EFAS (Van der Knijff et al, 2008). Its upcoming recalibration over more then 200 catchments, each with an average runtime of 2-3 minutes, proved a perfect occasion to put several existing calibration algorithms to the test. The tested routines are Downhill Simplex (DHS, Nelder and Mead, 1965), SCEUA (Duan et Al. 1993), SCEM (Vrugt et al., 2003) and AMALGAM (Vrugt et al., 2008), and they were evaluated on their capability to efficiently converge onto the global minimum and on the spread in the found solutions in repeated runs. The routines were let loose on a simple hyperbolic function, on a Lisflood catchment using model output as observation, and on two Lisflood catchments using real observations (one on the river Inn in the Alps, the other along the downstream stretch of the Elbe). On the mathematical problem and on the catchment with synthetic observations DHS proved to be the fastest and the most efficient in finding a solution. SCEUA and AMALGAM are a slower, but while SCEUA keeps converging on the exact solution, AMALGAM slows down after about 600 runs. For the Lisflood models with real-time observations AMALGAM (hybrid algorithm that combines several other algorithms, we used CMA, PSO and GA) came as fastest out of the tests, and giving comparable results in consecutive runs. However, some more work is needed to tweak the stopping

  18. Operational Testing of Satellite based Hydrological Model (SHM) (United States)

    Gaur, Srishti; Paul, Pranesh Kumar; Singh, Rajendra; Mishra, Ashok; Gupta, Praveen Kumar; Singh, Raghavendra P.


    Incorporation of the concept of transposability in model testing is one of the prominent ways to check the credibility of a hydrological model. Successful testing ensures ability of hydrological models to deal with changing conditions, along with its extrapolation capacity. For a newly developed model, a number of contradictions arises regarding its applicability, therefore testing of credibility of model is essential to proficiently assess its strength and limitations. This concept emphasizes to perform 'Hierarchical Operational Testing' of Satellite based Hydrological Model (SHM), a newly developed surface water-groundwater coupled model, under PRACRITI-2 program initiated by Space Application Centre (SAC), Ahmedabad. SHM aims at sustainable water resources management using remote sensing data from Indian satellites. It consists of grid cells of 5km x 5km resolution and comprises of five modules namely: Surface Water (SW), Forest (F), Snow (S), Groundwater (GW) and Routing (ROU). SW module (functions in the grid cells with land cover other than forest and snow) deals with estimation of surface runoff, soil moisture and evapotranspiration by using NRCS-CN method, water balance and Hragreaves method, respectively. The hydrology of F module is dependent entirely on sub-surface processes and water balance is calculated based on it. GW module generates baseflow (depending on water table variation with the level of water in streams) using Boussinesq equation. ROU module is grounded on a cell-to-cell routing technique based on the principle of Time Variant Spatially Distributed Direct Runoff Hydrograph (SDDH) to route the generated runoff and baseflow by different modules up to the outlet. For this study Subarnarekha river basin, flood prone zone of eastern India, has been chosen for hierarchical operational testing scheme which includes tests under stationary as well as transitory conditions. For this the basin has been divided into three sub-basins using three flow

  19. Integrating understanding of hydrology, geomorphology and ecology to better predict periphyton abundance in New Zealand rivers (United States)

    Hoyle, Jo; Kilroy, Cathy; Hicks, Murray


    concentration and periphyton biomass data (laboratory measures of chlorophyll a and percentage cover of thin films, filaments and mats/sludge). For each reach we set up a 1-d hydraulic model and established relationships between discharge and a number of hydraulic and geomorphic variables, including the discharge required to partially and fully mobilise the bed sediment. These were then related to the flow and periphyton monitoring records to examine the strength of relationships. Relating periphyton biomass data to antecedent flow data allowed us to identify threshold flows for periphyton removal. These flows were found to be 0.9 - 9.8 times the median flow, depending on the site, with the average across sites being 3.3 times the median flow. Results also showed that general mobility of the gravelly/cobbly bed material was not required to remove periphyton but that mobility of over-passing sand (through its abrasive action) is a key control on periphyton abundance. Relationships between soluble inorganic nitrogen and periphyton abundance were found to be strong at sites where sand is mobilized infrequently but weak at sites where sand is mobilized often. Overall results indicate that integrating understanding of geomorphology, hydrology and ecology can improve prediction of periphyton abundance in New Zealand rivers.

  20. HD Hydrological modelling at catchment scale using rainfall radar observations (United States)

    Ciampalini Rossano. Ciampalini@Gmail. Com), Rossano; Follain, Stéphane; Raclot, Damien; Crabit, Armand; Pastor, Amandine; Augas, Julien; Moussa, Roger; Colin, François; Le Bissonnais, Yves


    Hydrological simulations at catchment scale repose on the quality and data availability both for soil and rainfall data. Soil data are quite easy to be collected, although their quality depends on the resources devoted to this task, rainfall data observations, instead, need further effort because of their spatiotemporal variability. Rainfalls are normally recorded with rain gauges located in the catchment, they can provide detailed temporal data, but, the representativeness is limited to the point where the data are collected. Combining different gauges in space can provide a better representation of the rainfall event but the spatialization is often the main obstacle to obtain data close to the reality. Since several years, radar observations overcome this gap providing continuous data registration, that, when properly calibrated, can offer an adequate, continuous, cover in space and time for medium-wide catchments. Here, we use radar records for the south of the France on the La Peyne catchment with the protocol there adopted by the national meteo agency, with resolution of 1 km space and 5' time scale observations. We present here the realisation of a model able to perform from rainfall radar observations, continuous hydrological and soil erosion simulations. The model is semi-theoretically based, once it simulates water fluxes (infiltration-excess overland flow, saturation overland flow, infiltration and channel routing) with a cinematic wave using the St. Venant equation on a simplified "bucket" conceptual model for ground water, and, an empirical representation of sediment load as adopted in models such as STREAM-LANDSOIL (Cerdan et al., 2002, Ciampalini et al., 2012). The advantage of this approach is to furnish a dynamic representation - simulation of the rainfall-runoff events more easily than using spatialized rainfalls from meteo stations and to offer a new look on the spatial component of the events.

  1. Modeling of thermally driven hydrological processes in partially saturated fractured rock (United States)

    Tsang, Y. W.; Birkholzer, J. T.; Mukhopadhyay, S.


    This paper is a review of the research that led to an in-depth understanding of flow and transport processes under strong heat stimulation in fractured, porous rock. It first describes the anticipated multiple processes that come into play in a partially saturated, fractured porous volcanic tuff geological formation when it is subject to a heat source such as that originating from the decay of radionuclides. The rationale is then given for numerical modeling being a key element in the study of multiple processes that are coupled. The paper outlines how the conceptualization and the numerical modeling of the problem evolved, progressing from the simplified to the more realistic. Examples of numerical models are presented so as to illustrate the advancement and maturation of the research over the last 2 decades. The most recent model applied to in situ field thermal tests is characterized by (1) incorporation of a full set of thermal-hydrological processes into a numerical simulator, (2) realistic representation of the field test geometry in three dimensions, and (3) use of site-specific characterization data for model inputs. Model predictions were carried out prior to initiation of data collection, and the model results were compared to diverse sets of measurements. The approach of close integration between modeling and field measurements has yielded a better understanding of how coupled thermal hydrological processes produce redistribution of moisture within the rock, which affects local permeability values and subsequently the flow of liquid and gases. The fluid flow, in turn, will change the temperature field. We end with a note on future research opportunities, specifically those incorporating chemical, mechanical, and microbiological factors into the study of thermal and hydrological processes.

  2. Predicting Hydrological Drought: Relative Contributions of Soil Moisture and Snow Information to Seasonal Streamflow Prediction Skill (United States)

    Koster, R.; Mahanama, S.; Livneh, B.; Lettenmaier, D.; Reichle, R.


    in this study we examine how knowledge of mid-winter snow accumulation and soil moisture conditions contribute to our ability to predict streamflow months in advance. A first "synthetic truth" analysis focuses on a series of numerical experiments with multiple sophisticated land surface models driven with a dataset of observations-based meteorological forcing spanning multiple decades and covering the continental United States. Snowpack information by itself obviously contributes to the skill attained in streamflow prediction, particularly in the mountainous west. The isolated contribution of soil moisture information, however, is found to be large and significant in many areas, particularly in the west but also in region surrounding the Great Lakes. The results are supported by a supplemental, observations-based analysis using (naturalized) March-July streamflow measurements covering much of the western U.S. Additional forecast experiments using start dates that span the year indicate a strong seasonality in the skill contributions; soil moisture information, for example, contributes to kill at much longer leads for forecasts issued in winter than for those issued in summer.

  3. Candidate Prediction Models and Methods

    DEFF Research Database (Denmark)

    Nielsen, Henrik Aalborg; Nielsen, Torben Skov; Madsen, Henrik


    This document lists candidate prediction models for Work Package 3 (WP3) of the PSO-project called ``Intelligent wind power prediction systems'' (FU4101). The main focus is on the models transforming numerical weather predictions into predictions of power production. The document also outlines...... the possibilities w.r.t. different numerical weather predictions actually available to the project....

  4. Towards a regional distributed hydrological modelling for flash-flood risk assessment (United States)

    Braud, I.; Manus, C.; Anquetin, S.; Viallet, P.


    Flash floods result from the combination of meteorological and hydrological conditions. Recognition of the coupled meteorological / hydrological nature of flash floods is now evident in interpretative studies and in the development of predictive models. There is a real need for research to improve the understanding of the major atmospheric and hydrologic factors leading to extreme flood events, especially those affecting small to medium ungauged basins. The paper presents a regional distributed hydrological modeling approach aiming at providing useful information for flash-flood understanding and risk assessment, especially in small ungauged basins. The analysis of the September 2002 event in the south-east of France has shown that these small ungauged catchments are the most vulnerable to flask floods, with a large number of casualties (Ruin et al., 2008). The model discretization is based on the concept of hydro-landscapes proposed by Dehotin and Braud (2008). In a first approach, only sub-catchments and the soil units derived from an existing soil data base were used to delineate the hydro-landscapes. In order to study the feasibility of the regional approach, a first model, implemented within the LIQUID numerical modelling platform (Viallet et al., 2006) was set up in the Cévennes - Vivarais region. It is based on the 1D Richards equation for the simulation of infiltration and water redistribution within the hydro-landscapes (including the representation of the vertical soil heterogeneity). The ponding was routed to the closest river reach using a simple flux formulation and the routing through the river performed using the kinematic wave approximation of the St-Venant equation. The model was forced with 5 minutes radar images with a 1km2 resolution and used without any calibration phase. A verification of the results was conducted at the regional scale, based on distributed post-flood estimation of maximum peak discharge from the September 2002 event and

  5. Hydrologic Modeling of the White Sands Dune Field, New Mexico (United States)

    Bourret, S. M.; Newton, B. T.; Person, M. A.


    The shallow groundwater flow system of White Sands dune field, located within the Tularosa Basin of Southern New Mexico, likely stabilizes the base of the largest gypsum dunefield in the world. Water table geometry and elevation play a critical role in controlling dune thickness, spatial extent, and migration rates. The White Sands National Monument (WHSA) is concerned that lowering the water table may lead to increased scour and migration of the dune field, which could be unfavorable to the preservation of the flora and fauna that have adapted to survive there. In response to projected increases in groundwater pumping in the regional Tularosa Basin groundwater system, changes in surface water use, and the threat of climate change, the WHSA is interested in understanding how these changes on a regional scale may impact the shallow dune aquifer. We have collected hydrological, geochemical, and geophysical data in order to identify the sources of recharge that contribute to the shallow dune aquifer and to assess interactions between this water table aquifer and the basin-scale, regional system. Vertical head gradients, temperature, and water quality data strongly suggest that local precipitation is the primary source of recharge to the dune aquifer today. This suggests that the modern dune system is relatively isolated from the deeper regional system. However, geochemical and electrical resistivity data indicates that the deeper basin groundwater system does contribute to the shallow system and suggests that hydrologic conditions have changed on geologic time scales. We have constructed a preliminary cross-sectional hydrologic model to attempt to characterize the interaction of the shallow dune aquifer with the deeper basin groundwater. The model cross-section extends about 80 km across the Tularosa Basin in a NW-SE direction parallel to the primary flow path. We represented 6 km of Precambrian crystalline basement, Paleozoic sedimentary rocks as well as Pleistocene

  6. Physically based modeling in catchment hydrology at 50: Survey and outlook (United States)

    Paniconi, Claudio; Putti, Mario


    Integrated, process-based numerical models in hydrology are rapidly evolving, spurred by novel theories in mathematical physics, advances in computational methods, insights from laboratory and field experiments, and the need to better understand and predict the potential impacts of population, land use, and climate change on our water resources. At the catchment scale, these simulation models are commonly based on conservation principles for surface and subsurface water flow and solute transport (e.g., the Richards, shallow water, and advection-dispersion equations), and they require robust numerical techniques for their resolution. Traditional (and still open) challenges in developing reliable and efficient models are associated with heterogeneity and variability in parameters and state variables; nonlinearities and scale effects in process dynamics; and complex or poorly known boundary conditions and initial system states. As catchment modeling enters a highly interdisciplinary era, new challenges arise from the need to maintain physical and numerical consistency in the description of multiple processes that interact over a range of scales and across different compartments of an overall system. This paper first gives an historical overview (past 50 years) of some of the key developments in physically based hydrological modeling, emphasizing how the interplay between theory, experiments, and modeling has contributed to advancing the state of the art. The second part of the paper examines some outstanding problems in integrated catchment modeling from the perspective of recent developments in mathematical and computational science.

  7. On the deterministic and stochastic use of hydrologic models (United States)

    Farmer, William H.; Vogel, Richard M.


    Environmental simulation models, such as precipitation-runoff watershed models, are increasingly used in a deterministic manner for environmental and water resources design, planning, and management. In operational hydrology, simulated responses are now routinely used to plan, design, and manage a very wide class of water resource systems. However, all such models are calibrated to existing data sets and retain some residual error. This residual, typically unknown in practice, is often ignored, implicitly trusting simulated responses as if they are deterministic quantities. In general, ignoring the residuals will result in simulated responses with distributional properties that do not mimic those of the observed responses. This discrepancy has major implications for the operational use of environmental simulation models as is shown here. Both a simple linear model and a distributed-parameter precipitation-runoff model are used to document the expected bias in the distributional properties of simulated responses when the residuals are ignored. The systematic reintroduction of residuals into simulated responses in a manner that produces stochastic output is shown to improve the distributional properties of the simulated responses. Every effort should be made to understand the distributional behavior of simulation residuals and to use environmental simulation models in a stochastic manner.

  8. Forensic isotope analysis to refine a hydrologic conceptual model. (United States)

    Bassett, R L; Steinwand, Aaron; Jorat, Saeed; Petersen, Christian; Jackson, Randy


    Water resources in the arid southwestern United States are frequently the subject of conflict from competing private and public interests. Legal remedies may remove impasses, but the technical analysis of the problem often determines the future success of legal solutions. In Owens Valley, California, the source of water for the Los Angeles Aqueduct (LAA) is flow diverted from the Owens River and its tributaries and ground water from valley aquifers. Future management of ground water delivered to the LAA needs technical support regarding quantity available, interconnection of shallow and confined aquifers, impact on local springs, and rate of recharge. Ground water flow models and ground water composition are tools already in use, but these have large uncertainty for local interpretations. This study conducted targeted sampling of springs and wells to evaluate the hydrologic system to corroborate conceptual and numerical models. The effort included measurement of intrinsic isotopic composition at key locations in the aquifers. The stable isotopic data of boron (delta(11)B), sulfur (delta(34)S), oxygen (delta(18)O), hydrogen (delta D), and tritium ((3)H) supported by basic chemical data provided rules for characterizing the upper and the lower aquifer system, confirmed the interpretation of ground water flow near faults and flow barriers, and detected hydraulic connections between the LAA and the perennial springs at key locations along the unlined reach of the LAA. This study exemplifies the use of forensic isotopic approaches as independent checks on the consistency of interpretations of conceptual models of a ground water system and the numerical hydrologic simulations.

  9. Generating Distributed Forcing Fields for Spatial Hydrologic Modeling (United States)

    Nayak, A.; Marks, D.; Chandler, D.; Winstral, A.


    Spatial hydrologic modeling requires the development of distributed forcing fields of weather and precipitation. This is particularly difficult in mountainous regions of the western US, where measurement sites are limited and the landscape is dominated by complex terrain and variations in vegetation cover. The Reynolds Creek Experimental Watershed (RCEW), in southwestern Idaho offers a unique opportunity to evaluate the sensitivity of interpolation techniques to the number and location of measurement sites. The RCEW, a 239 km2 hydro-climatic observatory operated by the USDA Agricultural Research Service since the early 1960's, contains 36 hydro-climatic measurement sites for monitoring the range of weather, snow and precipitation conditions across this complex mountain watershed. The MicroMet weather distribution utility, a process and topographically based weather interpolation tool (Liston and Elder, 2006), is used to generate surfaces of temperature, humidity, wind and precipitation over the snow-dominated 55 km2 (elevation range1398-2244m) Tollgate sub-catchment of RCEW. Nineteen meteorological stations were used to simulate the distribution of weather and precipitation for a series of storms during the 2004 water year. Measured and simulated values were compared to evaluate the accuracy of the model, and a jackknife approach was used to evaluate its sensitivity to data from particular stations. To evaluate the effect of elevation and storm track, different combinations of stations were selected, and to evaluate topographic exposure and vegetation shelter stations were divided into groups based on wind exposure. Results show that, even using a sophisticated weather distribution utility like MicroMet, the interpolation is very sensitive to station location and wind exposure. A certain amount of smoothing occurs even when using all 19 stations, but significant differences occur if only protected sites (similar to NRCS Snotel sites), or only wind-exposed sites are

  10. Improved hydrological model parametrization for climate change impact assessment under data scarcity - The potential of field monitoring techniques and geostatistics. (United States)

    Meyer, Swen; Blaschek, Michael; Duttmann, Rainer; Ludwig, Ralf


    According to current climate projections, Mediterranean countries are at high risk for an even pronounced susceptibility to changes in the hydrological budget and extremes. These changes are expected to have severe direct impacts on the management of water resources, agricultural productivity and drinking water supply. Current projections of future hydrological change, based on regional climate model results and subsequent hydrological modeling schemes, are very uncertain and poorly validated. The Rio Mannu di San Sperate Basin, located in Sardinia, Italy, is one test site of the CLIMB project. The Water Simulation Model (WaSiM) was set up to model current and future hydrological conditions. The availability of measured meteorological and hydrological data is poor as it is common for many Mediterranean catchments. In this study we conducted a soil sampling campaign in the Rio Mannu catchment. We tested different deterministic and hybrid geostatistical interpolation methods on soil textures and tested the performance of the applied models. We calculated a new soil texture map based on the best prediction method. The soil model in WaSiM was set up with the improved new soil information. The simulation results were compared to standard soil parametrization. WaSiMs was validated with spatial evapotranspiration rates using the triangle method (Jiang and Islam, 1999). WaSiM was driven with the meteorological forcing taken from 4 different ENSEMBLES climate projections for a reference (1971-2000) and a future (2041-2070) times series. The climate change impact was assessed based on differences between reference and future time series. The simulated results show a reduction of all hydrological quantities in the future in the spring season. Furthermore simulation results reveal an earlier onset of dry conditions in the catchment. We show that a solid soil model setup based on short-term field measurements can improve long-term modeling results, which is especially important

  11. Hunting Solomonoff's Swans: Exploring the Boundary Between Physics and Statistics in Hydrological Modeling (United States)

    Nearing, G. S.


    Statistical models consistently out-perform conceptual models in the short term, however to account for a nonstationary future (or an unobserved past) scientists prefer to base predictions on unchanging and commutable properties of the universe - i.e., physics. The problem with physically-based hydrology models is, of course, that they aren't really based on physics - they are based on statistical approximations of physical interactions, and we almost uniformly lack an understanding of the entropy associated with these approximations. Thermodynamics is successful precisely because entropy statistics are computable for homogeneous (well-mixed) systems, and ergodic arguments explain the success of Newton's laws to describe systems that are fundamentally quantum in nature. Unfortunately, similar arguments do not hold for systems like watersheds that are heterogeneous at a wide range of scales. Ray Solomonoff formalized the situation in 1968 by showing that given infinite evidence, simultaneously minimizing model complexity and entropy in predictions always leads to the best possible model. The open question in hydrology is about what happens when we don't have infinite evidence - for example, when the future will not look like the past, or when one watershed does not behave like another. How do we isolate stationary and commutable components of watershed behavior? I propose that one possible answer to this dilemma lies in a formal combination of physics and statistics. In this talk I outline my recent analogue (Solomonoff's theorem was digital) of Solomonoff's idea that allows us to quantify the complexity/entropy tradeoff in a way that is intuitive to physical scientists. I show how to formally combine "physical" and statistical methods for model development in a way that allows us to derive the theoretically best possible model given any given physics approximation(s) and available observations. Finally, I apply an analogue of Solomonoff's theorem to evaluate the

  12. Repurposing of open data through large scale hydrological modelling - (United States)

    Strömbäck, Lena; Andersson, Jafet; Donnelly, Chantal; Gustafsson, David; Isberg, Kristina; Pechlivanidis, Ilias; Strömqvist, Johan; Arheimer, Berit


    Hydrological modelling demands large amounts of spatial data, such as soil properties, land use, topography, lakes and reservoirs, ice and snow coverage, water management (e.g. irrigation patterns and regulations), meteorological data and observed water discharge in rivers. By using such data, the hydrological model will in turn provide new data that can be used for new purposes (i.e. re-purposing). This presentation will give an example of how readily available open data from public portals have been re-purposed by using the Hydrological Predictions for the Environment (HYPE) model in a number of large-scale model applications covering numerous subbasins and rivers. HYPE is a dynamic, semi-distributed, process-based, and integrated catchment model. The model output is launched as new Open Data at the web site to be used for (i) Climate change impact assessments on water resources and dynamics; (ii) The European Water Framework Directive (WFD) for characterization and development of measure programs to improve the ecological status of water bodies; (iii) Design variables for infrastructure constructions; (iv) Spatial water-resource mapping; (v) Operational forecasts (1-10 days and seasonal) on floods and droughts; (vi) Input to oceanographic models for operational forecasts and marine status assessments; (vii) Research. The following regional domains have been modelled so far with different resolutions (number of subbasins within brackets): Sweden (37 000), Europe (35 000), Arctic basin (30 000), La Plata River (6 000), Niger River (800), Middle-East North-Africa (31 000), and the Indian subcontinent (6 000). The Hype web site provides several interactive web applications for exploring results from the models. The user can explore an overview of various water variables for historical and future conditions. Moreover the user can explore and download historical time series of discharge for each basin and explore the performance of the model

  13. Distributed Hydrologic Modeling of Semiarid Basins in Arizona: A Platform for Land Cover and Climate Change Assessments (United States)

    Hawkins, G. A.; Vivoni, E. R.


    Watershed management is challenged by rising concerns over climate change and its potential to interact with land cover alterations to impact regional water supplies and hydrologic processes. The inability to conduct experimental manipulations that address climate and land cover change at watershed scales limits the capacity of water managers to make decisions to protect future supplies. As a result, spatially-explicit, physically-based models possess value for predicting the possible consequences on watershed hydrology. In this study, we apply a distributed watershed model, the Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator (tRIBS), to the Beaver Creek basin in Arizona. This sub-basin of the Verde River is representative of the regional topography, land cover, soils distribution and availability of hydrologic data in forested regions of northern Arizona. As such, it can serve as a demonstration study in the broader region to illustrate the utility of distributed models for change assessment studies. Through a model application to summertime conditions, we compare the hydrologic response from three sources of meteorological input: (1) an available network of ground-based stations, (2) weather radar rainfall estimates, and (3) the North American Land Data Assimilation System (NLDAS). Comparisons focus on analysis of spatiotemporal distributions of precipitation, soil moisture, runoff generation, evapotranspiration and recharge from the root zone at high resolution for an assessment of sustainable water supplies for agricultural and domestic purposes. We also present a preliminary analysis of the impact of vegetation change arising from historical treatments in the Beaver Creek to inform the hydrologic consequences in the form of soil moisture and evapotranspiration patterns with differing degrees of proposed forest thinning. Our results are discussed in the context of improved hydrologic predictions for sustainability and decision

  14. Predictive Surface Complexation Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Sverjensky, Dimitri A. [Johns Hopkins Univ., Baltimore, MD (United States). Dept. of Earth and Planetary Sciences


    Surface complexation plays an important role in the equilibria and kinetics of processes controlling the compositions of soilwaters and groundwaters, the fate of contaminants in groundwaters, and the subsurface storage of CO2 and nuclear waste. Over the last several decades, many dozens of individual experimental studies have addressed aspects of surface complexation that have contributed to an increased understanding of its role in natural systems. However, there has been no previous attempt to develop a model of surface complexation that can be used to link all the experimental studies in order to place them on a predictive basis. Overall, my research has successfully integrated the results of the work of many experimentalists published over several decades. For the first time in studies of the geochemistry of the mineral-water interface, a practical predictive capability for modeling has become available. The predictive correlations developed in my research now enable extrapolations of experimental studies to provide estimates of surface chemistry for systems not yet studied experimentally and for natural and anthropogenically perturbed systems.

  15. Developing an Online Framework for Publication of Uncertainty Information in Hydrological Modeling (United States)

    Etienne, E.; Piasecki, M.


    Inaccuracies in data collection and parameters estimation, and imperfection of models structures imply uncertain predictions of the hydrological models. Finding a way to communicate the uncertainty information in a model output is important in decision-making. This work aims to publish uncertainty information (computed by project partner at Penn State) associated with hydrological predictions on catchments. To this end we have developed a DB schema (derived from the CUAHSI ODM design) which is focused on storing uncertainty information and its associated metadata. The technologies used to build the system are: OGC's Sensor Observation Service (SOS) for publication, the uncertML markup language (also developed by the OGC) to describe uncertainty information, and use of the Interoperability and Automated Mapping (INTAMAP) Web Processing Service (WPS) that handles part of the statistics computations. We develop a service to provide users with the capability to exploit all the functionality of the system (based on DRUPAL). Users will be able to request and visualize uncertainty data, and also publish their data in the system.

  16. Evaluating and improving the representation of heteroscedastic errors in hydrological models (United States)

    McInerney, D. J.; Thyer, M. A.; Kavetski, D.; Kuczera, G. A.


    Appropriate representation of residual errors in hydrological modelling is essential for accurate and reliable probabilistic predictions. In particular, residual errors of hydrological models are often heteroscedastic, with large errors associated with high rainfall and runoff events. Recent studies have shown that using a weighted least squares (WLS) approach - where the magnitude of residuals are assumed to be linearly proportional to the magnitude of the flow - captures some of this heteroscedasticity. In this study we explore a range of Bayesian approaches for improving the representation of heteroscedasticity in residual errors. We compare several improved formulations of the WLS approach, the well-known Box-Cox transformation and the more recent log-sinh transformation. Our results confirm that these approaches are able to stabilize the residual error variance, and that it is possible to improve the representation of heteroscedasticity compared with the linear WLS approach. We also find generally good performance of the Box-Cox and log-sinh transformations, although as indicated in earlier publications, the Box-Cox transform sometimes produces unrealistically large prediction limits. Our work explores the trade-offs between these different uncertainty characterization approaches, investigates how their performance varies across diverse catchments and models, and recommends practical approaches suitable for large-scale applications.

  17. An eco-hydrologic model of malaria outbreaks (United States)

    Montosi, E.; Manzoni, S.; Porporato, A.; Montanari, A.


    Malaria is a geographically widespread infectious disease that is well known to be affected by climate variability at both seasonal and interannual timescales. In an effort to identify climatic factors that impact malaria dynamics, there has been considerable research focused on the development of appropriate disease models for malaria transmission and their consideration alongside climatic datasets. These analyses have focused largely on variation in temperature and rainfall as direct climatic drivers of malaria dynamics. Here, we further these efforts by considering additionally the role that soil water content may play in driving malaria incidence. Specifically, we hypothesize that hydro-climatic variability should be an important factor in controlling the availability of mosquito habitats, thereby governing mosquito growth rates. To test this hypothesis, we reduce a nonlinear eco-hydrologic model to a simple linear model through a series of consecutive assumptions and apply this model to malaria incidence data from three South African provinces. Despite the assumptions made in the reduction of the model, we show that soil water content can account for a significant portion of malaria's case variability beyond its seasonal patterns, whereas neither temperature nor rainfall alone can do so. Future work should therefore consider soil water content as a simple and computable variable for incorporation into climate-driven disease models of malaria and other vector-borne infectious diseases.

  18. Data assimilation in integrated hydrological modeling using ensemble Kalman filtering

    DEFF Research Database (Denmark)

    Rasmussen, Jørn; Madsen, H.; Jensen, Karsten Høgh


    Groundwater head and stream discharge is assimilated using the ensemble transform Kalman filter in an integrated hydrological model with the aim of studying the relationship between the filter performance and the ensemble size. In an attempt to reduce the required number of ensemble members...... numbers and spatial distributions of groundwater head observations and with or without discharge assimilation and parameter estimation. The study shows that (1) more ensemble members are needed when fewer groundwater head observations are assimilated, and (2) assimilating discharge observations...... and estimating parameters requires a much larger ensemble size than just assimilating groundwater head observations. However, the required ensemble size can be greatly reduced with the use of adaptive localization, which by far outperforms distance-based localization. The study is conducted using synthetic data...

  19. Improved Regional Climate Model Simulation of Precipitation by a Dynamical Coupling to a Hydrology Model

    DEFF Research Database (Denmark)

    Larsen, Morten Andreas Dahl; Drews, Martin; Hesselbjerg Christensen, Jens

    convective precipitation systems. As a result climate model simulations let alone future projections of precipitation often exhibit substantial biases. Here we show that the dynamical coupling of a regional climate model to a detailed fully distributed hydrological model - including groundwater-, overland...... of local precipitation dynamics are seen for time scales of app. Seasonal duration and longer. We show that these results can be attributed to a more complete treatment of land surface feedbacks. The local scale effect on the atmosphere suggests that coupled high-resolution climate-hydrology models...... including a detailed 3D redistribution of sub- and land surface water have a significant potential for improving climate projections even diminishing the need for bias correction in climate-hydrology studies....

  20. Assessment of precipitation and temperature data from CMIP3 global climate models for hydrologic simulation (United States)

    McMahon, T. A.; Peel, M. C.; Karoly, D. J.


    The objective of this paper is to identify better performing Coupled Model Intercomparison Project phase 3 (CMIP3) global climate models (GCMs) that reproduce grid-scale climatological statistics of observed precipitation and temperature for input to hydrologic simulation over global land regions. Current assessments are aimed mainly at examining the performance of GCMs from a climatology perspective and not from a hydrology standpoint. The performance of each GCM in reproducing the precipitation and temperature statistics was ranked and better performing GCMs identified for later analyses. Observed global land surface precipitation and temperature data were drawn from the Climatic Research Unit (CRU) 3.10 gridded data set and re-sampled to the resolution of each GCM for comparison. Observed and GCM-based estimates of mean and standard deviation of annual precipitation, mean annual temperature, mean monthly precipitation and temperature and Köppen-Geiger climate type were compared. The main metrics for assessing GCM performance were the Nash-Sutcliffe efficiency (NSE) index and root mean square error (RMSE) between modelled and observed long-term statistics. This information combined with a literature review of the performance of the CMIP3 models identified the following better performing GCMs from a hydrologic perspective: HadCM3 (Hadley Centre for Climate Prediction and Research), MIROCm (Model for Interdisciplinary Research on Climate) (Center for Climate System Research (The University of Tokyo), National Institute for Environmental Studies, and Frontier Research Center for Global Change), MIUB (Meteorological Institute of the University of Bonn, Meteorological Research Institute of KMA, and Model and Data group), MPI (Max Planck Institute for Meteorology) and MRI (Japan Meteorological Research Institute). The future response of these GCMs was found to be representative of the 44 GCM ensemble members which confirms that the selected GCMs are reasonably

  1. Simulating cold-region hydrology in an intensively drained agricultural watershed in Manitoba, Canada, using the Cold Regions Hydrological Model (United States)

    Cordeiro, Marcos R. C.; Wilson, Henry F.; Vanrobaeys, Jason; Pomeroy, John W.; Fang, Xing; The Red-Assiniboine Project Biophysical Modelling Team


    Etrophication and flooding are perennial problems in agricultural watersheds of the northern Great Plains. A high proportion of annual runoff and nutrient transport occurs with snowmelt in this region. Extensive surface drainage modification, frozen soils, and frequent backwater or ice-damming impacts on flow measurement represent unique challenges to accurately modelling watershed-scale hydrological processes. A physically based, non-calibrated model created using the Cold Regions Hydrological Modelling platform (CRHM) was parameterized to simulate hydrological processes within a low slope, clay soil, and intensively surface drained agricultural watershed. These characteristics are common to most tributaries of the Red River of the north. Analysis of the observed water level records for the study watershed (La Salle River) indicates that ice cover and backwater issues at time of peak flow may impact the accuracy of both modelled and measured streamflows, highlighting the value of evaluating a non-calibrated model in this environment. Simulations best matched the streamflow record in years when peak and annual discharges were equal to or above the medians of 6.7 m3 s-1 and 1.25 × 107 m3, respectively, with an average Nash-Sutcliffe efficiency (NSE) of 0.76. Simulation of low-flow years (below the medians) was more challenging (average NSE attention in further model development efforts. Despite the complexities of the study watershed, simulations of flow for average to high-flow years and other components of the water balance were robust (snow water equivalency (SWE) and soil moisture). A sensitivity analysis of the flow routing model suggests a need for improved understanding of watershed functions under both dry and flooded conditions due to dynamic routing conditions, but overall CRHM is appropriate for simulation of hydrological processes in agricultural watersheds of the Red River. Falsifications of snow sublimation, snow transport, and infiltration to frozen

  2. Impacts of Hydrologic and Geochemical Uncertainty on Predicting Uranium Migration at the Hanford 300 Area (United States)

    Chen, X.; Hammond, G. E.; Lichtner, P. C.; Rockhold, M. L.


    In modeling the uranium migration within the Integrated Field Research Challenge (IFRC) site at the Hanford 300 Area, the model simulations are affected by both the hydrologic and geochemical uncertainties. This study investigates the propagation of both types of uncertainty in the simulation of a uranium desorption experiment using a Monte-Carlo framework. The hydrologic uncertainty arises from estimating the transient flow boundary conditions induced by the dynamics in the Columbia River and the underlying heterogeneous hydraulic conductivity field, while the geochemical uncertainty is a result of limited knowledge in the geochemical reaction processes that take place in field and heterogeneity in source terms and reaction coefficients. We also evaluated the effectiveness of various conditioning data in reducing the uncertainty in the simulated uranium plume. For example, identifying the optimal boundary condition and estimating the 3D hydraulic conductivity field through inversion of concurrent conservative tracer test, and exploring the possibility of including the geophysical and geochemical data available at the site to characterize hydrologic and geochemical heterogeneities. The multi-realization capability of the parallel simulator, PFLOTRAN, enables this computationally demanding task to be completed within a reasonable turn-around time.

  3. Hydrological Modelling Using a Rainfall Simulator over an Experimental Hillslope Plot

    Directory of Open Access Journals (Sweden)

    Arpit Chouksey


    Full Text Available Hydrological processes are complex to compute in hilly areas when compared to plain areas. The governing processes behind runoff generation on hillslopes are subsurface storm flow, saturation excess flow, overland flow, return flow and pipe storage. The simulations of the above processes in the soil matrix require detailed hillslope hydrological modelling. In the present study, a hillslope experimental plot has been designed to study the runoff generation processes on the plot scale. The setup is designed keeping in view the natural hillslope conditions prevailing in the Northwestern Himalayas, India where high intensity rainfall events occur frequently. A rainfall simulator was installed over the experimental hillslope plot to generate rainfall with an intensity of 100 mm/h, which represents the dominating rainfall intensity range in the region. Soil moisture sensors were also installed at variable depths from 100 to 1000 mm at different locations of the plot to observe the soil moisture regime. From the experimental observations it was found that once the soil is saturated, it remains at field capacity for the next 24–36 h. Such antecedent moisture conditions are most favorable for the generation of rapid stormflow from hillslopes. A dye infiltration test was performed on the undisturbed soil column to observe the macropore fraction variability over the vegetated hillslopes. The estimated macropore fractions are used as essential input for the hillslope hydrological model. The main objective of the present study was to develop and test a method for estimating runoff responses from natural rainfall over hillslopes of the Northwestern Himalayas using a portable rainfall simulator. Using the experimental data and the developed conceptual model, the overland flow and the subsurface flow through a macropore-dominated area have been estimated/analyzed. The surface and subsurface runoff estimated using the developed hillslope hydrological model

  4. Assessing Environmental Drivers of DOC Fluxes in the Shark River Estuary: Modeling the Effects of Climate, Hydrology and Water Management (United States)

    Regier, P.; Briceno, H.; Jaffe, R.


    Urban and agricultural development of the South Florida peninsula has disrupted freshwater flow in the Everglades, a hydrologically connected ecosystem stretching from central Florida to the Gulf of Mexico. Current system-scale restoration efforts aim to restore natural hydrologic regimes to reestablish pre-drainage ecosystem functioning through increased water availability, quality and timing. However, it is uncertain how hydrologic restoration combined with climate change will affect the downstream section of the system, including the mangrove estuaries of Everglades National Park. Aquatic transport of carbon, primarily as dissolved organic carbon (DOC), plays a critical role in biogeochemical cycling and food-web dynamics, and will be affected both by water management policies and climate change. To better understand DOC dynamics in these estuaries and how hydrology, climate and water management may affect them, 14 years of monthly data collected in the Shark River estuary were used to build a DOC flux model. Multi-variate methods were applied to long-term data-sets for hydrology, water quality and climate to untangle the interconnected environmental drivers that control DOC export at intra and inter-annual scales. DOC fluxes were determined to be primarily controlled by hydrology but also by seasonality and long-term climate patterns. Next, a 4-component model (salinity, inflow, rainfall, Atlantic Multidecadal Oscillation) capable of predicting DOC fluxes (R2=0.78, p<0.0001, n=161) was established. Finally, potential climate change scenarios for the Everglades were applied to this model to assess DOC flux variations in response to climate and restoration variables. Although global predictions anticipate that DOC export will generally increase in the future, the majority of scenario runs indicated that DOC export from the Everglades is expected to decrease due to changes in rainfall, evapotranspiration, inflows and sea-level rise.

  5. Significant uncertainty in global scale hydrological modeling from precipitation data errors

    NARCIS (Netherlands)

    Weiland, Frederiek C. Sperna; Vrugt, Jasper A.; van Beek, Rens (L. ) P. H.|info:eu-repo/dai/nl/14749799X; Weerts, Albrecht H.; Bierkens, Marc F. P.|info:eu-repo/dai/nl/125022794


    In the past decades significant progress has been made in the fitting of hydrologic models to data. Most of this work has focused on simple, CPU-efficient, lumped hydrologic models using discharge, water table depth, soil moisture, or tracer data from relatively small river basins. In this paper, we

  6. Significant uncertainty in global scale hydrological modeling from precipitation data erros

    NARCIS (Netherlands)

    Sperna Weiland, F.; Vrugt, J.A.; Beek, van P.H.; Weerts, A.H.; Bierkens, M.F.P.


    In the past decades significant progress has been made in the fitting of hydrologic models to data. Most of this work has focused on simple, CPU-efficient, lumped hydrologic models using discharge, water table depth, soil moisture, or tracer data from relatively small river basins. In this paper, we

  7. Hydrological modelling improvements required in basins in the Hindukush-Karakoram-Himalayas region (United States)

    Khan, Asif; Richards, Keith S.; McRobie, Allan; Booij, Martijn


    Millions of people rely on river water originating from basins in the Hindukush-Karakoram-Himalayas (HKH), where snow- and ice-melt are significant flow components. One such basin is the Upper Indus Basin (UIB), where snow- and ice-melt can contribute more than 80% of total flow. Containing some of the world's largest alpine glaciers, this basin may be highly susceptible to global warming and climate change, and reliable predictions of future water availability are vital for resource planning for downstream food and energy needs in a changing climate, but depend on significantly improved