Real Time Updating in Distributed Urban Rainfall Runoff Modelling
Borup, Morten; Mikkelsen, Peter Steen; Grum, Morten; Madsen, Henrik
2014-01-01
When it rains on urban areas the rainfall runoff is transported out of the city via the drainage system. Frequently, the drainage system cannot handle all the rain water, which results in problems like flooding or overflows into natural water bodies. To reduce these problems the systems are equipped with basins and automated structures that allow for a large degree of control of the systems, but in order to do this optimally it is required to know what is happening throughout the system. For ...
Modification of a rainfall-runoff model for distributed modeling in a GIS and its validation
Nyabeze, W. R.
A rainfall-runoff model, which can be inter-faced with a Geographical Information System (GIS) to integrate definition, measurement, calculating parameter values for spatial features, presents considerable advantages. The modification of the GWBasic Wits Rainfall-Runoff Erosion Model (GWBRafler) to enable parameter value estimation in a GIS (GISRafler) is presented in this paper. Algorithms are applied to estimate parameter values reducing the number of input parameters and the effort to populate them. The use of a GIS makes the relationship between parameter estimates and cover characteristics more evident. This paper has been produced as part of research to generalize the GWBRafler on a spatially distributed basis. Modular data structures are assumed and parameter values are weighted relative to the module area and centroid properties. Modifications to the GWBRafler enable better estimation of low flows, which are typical in drought conditions.
Real Time Updating in Distributed Urban Rainfall Runoff Modelling
DEFF Research Database (Denmark)
Borup, Morten; Madsen, Henrik
that are being updated from system measurements was studied. The results showed that the fact alone that it takes time for rainfall data to travel the distance between gauges and catchments has such a big negative effect on the forecast skill of updated models, that it can justify the choice of even very...... as in a real data case study. The results confirmed that the method is indeed suitable for DUDMs and that it can be used to utilise upstream as well as downstream water level and flow observations to improve model estimates and forecasts. Due to upper and lower sensor limits many sensors in urban drainage...
Decker, P.; Cohen, M. J.; Jawitz, J. W.
2017-12-01
Previous hydrologic studies primarily focus on processes related to montane catchments with significant runoff ratios, low evapotranspiration rates, and reasonably short travel times. There is a significant lack of research for hydrologic processes occurring within the United States Southeastern Coastal Plain landscape where low-relief and high rates of evapotranspiration impact water fluxes. Hydrologic modeling efforts within this region may elucidate possible interactions and timescales of solute travel where much of the landscape is managed for agricultural crops, namely plantation forestry. A long-term paired watershed study carried out in northern Florida monitored two second-order blackwater streams for five years. Rainfall-runoff models for both catchments were created using daily discharge, precipitation, and modeled evapotranspiration as input parameters. Best fit occurred (NSE = 0.8) when the catchments were modeled as two-storage (shallow and deep) reservoirs in parallel and overland flow was allowed to contribute to streamflow in periods were shallow groundwater storage was at capacity. In addition, streamflow and rainfall chloride concentrations were used to model in-variable transit time distributions using spectral methods. In both catchments this transit time was unresolvable because output spectral power exceeded input spectral power, a result assumed to be driven by the evaporative demand of the region. A modeled chloride time series from random input concentration and modeled output through the rainfall-runoff model was used to alter the evaporation ratio. Once evaporation rates equaled known rates found in cool, high-relief catchments, spectral analysis illustrated higher input spectral power and therefore resolvable transit times. Findings from this study illustrate significant effects from evaporation within the catchment - often exceeding the signal from the background catchment process itself. Calculations illustrate a proposed mean transit
Added value of distribution in rainfall-runoff models for the Meuse basin
de Boer, T.
2017-01-01
Why do equal precipitation events not lead to equal discharge events across space and time? The easy answer would be because catchments are different, which then leads to the second question: Why do hydrologists often use the same rainfall-runoff model for different catchments? Probably because
Directory of Open Access Journals (Sweden)
Weijian Guo
2015-05-01
Full Text Available Spatial variability plays an important role in nonlinear hydrologic processes. Due to the limitation of computational efficiency and data resolution, subgrid variability is usually assumed to be uniform for most grid-based rainfall-runoff models, which leads to the scale-dependence of model performances. In this paper, the scale effect on the Grid-Xinanjiang model was examined. The bias of the estimation of precipitation, runoff, evapotranspiration and soil moisture at the different grid scales, along with the scale-dependence of the effective parameters, highlights the importance of well representing the subgrid variability. This paper presents a subgrid parameterization method to incorporate the subgrid variability of the soil storage capacity, which is a key variable that controls runoff generation and partitioning in the Grid-Xinanjiang model. In light of the similar spatial pattern and physical basis, the soil storage capacity is correlated with the topographic index, whose spatial distribution can more readily be measured. A beta distribution is introduced to represent the spatial distribution of the soil storage capacity within the grid. The results derived from the Yanduhe Basin show that the proposed subgrid parameterization method can effectively correct the watershed soil storage capacity curve. Compared to the original Grid-Xinanjiang model, the model performances are quite consistent at the different grid scales when the subgrid variability is incorporated. This subgrid parameterization method reduces the recalibration necessity when the Digital Elevation Model (DEM resolution is changed. Moreover, it improves the potential for the application of the distributed model in the ungauged basin.
Directory of Open Access Journals (Sweden)
G. Moretti
2008-08-01
Full Text Available The estimation of the peak river flow for ungauged river sections is a topical issue in applied hydrology. Spatially distributed rainfall-runoff models can be a useful tool to this end, since they are potentially able to simulate the river flow at any location of the watershed drainage network. However, it is not fully clear to what extent these models can provide reliable simulations over a wide range of spatial scales. This issue is investigated here by applying a spatially distributed, continuous simulation rainfall-runoff model to infer the flood frequency distribution of the Riarbero River. This is an ungauged mountain creek located in northern Italy, whose drainage area is 17 km^{2}. The hydrological model is first calibrated by using a 1-year record of hourly meteorological data and river flows observed at the outlet of the 1294 km^{2} wide Secchia River basin, of which the Riarbero is a tributary. The model is then validated by performing a 100-year long simulation of synthetic river flow data, which allowed us to compare the simulated and observed flood frequency distributions at the Secchia River outlet and the internal cross river section of Cavola Bridge, where the basin area is 337 km^{2}. Finally, another simulation of hourly river flows was performed by referring to the outlet of the Riarbero River, therefore allowing us to estimate the related flood frequency distribution. The results were validated by using estimates of peak river flow obtained by applying hydrological similarity principles and a regional method. The results show that the flood flow estimated through the application of the distributed model is consistent with the estimate provided by the regional procedure as well as the behaviors of the river banks. Conversely, the method based on hydrological similarity delivers an estimate that seems to be not as reliable. The analysis highlights interesting perspectives for the application of
Directory of Open Access Journals (Sweden)
M. Coustau
2012-04-01
Full Text Available Rainfall-runoff models are crucial tools for the statistical prediction of flash floods and real-time forecasting. This paper focuses on a karstic basin in the South of France and proposes a distributed parsimonious event-based rainfall-runoff model, coherent with the poor knowledge of both evaporative and underground fluxes. The model combines a SCS runoff model and a Lag and Route routing model for each cell of a regular grid mesh. The efficiency of the model is discussed not only to satisfactorily simulate floods but also to get powerful relationships between the initial condition of the model and various predictors of the initial wetness state of the basin, such as the base flow, the Hu2 index from the Meteo-France SIM model and the piezometric levels of the aquifer. The advantage of using meteorological radar rainfall in flood modelling is also assessed. Model calibration proved to be satisfactory by using an hourly time step with Nash criterion values, ranging between 0.66 and 0.94 for eighteen of the twenty-one selected events. The radar rainfall inputs significantly improved the simulations or the assessment of the initial condition of the model for 5 events at the beginning of autumn, mostly in September–October (mean improvement of Nash is 0.09; correction in the initial condition ranges from −205 to 124 mm, but were less efficient for the events at the end of autumn. In this period, the weak vertical extension of the precipitation system and the low altitude of the 0 °C isotherm could affect the efficiency of radar measurements due to the distance between the basin and the radar (~60 km. The model initial condition S is correlated with the three tested predictors (R^{2} > 0.6. The interpretation of the model suggests that groundwater does not affect the first peaks of the flood, but can strongly impact subsequent peaks in the case of a multi-storm event. Because this kind of model is based on a limited
Directory of Open Access Journals (Sweden)
Rosli, M.H.
2017-07-01
Full Text Available With the advance of GIS technology, hydrology model can simulated at catchment wide scale. The objective is to integrate National Resource Conservation Service (NRCS Curve Number (CN with kinematic wave and manning’s equation using GIS to develop a simple GIS-based distributed model to simulate rainfall runoff in Bentong catchment. Model was built using Spatial Distributed Direct Hydrograph (SDDH concept and applying the time area (TA approach in presenting the predicted discharge hydrograph. The effective precipitation estimation was first calculated using the NRCS CN method. Then, the core maps that consists of digital elevation model (DEM, soil and land use map in grid. DEM was used to derive slope, flow direction and flow accumulation while soil and land use map used to derive roughness coefficient and CN. The overland velocity and channel velocity estimation derived from combination of kinematic wave theory with Manning’s equation. To capture the time frame, the travel time map was divided into isochrones in order to generate the TA histogram and finally. The creation of SDDH using the TA histogram which will lead to the estimation of travel time for the catchment. Simulated hydrograph was plotted together with the observed discharge for comparison. Six storm events used for model performance evaluation using statistical measure such as Nash-Sutcliffe efficiency (NSE, percent bias (PBIAS and coefficient of determination (R2;. SDDH model performed quite well as NSE gave result ranging from 0.55 to 0.68 with mean of 0.6. PBIAS indicate that the model slightly over predicted compared to observed hydrograph with result ranges from -46.71 (the most over predicted to +4.83 (the most under predicted with average of -20.73%. R2; ranges between 0.55 to 0.82 with mean of 0.67. When comparing the time to peak, (tp, min, and peak discharge, (pd, m3/s, results gave NSEtp 0.82, PBIAStp 0.65, R2tp 0.32, NSEpd 0.95, PBIASpd 14.49 and R2pd 0
Hazenberg, P.; Leijnse, H.; Torfs, P.; Uijlenhoet, R.; Weerts, A.; Reggiani, P.; Delobbe, L.
2008-12-01
In the southern Ardennes region of Belgium near the border with Luxembourg, the Royal Meteorological Institute of Belgium (RMI) installed a C-band Doppler weather radar at an elevation of 600 m in the year 2001. This volumetric weather radar scans over multiple elevations at a temporal resolution of 5 minutes. The current study explores the possibility of using the volumetric information of the precipitation field to correct for the effects of the Vertical Profile of Reflectivity (VPR) over the period October 1, 2002 until March 31, 2003. During this winter half year storm events are mainly stratiform, giving rise to bright band effects which can decrease the performance of the radar. Previous studies have shown multiple drawbacks in applying a single estimated VPR profile to correct such reflectivity data. Therefore, the focus here is on the temporal variability of the VPR as measured by the radar and its variability over different spatial scales. This information is applied to generate a number of possible rainfall fields. These realizations are employed to try to quantify some of the discrepancies in precipitation intensities as estimated by the weather radar and those measured by a raingauge network. The final step then is to assess their potential within a distributed rainfall runoff model. The 1597 km2 Ourthe catchment lies within 60 km of the radar. Over this medium sized watershed ten raingauges measuring at an hourly interval are more or less equally distributed. Near the outlet discharge data are collected at the same time step. The distributed hydrological Representative Elementary Watershed (REW) model is applied to model the hydrological behavior of the Ourthe over the six month period. The benefits of the high spatial and temporal resolution of weather radar data compared to a conventional raingauge network plus the possibility of generating multiple realizations of the precipitation field are expected to yield more information about the hydrological
Development of rainfall-runoff forecast model | Oyebode | Journal of ...
African Journals Online (AJOL)
... and meterological variables involved in rainfall-runoff process to improve forecast accuracy of rainfallrunoff. ... The simulation was done using MATLAB® 7.0. The simulation results showed that neurofuzzy-based model has higher coefficient ...
Regionalising Parameters of a Conceptual Rainfall-Runoff Model for ...
African Journals Online (AJOL)
IHACRES, a lumped conceptual rainfall-runoff model, was calibrated to six catchments ranging in size from 49km2 to 600 km2 within the upper Tana River basin to obtain a set of model parameters that characterise the hydrological behaviour within the region. Physical catchment attributes indexing topography, soil and ...
An Overview of Rainfall-Runoff Model Types
This report explores rainfall-runoff models, their generation methods, and the categories under which they fall. Runoff plays an important role in the hydrological cycle by returning excess precipitation to the oceans and controlling how much water flows into stream systems. Mode...
DAILY RAINFALL-RUNOFF MODELLING BY NEURAL NETWORKS ...
African Journals Online (AJOL)
K. Benzineb, M. Remaoun
2016-09-01
Sep 1, 2016 ... The hydrologic behaviour modelling of w. Journal of ... i Ouahrane's basin from rainfall-runoff relation which is non-linea networks ... will allow checking efficiency of formal neural networks for flows simulation in semi-arid zone.
Modeling rainfall-runoff relationship using multivariate GARCH model
Modarres, R.; Ouarda, T. B. M. J.
2013-08-01
The traditional hydrologic time series approaches are used for modeling, simulating and forecasting conditional mean of hydrologic variables but neglect their time varying variance or the second order moment. This paper introduces the multivariate Generalized Autoregressive Conditional Heteroscedasticity (MGARCH) modeling approach to show how the variance-covariance relationship between hydrologic variables varies in time. These approaches are also useful to estimate the dynamic conditional correlation between hydrologic variables. To illustrate the novelty and usefulness of MGARCH models in hydrology, two major types of MGARCH models, the bivariate diagonal VECH and constant conditional correlation (CCC) models are applied to show the variance-covariance structure and cdynamic correlation in a rainfall-runoff process. The bivariate diagonal VECH-GARCH(1,1) and CCC-GARCH(1,1) models indicated both short-run and long-run persistency in the conditional variance-covariance matrix of the rainfall-runoff process. The conditional variance of rainfall appears to have a stronger persistency, especially long-run persistency, than the conditional variance of streamflow which shows a short-lived drastic increasing pattern and a stronger short-run persistency. The conditional covariance and conditional correlation coefficients have different features for each bivariate rainfall-runoff process with different degrees of stationarity and dynamic nonlinearity. The spatial and temporal pattern of variance-covariance features may reflect the signature of different physical and hydrological variables such as drainage area, topography, soil moisture and ground water fluctuations on the strength, stationarity and nonlinearity of the conditional variance-covariance for a rainfall-runoff process.
EVALUATION OF RAINFALL-RUNOFF MODELS FOR MEDITERRANEAN SUBCATCHMENTS
Directory of Open Access Journals (Sweden)
A. Cilek
2016-06-01
Full Text Available The development and the application of rainfall-runoff models have been a corner-stone of hydrological research for many decades. The amount of rainfall and its intensity and variability control the generation of runoff and the erosional processes operating at different scales. These interactions can be greatly variable in Mediterranean catchments with marked hydrological fluctuations. The aim of the study was to evaluate the performance of rainfall-runoff model, for rainfall-runoff simulation in a Mediterranean subcatchment. The Pan-European Soil Erosion Risk Assessment (PESERA, a simplified hydrological process-based approach, was used in this study to combine hydrological surface runoff factors. In total 128 input layers derived from data set includes; climate, topography, land use, crop type, planting date, and soil characteristics, are required to run the model. Initial ground cover was estimated from the Landsat ETM data provided by ESA. This hydrological model was evaluated in terms of their performance in Goksu River Watershed, Turkey. It is located at the Central Eastern Mediterranean Basin of Turkey. The area is approximately 2000 km2. The landscape is dominated by bare ground, agricultural and forests. The average annual rainfall is 636.4mm. This study has a significant importance to evaluate different model performances in a complex Mediterranean basin. The results provided comprehensive insight including advantages and limitations of modelling approaches in the Mediterranean environment.
Versini, Pierre-Antoine; Gires, Auguste; Tchinguirinskaia, Ioulia; Schertzer, Daniel
2016-10-01
Currently widespread in new urban projects, green roofs have shown a positive impact on urban runoff at the building scale: decrease and slow-down of the peak discharge, and decrease of runoff volume. The present work aims to study their possible impact at the catchment scale, more compatible with stormwater management issues. For this purpose, a specific module dedicated to simulating the hydrological behaviour of a green roof has been developed in the distributed rainfall-runoff model (Multi-Hydro). It has been applied on a French urban catchment where most of the building roofs are flat and assumed to accept the implementation of a green roof. Catchment responses to several rainfall events covering a wide range of meteorological situations have been simulated. The simulation results show green roofs can significantly reduce runoff volume and the magnitude of peak discharge (up to 80%) depending on the rainfall event and initial saturation of the substrate. Additional tests have been made to assess the susceptibility of this response regarding both spatial distributions of green roofs and precipitation. It appears that the total area of greened roofs is more important than their locations. On the other hand, peak discharge reduction seems to be clearly dependent on spatial distribution of precipitation.
Parameter estimation in stochastic rainfall-runoff models
DEFF Research Database (Denmark)
Jonsdottir, Harpa; Madsen, Henrik; Palsson, Olafur Petur
2006-01-01
A parameter estimation method for stochastic rainfall-runoff models is presented. The model considered in the paper is a conceptual stochastic model, formulated in continuous-discrete state space form. The model is small and a fully automatic optimization is, therefore, possible for estimating all...... the parameter values are optimal for simulation or prediction. The data originates from Iceland and the model is designed for Icelandic conditions, including a snow routine for mountainous areas. The model demands only two input data series, precipitation and temperature and one output data series...
Modeling rainfall-runoff process using soft computing techniques
Kisi, Ozgur; Shiri, Jalal; Tombul, Mustafa
2013-02-01
Rainfall-runoff process was modeled for a small catchment in Turkey, using 4 years (1987-1991) of measurements of independent variables of rainfall and runoff values. The models used in the study were Artificial Neural Networks (ANNs), Adaptive Neuro-Fuzzy Inference System (ANFIS) and Gene Expression Programming (GEP) which are Artificial Intelligence (AI) approaches. The applied models were trained and tested using various combinations of the independent variables. The goodness of fit for the model was evaluated in terms of the coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), coefficient of efficiency (CE) and scatter index (SI). A comparison was also made between these models and traditional Multi Linear Regression (MLR) model. The study provides evidence that GEP (with RMSE=17.82 l/s, MAE=6.61 l/s, CE=0.72 and R2=0.978) is capable of modeling rainfall-runoff process and is a viable alternative to other applied artificial intelligence and MLR time-series methods.
Assessment of runoff contributing catchment areas in rainfall runoff modelling
DEFF Research Database (Denmark)
Thorndahl, Søren; Johansen, C.; Schaarup-Jensen, Kjeld
2006-01-01
In numerical modelling of rainfall caused runoff in urban sewer systems an essential parameter is the hydrological reduction factor which defines the percentage of the impervious area contributing to the surface flow towards the sewer. As the hydrological processes during a rainfall are difficult...... to determine with significant precision the hydrological reduction factor is implemented to account all hydrological losses except the initial loss. This paper presents an inconsistency between calculations of the hydrological reduction factor, based on measurements of rainfall and runoff, and till now...... recommended literature values for residential areas. It is proven by comparing rainfall-runoff measurements from four different residential catchments that the literature values of the hydrological reduction factor are over-estimated for this type of catchment. In addition, different catchment descriptions...
Rainfall-runoff modeling in the Turkey River using numerical and ...
African Journals Online (AJOL)
Modeling rainfall-runoff relationships in a watershed have an important role in water resources engineering. Researchers have used numerical models for modeling rainfall-runoff ... Also, by using SPSS software, the regression equations were developed and then the best equation was selected from regression analysis.
Modeling of the Monthly Rainfall-Runoff Process Through Regressions
Directory of Open Access Journals (Sweden)
Campos-Aranda Daniel Francisco
2014-10-01
Full Text Available To solve the problems associated with the assessment of water resources of a river, the modeling of the rainfall-runoff process (RRP allows the deduction of runoff missing data and to extend its record, since generally the information available on precipitation is larger. It also enables the estimation of inputs to reservoirs, when their building led to the suppression of the gauging station. The simplest mathematical model that can be set for the RRP is the linear regression or curve on a monthly basis. Such a model is described in detail and is calibrated with the simultaneous record of monthly rainfall and runoff in Ballesmi hydrometric station, which covers 35 years. Since the runoff of this station has an important contribution from the spring discharge, the record is corrected first by removing that contribution. In order to do this a procedure was developed based either on the monthly average regional runoff coefficients or on nearby and similar watershed; in this case the Tancuilín gauging station was used. Both stations belong to the Partial Hydrologic Region No. 26 (Lower Rio Panuco and are located within the state of San Luis Potosi, México. The study performed indicates that the monthly regression model, due to its conceptual approach, faithfully reproduces monthly average runoff volumes and achieves an excellent approximation in relation to the dispersion, proved by calculation of the means and standard deviations.
Mufeti, P.; Rientjes, T.H.M.; Mabande, P.; Maathuis, B.H.P.
2013-01-01
Applications of distributed hydrological models are often constrained by poor data availability. Models rely on distributed inputs for meteorological forcing and land surface parameterization. In this pilot the rainfall runoff model LISFLOOD for large scale streamflow simulation is tested for the
Rainfall-runoff and hydraulic modelling integration in the Blatina River
International Nuclear Information System (INIS)
Timko, J.
2017-01-01
This paper investigates the use and integration of rainfall-runoff modelling and hydrologic modelling of Blatina river catchment. Characteristics of physical-geographical sphere and its components were created within the model, enhancing the robustness of input data for the mathematical modelling of landscape runoff. Rainfall-runoff model HEC-HMS utilised in this research allows using a wide range of methodologies to determine the movement of water in the riverbed, water losses in the basin, hydraulic and hydrological methods of transformation and base-flow. Loss and transformation of water in the basin were modeled with curve numbers method SCS-CN. The simulated hydrograph was calibrated using rainfall-runoff event from June 2009. The same event was also modelled after the deforestation of the focus area. Using hydraulic model MIKE 21, a flood of focus rainfall-runoff area was simulated under both current real and changed land cover scenarios. (authors)
Improved rainfall-runoff approach using lumped and conceptual modelling
Durán Barroso, Pablo
2016-01-01
Rainfall-runoff quantification is one of the most important tasks in both engineering and watershed management as it allows to identify, forecast and explain watershed response. The division of the rainfall depth between infiltration and runoff has a high level of complexity due to the spatial heterogeneity in real catchments and the temporal precipitation variability, which provide scale effects on the overall runoff volumes. The Natural Resources Conservation Service Curve Number (NRCS CN) ...
Multi-Site Calibration of Linear Reservoir Based Geomorphologic Rainfall-Runoff Models
Directory of Open Access Journals (Sweden)
Bahram Saeidifarzad
2014-09-01
Full Text Available Multi-site optimization of two adapted event-based geomorphologic rainfall-runoff models was presented using Non-dominated Sorting Genetic Algorithm (NSGA-II method for the South Fork Eel River watershed, California. The first model was developed based on Unequal Cascade of Reservoirs (UECR and the second model was presented as a modified version of Geomorphological Unit Hydrograph based on Nash’s model (GUHN. Two calibration strategies were considered as semi-lumped and semi-distributed for imposing (or unimposing the geomorphology relations in the models. The results of models were compared with Nash’s model. Obtained results using the observed data of two stations in the multi-site optimization framework showed reasonable efficiency values in both the calibration and the verification steps. The outcomes also showed that semi-distributed calibration of the modified GUHN model slightly outperformed other models in both upstream and downstream stations during calibration. Both calibration strategies for the developed UECR model during the verification phase showed slightly better performance in the downstream station, but in the upstream station, the modified GUHN model in the semi-lumped strategy slightly outperformed the other models. The semi-lumped calibration strategy could lead to logical lag time parameters related to the basin geomorphology and may be more suitable for data-based statistical analyses of the rainfall-runoff process.
Assessment of Runoff Contributing Catchment Areas in Rainfall Runoff Modelling
DEFF Research Database (Denmark)
Thorndahl, Søren Liedtke; Johansen, C.; Schaarup-Jensen, Kjeld
2005-01-01
to determine with significant precision the hydrological reduction factor is implemented to account all hydrological losses except the initial loss. This paper presents an inconsistency between calculations of the hydrological reduction factor, based on measurements of rainfall and runoff, and till now...... recommended literary values for residential areas. It is proven by comparing rainfall-runoff measurements from four different residential catchments that the literary values of the hydrological reduction factor are over-estimated for this type of catchments. In addition, different catchment descriptions...
Daily rainfall-runoff modelling by neural networks in semi-arid zone ...
African Journals Online (AJOL)
This research work will allow checking efficiency of formal neural networks for flows' modelling of wadi Ouahrane's basin from rainfall-runoff relation which is non-linear. Two models of neural networks were optimized through supervised learning and compared in order to achieve this goal, the first model with input rain, and ...
Wildcat5 for Windows, a rainfall-runoff hydrograph model: user manual and documentation
R. H. Hawkins; A. Barreto-Munoz
2016-01-01
Wildcat5 for Windows (Wildcat5) is an interactive Windows Excel-based software package designed to assist watershed specialists in analyzing rainfall runoff events to predict peak flow and runoff volumes generated by single-event rainstorms for a variety of watershed soil and vegetation conditions. Model inputs are: (1) rainstorm characteristics, (2) parameters related...
Directory of Open Access Journals (Sweden)
Xiuli Sang
2012-01-01
Full Text Available We constructed a similarity model (based on Euclidean distance between rainfall and runoff to study time-correlated characteristics of rainfall-runoff similar patterns in the upstream Red River Basin and presented a detailed evaluation of the time correlation of rainfall-runoff similarity. The rainfall-runoff similarity was used to determine the optimum similarity. The results showed that a time-correlated model was found to be capable of predicting the rainfall-runoff similarity in the upstream Red River Basin in a satisfactory way. Both noised and denoised time series by thresholding the wavelet coefficients were applied to verify the accuracy of model. And the corresponding optimum similar sets obtained as the equation solution conditions showed an interesting and stable trend. On the whole, the annual mean similarity presented a gradually rising trend, for quantitatively estimating comprehensive influence of climate change and of human activities on rainfall-runoff similarity.
Application of random number generators in genetic algorithms to improve rainfall-runoff modelling
Chlumecký, Martin; Buchtele, Josef; Richta, Karel
2017-10-01
The efficient calibration of rainfall-runoff models is a difficult issue, even for experienced hydrologists. Therefore, fast and high-quality model calibration is a valuable improvement. This paper describes a novel methodology and software for the optimisation of a rainfall-runoff modelling using a genetic algorithm (GA) with a newly prepared concept of a random number generator (HRNG), which is the core of the optimisation. The GA estimates model parameters using evolutionary principles, which requires a quality number generator. The new HRNG generates random numbers based on hydrological information and it provides better numbers compared to pure software generators. The GA enhances the model calibration very well and the goal is to optimise the calibration of the model with a minimum of user interaction. This article focuses on improving the internal structure of the GA, which is shielded from the user. The results that we obtained indicate that the HRNG provides a stable trend in the output quality of the model, despite various configurations of the GA. In contrast to previous research, the HRNG speeds up the calibration of the model and offers an improvement of rainfall-runoff modelling.
Assessment of initial soil moisture conditions for event-based rainfall-runoff modelling
Tramblay, Yves; Bouvier, Christophe; Martin, C.; Didon-Lescot, J. F.; Todorovik, D.; Domergue, J. M.
2010-01-01
Flash floods are the most destructive natural hazards that occur in the Mediterranean region. Rainfall-runoff models can be very useful for flash flood forecasting and prediction. Event-based models are very popular for operational purposes, but there is a need to reduce the uncertainties related to the initial moisture conditions estimation prior to a flood event. This paper aims to compare several soil moisture indicators: local Time Domain Reflectometry (TDR) measurements of soil moisture,...
Aronica, G. T.; Candela, A.
2007-12-01
SummaryIn this paper a Monte Carlo procedure for deriving frequency distributions of peak flows using a semi-distributed stochastic rainfall-runoff model is presented. The rainfall-runoff model here used is very simple one, with a limited number of parameters and practically does not require any calibration, resulting in a robust tool for those catchments which are partially or poorly gauged. The procedure is based on three modules: a stochastic rainfall generator module, a hydrologic loss module and a flood routing module. In the rainfall generator module the rainfall storm, i.e. the maximum rainfall depth for a fixed duration, is assumed to follow the two components extreme value (TCEV) distribution whose parameters have been estimated at regional scale for Sicily. The catchment response has been modelled by using the Soil Conservation Service-Curve Number (SCS-CN) method, in a semi-distributed form, for the transformation of total rainfall to effective rainfall and simple form of IUH for the flood routing. Here, SCS-CN method is implemented in probabilistic form with respect to prior-to-storm conditions, allowing to relax the classical iso-frequency assumption between rainfall and peak flow. The procedure is tested on six practical case studies where synthetic FFC (flood frequency curve) were obtained starting from model variables distributions by simulating 5000 flood events combining 5000 values of total rainfall depth for the storm duration and AMC (antecedent moisture conditions) conditions. The application of this procedure showed how Monte Carlo simulation technique can reproduce the observed flood frequency curves with reasonable accuracy over a wide range of return periods using a simple and parsimonious approach, limited data input and without any calibration of the rainfall-runoff model.
Neill, Aaron; Reaney, Sim
2015-04-01
Fully-distributed, physically-based rainfall-runoff models attempt to capture some of the complexity of the runoff processes that operate within a catchment, and have been used to address a variety of issues including water quality and the effect of climate change on flood frequency. Two key issues are prevalent, however, which call into question the predictive capability of such models. The first is the issue of parameter equifinality which can be responsible for large amounts of uncertainty. The second is whether such models make the right predictions for the right reasons - are the processes operating within a catchment correctly represented, or do the predictive abilities of these models result only from the calibration process? The use of additional data sources, such as environmental tracers, has been shown to help address both of these issues, by allowing for multi-criteria model calibration to be undertaken, and by permitting a greater understanding of the processes operating in a catchment and hence a more thorough evaluation of how well catchment processes are represented in a model. Using discharge and oxygen-18 data sets, the ability of the fully-distributed, physically-based CRUM3 model to represent the runoff processes in three sub-catchments in Cumbria, NW England has been evaluated. These catchments (Morland, Dacre and Pow) are part of the of the River Eden demonstration test catchment project. The oxygen-18 data set was firstly used to derive transit-time distributions and mean residence times of water for each of the catchments to gain an integrated overview of the types of processes that were operating. A generalised likelihood uncertainty estimation procedure was then used to calibrate the CRUM3 model for each catchment based on a single discharge data set from each catchment. Transit-time distributions and mean residence times of water obtained from the model using the top 100 behavioural parameter sets for each catchment were then compared to
A geomorphology-based ANFIS model for multi-station modeling of rainfall-runoff process
Nourani, Vahid; Komasi, Mehdi
2013-05-01
This paper demonstrates the potential use of Artificial Intelligence (AI) techniques for predicting daily runoff at multiple gauging stations. Uncertainty and complexity of the rainfall-runoff process due to its variability in space and time in one hand and lack of historical data on the other hand, cause difficulties in the spatiotemporal modeling of the process. In this paper, an Integrated Geomorphological Adaptive Neuro-Fuzzy Inference System (IGANFIS) model conjugated with C-means clustering algorithm was used for rainfall-runoff modeling at multiple stations of the Eel River watershed, California. The proposed model could be used for predicting runoff in the stations with lack of data or any sub-basin within the watershed because of employing the spatial and temporal variables of the sub-basins as the model inputs. This ability of the integrated model for spatiotemporal modeling of the process was examined through the cross validation technique for a station. In this way, different ANFIS structures were trained using Sugeno algorithm in order to estimate daily discharge values at different stations. In order to improve the model efficiency, the input data were then classified into some clusters by the means of fuzzy C-means (FCMs) method. The goodness-of-fit measures support the gainful use of the IGANFIS and FCM methods in spatiotemporal modeling of hydrological processes.
Integrating Artificial Neural Networks into the VIC Model for Rainfall-Runoff Modeling
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Changqing Meng
2016-09-01
Full Text Available A hybrid rainfall-runoff model was developed in this study by integrating the variable infiltration capacity (VIC model with artificial neural networks (ANNs. In the proposed model, the prediction interval of the ANN replaces separate, individual simulation (i.e., single simulation. The spatial heterogeneity of horizontal resolution, subgrid-scale features and their influence on the streamflow can be assessed according to the VIC model. In the routing module, instead of a simple linear superposition of the streamflow generated from each subbasin, ANNs facilitate nonlinear mappings of the streamflow produced from each subbasin into the total streamflow at the basin outlet. A total of three subbasins were delineated and calibrated independently via the VIC model; daily runoff errors were simulated for each subbasin, then corrected by an ANN bias-correction model. The initial streamflow and corrected runoff from the simulation for individual subbasins serve as inputs to the ANN routing model. The feasibility of this proposed method was confirmed according to the performance of its application to a case study on rainfall-runoff prediction in the Jinshajiang River Basin, the headwater area of the Yangtze River.
Fowler, Keirnan J. A.; Peel, Murray C.; Western, Andrew W.; Zhang, Lu; Peterson, Tim J.
2016-03-01
Hydrologic models have potential to be useful tools in planning for future climate variability. However, recent literature suggests that the current generation of conceptual rainfall runoff models tend to underestimate the sensitivity of runoff to a given change in rainfall, leading to poor performance when evaluated over multiyear droughts. This research revisited this conclusion, investigating whether the observed poor performance could be due to insufficient model calibration and evaluation techniques. We applied an approach based on Pareto optimality to explore trade-offs between model performance in different climatic conditions. Five conceptual rainfall runoff model structures were tested in 86 catchments in Australia, for a total of 430 Pareto analyses. The Pareto results were then compared with results from a commonly used model calibration and evaluation method, the Differential Split Sample Test. We found that the latter often missed potentially promising parameter sets within a given model structure, giving a false negative impression of the capabilities of the model. This suggests that models may be more capable under changing climatic conditions than previously thought. Of the 282[347] cases of apparent model failure under the split sample test using the lower [higher] of two model performance criteria trialed, 155[120] were false negatives. We discuss potential causes of remaining model failures, including the role of data errors. Although the Pareto approach proved useful, our aim was not to suggest an alternative calibration strategy, but to critically assess existing methods of model calibration and evaluation. We recommend caution when interpreting split sample results.
Application of random number generators in genetic algorithms to improve rainfall-runoff modelling
Czech Academy of Sciences Publication Activity Database
Chlumecký, M.; Buchtele, Josef; Richta, K.
2017-01-01
Roč. 553, October (2017), s. 350-355 ISSN 0022-1694 Institutional support: RVO:67985874 Keywords : genetic algorithm * optimisation * rainfall-runoff modeling * random generator Subject RIV: DA - Hydrology ; Limnology OBOR OECD: Hydrology Impact factor: 3.483, year: 2016 https://ac.els-cdn.com/S0022169417305516/1-s2.0-S0022169417305516-main.pdf?_tid=fa1bad8a-bd6a-11e7-8567-00000aab0f27&acdnat=1509365462_a1335d3d997e9eab19e23b1eee977705
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A. E. Sikorska
2012-04-01
Full Text Available Urbanization and the resulting land-use change strongly affect the water cycle and runoff-processes in watersheds. Unfortunately, small urban watersheds, which are most affected by urban sprawl, are mostly ungauged. This makes it intrinsically difficult to assess the consequences of urbanization. Most of all, it is unclear how to reliably assess the predictive uncertainty given the structural deficits of the applied models. In this study, we therefore investigate the uncertainty of flood predictions in ungauged urban basins from structurally uncertain rainfall-runoff models. To this end, we suggest a procedure to explicitly account for input uncertainty and model structure deficits using Bayesian statistics with a continuous-time autoregressive error model. In addition, we propose a concise procedure to derive prior parameter distributions from base data and successfully apply the methodology to an urban catchment in Warsaw, Poland. Based on our results, we are able to demonstrate that the autoregressive error model greatly helps to meet the statistical assumptions and to compute reliable prediction intervals. In our study, we found that predicted peak flows were up to 7 times higher than observations. This was reduced to 5 times with Bayesian updating, using only few discharge measurements. In addition, our analysis suggests that imprecise rainfall information and model structure deficits contribute mostly to the total prediction uncertainty. In the future, flood predictions in ungauged basins will become more important due to ongoing urbanization as well as anthropogenic and climatic changes. Thus, providing reliable measures of uncertainty is crucial to support decision making.
Calibration of a rainfall-runoff hydrological model and flood simulation using data assimilation
Piacentini, A.; Ricci, S. M.; Thual, O.; Coustau, M.; Marchandise, A.
2010-12-01
Rainfall-runoff models are crucial tools for long-term assessment of flash floods or real-time forecasting. This work focuses on the calibration of a distributed parsimonious event-based rainfall-runoff model using data assimilation. The model combines a SCS-derived runoff model and a Lag and Route routing model for each cell of a regular grid mesh. The SCS-derived runoff model is parametrized by the initial water deficit, the discharge coefficient for the soil reservoir and a lagged discharge coefficient. The Lag and Route routing model is parametrized by the velocity of travel and the lag parameter. These parameters are assumed to be constant for a given catchment except for the initial water deficit and the velocity travel that are event-dependent (landuse, soil type and moisture initial conditions). In the present work, a BLUE filtering technique was used to calibrate the initial water deficit and the velocity travel for each flood event assimilating the first available discharge measurements at the catchment outlet. The advantages of the BLUE algorithm are its low computational cost and its convenient implementation, especially in the context of the calibration of a reduced number of parameters. The assimilation algorithm was applied on two Mediterranean catchment areas of different size and dynamics: Gardon d'Anduze and Lez. The Lez catchment, of 114 km2 drainage area, is located upstream Montpellier. It is a karstic catchment mainly affected by floods in autumn during intense rainstorms with short Lag-times and high discharge peaks (up to 480 m3.s-1 in September 2005). The Gardon d'Anduze catchment, mostly granite and schistose, of 545 km2 drainage area, lies over the departements of Lozère and Gard. It is often affected by flash and devasting floods (up to 3000 m3.s-1 in September 2002). The discharge observations at the beginning of the flood event are assimilated so that the BLUE algorithm provides optimal values for the initial water deficit and the
Future climate scenarios and rainfall-runoff modelling in the Upper Gallego catchment (Spain)
International Nuclear Information System (INIS)
Buerger, C.M.; Kolditz, O.; Fowler, H.J.; Blenkinsop, S.
2007-01-01
Global climate change may have large impacts on water supplies, drought or flood frequencies and magnitudes in local and regional hydrologic systems. Water authorities therefore rely on computer models for quantitative impact prediction. In this study we present kernel-based learning machine river flow models for the Upper Gallego catchment of the Ebro basin. Different learning machines were calibrated using daily gauge data. The models posed two major challenges: (1) estimation of the rainfall-runoff transfer function from the available time series is complicated by anthropogenic regulation and mountainous terrain and (2) the river flow model is weak when only climate data are used, but additional antecedent flow data seemed to lead to delayed peak flow estimation. These types of models, together with the presented downscaled climate scenarios, can be used for climate change impact assessment in the Gallego, which is important for the future management of the system. - Future climate change and data-based rainfall-runoff predictions are presented for the Upper Gallego
Vannametee, E.; Karssenberg, D.; Hendriks, M. R.; de Jong, S. M.; Bierkens, M. F. P.
2010-05-01
We propose a modelling framework for distributed hydrological modelling of 103-105 km2 catchments by discretizing the catchment in geomorphologic units. Each of these units is modelled using a lumped model representative for the processes in the unit. Here, we focus on the development and parameterization of this lumped model as a component of our framework. The development of the lumped model requires rainfall-runoff data for an extensive set of geomorphological units. Because such large observational data sets do not exist, we create artificial data. With a high-resolution, physically-based, rainfall-runoff model, we create artificial rainfall events and resulting hydrographs for an extensive set of different geomorphological units. This data set is used to identify the lumped model of geomorphologic units. The advantage of this approach is that it results in a lumped model with a physical basis, with representative parameters that can be derived from point-scale measurable physical parameters. The approach starts with the development of the high-resolution rainfall-runoff model that generates an artificial discharge dataset from rainfall inputs as a surrogate of a real-world dataset. The model is run for approximately 105 scenarios that describe different characteristics of rainfall, properties of the geomorphologic units (i.e. slope gradient, unit length and regolith properties), antecedent moisture conditions and flow patterns. For each scenario-run, the results of the high-resolution model (i.e. runoff and state variables) at selected simulation time steps are stored in a database. The second step is to develop the lumped model of a geomorphological unit. This forward model consists of a set of simple equations that calculate Hortonian runoff and state variables of the geomorphologic unit over time. The lumped model contains only three parameters: a ponding factor, a linear reservoir parameter, and a lag time. The model is capable of giving an appropriate
Assimilating satellite soil moisture into rainfall-runoff modelling: towards a systematic study
Massari, Christian; Tarpanelli, Angelica; Brocca, Luca; Moramarco, Tommaso
2015-04-01
Soil moisture is the main factor for the repartition of the mass and energy fluxes between the land surface and the atmosphere thus playing a fundamental role in the hydrological cycle. Indeed, soil moisture represents the initial condition of rainfall-runoff modelling that determines the flood response of a catchment. Different initial soil moisture conditions can discriminate between catastrophic and minor effects of a given rainfall event. Therefore, improving the estimation of initial soil moisture conditions will reduce uncertainties in early warning flood forecasting models addressing the mitigation of flood hazard. In recent years, satellite soil moisture products have become available with fine spatial-temporal resolution and a good accuracy. Therefore, a number of studies have been published in which the impact of the assimilation of satellite soil moisture data into rainfall-runoff modelling is investigated. Unfortunately, data assimilation involves a series of assumptions and choices that significantly affect the final result. Given a satellite soil moisture observation, a rainfall-runoff model and a data assimilation technique, an improvement or a deterioration of discharge predictions can be obtained depending on the choices made in the data assimilation procedure. Consequently, large discrepancies have been obtained in the studies published so far likely due to the differences in the implementation of the data assimilation technique. On this basis, a comprehensive and robust procedure for the assimilation of satellite soil moisture data into rainfall-runoff modelling is developed here and applied to six subcatchment of the Upper Tiber River Basin for which high-quality hydrometeorological hourly observations are available in the period 1989-2013. The satellite soil moisture product used in this study is obtained from the Advanced SCATterometer (ASCAT) onboard Metop-A satellite and it is available since 2007. The MISDc ("Modello Idrologico Semi
Rainfall-runoff model for prediction of waterborne viral contamination in a small river catchment
Gelati, E.; Dommar, C.; Lowe, R.; Polcher, J.; Rodó, X.
2013-12-01
We present a lumped rainfall-runoff model aimed at providing useful information for the prediction of waterborne viral contamination in small rivers. Viral contamination of water bodies may occur because of the discharge of sewage effluents and of surface runoff over areas affected by animal waste loads. Surface runoff is caused by precipitation that cannot infiltrate due to its intensity and to antecedent soil water content. It may transport animal feces to adjacent water bodies and cause viral contamination. We model streamflow by separating it into two components: subsurface flow, which is produced by infiltrated precipitation; and surface runoff. The model estimates infiltrated and non-infiltrated precipitation and uses impulse-response functions to compute the corresponding fractions of streamflow. The developed methodologies are applied to the Glafkos river, whose catchment extends for 102 km2 and includes the city of Patra. Streamflow and precipitation observations are available at a daily time resolution. Waterborne virus concentration measurements were performed approximately every second week from the beginning of 2011 to mid 2012. Samples were taken at several locations: in river water upstream of Patras and in the urban area; in sea water at the river outlet and approximately 2 km south-west of Patras; in sewage effluents before and after treatment. The rainfall-runoff model was calibrated and validated using observed streamflow and precipitation data. The model contribution to waterborne viral contamination prediction was benchmarked by analyzing the virus concentration measurements together with the estimated surface runoff values. The presented methodology may be a first step towards the development of waterborne viral contamination alert systems. Predicting viral contamination of water bodies would benefit sectors such as water supply and tourism.
Hazenberg, P.; Leijnse, H.; Uijlenhoet, R.; Delobbe, L.; Weerts, A.; Reggiani, P.
2009-04-01
In the current study half a year of volumetric radar data for the period October 1, 2002 until March 31, 2003 is being analyzed which was sampled at 5 minutes intervals by C-band Doppler radar situated at an elevation of 600 m in the southern Ardennes region, Belgium. During this winter half year most of the rainfall has a stratiform character. Though radar and raingauge will never sample the same amount of rainfall due to differences in sampling strategies, for these stratiform situations differences between both measuring devices become even larger due to the occurrence of a bright band (the point where ice particles start to melt intensifying the radar reflectivity measurement). For these circumstances the radar overestimates the amount of precipitation and because in the Ardennes bright bands occur within 1000 meter from the surface, it's detrimental effects on the performance of the radar can already be observed at relatively close range (e.g. within 50 km). Although the radar is situated at one of the highest points in the region, very close to the radar clutter is a serious problem. As a result both nearby and farther away, using uncorrected radar results in serious errors when estimating the amount of precipitation. This study shows the effect of carefully correcting for these radar errors using volumetric radar data, taking into account the vertical reflectivity profile of the atmosphere, the effects of attenuation and trying to limit the amount of clutter. After applying these correction algorithms, the overall differences between radar and raingauge are much smaller which emphasizes the importance of carefully correcting radar rainfall measurements. The next step is to assess the effect of using uncorrected and corrected radar measurements on rainfall-runoff modeling. The 1597 km2 Ourthe catchment lies within 60 km of the radar. Using a lumped hydrological model serious improvement in simulating observed discharges is found when using corrected radar
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R. J. Moore
2002-01-01
Full Text Available Intermittent streamflow is a common occurrence in permeable catchments, especially where there are pumped abstractions to water supply. Many rainfall-runoff models are not formulated so as to represent ephemeral streamflow behaviour or to allow for the possibility of negative recharge arising from groundwater pumping. A groundwater model component is formulated here for use in extending existing rainfall-runoff models to accommodate such ephemeral behaviour. Solutions to the Horton-Izzard equation resulting from the conceptual model of groundwater storage are adapted and the form of nonlinear storage extended to accommodate negative inputs, water storage below which outflow ceases, and losses to external springs and underflows below the gauged catchment outlet. The groundwater model component is demonstrated through using it as an extension of the PDM rainfall-runoff model. It is applied to the River Lavant, a catchment in Southern England on the English Chalk, where it successfully simulates the ephemeral streamflow behaviour and flood response together with well level variations. Keywords: groundwater, rainfall-runoff model, ephemeral stream, well level, spring, abstraction
Event-based model diagnosis of rainfall-runoff model structures
International Nuclear Information System (INIS)
Stanzel, P.
2012-01-01
The objective of this research is a comparative evaluation of different rainfall-runoff model structures. Comparative model diagnostics facilitate the assessment of strengths and weaknesses of each model. The application of multiple models allows an analysis of simulation uncertainties arising from the selection of model structure, as compared with effects of uncertain parameters and precipitation input. Four different model structures, including conceptual and physically based approaches, are compared. In addition to runoff simulations, results for soil moisture and the runoff components of overland flow, interflow and base flow are analysed. Catchment runoff is simulated satisfactorily by all four model structures and shows only minor differences. Systematic deviations from runoff observations provide insight into model structural deficiencies. While physically based model structures capture some single runoff events better, they do not generally outperform conceptual model structures. Contributions to uncertainty in runoff simulations stemming from the choice of model structure show similar dimensions to those arising from parameter selection and the representation of precipitation input. Variations in precipitation mainly affect the general level and peaks of runoff, while different model structures lead to different simulated runoff dynamics. Large differences between the four analysed models are detected for simulations of soil moisture and, even more pronounced, runoff components. Soil moisture changes are more dynamical in the physically based model structures, which is in better agreement with observations. Streamflow contributions of overland flow are considerably lower in these models than in the more conceptual approaches. Observations of runoff components are rarely made and are not available in this study, but are shown to have high potential for an effective selection of appropriate model structures (author) [de
Impact of the calibration period on the conceptual rainfall-runoff model parameter estimates
Todorovic, Andrijana; Plavsic, Jasna
2015-04-01
A conceptual rainfall-runoff model is defined by its structure and parameters, which are commonly inferred through model calibration. Parameter estimates depend on objective function(s), optimisation method, and calibration period. Model calibration over different periods may result in dissimilar parameter estimates, while model efficiency decreases outside calibration period. Problem of model (parameter) transferability, which conditions reliability of hydrologic simulations, has been investigated for decades. In this paper, dependence of the parameter estimates and model performance on calibration period is analysed. The main question that is addressed is: are there any changes in optimised parameters and model efficiency that can be linked to the changes in hydrologic or meteorological variables (flow, precipitation and temperature)? Conceptual, semi-distributed HBV-light model is calibrated over five-year periods shifted by a year (sliding time windows). Length of the calibration periods is selected to enable identification of all parameters. One water year of model warm-up precedes every simulation, which starts with the beginning of a water year. The model is calibrated using the built-in GAP optimisation algorithm. The objective function used for calibration is composed of Nash-Sutcliffe coefficient for flows and logarithms of flows, and volumetric error, all of which participate in the composite objective function with approximately equal weights. Same prior parameter ranges are used in all simulations. The model is calibrated against flows observed at the Slovac stream gauge on the Kolubara River in Serbia (records from 1954 to 2013). There are no trends in precipitation nor in flows, however, there is a statistically significant increasing trend in temperatures at this catchment. Parameter variability across the calibration periods is quantified in terms of standard deviations of normalised parameters, enabling detection of the most variable parameters
Sensitivity analysis of Takagi-Sugeno-Kang rainfall-runoff fuzzy models
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A. P. Jacquin
2009-01-01
Full Text Available This paper is concerned with the sensitivity analysis of the model parameters of the Takagi-Sugeno-Kang fuzzy rainfall-runoff models previously developed by the authors. These models are classified in two types of fuzzy models, where the first type is intended to account for the effect of changes in catchment wetness and the second type incorporates seasonality as a source of non-linearity. The sensitivity analysis is performed using two global sensitivity analysis methods, namely Regional Sensitivity Analysis and Sobol's variance decomposition. The data of six catchments from different geographical locations and sizes are used in the sensitivity analysis. The sensitivity of the model parameters is analysed in terms of several measures of goodness of fit, assessing the model performance from different points of view. These measures include the Nash-Sutcliffe criteria, volumetric errors and peak errors. The results show that the sensitivity of the model parameters depends on both the catchment type and the measure used to assess the model performance.
An investigation of the effect of hysteresis in a simple rainfall-runoff model
Flynn, D. P.; O'Kane, J. P.
2009-04-01
Multiphase porous media such as soils are known to exhibit hysteresis, e.g. in soils there is a strong hysteretic relationship between the moisture content and the matric potential and to date the Preisach model has been successful in modelling this relationship. Subsequently ODEs with Preisach hysteresis have been developed, such as a hysteretic version of Darcy's law and a hysteretic version of the linear reservoir known as the Preisach reservoir. In this paper we combine the above Hysteretic Differential Equations (HDEs) with three linear reservoirs so as to develop a simple rainfall runoff model. The model can be represented by a block diagram: Rainfall q(t) enters the soil component and either infiltrates and/or runs off when it exceeds the maximum rate of infiltration. The runoff part is fed into two linear reservoirs in series. Next, the drainage from the soil to groundwater is represented by a single linear reservoir, where the output from the soil becomes the input to the ground reservoir and vice-versa for capillary rise. Finally the groundwater and surface runoff are combined at some point and contribute to the total outflow from the catchment. Finally we investigate the effects of hysteresis in this system and compare it to the non-hysteretic case.
Ouyang, Wei; Guo, Bobo; Hao, Fanghua; Huang, Haobo; Li, Junqi; Gong, Yongwei
2012-12-30
Managing storm rainfall runoff is paramount in semi-arid regions with urban development. In Beijing, pollution prevention in urban storm runoff and storm water utilization has been identified as the primary strategy for urban water management. In this paper, we sampled runoff during storm rainfall events and analyzed the concentration of chemical oxygen demand (COD), total suspended solids (TSS) and total phosphorus (TP) in the runoff. Furthermore, the first flush effect of storm rainfall from diverse underlying surfaces was also analyzed. With the Storm Water Management Model (SWMM), the different impervious rates of underlying surfaces during the storm runoff process were expressed. The removal rates of three typical pollutants and their interactions with precipitation and underlying surfaces were identified. From these rates, the scenarios regarding the urban storm runoff pollution loading from different designs of underlying previous rates were assessed with the SWMM. First flush effect analysis showed that the first 20% of the storm runoff should be discarded, which can help in utilizing the storm water resource. The results of this study suggest that the SWMM can express in detail the storm water pollution patterns from diverse underlying surfaces in Beijing, which significantly affected water quality. The scenario analysis demonstrated that impervious rate adjustment has the potential to reduce runoff peak and decrease pollution loading. Copyright © 2012 Elsevier Ltd. All rights reserved.
Costa, Veber; Fernandes, Wilson
2017-11-01
Extreme flood estimation has been a key research topic in hydrological sciences. Reliable estimates of such events are necessary as structures for flood conveyance are continuously evolving in size and complexity and, as a result, their failure-associated hazards become more and more pronounced. Due to this fact, several estimation techniques intended to improve flood frequency analysis and reducing uncertainty in extreme quantile estimation have been addressed in the literature in the last decades. In this paper, we develop a Bayesian framework for the indirect estimation of extreme flood quantiles from rainfall-runoff models. In the proposed approach, an ensemble of long daily rainfall series is simulated with a stochastic generator, which models extreme rainfall amounts with an upper-bounded distribution function, namely, the 4-parameter lognormal model. The rationale behind the generation model is that physical limits for rainfall amounts, and consequently for floods, exist and, by imposing an appropriate upper bound for the probabilistic model, more plausible estimates can be obtained for those rainfall quantiles with very low exceedance probabilities. Daily rainfall time series are converted into streamflows by routing each realization of the synthetic ensemble through a conceptual hydrologic model, the Rio Grande rainfall-runoff model. Calibration of parameters is performed through a nonlinear regression model, by means of the specification of a statistical model for the residuals that is able to accommodate autocorrelation, heteroscedasticity and nonnormality. By combining the outlined steps in a Bayesian structure of analysis, one is able to properly summarize the resulting uncertainty and estimating more accurate credible intervals for a set of flood quantiles of interest. The method for extreme flood indirect estimation was applied to the American river catchment, at the Folsom dam, in the state of California, USA. Results show that most floods
HYDROSCAPE: A SCAlable and ParallelizablE Rainfall Runoff Model for Hydrological Applications
Piccolroaz, S.; Di Lazzaro, M.; Zarlenga, A.; Majone, B.; Bellin, A.; Fiori, A.
2015-12-01
In this work we present HYDROSCAPE, an innovative streamflow routing method based on the travel time approach, and modeled through a fine-scale geomorphological description of hydrological flow paths. The model is designed aimed at being easily coupled with weather forecast or climate models providing the hydrological forcing, and at the same time preserving the geomorphological dispersion of the river network, which is kept unchanged independently on the grid size of rainfall input. This makes HYDROSCAPE particularly suitable for multi-scale applications, ranging from medium size catchments up to the continental scale, and to investigate the effects of extreme rainfall events that require an accurate description of basin response timing. Key feature of the model is its computational efficiency, which allows performing a large number of simulations for sensitivity/uncertainty analyses in a Monte Carlo framework. Further, the model is highly parsimonious, involving the calibration of only three parameters: one defining the residence time of hillslope response, one for channel velocity, and a multiplicative factor accounting for uncertainties in the identification of the potential maximum soil moisture retention in the SCS-CN method. HYDROSCAPE is designed with a simple and flexible modular structure, which makes it particularly prone to massive parallelization, customization according to the specific user needs and preferences (e.g., rainfall-runoff model), and continuous development and improvement. Finally, the possibility to specify the desired computational time step and evaluate streamflow at any location in the domain, makes HYDROSCAPE an attractive tool for many hydrological applications, and a valuable alternative to more complex and highly parametrized large scale hydrological models. Together with model development and features, we present an application to the Upper Tiber River basin (Italy), providing a practical example of model performance and
Zheng, Y.; Luo, X.; Lin, Z.
2016-12-01
The urban environment has a variety of Persistent Toxic Substances (PTS), such as Polycyclic Aromatic Hydrocarbons (PAHs) and mercury. Soil in pervious lands and dust deposited on impervious surfaces are two major sinks of PTSs in urbanized areas, which could contribute significant nonpoint source loadings of PTSs to adjacent waterbodies during rainfall-runoff events and therefore jeopardize aquatic ecosystems. However, PTSs have been much less understood regarding their export mechanisms in urban land uses, and efforts to model nonpoint source pollution processes of PTSs have been rare. We designed and performed in-lab rainfall-runoff simulation experiments to investigate transport of PAHs and mercury by runoff from urban soils. Organic petrology analysis (OPA) techniques were introduced to analyze the soil and sediment compositions. Our study revealed the limitation of the classic enrichment theory which attributes enrichment of pollutants in eroded sediment solely to the sediment's particle size distribution and adopts simple relationships between enrichment ratio and sediment flux. We found that carbonaceous materials (CMs) in soil are the direct and major sorbents for PAHs and mercury, and highly different in content, mobility and adsorption capacity for the PTSs. Anthropogenic CMs like black carbon components largely control the transport of soil PAHs, while humic substances have a dominant influence on the transport of soil mercury. A model was further developed to estimate the enrichment ratio of PAHs, which innovatively applies the fugacity concept.We also conducted field studies on export of PAHs by runoff from urban roads. A variable time-step model was developed to simulate the continuous cycles of PAH buildup and washoff on urban roads. The dependence of the pollution level on antecedent weather conditions was investigated and embodied in the model. The applicability of this approach and its value to environmental management was demonstrated by a case
Catchment area-based evaluation of the AMC-dependent SCS-CN-based rainfall-runoff models
Mishra, S. K.; Jain, M. K.; Pandey, R. P.; Singh, V. P.
2005-09-01
Using a large set of rainfall-runoff data from 234 watersheds in the USA, a catchment area-based evaluation of the modified version of the Mishra and Singh (2002a) model was performed. The model is based on the Soil Conservation Service Curve Number (SCS-CN) methodology and incorporates the antecedent moisture in computation of direct surface runoff. Comparison with the existing SCS-CN method showed that the modified version performed better than did the existing one on the data of all seven area-based groups of watersheds ranging from 0.01 to 310.3 km2.
Abrahart, R. J.; Beriro, D. J.
2012-04-01
The information content in a rainfall-runoff record is sufficient to support models of only very limited complexity (Jakeman and Hornberger, 1993). This begs the question of what limits should observed data place on the allowable complexity of rainfall-runoff models? Eureqa1 (Schmidt and Lipson, 2009) - pronounced "eureka" - is a software tool for finding equations and detecting mathematical relationships in a dataset. The challenge, for both software and modeller, is to identify, by means of symbolic regression, the simplest mathematical formulas which describe the underlying mechanisms that produced the data. It actually delivers, however, a series of preferred modelling solutions comprising one champion for each specific level of complexity i.e. related to solution enlargement involving the progressive incorporation of additional permitted factors (internal operators/ external drivers). The potential benefit of increased complexity can as a result be assessed in a rational manner. Eureqa is free to download and use; and, in the current study, has been employed to construct a set of rainfall-runoff transfer function models for the Annapolis River at Wilmot, in north-western Nova Scotia, Canada. The climatic conditions in this catchment present an interesting set of modelling challenges; daily variations and seasonal changes in temperature, snowfall and retention result in great difficulty for runoff prediction by means of a data-driven approach. Data from 10 years of daily observations are used in the present study (01/01/2000-31/12/2009): comprising [i] discharge, [ii] total rainfall (excluding snowfall), [iii] total snowfall, [iv] thickness of snow cover, and [v] maximum and [vi] minimum temperature. Precipitation occurs throughout the whole year being slightly lower during summer. Snowfall is common from November until April and rare hurricane weather may occur in autumn. The average maximum temperature is below 0 0C in January and February, but significant
Donker, N. H. W.
2001-01-01
A hydrological model (YWB, yearly water balance) has been developed to model the daily rainfall-runoff relationship of the 202 km2 Teba river catchment, located in semi-arid south-eastern Spain. The period of available data (1976-1993) includes some very rainy years with intensive storms (responsible for flooding parts of the town of Malaga) and also some very dry years.The YWB model is in essence a simple tank model in which the catchment is subdivided into a limited number of meaningful hydrological units. Instead of generating per unit surface runoff resulting from infiltration excess, runoff has been made the result of storage excess. Actual evapotranspiration is obtained by means of curves, included in the software, representing the relationship between the ratio of actual to potential evapotranspiration as a function of soil moisture content for three soil texture classes.The total runoff generated is split between base flow and surface runoff according to a given baseflow index. The two components are routed separately and subsequently joined. A large number of sequential years can be processed, and the results of each year are summarized by a water balance table and a daily based rainfall runoff time series. An attempt has been made to restrict the amount of input data to the minimum.Interactive manual calibration is advocated in order to allow better incorporation of field evidence and the experience of the model user. Field observations allowed for an approximate calibration at the hydrological unit level.
van Emmerik, Tim; Eilander, Dirk; Piet, Marijn; Mulder, Gert
2013-04-01
The Chamcar Bei catchment in southern Cambodia is a typical ungauged basin. Neither meteorological data or discharge measurements are available. In this catchment, local farmers are highly dependent on the irrigation system. However, due to the unreliability of the water supply, it was required to make a hydrological model, with which further improvements of the irrigation system could be planned. First, we used knowledge generated in the IAHS decade on Predictions in Ungauged Basins (PUB) to estimate the annual water balance of the Chamcar Bei catchment. Next, using remotely sensed precipitation, vegetation, elevation and transpiration data, a monthly rainfall-runoff model has been developed. The rainfall-runoff model was linked to the irrigation system reservoir, which allowed to validate the model based on soft data such as historical knowledge of the reservoir water level and groundwater levels visible in wells. This study shows that combining existing remote sensing data and soft ground data can lead to useful modeling results. The approach presented in this study can be applied in other ungauged basins, which can be extremely helpful in managing water resources in developing countries.
Capra, Lucia; Coviello, Velio; Borselli, Lorenzo; Márquez-Ramírez, Víctor-Hugo; Arámbula-Mendoza, Raul
2018-03-01
The Volcán de Colima, one of the most active volcanoes in Mexico, is commonly affected by tropical rains related to hurricanes that form over the Pacific Ocean. In 2011, 2013 and 2015 hurricanes Jova, Manuel and Patricia, respectively, triggered tropical storms that deposited up to 400 mm of rain in 36 h, with maximum intensities of 50 mm h -1. The effects were devastating, with the formation of multiple lahars along La Lumbre and Montegrande ravines, which are the most active channels in sediment delivery on the south-southwest flank of the volcano. Deep erosion along the river channels and several marginal landslides were observed, and the arrival of block-rich flow fronts resulted in damages to bridges and paved roads in the distal reaches of the ravines. The temporal sequence of these flow events is reconstructed and analyzed using monitoring data (including video images, seismic records and rainfall data) with respect to the rainfall characteristics and the hydrologic response of the watersheds based on rainfall-runoff numerical simulation. For the studied events, lahars occurred 5-6 h after the onset of rainfall, lasted several hours and were characterized by several pulses with block-rich fronts and a maximum flow discharge of 900 m3 s -1. Rainfall-runoff simulations were performer using the SCS-curve number and the Green-Ampt infiltration models, providing a similar result in the detection of simulated maximum watershed peaks discharge. Results show different behavior for the arrival times of the first lahar pulses that correlate with the simulated catchment's peak discharge for La Lumbre ravine and with the peaks in rainfall intensity for Montegrande ravine. This different behavior is related to the area and shape of the two watersheds. Nevertheless, in all analyzed cases, the largest lahar pulse always corresponds with the last one and correlates with the simulated maximum peak discharge of these catchments. Data presented here show that flow pulses
Classic rainfall-runoff models usually use historical data to estimate model parameters and mean values of parameters are considered for predictions. However, due to climate changes and human effects, the parameters of model change temporally. To overcome this problem, Normalized Difference Vegetati...
Chardon, J.; Mathevet, T.; Le Lay, M.; Gailhard, J.
2012-04-01
dynamic and processes, i. e. sample heterogeneity. For a same streamflow range corresponds different processes such as rising limbs or recession, where uncertainties are different. The dynamical approach improves reliability, skills and sharpness of forecasts and globally reduces confidence intervals width. When compared in details, the dynamical approach allows a noticeable reduction of confidence intervals during recessions where uncertainty is relatively lower and a slight increase of confidence intervals during rising limbs or snowmelt where uncertainty is greater. The dynamic approach, validated by forecaster's experience that considered the empirical approach not discriminative enough, improved forecaster's confidence and communication of uncertainties. Montanari, A. and Brath, A., (2004). A stochastic approach for assessing the uncertainty of rainfall-runoff simulations. Water Resources Research, 40, W01106, doi:10.1029/2003WR002540. Schaefli, B., Balin Talamba, D. and Musy, A., (2007). Quantifying hydrological modeling errors through a mixture of normal distributions. Journal of Hydrology, 332, 303-315.
Todini, E.; Bartholmes, J.
The project EFFS (European Flood Forecasting System) aims at developing a flood forecasting system for the major river basins all over Europe. To extend the forecast- ing and thus the warning time in a significant way (up to 10 days) meteorological forecasting data from the ECMWF will be used as input to hydrological models. For this purpose it is fundamental to have a reliable rainfall-runoff model. For the river Po basin we chose the TOPKAPI model (Ciarapica, Todini 1998). TOPKAPI is a physi- cally based rainfall-runoff model that maintains its physical significance passing from hillslope to large basin scale. The aim of the distributed version is to reproduce the spatial variability and to lead to a better understanding of scaling effects on meteo- rological data used as well as of physical phenomena and parameters. By now the TOPKAPI model has been applied successfully to basins of smaller and medium size (up to 8000 km2). The present work also proves that TOPKAPI is a valuable flood forecasting tool for larger basins such as the Po river. An advantage of the TOPKAPI model is its physical basis. It doesn't need a "real" calibration in the common sense of the expression. The calibration work that has to be done is due to the unavoidable averaging and approximation in the input data representing various phenomena. This reduces the calibration work as well as the length of data required. The model was implemented on the Po river at spatial steps of 1km and time steps of 1 hour using available data during the year 1994. After the calibration phase, mesoscale forecasts (from ECMWF) as well as forecasts of LAM models (DWD,DMI) will be used as input to the Po river models and their behaviour will be studied as a function of the prediction quality and of the coarseness of the spatial discretisation.
Bayesian analysis of data and model error in rainfall-runoff hydrological models
Kavetski, D.; Franks, S. W.; Kuczera, G.
2004-12-01
A major unresolved issue in the identification and use of conceptual hydrologic models is realistic description of uncertainty in the data and model structure. In particular, hydrologic parameters often cannot be measured directly and must be inferred (calibrated) from observed forcing/response data (typically, rainfall and runoff). However, rainfall varies significantly in space and time, yet is often estimated from sparse gauge networks. Recent work showed that current calibration methods (e.g., standard least squares, multi-objective calibration, generalized likelihood uncertainty estimation) ignore forcing uncertainty and assume that the rainfall is known exactly. Consequently, they can yield strongly biased and misleading parameter estimates. This deficiency confounds attempts to reliably test model hypotheses, to generalize results across catchments (the regionalization problem) and to quantify predictive uncertainty when the hydrologic model is extrapolated. This paper continues the development of a Bayesian total error analysis (BATEA) methodology for the calibration and identification of hydrologic models, which explicitly incorporates the uncertainty in both the forcing and response data, and allows systematic model comparison based on residual model errors and formal Bayesian hypothesis testing (e.g., using Bayes factors). BATEA is based on explicit stochastic models for both forcing and response uncertainty, whereas current techniques focus solely on response errors. Hence, unlike existing methods, the BATEA parameter equations directly reflect the modeler's confidence in all the data. We compare several approaches to approximating the parameter distributions: a) full Markov Chain Monte Carlo methods and b) simplified approaches based on linear approximations. Studies using synthetic and real data from the US and Australia show that BATEA systematically reduces the parameter bias, leads to more meaningful model fits and allows model comparison taking
Hong, Nian; Hama, Takehide; Suenaga, Yuichi; Aqili, Sayed Waliullah; Huang, Xiaowu; Wei, Qiaoyan; Kawagoshi, Yasunori
2016-01-15
Groundwater level simulation models can help ensure the proper management and use of urban and rural water supply. In this paper, we propose a groundwater level tank model (GLTM) based on a conceptual rainfall-runoff model (tank model) to simulate fluctuations in groundwater level. The variables used in the simulations consist of daily rainfall and daily groundwater level, which were recorded between April 2011 and March 2015 at two representative observation wells in Kumamoto City, Japan. We determined the best-fit model parameters by root-mean-square error through use of the Shuffled Complex Evolution-University of Arizona algorithm on a simulated data set. Calibration and validation results were evaluated by their coefficients of determination, Nash-Sutcliffe efficiency coefficients, and root-mean-square error values. The GLTM provided accurate results in both the calibration and validation of fluctuations in groundwater level. The split sample test results indicate a good reliability. These results indicate that this model can provide a simple approach to the accurate simulation of groundwater levels. Copyright © 2015 Elsevier B.V. All rights reserved.
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Sleziak P.
2016-12-01
Full Text Available The main objective of the paper is to understand how the model’s efficiency and the selected climatic indicators are related. The hydrological model applied in this study is a conceptual rainfall-runoff model (the TUW model, which was developed at the Vienna University of Technology. This model was calibrated over three different periods between 1981-2010 in three groups of Austrian catchments (snow, runoff, and soil catchments, which represent a wide range of the hydroclimatic conditions of Austria. The model’s calibration was performed using a differential evolution algorithm (Deoptim. As an objective function, we used a combination of the Nash-Sutcliffe coefficient (NSE and the logarithmic Nash-Sutcliffe coefficient (logNSE. The model’s efficiency was evaluated by Volume error (VE. Subsequently, we evaluated the relationship between the model’s efficiency (VE and changes in the climatic indicators (precipitation ΔP, air temperature ΔT. The implications of findings are discussed in the conclusion.
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Rafael Garcia-Lorenzo
2010-11-01
Full Text Available This paper shows the combined use of remotely sensed data and hydraulic geometry methods as an alternative to rainfall-runoff models. Hydraulic geometric data and boolean images of water sheets obtained from satellite images after storm events were integrated in a Geographical Information System. Channel cross-sections were extracted from a high resolution Digital Terrain Model (DTM and superimposed on the image cover to estimate the peak flow using HEC-RAS. The proposed methodology has been tested in ephemeral channels (ramblas on the coastal zone in south-eastern Spain. These fluvial systems constitute an important natural hazard due to their high discharges and sediment loads. In particular, different areas affected by floods during the period 1997 to 2009 were delimited through HEC-GeoRAs from hydraulic geometry data and Landsat images of these floods (Landsat‑TM5 and Landsat-ETM+7. Such an approach has been validated against rainfall-surface runoff models (SCS Dimensionless Unit Hydrograph, SCSD, Témez gamma HU Tγ and the Modified Rational method, MRM comparing their results with flood hydrographs of the Automatic Hydrologic Information System (AHIS in several ephemeral channels in the Murcia Region. The results obtained from the method providing a better fit were used to calculate different hydraulic geometry parameters, especially in residual flood areas.
da Silva, Felipe das Neves Roque; Alves, José Luis Drummond; Cataldi, Marcio
2018-03-01
This paper aims to validate inflow simulations concerning the present-day climate at Água Vermelha Hydroelectric Plant (AVHP—located on the Grande River Basin) based on the Soil Moisture Accounting Procedure (SMAP) hydrological model. In order to provide rainfall data to the SMAP model, the RegCM regional climate model was also used working with boundary conditions from the MIROC model. Initially, present-day climate simulation performed by RegCM model was analyzed. It was found that, in terms of rainfall, the model was able to simulate the main patterns observed over South America. A bias correction technique was also used and it was essential to reduce mistakes related to rainfall simulation. Comparison between rainfall simulations from RegCM and MIROC showed improvements when the dynamical downscaling was performed. Then, SMAP, a rainfall-runoff hydrological model, was used to simulate inflows at Água Vermelha Hydroelectric Plant. After calibration with observed rainfall, SMAP simulations were evaluated in two different periods from the one used in calibration. During calibration, SMAP captures the inflow variability observed at AVHP. During validation periods, the hydrological model obtained better results and statistics with observed rainfall. However, in spite of some discrepancies, the use of simulated rainfall without bias correction captured the interannual flow variability. However, the use of bias removal in the simulated rainfall performed by RegCM brought significant improvements to the simulation of natural inflows performed by SMAP. Not only the curve of simulated inflow became more similar to the observed inflow, but also the statistics improved their values. Improvements were also noticed in the inflow simulation when the rainfall was provided by the regional climate model compared to the global model. In general, results obtained so far prove that there was an added value in rainfall when regional climate model was compared to global climate
Event-based rainfall-runoff modelling of the Kelantan River Basin
Basarudin, Z.; Adnan, N. A.; Latif, A. R. A.; Tahir, W.; Syafiqah, N.
2014-02-01
Flood is one of the most common natural disasters in Malaysia. According to hydrologists there are many causes that contribute to flood events. The two most dominant factors are the meteorology factor (i.e climate change) and change in land use. These two factors contributed to floods in recent decade especially in the monsoonal catchment such as Malaysia. This paper intends to quantify the influence of rainfall during extreme rainfall events on the hydrological model in the Kelantan River catchment. Therefore, two dynamic inputs were used in the study: rainfall and river discharge. The extreme flood events in 2008 and 2004 were compared based on rainfall data for both years. The events were modeled via a semi-distributed HEC-HMS hydrological model. Land use change was not incorporated in the study because the study only tries to quantify rainfall changes during these two events to simulate the discharge and runoff value. Therefore, the land use data representing the year 2004 were used as inputs in the 2008 runoff model. The study managed to demonstrate that rainfall change has a significant impact to determine the peak discharge and runoff depth for the study area.
Event-based rainfall-runoff modelling of the Kelantan River Basin
International Nuclear Information System (INIS)
Basarudin, Z; Adnan, N A; Latif, A R A; Syafiqah, N; Tahir, W
2014-01-01
Flood is one of the most common natural disasters in Malaysia. According to hydrologists there are many causes that contribute to flood events. The two most dominant factors are the meteorology factor (i.e climate change) and change in land use. These two factors contributed to floods in recent decade especially in the monsoonal catchment such as Malaysia. This paper intends to quantify the influence of rainfall during extreme rainfall events on the hydrological model in the Kelantan River catchment. Therefore, two dynamic inputs were used in the study: rainfall and river discharge. The extreme flood events in 2008 and 2004 were compared based on rainfall data for both years. The events were modeled via a semi-distributed HEC-HMS hydrological model. Land use change was not incorporated in the study because the study only tries to quantify rainfall changes during these two events to simulate the discharge and runoff value. Therefore, the land use data representing the year 2004 were used as inputs in the 2008 runoff model. The study managed to demonstrate that rainfall change has a significant impact to determine the peak discharge and runoff depth for the study area
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R. Moussa
2009-04-01
Full Text Available A conceptual lumped rainfall-runoff flood event model was developed and applied on the Gardon catchment located in Southern France and various single-objective and multi-objective functions were used for its calibration. The model was calibrated on 15 events and validated on 14 others. The results of both the calibration and validation phases are compared on the basis of their performance with regards to six criteria, three global criteria and three relative criteria representing volume, peakflow, and the root mean square error. The first type of criteria gives more weight to large events whereas the second considers all events to be of equal weight. The results show that the calibrated parameter values are dependent on the type of criteria used. Significant trade-offs are observed between the different objectives: no unique set of parameters is able to satisfy all objectives simultaneously. Instead, the solution to the calibration problem is given by a set of Pareto optimal solutions. From this set of optimal solutions, a balanced aggregated objective function is proposed, as a compromise between up to three objective functions. The single-objective and multi-objective calibration strategies are compared both in terms of parameter variation bounds and simulation quality. The results of this study indicate that two well chosen and non-redundant objective functions are sufficient to calibrate the model and that the use of three objective functions does not necessarily yield different results. The problems of non-uniqueness in model calibration, and the choice of the adequate objective functions for flood event models, emphasise the importance of the modeller's intervention. The recent advances in automatic optimisation techniques do not minimise the user's responsibility, who has to choose multiple criteria based on the aims of the study, his appreciation on the errors induced by data and model structure and his knowledge of the
Deckers, Dave L.E.H.; Booij, Martijn J.; Rientjes, T.H.M.; Krol, Martinus S.
2010-01-01
This study attempts to examine if catchment variability favours regionalisation by principles of catchment similarity. Our work combines calibration of a simple conceptual model for multiple objectives and multi-regression analyses to establish a regional model between model sensitive parameters and
Uribe, Javier; Muñoz, José F.; Gironás, Jorge; Oyarzún, Ricardo; Aguirre, Evelyn; Aravena, Ramón
2015-11-01
Closed basins are catchments whose drainage networks converge to lakes, salt flats or alluvial plains. Salt flats in the closed basins in arid northern Chile are extremely important ecological niches. The Salar del Huasco, one of these salt flats located in the high plateau (Altiplano), is a Ramsar site located in a national park and is composed of a wetland ecosystem rich in biodiversity. The proper management of the groundwater, which is essential for the wetland function, requires accurate estimates of recharge in the Salar del Huasco basin. This study quantifies the spatio-temporal distribution of the recharge, through combined use of isotopic characterization of the different components of the water cycle and a rainfall-runoff model. The use of both methodologies aids the understanding of hydrological behavior of the basin and enabled estimation of a long-term average recharge of 22 mm/yr (i.e., 15 % of the annual rainfall). Recharge has a high spatial variability, controlled by the geological and hydrometeorological characteristics of the basin, and a high interannual variability, with values ranging from 18 to 26 mm/yr. The isotopic approach allowed not only the definition of the conceptual model used in the hydrological model, but also eliminated the possibility of a hydrogeological connection between the aquifer of the Salar del Huasco basin and the aquifer that feeds the springs of the nearby town of Pica. This potential connection has been an issue of great interest to agriculture and tourism activities in the region.
The last developments of the airGR R-package, an open source software for rainfall-runoff modelling
Thirel, Guillaume; Delaigue, Olivier; Coron, Laurent; Perrin, Charles; Andréassian, Vazken
2017-04-01
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 with the main objectives of designing models as efficient as possible in terms of streamflow simulation, applicable to a wide range of catchments and having low data requirements. 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. It includes: - the water balance annual GR1A model, - the monthly GR2M model, - three versions of the daily model, namely GR4J, GR5J and GR6J, - the hourly GR4H model, - a degree-day snow model CemaNeige. The airGR package has been designed to facilitate the use by non-expert users and allow the addition of evaluation criteria, models or calibration algorithm selected by the end-user. Each model core is coded in FORTRAN to ensure low computational time. The other package functions (i.e. mainly the calibration algorithm and the efficiency criteria) are coded in R. The package is also used for educational purposes. It allows for convenient implementation of model inter-comparisons and large sample hydrology experiments. The airGR package undergoes continuous developments for improving the efficiency, computational time
Versini, Pierre-Antoine; Tchiguirinskaia, Ioulia; Schertzer, Daniel
2017-04-01
Green roofs are commonly considered as efficient tools to mitigate urban runoff as they can store precipitation, and consequently provide retention and detention performances. Designed as a compromise between water holding capacity, weight and hydraulic conductivity, their substrate is usually an artificial media differentiating significantly from a traditional soil. In order to assess green roofs hydrological performances, many models have been developed. Classified into two categories (conceptual and physically based), they are usually applied to reproduce the discharge of a particular monitored green roof considered as homogeneous. Although the resulted simulations could be satisfactory, the question of robustness and consistency of the calibrated parameters is often not addressed. Here, a modeling framework has been developed to assess the efficiency and the robustness of both modelling approaches (conceptual and physically based) in reproducing green roof hydrological behaviour. SWMM and VS2DT models have been used for this purpose. This work also benefits from an experimental setup where several green roofs differentiated by their substrate thickness and vegetation cover are monitored. Based on the data collected for several rainfall events, it has been studied how the calibrated parameters are effectively linked to their physical properties and how they can vary from one green roof configuration to another. Although both models reproduce correctly the observed discharges in most of the cases, their calibrated parameters exhibit a high inconsistency. For a same green roof configuration, these parameters can vary significantly from one rainfall event to another, even if they are supposed to be linked to the green roof characteristics (roughness, residual moisture content for instance). They can also be different from one green roof configuration to another although the implemented substrate is the same. Finally, it appears very difficult to find any
Initial conditions of urban permeable surfaces in rainfall-runoff models using Horton’s infiltration
DEFF Research Database (Denmark)
Davidsen, Steffen; Löwe, Roland; Høegh Ravn, Nanna
2017-01-01
Infiltration is a key process controlling runoff, but varies depending on antecedent conditions. This study provides estimates on initial conditions for urban permeable surfaces via continuous simulation of the infiltration capacity using historical rain data. An analysis of historical rainfall...... records show that accumulated rainfall prior to large rain events does not depend on the return period of the event. Using an infiltration-runoff model we found that for a typical large rain storm, antecedent conditions in general lead to reduced infiltration capacity both for sandy and clayey soils...... and that there is substantial runoff for return periods above 1–10 years....
Modeling Rainfall-Runoff Response to Land Use and Land Cover Change in Rwanda (1990–2016
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Fidele Karamage
2017-02-01
Full Text Available Stormwater runoff poses serious environmental problems and public health issues in Rwanda, a tropical country that is increasingly suffering from severe floods, landslides, soil erosion and water pollution. Using the WetSpa Extension model, this study assessed the changes in rainfall runoff depth in Rwanda from 1990 to 2016 in response to precipitation and land use changes. Our results show that Rwanda has experienced a significant conversion of natural forest and grassland to cropland and built-up areas. During the period 1990–2016, 7090.02 km2 (64.5% and 1715.26 km2 (32.1% of forest and grassland covers were lost, respectively, while the cropland and built-up areas increased by 135.3% (8503.75 km2 and 304.3% (355.02 km2, respectively. According to our estimates, the land use change effect resulted in a national mean runoff depth increase of 2.33 mm/year (0.38%. Although precipitation change affected the inter-annual fluctuation of runoff, the long-term trend of runoff was dominated by land use change. The top five districts that experienced the annual runoff depth increase (all >3.8 mm/year are Rubavu, Nyabihu, Ngororero, Gakenke, and Musanze. Their annual runoff depths increased at a rate of >3.8 mm/year during the past 27 years, due to severe deforestation (ranging from 62% to 85% and cropland expansion (ranging from 123% to 293%. These areas require high priority in runoff control using terracing in croplands and rainwater harvesting systems such as dam/reservoirs, percolation tanks, storage tanks, etc. The wet season runoff was three times higher than the dry season runoff in Rwanda; appropriate rainwater management and reservation could provide valuable irrigation water for the dry season or drought years (late rainfall onsets or early rainfall cessations. It was estimated that a reservation of 30.5% (3.99 km3 of the runoff in the wet season could meet the cropland irrigation water gap during the dry season in 2016.
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J. Götzinger
2005-01-01
Full Text Available Water balance models provide significant input to integrated models that are used to simulate river basin processes. However, one of the primary problems involves the coupling and simultaneous calibration of rainfall-runoff and groundwater models. This problem manifests itself through circular arguments - the hydrologic model is modified to calculate highly discretized groundwater recharge rates as input to the groundwater model which provides modeled base flow for the flood-routing module of the rainfall-runoff model. A possibility to overcome this problem using a modified version of the HBV Model is presented in this paper. Regionalisation and optimization methods lead to objective and efficient calibration despite large numbers of parameters. The representation of model parameters by transfer functions of catchment characteristics enables consistent parameter estimation. By establishing such relationships, models are calibrated for the parameters of the transfer functions instead of the model parameters themselves. Simulated annealing, using weighted Nash-Sutcliffe-coefficients of variable temporal aggregation, assists in efficient parameterisations. The simulations are compared to observed discharge and groundwater recharge modeled by the State Institute for Environmental Protection Baden-Württemberg using the model TRAIN-GWN.
Watson, Andrew; Miller, Jodie; Fleischer, Melanie; de Clercq, Willem
2018-03-01
Wetlands are conservation priorities worldwide, due to their high biodiversity and productivity, but are under threat from agricultural and climate change stresses. To improve the water management practices and resource allocation in these complex systems, a modelling approach has been developed to estimate potential recharge for data poor catchments using rainfall data and basic assumptions regarding soil and aquifer properties. The Verlorenvlei estuarine lake (RAMSAR #525) on the west coast of South Africa is a data poor catchment where rainfall records have been supplemented with farmer's rainfall records. The catchment has multiple competing users. To determine the ecological reserve for the wetlands, the spatial and temporal distribution of recharge had to be well constrained using the J2000 rainfall/runoff model. The majority of rainfall occurs in the mountains (±650 mm/yr) and considerably less in the valley (±280 mm/yr). Percolation was modelled as ∼3.6% of rainfall in the driest parts of the catchment, ∼10% of rainfall in the moderately wet parts of the catchment and ∼8.4% but up to 28.9% of rainfall in the wettest parts of the catchment. The model results are representative of rainfall and water level measurements in the catchment, and compare well with water table fluctuation technique, although estimates are dissimilar to previous estimates within the catchment. This is most likely due to the daily timestep nature of the model, in comparison to other yearly average methods. These results go some way in understanding the fact that although most semi-arid catchments have very low yearly recharge estimates, they are still capable of sustaining high biodiversity levels. This demonstrates the importance of incorporating shorter term recharge event modeling for improving recharge estimates.
Choi, H.; Kim, S.
2012-12-01
Most of hydrologic models have generally been used to describe and represent the spatio-temporal variability of hydrological processes in the watershed scale. Though it is an obvious fact that hydrological responses have the time varying nature, optimal values of model parameters were normally considered as time invariants or constants in most cases. The recent paper of Choi and Beven (2007) presents a multi-period and multi-criteria model conditioning approach. The approach is based on the equifinality thesis within the Generalised Likelihood Uncertainty Estimation (GLUE) framework. In their application, the behavioural TOPMODEL parameter sets are determined by several performance measures for global (annual) and short (30-days) periods, clustered using a Fuzzy C-means algorithm, into 15 types representing different hydrological conditions. Their study shows a good performance on the calibration of a rainfall-runoff model in a forest catchment, and also gives strong indications that it is uncommon to find model realizations that were behavioural over all multi-periods and all performance measures, and multi-period model conditioning approach may become new effective tool for predictions of hydrological processes in ungauged catchments. This study is a follow-up study on the Choi and Beven's (2007) model conditioning approach to test how the approach is effective for the prediction of rainfall-runoff responses in ungauged catchments. To achieve this purpose, 6 small forest catchments are selected among the several hydrological experimental catchments operated by Korea Forest Research Institute. In each catchment, long-term hydrological time series data varying from 10 to 30 years were available. The areas of the selected catchments range from 13.6 to 37.8 ha, and all areas are covered by coniferous or broad-leaves forests. The selected catchments locate in the southern coastal area to the northern part of South Korea. The bed rocks are Granite gneiss, Granite or
Myo Lin, Nay; Rutten, Martine
2017-04-01
The Sittaung River is one of four major rivers in Myanmar. This river basin is developing fast and facing problems with flood, sedimentation, river bank erosion and salt intrusion. At present, more than 20 numbers of reservoirs have already been constructed for multiple purposes such as irrigation, domestic water supply, hydro-power generation, and flood control. The rainfall runoff models are required for the operational management of this reservoir system. In this study, the river basin is divided into (64) sub-catchments and the Sacramento Soil Moisture Accounting (SAC-SMA) models are developed by using satellite rainfall and Geographic Information System (GIS) data. The SAC-SMA model has sixteen calibration parameters, and also uses a unit hydrograph for surface flow routing. The Sobek software package is used for SAC-SMA modelling and simulation of river system. The models are calibrated and tested by using observed discharge and water level data. The statistical results show that the model is applicable to use for data scarce region. Keywords: Sacramento, Sobek, rainfall runoff, reservoir
Farmer, William H.; Knight, Rodney R.; Eash, David A.; Kasey J. Hutchinson,; Linhart, S. Mike; Christiansen, Daniel E.; Archfield, Stacey A.; Over, Thomas M.; Kiang, Julie E.
2015-08-24
Daily records of streamflow are essential to understanding hydrologic systems and managing the interactions between human and natural systems. Many watersheds and locations lack streamgages to provide accurate and reliable records of daily streamflow. In such ungaged watersheds, statistical tools and rainfall-runoff models are used to estimate daily streamflow. Previous work compared 19 different techniques for predicting daily streamflow records in the southeastern United States. Here, five of the better-performing methods are compared in a different hydroclimatic region of the United States, in Iowa. The methods fall into three classes: (1) drainage-area ratio methods, (2) nonlinear spatial interpolations using flow duration curves, and (3) mechanistic rainfall-runoff models. The first two classes are each applied with nearest-neighbor and map-correlated index streamgages. Using a threefold validation and robust rank-based evaluation, the methods are assessed for overall goodness of fit of the hydrograph of daily streamflow, the ability to reproduce a daily, no-fail storage-yield curve, and the ability to reproduce key streamflow statistics. As in the Southeast study, a nonlinear spatial interpolation of daily streamflow using flow duration curves is found to be a method with the best predictive accuracy. Comparisons with previous work in Iowa show that the accuracy of mechanistic models with at-site calibration is substantially degraded in the ungaged framework.
Luo, L.; Wang, Z.
2010-12-01
Soil Conservation Service Curve Number (SCS-CN) based hydrologic model, has widely been used for agricultural watersheds in recent years. However, there will be relative error when applying it due to differentiation of geographical and climatological conditions. This paper introduces a more adaptable and propagable model based on the modified SCS-CN method, which specializes into two different scale cases of research regions. Combining the typical conditions of the Zhanghe irrigation district in southern part of China, such as hydrometeorologic conditions and surface conditions, SCS-CN based models were established. The Xinbu-Qiao River basin (area =1207 km2) and the Tuanlin runoff test area (area =2.87 km2)were taken as the study areas of basin scale and field scale in Zhanghe irrigation district. Applications were extended from ordinary meso-scale watershed to field scale in Zhanghe paddy field-dominated irrigated . Based on actual measurement data of land use, soil classification, hydrology and meteorology, quantitative evaluation and modifications for two coefficients, i.e. preceding loss and runoff curve, were proposed with corresponding models, table of CN values for different landuse and AMC(antecedent moisture condition) grading standard fitting for research cases were proposed. The simulation precision was increased by putting forward a 12h unit hydrograph of the field area, and 12h unit hydrograph were simplified. Comparison between different scales show that it’s more effectively to use SCS-CN model on field scale after parameters calibrated in basin scale These results can help discovering the rainfall-runoff rule in the district. Differences of established SCS-CN model's parameters between the two study regions are also considered. Varied forms of landuse and impacts of human activities were the important factors which can impact the rainfall-runoff relations in Zhanghe irrigation district.
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G. Benito
2011-04-01
Full Text Available In this study we propose a multi-source data approach for quantifying long-term flooding and aquifer recharge in ungauged ephemeral rivers. The methodology is applied to the Buffels River, at 9000 km^{2} the largest ephemeral river in Namaqualand (NW South Africa, a region with scarce stream flow records limiting research investigating hydrological response to global change. Daily discharge and annual flood series (1965–2006 were estimated from a distributed rainfall-runoff hydrological model (TETIS using rainfall gauge records located within the catchment. The model was calibrated and validated with data collected during a two year monitoring programme (2005–2006 at two stream flow stations, one each in the upper and lower reaches of the catchment. In addition to the modelled flow records, non-systematic flood data were reconstructed using both sedimentary and documentary evidence. The palaeoflood record identified at least 25 large floods during the last 700 yr; with the largest floods reaching a minimum discharge of 255 m^{3} s^{−1} (450 yr return period in the upper basin, and 510 m^{3} s^{−1} (100 yr return period in the lower catchment. Since AD 1925, the flood hydrology of the Buffels River has been characterised by a decrease in the magnitude and frequency of extreme floods, with palaeoflood discharges (period 1500–1921 five times greater than the largest modelled floods during the period 1965–2006. Large floods generated the highest hydrograph volumes, however their contribution to aquifer recharge is limited as this depends on other factors such as flood duration and storage capacity of the unsaturated zone prior to the flood. Floods having average return intervals of 5–10 yr (120–140 m^{3} s^{−1} and flowing for 12 days are able to fully saturate the Spektakel aquifer in the lower Buffels River basin. Alluvial aquifer storage capacity limiting potential recharge
Milzow, Christian; Bauer-Gottwein, Peter
2010-05-01
The competition between human water use and ecosystem water use is one of the major challenges for water resources management at the global scale. We analyse the situation for the Okavango River basin of southern Africa. The Okavango River is representative for many large rivers throughout the developing world in that it is ungauged and poorly studied. The Okavango basin - spanning over Angola, Namibia and Botswana - represents a multi-objective problem in an international setting. Economic benefits of agricultural development and conservation of ecosystem services call for opposed actions. A semi-distributed rainfall-runoff model of the Okavango catchment is set up using the Soil and Water Assessment Tool (SWAT). The model is sufficiently physically based to simulate the impact on runoff of extent of agricultural use, crop types and management practices. Precipitation and temperature inputs are taken from datasets covering large parts of the globe. The methodology can thus easily be applied for other ungauged catchments. For temperature we use the ERA-Interim reanalysis product of the European Centre for Medium-Range Weather Forecasts and for precipitation the Famine Early Warning Systems Network data (FEWS-Net). Tropical Rainfall Measurement Mission (TRMM) data resulted in poor model performance compared to the FEWS-Net data. Presently, the upstream catchment in Angola is largely pristine and agriculture is basically restricted to dry land subsistence farming. But economic growth in Angola is likely to result in agricultural development and consequent impacts on catchment runoff. Land use scenarios that are simulated include large scale irrigated agriculture with water extractions from the river and the shallow aquifer. Climate change impacts are also studied and compared to land use change impacts. The downstream part of the basin consists of the large Okavango Wetlands, which are a biodiversity hotspot of global importance and, through tourism, an important
Haberlandt, U.; Radtke, I.
2013-08-01
Derived flood frequency analysis allows to estimate design floods with hydrological modelling for poorly observed basins considering change and taking into account flood protection measures. There are several possible choices about precipitation input, discharge output and consequently regarding the calibration of the model. The objective of this study is to compare different calibration strategies for a hydrological model considering various types of rainfall input and runoff output data sets. Event based and continuous observed hourly rainfall data as well as disaggregated daily rainfall and stochastically generated hourly rainfall data are used as input for the model. As output short hourly and longer daily continuous flow time series as well as probability distributions of annual maximum peak flow series are employed. The performance of the strategies is evaluated using the obtained different model parameter sets for continuous simulation of discharge in an independent validation period and by comparing the model derived flood frequency distributions with the observed one. The investigations are carried out for three mesoscale catchments in Northern Germany with the hydrological model HEC-HMS. The results show that: (i) the same type of precipitation input data should be used for calibration and application of the hydrological model, (ii) a model calibrated using a small sample of extreme values works quite well for the simulation of continuous time series with moderate length but not vice versa, (iii) the best performance with small uncertainty is obtained when stochastic precipitation data and the observed probability distribution of peak flows are used for model calibration. This outcome suggests to calibrate a hydrological model directly on probability distributions of observed peak flows using stochastic rainfall as input if its purpose is the application for derived flood frequency analysis.
Directory of Open Access Journals (Sweden)
Derdour Abdessamed
2018-03-01
Full Text Available Ain Sefra is one of the Algerian cities that had been experienced several devastating floods during the past 100 years. The purpose of this study is to simulate runoff in the semi-arid region of Ain Sefra watershed through the employing of the Hydrologic Engineering Center – Hydrologic Modelling System (HEC-HMS. In this paper, the frequency storm is used for the meteorological model, the Soil Conservation Service – curve number (SCS-CN is selected to calculate the loss rate and Soil Conservation Service unit hydrograph method have been applied to simulate the runoff rate. After calibration and validation, the simulated peak discharges were very close with observed values. The Nash–Sutcliffe efficiency coefficient was 0.95, indicates that the hydrological modeling results are satisfactory and accepted for simulation of rainfall-runoff. The peak discharges obtained for the 10, 50, 100 and 1000 year storms are respectively 425.8, 750.5, 904.3 and 1328.3 m3∙s−1.
Directory of Open Access Journals (Sweden)
Mohammad Taghi Dastorani
2012-01-01
Full Text Available During recent few decades, due to the importance of the availability of water, and therefore the necesity of predicting run off resulted from rain fall there has been an increase in developing and implementation of new suitable method for prediction of run off using precipitation data. One of these approaches that have been developed in several areas of sciences including water related fields, is soft computing techniques such as artificial neural networks and fuzzy logic systems. This research was designed to evaluate the applicability of artificial neural network and adaptive neuro –fuzzy inference system to model rainfall-runoff process in Zayandeh_rood dam basin. It must be mentioned that, data have been analysed using Wingamma software, to select appropriate type and number of training input data before they can be used in the models. Then, it has been tried to evaluated applicability of artificial neural networks and neuro-fuzzy techniques to predict runoff generated from daily rainfall. Finally, the accuracy of the results produced by these methods has been compared using statistical criterion. Results taken from this research show that artificial neural networks and neuro-fuzzy technique presented different outputs in different conditions in terms of type and number of inputs variables, but both method have been able to produce acceptable results when suitable input variables and network structures are used.
Santos, Léonard; Thirel, Guillaume; Perrin, Charles
2018-04-01
In many conceptual rainfall-runoff models, the water balance differential equations are not explicitly formulated. These differential equations are solved sequentially by splitting the equations into terms that can be solved analytically with a technique called operator splitting. As a result, only the solutions of the split equations are used to present the different models. This article provides a methodology to make the governing water balance equations of a bucket-type rainfall-runoff model explicit and to solve them continuously. This is done by setting up a comprehensive state-space representation of the model. By representing it in this way, the operator splitting, which makes the structural analysis of the model more complex, could be removed. In this state-space representation, the lag functions (unit hydrographs), which are frequent in rainfall-runoff models and make the resolution of the representation difficult, are first replaced by a so-called Nash cascade and then solved with a robust numerical integration technique. To illustrate this methodology, the GR4J model is taken as an example. The substitution of the unit hydrographs with a Nash cascade, even if it modifies the model behaviour when solved using operator splitting, does not modify it when the state-space representation is solved using an implicit integration technique. Indeed, the flow time series simulated by the new representation of the model are very similar to those simulated by the classic model. The use of a robust numerical technique that approximates a continuous-time model also improves the lag parameter consistency across time steps and provides a more time-consistent model with time-independent parameters.
A simple rainfall-runoff model for the single and long term hydrological performance of green roofs
DEFF Research Database (Denmark)
Locatelli, Luca; Mark, Ole; Mikkelsen, Peter Steen
Green roofs are being widely implemented for storm water control and runoff reduction. There is need for incorporating green roofs into urban drainage models in order to evaluate their impact. These models must have low computational costs and fine time resolution. This paper aims to develop...... a model of green roof hydrological performance. A simple conceptual model for the long term and single event hydrological performance of green roofs, shows to be capable of reproducing observed runoff measurements. The model has surface and subsurface storage components representing the overall retention...... capacity of the green roof. The runoff from the system is described by the non-linear reservoir method and the storage capacity of the green roof is continuously re-established by evapotranspiration. Runoff data from a green roof in Denmark are collected and used for parameter calibration....
Czech Academy of Sciences Publication Activity Database
Košková, Romana; Němečková, Soňa; Sitková, Z.
2008-01-01
Roč. 4, č. 1 (2008), s. 012002 ISSN 1755-1315. [Conference of the Danubian Countries /24./. Bled, 02.06.2008-04.06.2008] R&D Projects: GA AV ČR(CZ) KJB300600602 Institutional research plan: CEZ:AV0Z20600510 Keywords : hydrological modelling * soil water content * evapotranspiration * SWIM model Subject RIV: DA - Hydrology ; Limnology http://www.iop.org/EJ/abstract/1755-1315/4/1/012002
Elizabeth N. Mihalik; Norm S. Levine; Devendra M. Amatya
2008-01-01
Chapel Branch Creek (CBC), located within the Town of Santee adjacent to Lake Marion in Orangeburg County, SC, is listed on the SC 2004 303(d) list of impaired waterbodies due to elevated levels of nitrogen (N), phosphorus (P), chlorophyll-a, and pH. In this study, using a GIS-based approach, two runoff modeling methods, the Rational and SCS-CN methods, have been...
Liu, Yaoze; Bralts, Vincent F; Engel, Bernard A
2015-04-01
The adverse influence of urban development on hydrology and water quality can be reduced by applying best management practices (BMPs) and low impact development (LID) practices. This study applied green roof, rain barrel/cistern, bioretention system, porous pavement, permeable patio, grass strip, grassed swale, wetland channel, retention pond, detention basin, and wetland basin, on Crooked Creek watershed. The model was calibrated and validated for annual runoff volume. A framework for simulating BMPs and LID practices at watershed scales was created, and the impacts of BMPs and LID practices on water quantity and water quality were evaluated with the Long-Term Hydrologic Impact Assessment-Low Impact Development 2.1 (L-THIA-LID 2.1) model for 16 scenarios. The various levels and combinations of BMPs/LID practices reduced runoff volume by 0 to 26.47%, Total Nitrogen (TN) by 0.30 to 34.20%, Total Phosphorus (TP) by 0.27 to 47.41%, Total Suspended Solids (TSS) by 0.33 to 53.59%, Lead (Pb) by 0.30 to 60.98%, Biochemical Oxygen Demand (BOD) by 0 to 26.70%, and Chemical Oxygen Demand (COD) by 0 to 27.52%. The implementation of grass strips in 25% of the watershed where this practice could be applied was the most cost-efficient scenario, with cost per unit reduction of $1m3/yr for runoff, while cost for reductions of two pollutants of concern was $445 kg/yr for Total Nitrogen (TN) and $4871 kg/yr for Total Phosphorous (TP). The scenario with very high levels of BMP and LID practice adoption (scenario 15) reduced runoff volume and pollutant loads from 26.47% to 60.98%, and provided the greatest reduction in runoff volume and pollutant loads among all scenarios. However, this scenario was not as cost-efficient as most other scenarios. The L-THIA-LID 2.1 model is a valid tool that can be applied to various locations to help identify cost effective BMP/LID practice plans at watershed scales. Copyright © 2014 Elsevier B.V. All rights reserved.
Enhancing a rainfall-runoff model to assess the impacts of BMPs and LID practices on storm runoff.
Liu, Yaoze; Ahiablame, Laurent M; Bralts, Vincent F; Engel, Bernard A
2015-01-01
Best management practices (BMPs) and low impact development (LID) practices are increasingly being used as stormwater management techniques to reduce the impacts of urban development on hydrology and water quality. To assist planners and decision-makers at various stages of development projects (planning, implementation, and evaluation), user-friendly tools are needed to assess the effectiveness of BMPs and LID practices. This study describes a simple tool, the Long-Term Hydrologic Impact Assessment-LID (L-THIA-LID), which is enhanced with additional BMPs and LID practices, improved approaches to estimate hydrology and water quality, and representation of practices in series (meaning combined implementation). The tool was used to evaluate the performance of BMPs and LID practices individually and in series with 30 years of daily rainfall data in four types of idealized land use units and watersheds (low density residential, high density residential, industrial, and commercial). Simulation results were compared with the results of other published studies. The simulated results showed that reductions in runoff volume and pollutant loads after implementing BMPs and LID practices, both individually and in series, were comparable with the observed impacts of these practices. The L-THIA-LID 2.0 model is capable of assisting decision makers in evaluating environmental impacts of BMPs and LID practices, thereby improving the effectiveness of stormwater management decisions. Copyright © 2014 Elsevier Ltd. All rights reserved.
Toth, Elena
2013-04-01
The Ridracoli reservoir is the main drinking water supply reservoir serving the whole Romagna region, in Northern Italy. Such water supply system has a crucial role in an area where the different characteristics of the communities to be served, their size, the mass tourism and the presence of food industries highlight strong differences in drinking water needs. Its operation allows high quality drinking water supply to a million resident customers, plus a few millions of tourists during the summer of people and it reduces the need for water pumping from underground sources, and this is particularly important since the coastal area is subject also to subsidence and saline ingression into aquifers. The system experienced water shortage conditions thrice in the last decade, in 2002, in 2007 and in autumn-winter 2011-2012, when the reservoir water storage fell below the attention and the pre-emergency thresholds, thus prompting the implementation of a set of mitigation measures, including limitations to the population's water consumption. The reservoir receives water not only from the headwater catchment, closed at the dam, but also from four diversion watersheds, linked to the reservoir through an underground water channel. Such withdrawals are currently undersized, abstracting only a part of the streamflow exceeding the established minimum flows, due to the design of the water intake structures; it is therefore crucial understanding how the reservoir water availability might be increased through a fuller exploitation of the existing diversion catchment area. Since one of the four diversion catchment is currently ungauged (at least at the fine temporal scale needed for keeping into account the minimum flow requirements downstream of the intakes), the study first presents the set up and parameterisation of a continuous rainfall-runoff model at hourly time-step for the three gauged diversion watersheds and for the headwater catchment: a regional parameterisation
Multi-catchment rainfall-runoff simulation for extreme flood estimation
Paquet, Emmanuel
2017-04-01
The SCHADEX method (Paquet et al., 2013) is a reference method in France for the estimation of extreme flood for dam design. The method is based on a semi-continuous rainfall-runoff simulation process: hundreds of different rainy events, randomly drawn up to extreme values, are simulated independently in the hydrological conditions of each day when a rainy event has been actually observed. This allows generating an exhaustive set of crossings between precipitation and soil saturation hazards, and to build a complete distribution of flood discharges up to extreme quantiles. The hydrological model used within SCHADEX, the MORDOR model (Garçon, 1996), is a lumped model, which implies that hydrological processes, e.g. rainfall and soil saturation, are supposed to be homogeneous throughout the catchment. Snow processes are nevertheless represented in relation with altitude. This hypothesis of homogeneity is questionable especially as the size of the catchment increases, or in areas of highly contrasted climatology (like mountainous areas). Conversely, modeling the catchment with a fully distributed approach would cause different problems, in particular distributing the rainfall-runoff model parameters trough space, and within the SCHADEX stochastic framework, generating extreme rain fields with credible spatio-temporal features. An intermediate solution is presented here. It provides a better representation of the hydro-climatic diversity of the studied catchment (especially regarding flood processes) while keeping the SCHADEX simulation framework. It consists in dividing the catchment in several, more homogeneous sub-catchments. Rainfall-runoff models are parameterized individually for each of them, using local discharge data if available. A first SCHADEX simulation is done at the global scale, which allows assigning a probability to each simulated event, mainly based on the global areal rainfall drawn for the event (see Paquet el al., 2013 for details). Then the
Beyond the SCS-CN method: A theoretical framework for spatially lumped rainfall-runoff response
Bartlett, M. S.; Parolari, A. J.; McDonnell, J. J.; Porporato, A.
2016-06-01
Since its introduction in 1954, the Soil Conservation Service curve number (SCS-CN) method has become the standard tool, in practice, for estimating an event-based rainfall-runoff response. However, because of its empirical origins, the SCS-CN method is restricted to certain geographic regions and land use types. Moreover, it does not describe the spatial variability of runoff. To move beyond these limitations, we present a new theoretical framework for spatially lumped, event-based rainfall-runoff modeling. In this framework, we describe the spatially lumped runoff model as a point description of runoff that is upscaled to a watershed area based on probability distributions that are representative of watershed heterogeneities. The framework accommodates different runoff concepts and distributions of heterogeneities, and in doing so, it provides an implicit spatial description of runoff variability. Heterogeneity in storage capacity and soil moisture are the basis for upscaling a point runoff response and linking ecohydrological processes to runoff modeling. For the framework, we consider two different runoff responses for fractions of the watershed area: "prethreshold" and "threshold-excess" runoff. These occur before and after infiltration exceeds a storage capacity threshold. Our application of the framework results in a new model (called SCS-CNx) that extends the SCS-CN method with the prethreshold and threshold-excess runoff mechanisms and an implicit spatial description of runoff. We show proof of concept in four forested watersheds and further that the resulting model may better represent geographic regions and site types that previously have been beyond the scope of the traditional SCS-CN method.
DEFF Research Database (Denmark)
Breinholt, Anders; Møller, Jan Kloppenborg; Madsen, Henrik
2012-01-01
While there seems to be consensus that hydrological model outputs should be accompanied with an uncertainty estimate the appropriate method for uncertainty estimation is not agreed upon and a debate is ongoing between advocators of formal statistical methods who consider errors as stochastic...... and GLUE advocators who consider errors as epistemic, arguing that the basis of formal statistical approaches that requires the residuals to be stationary and conform to a statistical distribution is unrealistic. In this paper we take a formal frequentist approach to parameter estimation and uncertainty...... necessary but the statistical assumptions were nevertheless not 100% justified. The residual analysis showed that significant autocorrelation was present for all simulation models. We believe users of formal approaches to uncertainty evaluation within hydrology and within environmental modelling in general...
Klotz, Daniel; Herrnegger, Mathew; Schulz, Karsten
2016-04-01
This contribution presents a framework, which enables the use of an Evolutionary Algorithm (EA) for the calibration and regionalization of the hydrological model COSEROreg. COSEROreg uses an updated version of the HBV-type model COSERO (Kling et al. 2014) for the modelling of hydrological processes and is embedded in a parameter regionalization scheme based on Samaniego et al. (2010). The latter uses subscale-information to estimate model via a-priori chosen transfer functions (often derived from pedotransfer functions). However, the transferability of the regionalization scheme to different model-concepts and the integration of new forms of subscale information is not straightforward. (i) The usefulness of (new) single sub-scale information layers is unknown beforehand. (ii) Additionally, the establishment of functional relationships between these (possibly meaningless) sub-scale information layers and the distributed model parameters remain a central challenge in the implementation of a regionalization procedure. The proposed method theoretically provides a framework to overcome this challenge. The implementation of the EA encompasses the following procedure: First, a formal grammar is specified (Ryan et al., 1998). The construction of the grammar thereby defines the set of possible transfer functions and also allows to incorporate hydrological domain knowledge into the search itself. The EA iterates over the given space by combining parameterized basic functions (e.g. linear- or exponential functions) and sub-scale information layers into transfer functions, which are then used in COSEROreg. However, a pre-selection model is applied beforehand to sort out unfeasible proposals by the EA and to reduce the necessary model runs. A second optimization routine is used to optimize the parameters of the transfer functions proposed by the EA. This concept, namely using two nested optimization loops, is inspired by the idea of Lamarckian Evolution and Baldwin Effect
Gires, A.; Tchiguirinskaia, I.; Schertzer, D. J.; Lovejoy, S.
2011-12-01
In large urban areas, storm water management is a challenge with enlarging impervious areas. Many cities have implemented real time control (RTC) of their urban drainage system to either reduce overflow or limit urban contamination. A basic component of RTC is hydraulic/hydrologic model. In this paper we use the multifractal framework to suggest an innovative way to test the sensitivity of such a model to the spatio-temporal variability of its rainfall input. Indeed the rainfall variability is often neglected in urban context, being considered as a non-relevant issue at the scales involve. Our results show that on the contrary the rainfall variability should be taken into account. Universal multifractals (UM) rely on the concept of multiplicative cascade and are a standard tool to analyze and simulate with a reduced number of parameters geophysical processes that are extremely variable over a wide range of scales. This study is conducted on a 3 400 ha urban area located in Seine-Saint-Denis, in the North of Paris (France). We use the operational semi-distributed model that was calibrated by the local authority (Direction Eau et Assainnissement du 93) that is in charge of urban drainage. The rainfall data comes from the C-Band radar of Trappes operated by Météo-France. The rainfall event of February 9th, 2009 was used. A stochastic ensemble approach was implemented to quantify the uncertainty on discharge associated to the rainfall variability occurring at scales smaller than 1 km x 1 km x 5 min that is usually available with C-band radar networks. An analysis of the quantiles of the simulated peak flow showed that the uncertainty exceeds 20 % for upstream links. To evaluate a potential gain from a direct use of the rainfall data available at the resolution of X-band radar, we performed similar analysis of the rainfall fields of the degraded resolution of 9 km x 9 km x 20 min. The results show a clear decrease in uncertainty when the original resolution of C
Derdour Abdessamed; Bouanani Abderrazak; Babahamed Kamila
2018-01-01
Ain Sefra is one of the Algerian cities that had been experienced several devastating floods during the past 100 years. The purpose of this study is to simulate runoff in the semi-arid region of Ain Sefra watershed through the employing of the Hydrologic Engineering Center – Hydrologic Modelling System (HEC-HMS). In this paper, the frequency storm is used for the meteorological model, the Soil Conservation Service – curve number (SCS-CN) is selected to calculate the loss rate and Soil Conserv...
Computational Intelligence in Rainfall-Runoff Modeling
De Vos, N.J.
2009-01-01
The transformation from precipitation over a river basin to river streamflow is the result of many interacting processes which manifest themselves at various scales of time and space. The resulting complexity of hydrological systems, and the difficulty to properly and quantitatively express the
Quantifying rainfall-runoff relationships on the Mieso Hypo Calcic ...
African Journals Online (AJOL)
The mean annual rainfall at Mieso is 738 mm. The soil is a Hypo Calcic Vertisol with a high clay and silt content and is very susceptible to crusting. To achieve the objective of the study, rainfall-runoff measurements were made during 2003 and 2004 on 2 m x 2 m plots provided with a runoff measuring system, and replicated ...
Ying, G.; Sansalone, J.
2010-03-01
SummaryWith respect to hydrologic processes, the impervious pavement interface significantly alters relationships between rainfall and runoff. Commensurate with alteration of hydrologic processes the pavement also facilitates transport and solubility of dry deposition particulate matter (PM) in runoff. This study examines dry depositional flux rates, granulometric modification by runoff transport, as well as generation of total dissolved solids (TDS), alkalinity and conductivity in source area runoff resulting from PM solubility. PM is collected from a paved source area transportation corridor (I-10) in Baton Rouge, Louisiana encompassing 17 dry deposition and 8 runoff events. The mass-based granulometric particle size distribution (PSD) is measured and modeled through a cumulative gamma function, while PM surface area distributions across the PSD follow a log-normal distribution. Dry deposition flux rates are modeled as separate first-order exponential functions of previous dry hours (PDH) for PM and suspended, settleable and sediment fractions. When trans-located from dry deposition into runoff, PSDs are modified, with a d50m decreasing from 331 to 14 μm after transport and 60 min of settling. Solubility experiments as a function of pH, contact time and particle size using source area rainfall generate constitutive models to reproduce pH, alkalinity, TDS and alkalinity for historical events. Equilibrium pH, alkalinity and TDS are strongly influenced by particle size and contact times. The constitutive leaching models are combined with measured PSDs from a series of rainfall-runoff events to demonstrate that the model results replicate alkalinity and TDS in runoff from the subject watershed. Results illustrate the granulometry of dry deposition PM, modification of PSDs along the drainage pathway, and the role of PM solubility for generation of TDS, alkalinity and conductivity in urban source area rainfall-runoff.
Which resilience of the continental rainfall-runoff chain?
Fraedrich, Klaus
2015-04-01
Processes along the continental rainfall-runoff chain are extremely variable over a wide range of time and space scales. A key societal question is the multiscale resilience of this chain. We argue that the adequate framework to tackle this question can be obtained by combining observations (ranging from minutes to decades) and minimalist concepts: (i) Rainfall exhibits 1/f-spectra if presented as binary events (tropics) and extrema world wide increase with duration according to Jennings' scaling law as simulated by a censored first-order autoregressive process representing vertical moisture fluxes. (ii) Runoff volatility (Yangtze) shows data collapse which, linked to an intra-annual 1/f-spectrum, is represented by a single function (Gumbel) not unlike physical systems at criticality, while short and long return times of extremes are Weibull-distributed. (iii) Soil moisture, interpreted by a biased coinflip Ansatz for rainfall events, provides an equation of state to the surface energy and water flux balances comprising Budyko's framework for quasi-stationary watershed analysis. (iv) Vegetation-greenness (NDVI), included as an active tracer extends Budyko's eco-hydrologic state space analysis, supplements the common geographical presentations, and it may be linked to a minimalist biodiversity concept. (v) Finally, attributions of change to external (or climate) and internal (or anthropogenic) causes are determined by eco-hydrologic state space trajectories using surface flux ratios of energy excess (loss by sensible heat over supply by net radiation) versus water excess (loss by discharge over gain by precipitation). Risk-estimates (by GCM-emulators) and possible policy advice mechanisms enter the outlook.
Linking landscape structure and rainfall runoff behaviour in a thermodynamic optimality context
Zehe, Erwin; Ehret, Uwe; Blume, Theresa; Kleidon, Axel; Scherer, Ulrike; Westhoff, Martijn
2015-04-01
gradients, and thus a faster relaxation back towards local thermodynamic equilibrium. Thermodynamic optimality principles allow for a priory optimization of the resistance field at a given gradient, not in the sense how they exactly look like but in the sense how they function with respect to export and dissipation of free energy associated with rainfall runoff processes. Based on this framework we explored the possibility of independent predictions of rainfall runoff, in the sense that the a-priory optimum model structures should match independent observations. We found that spatially organized patterns of soils and macropores observed in two distinctly different landscapes are in close accordance with thermodynamic optima expressed either by minimized relaxation times towards local thermodynamic equilibrium in cohesive soils or as steady state in the potential energy of soil water in non-cohesive soils. Predicted rainfall runoff based on the two optimized model structures was in both catchments in acceptable accordance with independent discharge observations. However, the nature of these optima suggests there might be two distinctly different thermodynamically optimal regimes of rainfall runoff behaviour. In the capillary- or c--regime, free energy dynamics of soil water is dominated by changes in its capillary binding energy, which is the case for cohesive soils. Soil wetting during rainfall in the c-regime implies pushing the system back towards LTE, especially after long dry spells. Dead ended macropores (roots, worm burrows which end in the soil matrix) act as dissipative wetting structures by enlarging water flows against steep gradients in soil water potential after long dry spells. This implies accelerated depletion of these gradients and faster relaxation back towards LTE during rainfall runoff. In the c-regime several optimum macropore densities with respect to maximization of net reduction of free energy exist. This is because the governing equation is a second
Characteristics of PAHs in farmland soil and rainfall runoff in Tianjin, China.
Shi, Rongguang; Xu, Mengmeng; Liu, Aifeng; Tian, Yong; Zhao, Zongshan
2017-10-14
Rainfall runoff can remove certain amounts of pollutants from contaminated farmland soil and result in a decline in water quality. However, the leaching behaviors of polycyclic aromatic hydrocarbons (PAHs) with rainfall have been rarely reported due to wide variations in the soil compositions, rainfall conditions, and sources of soil PAHs in complex farmland ecosystems. In this paper, the levels, spatial distributions, and composition profiles of PAHs in 30 farmland soil samples and 49 rainfall-runoff samples from the Tianjin region in 2012 were studied to investigate their leaching behaviors caused by rainfall runoff. The contents of the Σ 16 PAHs ranged from 58.53 to 3137.90 μg/kg in the soil and 146.58 to 3636.59 μg/L in the runoff. In total, most of the soil sampling sites (23 of 30) were contaminated, and biomass and petroleum combustion were proposed as the main sources of the soil PAHs. Both the spatial distributions of the soil and the runoff PAHs show a decreasing trend moving away from the downtown, which suggested that the leaching behaviors of PAHs in a larger region during rainfall may be mainly affected by the compounds themselves. In addition, 4- and 5-ring PAHs are the dominant components in farmland soil and 3- and 4-ring PAHs dominate the runoff. Comparisons of the PAH pairs and enrichment ratios showed that acenaphthylene, acenaphthene, benzo[a]anthracene, chrysene, and fluoranthene were more easily transferred into water systems from soil than benzo[b]fluoranthene, benzo[k]fluoranthene, benzo[ghi]perylene, and indeno[123-cd]pyrene, which indicated that PAHs with low molecular weight are preferentially dissolved due to their higher solubility compared to those with high molecular weight.
Anomaa Senaviratne, G. M. M. M.; Udawatta, Ranjith P.; Anderson, Stephen H.; Baffaut, Claire; Thompson, Allen
2014-09-01
Fuzzy rainfall-runoff models are often used to forecast flood or water supply in large catchments and applications at small/field scale agricultural watersheds are limited. The study objectives were to develop, calibrate, and validate a fuzzy rainfall-runoff model using long-term data of three adjacent field scale row crop watersheds (1.65-4.44 ha) with intermittent discharge in the claypan soils of Northeast Missouri. The watersheds were monitored for a six-year calibration period starting 1991 (pre-buffer period). Thereafter, two of them were treated with upland contour grass and agroforestry (tree + grass) buffers (4.5 m wide, 36.5 m apart) to study water quality benefits. The fuzzy system was based on Mamdani method using MATLAB 7.10.0. The model predicted event-based runoff with model performance coefficients of r2 and Nash-Sutcliffe Coefficient (NSC) values greater than 0.65 for calibration and validation. The pre-buffer fuzzy system predicted event-based runoff for 30-50 times larger corn/soybean watersheds with r2 values of 0.82 and 0.68 and NSC values of 0.77 and 0.53, respectively. The runoff predicted by the fuzzy system closely agreed with values predicted by physically-based Agricultural Policy Environmental eXtender model (APEX) for the pre-buffer watersheds. The fuzzy rainfall-runoff model has the potential for runoff predictions at field-scale watersheds with minimum input. It also could up-scale the predictions for large-scale watersheds to evaluate the benefits of conservation practices.
Rainfall, runoff and sediment transport in a Mediterranean mountainous catchment.
Tuset, J; Vericat, D; Batalla, R J
2016-01-01
The relation between rainfall, runoff, erosion and sediment transport is highly variable in Mediterranean catchments. Their relation can be modified by land use changes and climate oscillations that, ultimately, will control water and sediment yields. This paper analyses rainfall, runoff and sediment transport relations in a meso-scale Mediterranean mountain catchment, the Ribera Salada (NE Iberian Peninsula). A total of 73 floods recorded between November 2005 and November 2008 at the Inglabaga Sediment Transport Station (114.5 km(2)) have been analysed. Suspended sediment transport and flow discharge were measured continuously. Rainfall data was obtained by means of direct rain gauges and daily rainfall reconstructions from radar information. Results indicate that the annual sediment yield (2.3 t km(-1) y(-1) on average) and the flood-based runoff coefficients (4.1% on average) are low. The Ribera Salada presents a low geomorphological and hydrological activity compared with other Mediterranean mountain catchments. Pearson correlations between rainfall, runoff and sediment transport variables were obtained. The hydrological response of the catchment is controlled by the base flows. The magnitude of suspended sediment concentrations is largely correlated with flood magnitude, while sediment load is correlated with the amount of direct runoff. Multivariate analysis shows that total suspended load can be predicted by integrating rainfall and runoff variables. The total direct runoff is the variable with more weight in the equation. Finally, three main hydro-sedimentary phases within the hydrological year are defined in this catchment: (a) Winter, where the catchment produces only water and very little sediment; (b) Spring, where the majority of water and sediment is produced; and (c) Summer-Autumn, when little runoff is produced but significant amount of sediments is exported out of the catchment. Results show as land use and climate change may have an important
Bartlett, M. S.; Parolari, A. J.; McDonnell, J. J.; Porporato, A.
2017-07-01
Though Ogden et al. list several shortcomings of the original SCS-CN method, fit for purpose is a key consideration in hydrological modelling, as shown by the adoption of SCS-CN method in many design standards. The theoretical framework of Bartlett et al. [2016a] reveals a family of semidistributed models, of which the SCS-CN method is just one member. Other members include event-based versions of the Variable Infiltration Capacity (VIC) model and TOPMODEL. This general model allows us to move beyond the limitations of the original SCS-CN method under different rainfall-runoff mechanisms and distributions for soil and rainfall variability. Future research should link this general model approach to different hydrogeographic settings, in line with the call for action proposed by Ogden et al.
Analysis of one dimension migration law from rainfall runoff on urban roof
Weiwei, Chen
2017-08-01
Research was taken on the hydrology and water quality process in the natural rain condition and water samples were collected and analyzed. The pollutant were included SS, COD and TN. Based on the mass balance principle, one dimension migration model was built for the rainfall runoff pollution in surface. The difference equation was developed according to the finite difference method, by applying the Newton iteration method for solving it. The simulated pollutant concentration process was in consistent with the measured value on model, and Nash-Sutcliffe coefficient was higher than 0.80. The model had better practicability, which provided evidence for effectively utilizing urban rainfall resource, non-point source pollution of making management technologies and measures, sponge city construction, and so on.
A coupled weather generator - rainfall-runoff approach on hourly time steps for flood risk analysis
Winter, Benjamin; Schneeberger, Klaus; Dung Nguyen, Viet; Vorogushyn, Sergiy; Huttenlau, Matthias; Merz, Bruno; Stötter, Johann
2017-04-01
The evaluation of potential monetary damage of flooding is an essential part of flood risk management. One possibility to estimate the monetary risk is to analyze long time series of observed flood events and their corresponding damages. In reality, however, only few flood events are documented. This limitation can be overcome by the generation of a set of synthetic, physically and spatial plausible flood events and subsequently the estimation of the resulting monetary damages. In the present work, a set of synthetic flood events is generated by a continuous rainfall-runoff simulation in combination with a coupled weather generator and temporal disaggregation procedure for the study area of Vorarlberg (Austria). Most flood risk studies focus on daily time steps, however, the mesoscale alpine study area is characterized by short concentration times, leading to large differences between daily mean and daily maximum discharge. Accordingly, an hourly time step is needed for the simulations. The hourly metrological input for the rainfall-runoff model is generated in a two-step approach. A synthetic daily dataset is generated by a multivariate and multisite weather generator and subsequently disaggregated to hourly time steps with a k-Nearest-Neighbor model. Following the event generation procedure, the negative consequences of flooding are analyzed. The corresponding flood damage for each synthetic event is estimated by combining the synthetic discharge at representative points of the river network with a loss probability relation for each community in the study area. The loss probability relation is based on exposure and susceptibility analyses on a single object basis (residential buildings) for certain return periods. For these impact analyses official inundation maps of the study area are used. Finally, by analyzing the total event time series of damages, the expected annual damage or losses associated with a certain probability of occurrence can be estimated for
Transport mechanisms of soil-bound mercury in the erosion process during rainfall-runoff events.
Zheng, Yi; Luo, Xiaolin; Zhang, Wei; Wu, Xin; Zhang, Juan; Han, Feng
2016-08-01
Soil contamination by mercury (Hg) is a global environmental issue. In watersheds with a significant soil Hg storage, soil erosion during rainfall-runoff events can result in nonpoint source (NPS) Hg pollution and therefore, can extend its environmental risk from soils to aquatic ecosystems. Nonetheless, transport mechanisms of soil-bound Hg in the erosion process have not been explored directly, and how different fractions of soil organic matter (SOM) impact transport is not fully understood. This study investigated transport mechanisms based on rainfall-runoff simulation experiments. The experiments simulated high-intensity and long-duration rainfall conditions, which can produce significant soil erosion and NPS pollution. The enrichment ratio (ER) of total mercury (THg) was the key variable in exploring the mechanisms. The main study findings include the following: First, the ER-sediment flux relationship for Hg depends on soil composition, and no uniform ER-sediment flux function exists for different soils. Second, depending on soil composition, significantly more Hg could be released from a less polluted soil in the early stage of large rainfall events. Third, the heavy fraction of SOM (i.e., the remnant organic matter coating on mineral particles) has a dominant influence on the enrichment behavior and transport mechanisms of Hg, while clay mineral content exhibits a significant, but indirect, influence. The study results imply that it is critical to quantify the SOM composition in addition to total organic carbon (TOC) for different soils in the watershed to adequately model the NPS pollution of Hg and spatially prioritize management actions in a heterogeneous watershed. Copyright © 2016 Elsevier Ltd. All rights reserved.
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L. Santos
2018-04-01
Full Text Available In many conceptual rainfall–runoff models, the water balance differential equations are not explicitly formulated. These differential equations are solved sequentially by splitting the equations into terms that can be solved analytically with a technique called operator splitting. As a result, only the solutions of the split equations are used to present the different models. This article provides a methodology to make the governing water balance equations of a bucket-type rainfall–runoff model explicit and to solve them continuously. This is done by setting up a comprehensive state-space representation of the model. By representing it in this way, the operator splitting, which makes the structural analysis of the model more complex, could be removed. In this state-space representation, the lag functions (unit hydrographs, which are frequent in rainfall–runoff models and make the resolution of the representation difficult, are first replaced by a so-called Nash cascade and then solved with a robust numerical integration technique. To illustrate this methodology, the GR4J model is taken as an example. The substitution of the unit hydrographs with a Nash cascade, even if it modifies the model behaviour when solved using operator splitting, does not modify it when the state-space representation is solved using an implicit integration technique. Indeed, the flow time series simulated by the new representation of the model are very similar to those simulated by the classic model. The use of a robust numerical technique that approximates a continuous-time model also improves the lag parameter consistency across time steps and provides a more time-consistent model with time-independent parameters.
Soulis, K. X.; Valiantzas, J. D.
2011-10-01
The Soil Conservation Service Curve Number (SCS-CN) approach is widely used as a simple method for predicting direct runoff volume for a given rainfall event. The CN values can be estimated by being selected from tables. However, it is more accurate to estimate the CN value from measured rainfall-runoff data (assumed available) in a watershed. Previous researchers indicated that the CN values calculated from measured rainfall-runoff data vary systematically with the rainfall depth. They suggested the determination of a single asymptotic CN value observed for very high rainfall depths to characterize the watersheds' runoff response. In this paper, the novel hypothesis that the observed correlation between the calculated CN value and the rainfall depth in a watershed reflects the effect of the inevitable presence of soil-cover complex spatial variability along watersheds is being tested. Based on this hypothesis, the simplified concept of a two-CN heterogeneous system is introduced to model the observed CN-rainfall variation by reducing the CN spatial variability into two classes. The behavior of the CN-rainfall function produced by the proposed two-CN system concept is approached theoretically, it is analyzed systematically, and it is found to be similar to the variation observed in natural watersheds. Synthetic data tests, natural watersheds examples, and detailed study of two natural experimental watersheds with known spatial heterogeneity characteristics were used to evaluate the method. The results indicate that the determination of CN values from rainfall runoff data using the proposed two-CN system approach provides reasonable accuracy and it over performs the previous original method based on the determination of a single asymptotic CN value. Although the suggested method increases the number of unknown parameters to three (instead of one), a clear physical reasoning for them is presented.
Soulis, K. X.; Valiantzas, J. D.
2012-03-01
The Soil Conservation Service Curve Number (SCS-CN) approach is widely used as a simple method for predicting direct runoff volume for a given rainfall event. The CN parameter values corresponding to various soil, land cover, and land management conditions can be selected from tables, but it is preferable to estimate the CN value from measured rainfall-runoff data if available. However, previous researchers indicated that the CN values calculated from measured rainfall-runoff data vary systematically with the rainfall depth. Hence, they suggested the determination of a single asymptotic CN value observed for very high rainfall depths to characterize the watersheds' runoff response. In this paper, the hypothesis that the observed correlation between the calculated CN value and the rainfall depth in a watershed reflects the effect of soils and land cover spatial variability on its hydrologic response is being tested. Based on this hypothesis, the simplified concept of a two-CN heterogeneous system is introduced to model the observed CN-rainfall variation by reducing the CN spatial variability into two classes. The behaviour of the CN-rainfall function produced by the simplified two-CN system is approached theoretically, it is analysed systematically, and it is found to be similar to the variation observed in natural watersheds. Synthetic data tests, natural watersheds examples, and detailed study of two natural experimental watersheds with known spatial heterogeneity characteristics were used to evaluate the method. The results indicate that the determination of CN values from rainfall runoff data using the proposed two-CN system approach provides reasonable accuracy and it over performs the previous methods based on the determination of a single asymptotic CN value. Although the suggested method increases the number of unknown parameters to three (instead of one), a clear physical reasoning for them is presented.
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J. D. Valiantzas
2012-03-01
Full Text Available The Soil Conservation Service Curve Number (SCS-CN approach is widely used as a simple method for predicting direct runoff volume for a given rainfall event. The CN parameter values corresponding to various soil, land cover, and land management conditions can be selected from tables, but it is preferable to estimate the CN value from measured rainfall-runoff data if available. However, previous researchers indicated that the CN values calculated from measured rainfall-runoff data vary systematically with the rainfall depth. Hence, they suggested the determination of a single asymptotic CN value observed for very high rainfall depths to characterize the watersheds' runoff response. In this paper, the hypothesis that the observed correlation between the calculated CN value and the rainfall depth in a watershed reflects the effect of soils and land cover spatial variability on its hydrologic response is being tested. Based on this hypothesis, the simplified concept of a two-CN heterogeneous system is introduced to model the observed CN-rainfall variation by reducing the CN spatial variability into two classes. The behaviour of the CN-rainfall function produced by the simplified two-CN system is approached theoretically, it is analysed systematically, and it is found to be similar to the variation observed in natural watersheds. Synthetic data tests, natural watersheds examples, and detailed study of two natural experimental watersheds with known spatial heterogeneity characteristics were used to evaluate the method. The results indicate that the determination of CN values from rainfall runoff data using the proposed two-CN system approach provides reasonable accuracy and it over performs the previous methods based on the determination of a single asymptotic CN value. Although the suggested method increases the number of unknown parameters to three (instead of one, a clear physical reasoning for them is presented.
Rainfall Runoff Mitigation by Retrofitted Permeable Pavement in an Urban Area
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Muhammad Shafique
2018-04-01
Full Text Available Permeable pavement is an effective low impact development (LID practice that can play an important role in reducing rainfall runoff amount in urban areas. Permeable interlocking concrete pavement (PICP was retrofitted in a tremendously developed area of Seoul, Korea and the data was monitored to evaluate its effect on the hydrology and stormwater quality performance for four months. Rainfall runoff was first absorbed by different layers of the PICP system and then contributed to the sewage system. This not only helps to reduce the runoff volume, but also increase the time of concentration. In this experiment, different real rain events were observed and the field results were investigated to check the effectiveness of the PICP system for controlling the rainfall runoff in Songpa, Korea. From the analysis of data, results showed that the PCIP system was very effective in controlling rainfall runoff. Overall runoff reduction performance from the PCIP was found to be around 30–65% during various storm events. In addition, PICP significantly reduced peak flows in different storm events which is very helpful in reducing the chances of water-logging in an urbanized area. Research results also allow us to sum up that retrofitted PICP is a very effective approach for rainfall runoff management in urban areas.
[Monitoring and analysis on evolution process of rainfall runoff water quality in urban area].
Dong, Wen; Li, Huai-En; Li, Jia-Ke
2013-02-01
In order to find the water quality evolution law and pollution characteristics of the rainfall runoff from undisturbed to the neighborhood exit, 6 times evolution process of rainfall runoff water quality were monitored and analyzed from July to October in 2011, and contrasted the clarification efficiency of the grassland to the roof runoff rudimentarily at the same time. The research showed: 1. the results of the comparison from "undisturbed, rainfall-roof, rainfall runoff-road, rainfall-runoff the neighborhood exit runoff " showed that the water quality of the undisturbed rain was better than that from the roof and the neighborhood exist, but the road rainfall runoff water quality was the worst; 2. the average concentrations of the parameters such as COD, ammonia nitrogen and total nitrogen all exceeded the Fifth Class of the Surface Water Quality Standard except for the soluble total phosphorus from undisturbed rainfall to the neighborhood exit; 3. the runoff water quality of the short early fine days was better than that of long early fine days, and the last runoff water quality was better than that of the initial runoff in the same rainfall process; 4. the concentration reduction of the grassland was notable, and the reduction rate of the grassland which is 1.0 meter wide of the roof runoff pollutants such as COD and nitrogen reached 30%.
Simulation of Urban Rainfall-Runoff in Piedmont Cities: A Case Study in Jinan City, China
Chang, X.; Xu, Z.; Zhao, G.; Li, H.
2017-12-01
During the past decades, frequent flooding disasters in urban areas resulted in catastrophic impacts such as human life casualties and property damages especially in piedmont cities due to its specific topography. In this study, a piedmont urban flooding model was developed in the Huangtaiqiao catchment based on SWMM. The sub-catchments in this piedmont area were divided into mountainous area, plain area and main urban area according to the variations of underlying surface topography. The impact of different routing mode and channel roughness on simulation results was quantitatively analyzed under different types of scenarios, and genetic algorithm was used to optimize model parameters. Results show that the simulation is poor (with a mean Nash coefficient of 0.61) when using the traditional routing mode in SWMM model, which usually ignores terrain variance in piedmont area. However, when the difference of routing mode, percent routed and channel roughness are considered, the prediction precision of model were significantly increased (with a mean Nash coefficient of 0.86), indicating that the difference of surface topography significantly affects the simulation results in piedmont cities. The relevant results would provide the scientific basis and technical support for rainfall-runoff simulation, flood control and disaster alleviation in piedmont cities.
Wang, Xiao-Ling; Qiao, Bin; Li, Song-Min; Li, Jian-Sheng
2016-03-01
The potential of natural Chinese zeolite to remove ammonium from rainfall runoff following urea applications to a paddy rice field is assessed in this study. Laboratory batch kinetic and isotherm experiments were carried out first to investigate the ammonium adsorption capacity of the natural zeolite. Field experiments using zeolite adsorption barriers installed at drain outlets in a paddy rice field were also carried out during natural rainfall events to evaluate the barrier's dynamic removal capacity of ammonium. The results demonstrate that the adsorption kinetics are accurately described by the Elovich model, with a coefficient of determination (R (2)) ranging from 0.9705 to 0.9709, whereas the adsorption isotherm results indicate that the Langmuir-Freundlich model provides the best fit (R (2) = 0.992) for the equilibrium data. The field experiments show that both the flow rate and the barrier volume are important controls on ammonium removal from rainfall runoff. A low flow rate leads to a higher ammonium removal efficiency at the beginning of the tests, while a high flow rate leads to a higher quantity of ammonium adsorbed over the entire runoff process.
International Nuclear Information System (INIS)
Luo, Xiaolin; Zheng, Yi; Wu, Bin; Lin, Zhongrong; Han, Feng; Zhang, Wei; Wang, Xuejun
2013-01-01
Polycyclic Aromatic Hydrocarbons (PAHs) transported from contaminated soils by surface runoff pose significant risk for aquatic ecosystems. Based on a rainfall-runoff simulation experiment, this study investigated the impact of carbonaceous materials (CMs) in soil, identified by organic petrology analysis, on the transport of soil-bound PAHs under rainfall conditions. The hypothesis that composition of soil organic matter significantly impacts the enrichment and transport of PAHs was proved. CMs in soil, varying significantly in content, mobility and adsorption capacity, act differently on the transport of PAHs. Anthropogenic CMs like black carbon (BC) largely control the transport, as PAHs may be preferentially attached to them. Eventually, this study led to a rethink of the traditional enrichment theory. An important implication is that CMs in soil have to be explicitly considered to appropriately model the nonpoint source pollution of PAHs (possibly other hydrophobic chemicals as well) and assess its environmental risk. -- Highlights: •Composition of SOM significantly impacts the enrichment and transport of PAHs. •Anthropogenic carbonaceous materials in soil largely control the transport of PAHs. •The classic enrichment theory is invalid if anthropogenic CMs are abundant in the soil. •Organic petrology analysis introduced to study the fate and transport of PAHs. -- Anthropogenic carbonaceous materials in soil, especially black carbon, largely control the transport of soil-bound PAHs during rainfall-runoff events
RAINFALL-RUNOFF MODELING IN THE TURKEY RIVER USING ...
African Journals Online (AJOL)
2015-01-15
Jan 15, 2015 ... self-correction of the network, self-organization, which means that the ... Fuzzy logic and fuzzy set theory have been widely used to simulate the ambiguity and ... 80% and 20% data were used in train and verification process.
Regional Analysis of Conceptual Rainfall Runoff Models for Runoff ...
African Journals Online (AJOL)
Journal of Civil Engineering Research and Practice. Journal Home · ABOUT THIS JOURNAL · Advanced Search · Current Issue · Archives · Journal Home > Vol 2, No 1 (2005) >. Log in or Register to get access to full text downloads.
Consequences of changes to the NRCS rainfall-runoff relations on hydrologic design
A proposed quantification of the fundamental concepts in the Natural Resources Conservation Service (NRCS) rainfall-runoff relation is examined to determine changes relevant to peak discharge estimation and drainage design. Changes to the NRCS curve number, storage, and initial abstraction relations...
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F. Fenicia
2009-09-01
Full Text Available The objective of this paper is to investigate the time variability of catchment characteristics in the Meuse basin through its effect on catchment response. The approach uses a conceptual model to represent rainfall-runoff behaviour of this catchment, and evaluates possible time-dependence of model parameters. The main hypothesis is that conceptual model parameters, although not measurable quantities, are representative of specific catchment attributes (e.g. geology, land-use, land management, topography. Hence, we assume that eventual trends in model parameters are representative of catchment attributes that may have changed over time. The available hydrological record involves ninety years of data, starting in 1911. During this period the Meuse catchment has undergone significant modifications. The catchment structural modifications, although documented, are not available as "hard-data". Hence, our results should be considered as "plausible hypotheses". The main motivation of this work is the "anomaly" found in the rainfall runoff behaviour of the Meuse basin, where ninety years of rainfall-runoff simulations show a consistent overestimation of the runoff in the period between 1930 and 1965. Different authors have debated possible causes for the "anomaly", including climatic variability, land-use change and data errors. None of the authors considered the way in which the land is used by for instance agricultural and forestry practises. This aspect influenced the model design, which has been configured to account for different evaporation demand of growing forest. As a result of our analysis, we conclude that the lag time of the catchment has decreased significantly over time, which we attribute to more intensive drainage and river training works. Furthermore, we hypothesise that forest rotation has had a significant impact on the evaporation of the catchment. These results contrast with previous studies, where the effect of land-use change on
Fraedrich, K.
2014-12-01
Processes along the continental rainfall-runoff chain cover a wide range of time and space scales which are presented here combining observations (ranging from minutes to decades) and minimalist concepts. (i) Rainfall, which can be simulated by a censored first-order autoregressive process (vertical moisture fluxes), exhibits 1/f-spectra if presented as binary events (tropics), while extrema world wide increase with duration according to Jennings' scaling law. (ii) Runoff volatility (Yangtze) shows data collapse which, linked to an intra-annual 1/f-spectrum, is represented by a single function not unlike physical systems at criticality and the short and long return times of extremes are Weibull-distributed. Atmospheric and soil moisture variabilities are also discussed. (iii) Soil moisture (in a bucket), whose variability is interpreted by a biased coinflip Ansatz for rainfall events, adds an equation of state to energy and water flux balances comprising Budyko's frame work for quasi-stationary watershed analysis. Eco-hydrologic state space presentations in terms of surface flux ratios of energy excess (loss by sensible heat over supply by net radiation) versus water excess (loss by discharge over gain by precipitation) allow attributions of state change to external (or climate) and internal (or anthropogenic) causes. Including the vegetation-greenness index (NDVI) as an active tracer extends the eco-hydrologic state space analysis to supplement the common geographical presentations. Two examples demonstrate the approach combining ERA and MODIS data sets: (a) global geobotanic classification by combining first and second moments of the dryness ratio (net radiation over precipitation) and (b) regional attributions (Tibetan Plateau) of vegetation changes.
EVALUATION OF RAINFALL-RUNOFF EROSIVITY FACTOR FOR CAMERON HIGHLAND, PAHANG, MALAYSIA
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Abdulkadir Taofeeq Sholagberu
2016-07-01
Full Text Available Rainfall-runoff is the active agent of soil erosion which often resulted in land degradation and water quality deterioration. Its aggressiveness to induce erosion is usually termed as rainfall erosivity index or factor (R. R-factor is one of the factors to be parameterized in the evaluation of soil loss using the Universal Soil Loss Equation and its reversed versions (USLE/RUSLE. The computation of accurate R-factor for a particular watershed requires high temporal resolution rainfall (pluviograph data with less than 30-minutes intensities for at least 20 yrs, which is available only in a few regions of the world. As a result, various simplified models have been proposed by researchers to evaluate R-factor using readily available daily, monthly or annual precipitation data. This study is thus aimed at estimating R-factor and to establish an approximate relationship between R-factor and rainfall for subsequent usage in the estimation of soil loss in Cameron highlands watershed. The results of the analysis showed that the least and peak (critical R-factors occurred in the months of January and April with 660.82 and 2399.18 MJ mm ha-1 h-1year-1 respectively. Also, it was observed that erosivity power starts to increase from the month of January through April before started falling in the month of July. The monthly and annual peaks (critical periods may be attributed to increased rainfall amount due to climate change which in turn resulted to increased aggressiveness of rains to cause erosion in the study area. The correlation coefficient of 0.985 showed that there was a strong relationship rainfall and R-factor.
Luo, Xiaolin; Zheng, Yi; Wu, Bin; Lin, Zhongrong; Han, Feng; Zhang, Wei; Wang, Xuejun
2013-11-01
Polycyclic Aromatic Hydrocarbons (PAHs) transported from contaminated soils by surface runoff pose significant risk for aquatic ecosystems. Based on a rainfall-runoff simulation experiment, this study investigated the impact of carbonaceous materials (CMs) in soil, identified by organic petrology analysis, on the transport of soil-bound PAHs under rainfall conditions. The hypothesis that composition of soil organic matter significantly impacts the enrichment and transport of PAHs was proved. CMs in soil, varying significantly in content, mobility and adsorption capacity, act differently on the transport of PAHs. Anthropogenic CMs like black carbon (BC) largely control the transport, as PAHs may be preferentially attached to them. Eventually, this study led to a rethink of the traditional enrichment theory. An important implication is that CMs in soil have to be explicitly considered to appropriately model the nonpoint source pollution of PAHs (possibly other hydrophobic chemicals as well) and assess its environmental risk. Copyright © 2013 Elsevier Ltd. All rights reserved.
Enrichment behavior and transport mechanism of soil-bound PAHs during rainfall-runoff events
International Nuclear Information System (INIS)
Zheng Yi; Luo Xiaolin; Zhang Wei; Wu Bin; Han Feng; Lin Zhongrong; Wang Xuejun
2012-01-01
Polycyclic Aromatic Hydrocarbons (PAHs) transported by surface runoff result in nonpoint source pollution and jeopardize aquatic ecosystems. The transport mechanism of PAHs during rainfall-runoff events has been rarely studied regarding pervious areas. An experimental system was setup to simulate the runoff pollution process on PAHs-contaminated soil. The enrichment behavior of soil-bound PAHs was investigated. The results show that soil organic matters (SOM), rather than clay particles, seem to be the main carrier of PAHs. The enrichment is highly conditioned on runoff and erosion processes, and its magnitude varies among PAH compounds. It is not feasible to build a simple and universal relationship between enrichment ratio and sediment discharge following the traditional enrichment theory. To estimate the flux of PAHs from pervious areas, soil erosion process has to be clearly understood, and both organic carbon content and composition of SOM should be factored into the calculation. - Highlights: ► Significant enrichment of particle-bound PAHs during rainfall-runoff events. ► Organic matters as the direct carrier of PAHs in runoff from contaminated soil. ► The traditional enrichment theory is not fully valid for PAHs. - The traditional enrichment theory is not fully valid for PAHs, and soil organic matters have a significant impact on the transport of PAHs during rainfall-runoff events.
Simulation of rainfall-runoff for major flash flood events in Karachi
Zafar, Sumaira
2016-07-01
Metropolitan city Karachi has strategic importance for Pakistan. With the each passing decade the city is facing urban sprawl and rapid population growth. These rapid changes directly affecting the natural resources of city including its drainage pattern. Karachi has three major cities Malir River with the catchment area of 2252 sqkm and Lyari River has catchment area about 470.4 sqkm. These are non-perennial rivers and active only during storms. Change of natural surfaces into hard pavement causing an increase in rainfall-runoff response. Curve Number is increased which is now causing flash floods in the urban locality of Karachi. There is only one gauge installed on the upstream of the river but there no record for the discharge. Only one gauge located at the upstream is not sufficient for discharge measurements. To simulate the maximum discharge of Malir River rainfall (1985 to 2014) data were collected from Pakistan meteorological department. Major rainfall events use to simulate the rainfall runoff. Maximum rainfall-runoff response was recorded in during 1994, 2007 and 2013. This runoff causes damages and inundation in floodplain areas of Karachi. These flash flooding events not only damage the property but also cause losses of lives
K. X. Soulis; J. D. Valiantzas
2011-01-01
The Soil Conservation Service Curve Number (SCS-CN) approach is widely used as a simple method for predicting direct runoff volume for a given rainfall event. The CN values can be estimated by being selected from tables. However, it is more accurate to estimate the CN value from measured rainfall-runoff data (assumed available) in a watershed. Previous researchers indicated that the CN values calculated from measured rainfall-runoff data vary systematically with the rainfall depth. The...
Rainfall runoff and erosion in Napa Valley vineyards: effects of slope, cover and surface roughness
Battany, M. C.; Grismer, M. E.
2000-05-01
The effects of slope, cover and surface roughness on rainfall runoff, infiltration and erosion were determined at two sites on a hillside vineyard in Napa County, California, using a portable rainfall simulator. Rainfall simulation experiments were carried out at two sites, with five replications of three slope treatments (5%, 10% and 15%) in a randomized block design at each site (0%bsol;64 m2 plots). Prior to initiation of the rainfall simulations, detailed assessments, not considered in previous vineyard studies, of soil slope, cover and surface roughness were conducted. Significant correlations (at the 95% confidence level) between the physical characteristics of slope, cover and surface roughness, with total infiltration, runoff, sediment discharge and average sediment concentration were obtained. The extent of soil cracking, a physical characteristic not directly measured, also affected analysis of the rainfall-runoff-erosion process. Average cumulative runoff and cumulative sediment discharge from site A was 87% and 242% greater, respectively, than at site B. This difference was linked to the greater cover, extent of soil cracking and bulk density at site B than at site A. The extent of soil cover was the dominant factor limiting soil loss when soil cracking was not present. Field slopes within the range of 4-16%, although a statistically significant factor affecting soil losses, had only a minor impact on the amount of soil loss. The Horton infiltration equation fit field data better than the modified Philip's equation. Owing to the variability in the treatment parameters affecting the rainfall-runoff-erosion process, use of ANOVA methods were found to be inappropriate; multiple-factor regression analysis was more useful for identifying significant parameters. Overall, we obtained similar values for soil erosion parameters as those obtained from vineyard erosion studies in Europe. In addition, it appears that results from the small plot studies may be
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Mingguo Zheng
Full Text Available Correlation analysis is popular in erosion- or earth-related studies, however, few studies compare correlations on a basis of statistical testing, which should be conducted to determine the statistical significance of the observed sample difference. This study aims to statistically determine the erosivity index of single storms, which requires comparison of a large number of dependent correlations between rainfall-runoff factors and soil loss, in the Chinese Loess Plateau. Data observed at four gauging stations and five runoff experimental plots were presented. Based on the Meng's tests, which is widely used for comparing correlations between a dependent variable and a set of independent variables, two methods were proposed. The first method removes factors that are poorly correlated with soil loss from consideration in a stepwise way, while the second method performs pairwise comparisons that are adjusted using the Bonferroni correction. Among 12 rainfall factors, I30 (the maximum 30-minute rainfall intensity has been suggested for use as the rainfall erosivity index, although I30 is equally correlated with soil loss as factors of I20, EI10 (the product of the rainfall kinetic energy, E, and I10, EI20 and EI30 are. Runoff depth (total runoff volume normalized to drainage area is more correlated with soil loss than all other examined rainfall-runoff factors, including I30, peak discharge and many combined factors. Moreover, sediment concentrations of major sediment-producing events are independent of all examined rainfall-runoff factors. As a result, introducing additional factors adds little to the prediction accuracy of the single factor of runoff depth. Hence, runoff depth should be the best erosivity index at scales from plots to watersheds. Our findings can facilitate predictions of soil erosion in the Loess Plateau. Our methods provide a valuable tool while determining the predictor among a number of variables in terms of correlations.
Zheng, Mingguo; Chen, Xiaoan
2015-01-01
Correlation analysis is popular in erosion- or earth-related studies, however, few studies compare correlations on a basis of statistical testing, which should be conducted to determine the statistical significance of the observed sample difference. This study aims to statistically determine the erosivity index of single storms, which requires comparison of a large number of dependent correlations between rainfall-runoff factors and soil loss, in the Chinese Loess Plateau. Data observed at four gauging stations and five runoff experimental plots were presented. Based on the Meng’s tests, which is widely used for comparing correlations between a dependent variable and a set of independent variables, two methods were proposed. The first method removes factors that are poorly correlated with soil loss from consideration in a stepwise way, while the second method performs pairwise comparisons that are adjusted using the Bonferroni correction. Among 12 rainfall factors, I 30 (the maximum 30-minute rainfall intensity) has been suggested for use as the rainfall erosivity index, although I 30 is equally correlated with soil loss as factors of I 20, EI 10 (the product of the rainfall kinetic energy, E, and I 10), EI 20 and EI 30 are. Runoff depth (total runoff volume normalized to drainage area) is more correlated with soil loss than all other examined rainfall-runoff factors, including I 30, peak discharge and many combined factors. Moreover, sediment concentrations of major sediment-producing events are independent of all examined rainfall-runoff factors. As a result, introducing additional factors adds little to the prediction accuracy of the single factor of runoff depth. Hence, runoff depth should be the best erosivity index at scales from plots to watersheds. Our findings can facilitate predictions of soil erosion in the Loess Plateau. Our methods provide a valuable tool while determining the predictor among a number of variables in terms of correlations. PMID
Wu, Lei; Long, Tian-Yu; Liu, Xia; Mmereki, Daniel
2012-06-01
Jialing River is the largest tributary in the catchment area of Three Gorges Reservoir, and it is also one of the important areas of sediment yield in the upper reaches of the Yangtze River. In recent years, significant changes of water and sediment characteristics have taken place. The "Long Control" Project implemented since 1989 had greatly changed the surface appearance of the Jialing River Watershed (JRW), and it had made the environments of the watershed sediment yield and sediment transport change significantly. In this research, the Revised Universal Soil Loss Equation was selected and used to predict the annual average amount of soil erosion for the special water and sediment environments in the JRW after the implementation of the "Long Control" Project, and then the rainfall-runoff modulus and the time factor of governance were both considered as dynamic factors, the dynamic sediment transport model was built for soil erosion monitoring and forecasting based on the average sediment yield model. According to the dynamic model, the spatial and temporal distribution of soil erosion amount and sediment transport amount of the JRW from 1990 to 2007 was simulated using geographic information system (GIS) technology and space-grid algorithm. Simulation results showed that the average relative error of sediment transport was less than 10% except for the extreme hydrological year. The relationship between water and sediment from 1990 to 2007 showed that sediment interception effects of the soil and water conservation projects were obvious: the annual average sediment discharge reduced from 145.3 to 35 million tons, the decrement of sediment amount was about 111 million tons, and decreasing amplitude was 76%; the sediment concentration was also decreased from 2.01 to 0.578 kg/m(3). These data are of great significance for the prediction and estimation of the future changing trends of sediment storage in the Three Gorges Reservoir and the particulate non
Directory of Open Access Journals (Sweden)
Muhammad Shafique
2018-03-01
Full Text Available This field study elaborates the role of grass swale in the management of stormwater in an urban parking lot. Grass swale was constructed by using different vegetations and local soil media in the parking lot of Mapu-gu Seoul, Korea. In this study, rainfall runoff was first retained in soil and the vegetation layers of the grass swale, and then infiltrated rainwater was collected with the help of underground perforated pipe, and passed to an underground storage trench. In this way, grass swale detained a large amount of rainwater for a longer period of time and delayed peak discharge. In this field study, various real storm events were monitored and the research results were analyzed to evaluate the performance of grass swale for managing rainfall runoff in an urban area. From the analysis of field experiments, grass swale showed the significant rainfall runoff retention in different rain events. Grass swale markedly reduced total rainfall runoff volume and peak flow during the small storm events of intensity about 30 mm/h. From the analysis, on average rainfall runoff retention from the grass swale was found around 40 to 75% during the various small rain events. From the results, we can say that grass swale is a stormwater mitigation practice which can help avoid flash flooding problems in urban areas.
Shafique, Muhammad; Kim, Reeho; Kyung-Ho, Kwon
2018-03-16
This field study elaborates the role of grass swale in the management of stormwater in an urban parking lot. Grass swale was constructed by using different vegetations and local soil media in the parking lot of Mapu-gu Seoul, Korea. In this study, rainfall runoff was first retained in soil and the vegetation layers of the grass swale, and then infiltrated rainwater was collected with the help of underground perforated pipe, and passed to an underground storage trench. In this way, grass swale detained a large amount of rainwater for a longer period of time and delayed peak discharge. In this field study, various real storm events were monitored and the research results were analyzed to evaluate the performance of grass swale for managing rainfall runoff in an urban area. From the analysis of field experiments, grass swale showed the significant rainfall runoff retention in different rain events. Grass swale markedly reduced total rainfall runoff volume and peak flow during the small storm events of intensity about 30 mm/h. From the analysis, on average rainfall runoff retention from the grass swale was found around 40 to 75% during the various small rain events. From the results, we can say that grass swale is a stormwater mitigation practice which can help avoid flash flooding problems in urban areas.
Shafique, Muhammad; Kim, Reeho; Kyung-Ho, Kwon
2018-01-01
This field study elaborates the role of grass swale in the management of stormwater in an urban parking lot. Grass swale was constructed by using different vegetations and local soil media in the parking lot of Mapu-gu Seoul, Korea. In this study, rainfall runoff was first retained in soil and the vegetation layers of the grass swale, and then infiltrated rainwater was collected with the help of underground perforated pipe, and passed to an underground storage trench. In this way, grass swale detained a large amount of rainwater for a longer period of time and delayed peak discharge. In this field study, various real storm events were monitored and the research results were analyzed to evaluate the performance of grass swale for managing rainfall runoff in an urban area. From the analysis of field experiments, grass swale showed the significant rainfall runoff retention in different rain events. Grass swale markedly reduced total rainfall runoff volume and peak flow during the small storm events of intensity about 30 mm/h. From the analysis, on average rainfall runoff retention from the grass swale was found around 40 to 75% during the various small rain events. From the results, we can say that grass swale is a stormwater mitigation practice which can help avoid flash flooding problems in urban areas. PMID:29547567
Metzen, D.; Sheridan, G. J.; Benyon, R. G.; Lane, P. N. J.
2015-12-01
In topographically complex terrain, the interaction of aspect-dependent solar exposure and drainage-position-dependent flow accumulation results in energy and water partitioning that is highly spatially variable. Catchment scale rainfall-runoff relationships are dependent on these smaller scale spatial patterns. However, there remains considerable uncertainty as to how to represent this smaller scale variability within lumped parameter, catchment scale rainfall-runoff models. In this study we aim to measure and represent the key interactions between aridity and drainage position in complex terrain to inform the development of simple catchment-scale hydrologic model parameters. Six measurement plots were setup on opposing slopes in an east-west facing eucalypt forest headwater catchment. The field sites are spanning three drainage positions with two contrasting aridity indices each, while minimizing variations in other factors, e.g. geology and weather patterns. Sapflow, soil water content (SWC) and throughfall were continuously monitored on two convergent hillslopes with similar size (1.3 and 1.6ha) but contrasting aspects (north and south). Soil depth varied from 0.6m at the topslope to >2m at the bottomslope positions. Maximum tree heights ranged from 16.2m to 36.9m on the equator-facing slope and from 30.1m to 45.5m on the pole-facing slope, with height decreasing upslope on both aspects. Two evapotranspiration (ET) patterns emerged in relation to aridity and drainage position. On the equator-facing slope (AI~ 2.1), seasonal understorey and overstorey ET patterns were in sync, whereas on the pole-facing slope (AI~1.5) understorey ET showed larger seasonal fluctuations than overstorey ET. Seasonal ET patterns and competition between soil evaporation and root water uptake lead to distinct differences in profile SWC across the sites, likely caused by depletion from different depths. Topsoil water content on equator-facing slopes was generally lower and responded
Palumbo, Manuela; Ascione, Alessandra; Santangelo, Nicoletta; Santo, Antonio
2017-04-01
We present the first results of an analysis of flood hazard in ungauged mountain catchments that are associated with intensely urbanized alluvial fans. Assessment of hydrological hazard has been based on the integration of rainfall/runoff modelling of drainage basins with geomorphological analysis and mapping. Some small and steep, ungauged mountain catchments located in various areas of the southern Apennines, in southern Italy, have been chosen as test sites. In the last centuries, the selected basins have been subject to heavy and intense precipitation events, which have caused flash floods with serious damages in the correlated alluvial fan areas. Available spatial information (regional technical maps, DEMs, land use maps, geological/lithological maps, orthophotos) and an automated GIS-based procedure (ArcGis tools and ArcHydro tools) have been used to extract morphological, hydrological and hydraulic parameters. Such parameters have been used to run the HEC (Hydrologic Engineering Center of the US Army Corps of Engineers) software (GeoHMS, GeoRAS, HMS and RAS) based on rainfall-runoff models, which have allowed the hydrological and hydraulic simulations. As the floods occurred in the studied catchments have been debris flows dominated, the solid load simulation has been also performed. In order to validate the simulations, we have compared results of the modelling with the effects produced by past floods. Such effects have been quantified through estimations of both the sediment volumes within each catchment that have the potential to be mobilised (pre-event) during a sediment transfer event, and the volume of sediments delivered by the debris flows at basins' outlets (post-event). The post-event sediment volume has been quantified through post-event surveys and Lidar data. Evaluation of the pre-event sediment volumes in single catchments has been based on mapping of sediment storages that may constitute source zones of bed load transport and debris flows. For
Guay, Joel R.
2002-01-01
To better understand the rainfall-runoff characteristics of the eastern part of the San Jacinto River Basin and to estimate the effects of increased urbanization on streamflow, channel infiltration, and land-surface infiltration, a long-term (1950?98) time series of monthly flows in and out of the channels and land surfaces were simulated using the Hydrologic Simulation Program- FORTRAN (HSPF) rainfall-runoff model. Channel and land-surface infiltration includes rainfall or runoff that infiltrates past the zone of evapotranspiration and may become ground-water recharge. The study area encompasses about 256 square miles of the San Jacinto River drainage basin in Riverside County, California. Daily streamflow (for periods with available data between 1950 and 1998), and daily rainfall and evaporation (1950?98) data; monthly reservoir storage data (1961?98); and estimated mean annual reservoir inflow data (for 1974 conditions) were used to calibrate the rainfall-runoff model. Measured and simulated mean annual streamflows for the San Jacinto River near San Jacinto streamflow-gaging station (North-South Fork subbasin) for 1950?91 and 1997?98 were 14,000 and 14,200 acre-feet, respectively, a difference of 1.4 percent. The standard error of the mean for measured and simulated annual streamflow in the North-South Fork subbasin was 3,520 and 3,160 acre-feet, respectively. Measured and simulated mean annual streamflows for the Bautista Creek streamflow-gaging station (Bautista Creek subbasin) for 1950?98 were 980 acre-feet and 991 acre-feet, respectively, a difference of 1.1 percent. The standard error of the mean for measured and simulated annual streamflow in the Bautista Creek subbasin was 299 and 217 acre-feet, respectively. Measured and simulated annual streamflows for the San Jacinto River above State Street near San Jacinto streamflow-gaging station (Poppet subbasin) for 1998 were 23,400 and 23,500 acre-feet, respectively, a difference of 0.4 percent. The simulated
Enrichment behavior and transport mechanism of soil-bound PAHs during rainfall-runoff events.
Zheng, Yi; Luo, Xiaolin; Zhang, Wei; Wu, Bin; Han, Feng; Lin, Zhongrong; Wang, Xuejun
2012-12-01
Polycyclic Aromatic Hydrocarbons (PAHs) transported by surface runoff result in nonpoint source pollution and jeopardize aquatic ecosystems. The transport mechanism of PAHs during rainfall-runoff events has been rarely studied regarding pervious areas. An experimental system was setup to simulate the runoff pollution process on PAHs-contaminated soil. The enrichment behavior of soil-bound PAHs was investigated. The results show that soil organic matters (SOM), rather than clay particles, seem to be the main carrier of PAHs. The enrichment is highly conditioned on runoff and erosion processes, and its magnitude varies among PAH compounds. It is not feasible to build a simple and universal relationship between enrichment ratio and sediment discharge following the traditional enrichment theory. To estimate the flux of PAHs from pervious areas, soil erosion process has to be clearly understood, and both organic carbon content and composition of SOM should be factored into the calculation. Copyright © 2012 Elsevier Ltd. All rights reserved.
Increasing trends in rainfall-runoff erosivity in the Source Region of the Three Rivers, 1961-2012.
Wang, Yousheng; Cheng, Congcong; Xie, Yun; Liu, Baoyuan; Yin, Shuiqing; Liu, Yingna; Hao, Yanfang
2017-08-15
As the head source of the two longest rivers in China and the longest river in Southeast Asia, the East Qinghai-Tibetan Plateau (QTP) is experiencing increasing thaw snowmelt and more heavy precipitation events under global warming, which might lead to soil erosion risk. To understand the potential driving force of soil erosion and its relationship with precipitation in the context of climate change, this study analyzed long-term variations in annual rainfall-runoff erosivity, a climatic index of soil erosion, by using the Mann-Kendall statistical test and Theil and Sen's approach in the Source Region of the Three Rivers during 1961-2012. The results showed the followings: (i) increasing annual rainfall-runoff erosivity was observed over the past 52years, with a mean relative trend index (RT 1 ) value of 12.1%. The increasing trend was more obvious for the latest two decades: RT 1 was nearly three times larger than that over the entire period; (ii) more precipitation events and a higher precipitation amount were the major forces for the increasing rainfall-runoff erosivity; (iii) similar rising trends in sediment yields, which corresponded to rainfall-runoff erosivity under slightly increasing vegetation coverage in the study area, implied a large contribution of rainfall-runoff erosivity to the increasing sediment yields; and (iv) high warming rates increased the risk of soil destruction, soil erosion and sediment yields. Conservation measures, such as enclosing grassland, returning grazing land to grassland and rotation grazing since the 1980s, have maintained vegetation coverage and should be continued and strengthened. Copyright © 2017 Elsevier B.V. All rights reserved.
Gu, W.-Z.; Lu, J.-J.; Zhao, X.; Peters, N.E.
2007-01-01
Aimed at the rainfall-runoff tracing using inorganic ions, the experimental study is conducted in the Chuzhou Hydrology Laboratory with special designed experimental catchments, lysimeters, etc. The various runoff components including the surface runoff, interflow from the unsaturated zone and the groundwater flow from saturated zone were monitored hydrometrically. Hydrochemical inorganic ions including Na+, K+, Ca2+, Mg2+, Cl-, SO42-, HCO3- + CO32-, NO3-, F-, NH4-, PO42-, SiO2 and, pH, EC, 18O were measured within a one month period for all processes of rainfall, various runoff components and groundwater within the catchment from 17 boreholes distributed in the Hydrohill Catchment, few soil water samples were also included. The results show that: (a) all the runoff components are distinctly identifiable from both the relationships of Ca2+ versus Cl-/SO42-, EC versus Na+/(Na+ + Ca2+) and, from most inorganic ions individually; (b) the variation of inorganic ions in surface runoff is the biggest than that in other flow components; (c) most ions has its lowermost concentration in rainfall process but it increases as the generation depths of runoff components increased; (d) quantitatively, ion processes of rainfall and groundwater flow display as two end members of that of other runoff components; and (e) the 18O processes of rainfall and runoff components show some correlation with that of inorganic ions. The results also show that the rainfall input is not always the main source of inorganic ions of various runoff outputs due to the process of infiltration and dissolution resulted from the pre-event processes. The amount and sources of Cl- of runoff components with various generation mechanisms challenge the current method of groundwater recharge estimation using Cl-.
Qiu, Jiali; Shen, Zhenyao; Wei, Guoyuan; Wang, Guobo; Xie, Hui; Lv, Guanping
2018-03-01
The assessment of peak flow rate, total runoff volume, and pollutant loads during rainfall process are very important for the watershed management and the ecological restoration of aquatic environment. Real-time measurements of rainfall-runoff and pollutant loads are always the most reliable approach but are difficult to carry out at all desired location in the watersheds considering the large consumption of material and financial resources. An integrated environmental modeling approach for the estimation of flash streamflow that combines the various hydrological and quality processes during rainstorms within the agricultural watersheds is essential to develop targeted management strategies for the endangered drinking water. This study applied the Hydrological Simulation Program-Fortran (HSPF) to simulate the spatial and temporal variation in hydrological processes and pollutant transport processes during rainstorm events in the Miyun Reservoir watershed, a drinking water resource area in Beijing. The model performance indicators ensured the acceptable applicability of the HSPF model to simulate flow and pollutant loads in the studied watershed and to establish a relationship between land use and the parameter values. The proportion of soil and land use was then identified as the influencing factors of the pollution intensities. The results indicated that the flush concentrations were much higher than those observed during normal flow periods and considerably exceeded the limits of Class III Environmental Quality Standards for Surface Water (GB3838-2002) for the secondary protection zones of the drinking water resource in China. Agricultural land and leached cinnamon soils were identified as the key sources of sediment, nutrients, and fecal coliforms. Precipitation volume was identified as a driving factor that determined the amount of runoff and pollutant loads during rainfall processes. These results are useful to improve the streamflow predictions, provide
Curve Number Estimation for a Small Urban Catchment from Recorded Rainfall-Runoff Events
Directory of Open Access Journals (Sweden)
Banasik Kazimierz
2014-12-01
Full Text Available Runoff estimation is a key component in various hydrological considerations. Estimation of storm runoff is especially important for the effective design of hydraulic and road structures, for the ﬂood ﬂow management, as well as for the analysis of land use changes, i.e. urbanization or low impact development of urban areas. The curve number (CN method, developed by Soil Conservation Service (SCS of the U.S. Department of Agriculture for predicting the ﬂood runoff depth from ungauged catchments, has been in continuous use for ca. 60 years. This method has not been extensively tested in Poland, especially in small urban catchments, because of lack of data. In this study, 39 rainfall-runoff events, collected during four years (2009–2012 in a small (A=28.7 km2, urban catchment of Służew Creek in southwest part of Warsaw were used, with the aim of determining the CNs and to check its applicability to ungauged urban areas. The parameters CN, estimated empirically, vary from 65.1 to 95.0, decreasing with rainfall size and, when sorted rainfall and runoff separately, reaching the value from 67 to 74 for large rainfall events.
Characteristics of the event mean concentration (EMC) from rainfall runoff on an urban highway
International Nuclear Information System (INIS)
Lee, Ju Young; Kim, Hyoungjun; Kim, Youngjin; Han, Moo Young
2011-01-01
The purpose of this study was to investigate the characterization of the event mean concentration (EMC) of runoff during heavy precipitation events on highways. Highway runoff quality data were collected from the 7th highway, in South Korea during 2007-2009. The samples were analyzed for runoff quantity and quality parameters such as COD cr , TSS, TPHs, TKN, NO 3 , TP, PO 4 and six heavy metals, e.g., As, Cu, Cd, Ni, Pb and Zn. Analysis of resulting hydrographs and pollutant graphs indicates that the peak of the pollutant concentrations in runoff occurs 20 min after the first rainfall runoff occurrence. The first flush effect depends on the preceding dry period and the rainfall intensity. The results of this study can be used as a reference for water quality management of urban highways. - Research highlights: → Field test on urban highway were performed to 50 of 100 storm events for 3 years. → The peak pollutant concentrations occurs 20 min after the first runoff. → The first flush effect depends on the preceding dry period and rainfall intensity. → Relationship between runoff and event mean concentration for SS and COD. → A crest of the EMC by 70-80 m 3 /event and decreasing EMC after 70-80 m 3 /event. - This study investigate the characterization of the EMC of runoff during rainfall event on highway.
Impacts of water quality variation and rainfall runoff on Jinpen Reservoir, in Northwest China
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Zi-zhen Zhou
2015-10-01
Full Text Available The seasonal variation characteristics of the water quality of the Jinpen Reservoir and the impacts of rainfall runoff on the reservoir were investigated. Water quality monitoring results indicated that, during the stable stratification period, the maximum concentrations of total nitrogen, total phosphorus, ammonia nitrogen, total organic carbon, iron ion, and manganese ion in the water at the reservoir bottom on September 6 reached 2.5 mg/L, 0.12 mg/L, 0.58 mg/L, 3.2 mg/L, 0.97 mg/L, and 0.32 mg/L, respectively. Only heavy storm runoff can affect the main reservoir and cause the water quality to seriously deteriorate. During heavy storms, the stratification of the reservoir was destroyed, and the reservoir water quality consequently deteriorated due to the high-turbidity particulate phosphorus and organic matter in runoff. The turbidity and concentrations of total phosphorus and total organic carbon in the main reservoir increased to 265 NTU, 0.224 mg/L, and 3.9 mg/L, respectively. Potential methods of dealing with the water problems in the Jinpen Reservoir are proposed. Both in stratification and in storm periods, the use of measures such as adjusting intake height, storing clean water, and releasing turbid flow can be helpful to safeguarding the quality of water supplied to the water treatment plants.
Czech Academy of Sciences Publication Activity Database
Buchtele, Josef; Tesař, Miroslav
2009-01-01
Roč. 64, č. 3 (2009), s. 575-579 ISSN 0006-3088 R&D Projects: GA MŽP(CZ) SP/1A6/151/07 Institutional research plan: CEZ:AV0Z20600510 Keywords : evapotranspiration components * evapotranspiration demand * land use * natural affection of runoff * rainfall- runoff simulation * vegetation change Subject RIV: DA - Hydrology ; Limnology Impact factor: 0.617, year: 2009
Transport of three veterinary antimicrobials from feedlot pens via simulated rainfall runoff.
Sura, Srinivas; Degenhardt, Dani; Cessna, Allan J; Larney, Francis J; Olson, Andrew F; McAllister, Tim A
2015-07-15
Veterinary antimicrobials are introduced to wider environments by manure application to agricultural fields or through leaching or runoff from manure storage areas (feedlots, stockpiles, windrows, lagoons). Detected in manure, manure-treated soils, and surface and ground water near intensive cattle feeding operations, there is a concern that environmental contamination by these chemicals may promote the development of antimicrobial resistance in bacteria. Surface runoff and leaching appear to be major transport pathways by which veterinary antimicrobials eventually contaminate surface and ground water, respectively. A study was conducted to investigate the transport of three veterinary antimicrobials (chlortetracycline, sulfamethazine, tylosin), commonly used in beef cattle production, in simulated rainfall runoff from feedlot pens. Mean concentrations of veterinary antimicrobials were 1.4 to 3.5 times higher in surface material from bedding vs. non-bedding pen areas. Runoff rates and volumetric runoff coefficients were similar across all treatments but both were significantly higher from non-bedding (0.53Lmin(-1); 0.27) than bedding areas (0.40Lmin(-1); 0.19). In keeping with concentrations in pen surface material, mean concentrations of veterinary antimicrobials were 1.4 to 2.5 times higher in runoff generated from bedding vs. non-bedding pen areas. Water solubility and sorption coefficient of antimicrobials played a role in their transport in runoff. Estimated amounts of chlortetracycline, sulfamethazine, and tylosin that could potentially be transported to the feedlot catch basin during a one in 100-year precipitation event were 1.3 to 3.6ghead(-1), 1.9ghead(-1), and 0.2ghead(-1), respectively. This study demonstrates the magnitude of veterinary antimicrobial transport in feedlot pen runoff and supports the necessity of catch basins for runoff containment within feedlots. Crown Copyright © 2015. Published by Elsevier B.V. All rights reserved.
Yu, Xing-xiu; Li, Zhen-wei; Liu, Qian-jin; Jing, Guang-hua
2012-08-01
Relationships between phosphorus pollutant concentrations and precipitation-runoff were analyzed by monitoring pollutant losses at outlets of the Menglianggu watershed in 2010. A typical small watershed was selected to examine the runoff and quality parameters such as total phosphorus (TP), particle phosphorus (PP), dissolve phosphorus (DP) and dissolve inorganic phosphorus (DIP) in rainfall-runoff of 10 rainfall events. Precipitation was above 2 mm for all the 10 rainfall events. The results showed that the peak of phosphorus concentrations occurred before the peak of water flows, whereas change processes of the phosphorus fluxes were consistent with that of the water flows and the phosphorus flux also have a strong linear relationship with the water flows. The minimums of the phosphorus concentrations in every 10 natural rainfall events have small differences with each other, but the maximum and EMCs of the phosphorus concentrations have significant differences with each rainfall event. This was mainly influenced by the precipitation, maximum rainfall intensity and mean rainfall intensity (EMCs) and was less influenced by rainfall duration. DP and TP were mainly composed of DIP and PP, respectively. There were no significant correlations between DIP/DP dynamic changes and rainfall characteristics, whereas significant correlations between PP/TP dynamic changes and maximum rainfall intensity were detected. The production of DIP, DP, AND TP were mainly influenced by the direct runoff (DR) and base flow (BF). The EMCs of DIP, DP, TP and the variations of DIP/DP were all found to have significant polynomial relationships with DR/TR., but the dynamic changes of PP/ TP and the EMCS of PP were less influenced by the DR/TR.
Muhammad Shafique; Reeho Kim; Kwon Kyung-Ho
2018-01-01
This field study elaborates the role of grass swale in the management of stormwater in an urban parking lot. Grass swale was constructed by using different vegetations and local soil media in the parking lot of Mapu-gu Seoul, Korea. In this study, rainfall runoff was first retained in soil and the vegetation layers of the grass swale, and then infiltrated rainwater was collected with the help of underground perforated pipe, and passed to an underground storage trench. In this way, grass swale...
Development and evaluation of a watershed-scale hybrid hydrologic model
Cho, Younghyun
2016-01-01
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...
Ogden, Fred L.; Hawkins, Richard Pete; Walter, M. Todd; Goodrich, David C.
2017-07-01
Bartlett et al. (2016) performed a re-interpretation and modification of the space-time lumped USDA NRCS (formerly SCS) Curve Number (CN) method to extend its applicability to forested watersheds. We believe that the well documented limitations of the CN method severely constrains the applicability of the modifications proposed by Bartlett et al. (2016). This forward-looking comment urges the research communities in hydrologic science and engineering to consider the CN method as a stepping stone that has outlived its usefulness in research. The CN method fills a narrow niche in certain settings as a parsimonious method having utility as an empirical equation to estimate runoff from a given amount of rainfall, which originated as a static functional form that fits rainfall-runoff data sets. Sixty five years of use and multiple reinterpretations have not resulted in improved hydrological predictability using the method. We suggest that the research community should move forward by (1) identifying appropriate dynamic hydrological model formulations for different hydro-geographic settings, (2) specifying needed model capabilities for solving different classes of problems (e.g., flooding, erosion/sedimentation, nutrient transport, water management, etc.) in different hydro-geographic settings, and (3) expanding data collection and research programs to help ameliorate the so-called "overparameterization" problem in contemporary modeling. Many decades of advances in geo-spatial data and processing, computation, and understanding are being squandered on continued focus on the static CN regression method. It is time to truly "move beyond" the Curve Number method.
rainfall runoff model for cala noff model for calabar metropolis u
African Journals Online (AJOL)
eobe
developed for drains design and analysis for Calabar. Keywords: .... urban growth has, over the years, resulted in land use changes and ... network, reduce the flood storage and overwhelm the carrying ... quality issues, as well as regional issues [3]. Storm water ..... SWAT: Case Study Of Upstream watershed of Jebba.
Distributed modelling of hydrologic regime at three subcatchments of Kopaninský tok catchment
Žlábek, Pavel; Tachecí, Pavel; Kaplická, Markéta; Bystřický, Václav
2010-05-01
Kopaninský tok catchment is situated in crystalline area of Bohemo-Moravian highland hilly region, with cambisol cover and prevailing agricultural land use. It is a subject of long term (since 1980's) observation. Time series (discharge, precipitation, climatic parameters...) are nowadays available in 10 min. time step, water quality average daily composit samples plus samples during events are available. Soil survey resulting in reference soil hydraulic properties for horizons and vegetation cover survey incl. LAI measurement has been done. All parameters were analysed and used for establishing of distributed mathematical models of P6, P52 and P53 subcatchments, using MIKE SHE 2009 WM deterministic hydrologic modelling system. The aim is to simulate long-term hydrologic regime as well as rainfall-runoff events, serving the base for modelling of nitrate regime and agricultural management influence in the next step. Mentioned subcatchments differs in ratio of artificial drainage area, soil types, land use and slope angle. The models are set-up in a regular computational grid of 2 m size. Basic time step was set to 2 hrs, total simulated period covers 3 years. Runoff response and moisture regime is compared using spatially distributed simulation results. Sensitivity analysis revealed most important parameters influencing model response. Importance of spatial distribution of initial conditions was underlined. Further on, different runoff components in terms of their origin, flow paths and travel time were separated using a combination of two runoff separation techniques (a digital filter and a simple conceptual model GROUND) in 12 subcatchments of Kopaninský tok catchment. These two methods were chosen based on a number of methods testing. Ordinations diagrams performed with Canoco software were used to evaluate influence of different catchment parameters on different runoff components. A canonical ordination method analyses (RDA) was used to explain one data set
Directory of Open Access Journals (Sweden)
Nana Zhao
2014-09-01
Full Text Available The characteristics of rainfall-runoff are important aspects of hydrological processes. In this study, rainfall-runoff processes and soil moisture dynamics at different soil depths and slope positions of grassland with two different row spacings (5 cm and 10 cm, respectively, referred to as R5 and R10 were analyzed, by means of a solution of rainfall simulation experiments. Bare land was also considered as a comparison. The results showed that the mechanism of runoff generation was mainly excess infiltration overland flow. The surface runoff amount of R5 plot was greater than that of R10, while the interflow amount of R10 was larger than that of R5 plot, although the differences of the subsurface runoff processes between plots R5 and R10 were little. The effects of rainfall intensity on the surface runoff were significant, but not obvious on the interflow and recession curve, which can be described as a simple exponential equation, with a fitting degree of up to 0.854–0.996. The response of soil moisture to rainfall and evapotranspiration was mainly in the 0–20 cm layer, and the response at the 40 cm layer to rainfall was slower and generally occurred after the rainfall stopped. The upper slope generally responded fastest to rainfall, and the foot of the slope was the slowest. The results presented here could provide insights into understanding the surface and subsurface runoff processes and soil moisture dynamics for grasslands in semi-arid regions.
Czech Academy of Sciences Publication Activity Database
Buchtele, Josef; Tesař, Miroslav
2010-01-01
Roč. 41, - (2010), s. 103-110 ISSN 0071-6715 R&D Projects: GA MŽP(CZ) SP/1A6/151/07 EU Projects: European Commission(XE) 511179 - NEWATER Institutional research plan: CEZ:AV0Z20600510 Keywords : vegetation change * land use * rainfall - runoff simulation * evapotranspiration demand Subject RIV: DA - Hydrology ; Limnology
Choosing an Appropriate Hydrological Model for Rainfall-Runoff Extremes in Small Catchments
Czech Academy of Sciences Publication Activity Database
Kovář, P.; Hrabalíková, M.; Neruda, M.; Neruda, Roman; Šrejber, J.; Jelínková, A.; Bačinová, H.
2015-01-01
Roč. 10, č. 3 (2015), s. 137-146 ISSN 1801-5395 Grant - others:GA TA ČR(CZ) TA02020402 Institutional support: RVO:67985807 Keywords : flood prediction * infiltration * Jizerské hory Mts. * kinematic wave * neural network Subject RIV: IN - Informatics, Computer Science Impact factor: 0.580, year: 2015
On the role of model structure in hydrological modeling : Understanding models
Gharari, S.
2016-01-01
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,
A Bayesian Hierarchical Modeling Approach to Predicting Flow in Ungauged Basins
Gronewold, A.; Alameddine, I.; Anderson, R. M.
2009-12-01
States Environmental Protection Agency (USEPA) total maximum daily load (TMDL) program, as well as those addressing coastal population dynamics and sea level rise. Our approach has several advantages, including the propagation of parameter uncertainty through a nonparametric probability distribution which avoids common pitfalls of fitting parameters and model error structure to a predetermined parametric distribution function. In addition, by explicitly acknowledging correlation between model parameters (and reflecting those correlations in our predictive model) our model yields relatively efficient prediction intervals (unlike those in the current literature which are often unnecessarily large, and may lead to overly-conservative management actions). Finally, our model helps improve understanding of the rainfall-runoff process by identifying model parameters (and associated catchment attributes) which are most sensitive to current and future land use change patterns. Disclaimer: Although this work was reviewed by EPA and approved for publication, it may not necessarily reflect official Agency policy.
Chen, Lei; Zhi, Xiaosha; Shen, Zhenyao; Dai, Ying; Aini, Guzhanuer
2018-01-01
As a climate-driven event, nonpoint source (NPS) pollution is caused by rainfall- or snowmelt-runoff processes; however, few studies have compared the characteristics and mechanisms of these two kinds of NPS processes. In this study, three factors relating to urban NPS, including surface dust, snowmelt, and rainfall-runoff processes, were analyzed comprehensively by both field sampling and laboratory experiments. The seasonal variation and leaching characteristics of pollutants in surface dust were explored, and the runoff quality of snowmelt NPS and rainfall NPS were compared. The results indicated that dusts are the main sources of urban NPS and more pollutants are deposited in dust samples during winter and spring. However, pollutants in surface dust showed a low leaching ratio, which indicated most NPS pollutants would be carried as particulate forms. Compared to surface layer, underlying snow contained higher chemical oxygen demand, total suspended solids (TSS), Cu, Fe, Mn, and Pb concentrations, while the event mean concentration of most pollutants in snowmelt tended to be higher in roads. Moreover, the TSS and heavy metal content of snowmelt NPS was always higher than those of rainfall NPS, which indicated the importance of controlling snowmelt pollution for effective water quality management.
Sampling, testing and modeling particle size distribution in urban catch basins.
Garofalo, G; Carbone, M; Piro, P
2014-01-01
The study analyzed the particle size distribution of particulate matter (PM) retained in two catch basins located, respectively, near a parking lot and a traffic intersection with common high levels of traffic activity. Also, the treatment performance of a filter medium was evaluated by laboratory testing. The experimental treatment results and the field data were then used as inputs to a numerical model which described on a qualitative basis the hydrological response of the two catchments draining into each catch basin, respectively, and the quality of treatment provided by the filter during the measured rainfall. The results show that PM concentrations were on average around 300 mg/L (parking lot site) and 400 mg/L (road site) for the 10 rainfall-runoff events observed. PM with a particle diameter of model showed that a catch basin with a filter unit can remove 30 to 40% of the PM load depending on the storm characteristics.
Despite increased interest in watershed scale model simulations, literature lacks application of long-term data in fuzzy logic simulations and comparing outputs with physically based models such as APEX (Agricultural Policy Environmental eXtender). The objective of this study was to develop a fuzzy...
DEFF Research Database (Denmark)
Löwe, Roland; Mikkelsen, Peter Steen; Madsen, Henrik
2014-01-01
Probabilistic runoff forecasts generated by stochastic greybox models can be notably useful for the improvement of the decision-making process in real-time control setups for urban drainage systems because the prediction risk relationships in these systems are often highly nonlinear. To date...... the identification of models for cases with noisy in-sewer observations. For the prediction of the overflow risk, no improvement was demonstrated through the application of stochastic forecasts instead of point predictions, although this result is thought to be caused by the notably simplified setup used...
Cheng, Jiang; Yang, Kai; Huang, Xiao-Fang; Lü, Yong-Peng
2009-07-15
In order to obtain the processes of hydrology and water quality of urban combined sewerage system (CSS) in highly urbanized region, the precipitation, discharge and pollutant concentration of four different intensity rainfall (light rain, moderate rain, heavy rain and storm) were measured from Jul. to Sep. 2007 in the Chendulu CSS along Suzhou Creek in Shanghai. The results show that the shapes of runoff graph are similar to rainfall graph, with a weaker fluctuation range and a 15-25 min delay between rainfall and runoff graph. Runoff coefficients of the four different rainfall are 0.33, 0.62, 0.67 and 0.73, respectively. The 30/30 first flush phenomenon is found in Chendulu CSS. The peak of pollutant concentration graph lags rainfall peak about 30-40 min. The pH and event mean concentration (EMC) of Cu, Zn, Cr, Cd, Pb and Ni totally measure up to environmental quality standards V for surface water of China besides COD, BOD5, NH4(+) -N and TP, and the EMC of COD, BOD5, NH4(+) -N and TP are 225.0-544.1, 31.5-98.9, 8.9-44.2 and 1.98-3.52 mg x L(-1), respectively. The rainfall-runoff pollutant concentration in Chendulu CSS is close to those of other foreign cites. At the confidence level of p < 0.01, good relationships exist between SS and COD, BOD5, NH4(+) -N and TP, respectively, and the average proportion of particulate organic pollutant and nutrient is 70.21%.
Turbid releases from Glen Canyon Dam, Arizona, following rainfall-runoff events of September 2013
Wildman, Richard A.; Vernieu, William
2017-01-01
Glen Canyon Dam is a large dam on the Colorado River in Arizona. In September 2013, it released turbid water following intense thunderstorms in the surrounding area. Turbidity was >15 nephelometric turbidity units (NTU) for multiple days and >30 NTU at its peak. These unprecedented turbid releases impaired downstream fishing activity and motivated a rapid-response field excursion. At 5 locations upstream from the dam, temperature, specific conductance, dissolved oxygen, chlorophyll a, and turbidity were measured in vertical profiles. Local streamflow and rainfall records were retrieved, and turbidity and specific conductance data in dam releases were evaluated. Profiling was conducted to determine possible sources of turbidity from 3 tributaries nearest the dam, Navajo, Antelope, and Wahweap creeks, which entered Lake Powell as interflows during this study. We discuss 4 key conditions that must have been met for tributaries to influence turbidity of dam releases: tributary flows must have reached the dam, tributary flows must have been laden with sediment, inflow currents must have been near the depth of dam withdrawals, and the settling velocity of particles must have been slow. We isolate 2 key uncertainties that reservoir managers should resolve in future similar studies: the reach of tributary water into the reservoir thalweg and the distribution of particle size of suspended sediment. These uncertainties leave the source of the turbidity ambiguous, although an important role for Wahweap Creek is possible. The unique combination of limnological factors we describe implies that turbid releases at Glen Canyon Dam will continue to be rare.
Wu, Songbai; Yu, Minghui; Chen, Li
2017-02-01
The slope effect on flow erosivity and soil erosion still remains a controversial issue. This theoretical framework explained and quantified the direct slope effect by coupling the modified Green-Ampt equation accounting for slope effect on infiltration, 1-D kinematic wave overland flow routing model, and WEPP soil erosion model. The flow velocity, runoff rate, shear stress, interrill, and rill erosion were calculated on 0°-60° isotropic slopes with equal horizontal projective length. The results show that, for short-duration rainfall events, the flow erosivity and erosion amounts exhibit a bell-shaped trend which first increase with slope gradient, and then decrease after a critical slope angle. The critical slope angles increase significantly or even vanish with increasing rainfall duration but are nearly independent of the slope projective length. The soil critical shear stress, rainfall intensity, and temporal patterns have great influences on the slope effect trend, while the other soil erosion parameters, soil type, hydraulic conductivity, and antecedent soil moisture have minor impacts. Neglecting the slope effect on infiltration would generate smaller erosion and reduce critical slope angles. The relative slope effect on soil erosion in physically based model WEPP was compared to those in the empirical models USLE and RUSLE. The trends of relative slope effect were found quite different, but the difference may diminish with increasing rainfall duration. Finally, relatively smaller critical slope angles could be obtained with the equal slope length and the range of variation provides a possible explanation for the different critical slope angles reported in previous studies.
Zhang, Xiaodong; Kirilenko, Andrei; Lim, Howe; Teng, Williams
2010-01-01
This slide presentation reviews work to combine the hydrological models and remote sensing observations to monitor Devils Lake in North Dakota, to assist in flood damage mitigation. This reports on the use of a distributed rainfall-runoff model, HEC-HMS, to simulate the hydro-dynamics of the lake watershed, and used NASA's remote sensing data, including the TRMM Multi-Satellite Precipitation Analysis (TMPA) and AIRS surface air temperature, to drive the model.
Sharma, Deepshikha; Gupta, Ruchi; Singh, Ram Karan; Kansal, Arun
2012-03-01
This paper is focused on the monitoring of the diffuse pollution characteristics from the agricultural land confining the River Yamuna in Delhi (capital of India). Agricultural fields surrounding the Yamuna river are direct nonpoint source of pollution impacting the river quality. The study includes watershed delineation for the River Yamuna using SWAT (2005) and land use classification for the city using GIS and remote sensing. Thereafter, the rainfall-runoff pollutant concentrations from the mixed agricultural land use were assessed for the 2006 and 2007 monsoon period (July-September). Runoff was measured using SCS method and grab samples of rainfall runoff were collected at three stations namely Old Delhi Railway Bridge (ODRB), Nizamuddin and Okhla bridge in Delhi. The samples were analysed for physico-chemical and biological parameters. Rainfall runoff and event mean concentrations (EMCs) for different water quality parameters were characterized and the effect of land use was analyzed. The average EMCs for BOD, COD, ammonia, nitrate, TKN, hardness, TDS, TSS, chlorides, sulfates, phosphate, fluorides and TC were 21.82 mg/L, 73.48 mg/L, 72.68 μg/L, 229.87 μg/L, 15.32 μg/L, 11.36 mg/L, 117.44 mg/L, 77.60 mg/L, 117.64 mg/L, 135.82 mg/L, 0.08 mg/L, 0.85 mg/L and 2,827.47 MPN/100 mL, respectively. The EMCs of TSS, nitrogen and its compounds, phosphate and BOD were high.
Fauvel, Blandine; Cauchie, Henry-Michel; Gantzer, Christophe; Ogorzaly, Leslie
2016-05-01
Heavy rainfall events were previously reported to bring large amounts of microorganisms in surface water, including viruses. However, little information is available on the origin and transport of viral particles in water during such rain events. In this study, an integrative approach combining microbiological and hydrological measurements was investigated to appreciate the dynamics and origins of F-specific RNA bacteriophage fluxes during two distinct rainfall-runoff events. A high frequency sampling (automatic sampler) was set up to monitor the F-specific RNA bacteriophages fluxes at a fine temporal scale during the whole course of the rainfall-runoff events. A total of 276 rainfall-runoff samples were collected and analysed using both infectivity and RT-qPCR assays. The results highlight an increase of 2.5 log10 and 1.8 log10 of infectious F-specific RNA bacteriophage fluxes in parallel of an increase of the water flow levels for both events. Faecal pollution was characterised as being mainly from anthropic origin with a significant flux of phage particles belonging to the genogroup II. At the temporal scale, two successive distinct waves of phage pollution were established and identified through the hydrological measurements. The first arrival of phages in the water column was likely to be linked to the resuspension of riverbed sediments that was responsible for a high input of genogroup II. Surface runoff contributed further to the second input of phages, and more particularly of genogroup I. In addition, an important contribution of infectious phage particles has been highlighted. These findings imply the existence of a close relationship between the risk for human health and the viral contamination of flood water. Copyright © 2016 Luxembourg institute of Science and Technology. Published by Elsevier Ltd.. All rights reserved.
Optimal design of unit hydrographs using probability distribution and ...
Indian Academy of Sciences (India)
R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22
optimization formulation is solved using binary-coded genetic algorithms. The number of variables to ... Unit hydrograph; rainfall-runoff; hydrology; genetic algorithms; optimization; probability ..... Application of the model. Data derived from the ...
Bhattarai, K. P.; O'Connor, K. M.
2003-04-01
Inefficient natural land drainage and the consequent frequent flooding of rivers are a problem of particular significance to the Irish economy. Such problems can be attributed less to the amount of annual rainfall, than to the topological configuration of Ireland. Its high maritime rim and relatively flat interior results in poor river gradients, intercepted by many lakes. As a remedial measure to tackle these problems, Arterial Drainage Schemes (ADSs) were started in Ireland from as early as the beginning of the nineteenth century. The major activities carried out under ADSs have been the deepening and widening of channels to increase their discharge-carrying capacity, which naturally affected the hydrological behaviour of the catchments involved. Earlier studies carried out in order to assess the effects of such ADSs on the hydrological behaviour of Irish catchments were concentrated mainly on comparisons of unit hydrographs and relationship between flood peaks of pre- and post-drainage periods. The present study, carried out on the River Brosna catchment in Ireland, concentrates on assessing the changes in the rainfall runoff transformation process, by using the conceptual Soil Moisture Accounting and Routing Model (SMAR), one of the constituent models of the "Galway River Flow Modelling and Forecasting System (GFMFS)" software package. Hydro-meteorological data of the pre-drainage (1942--1947) and post-drainage (1954--2000) periods have been used in this study. The results of the present study show that, for similar patterns of rainfall, the catchment produces higher annual maximum daily flows, and lower annual minimum daily flows in the post-drainage period than in the pre-drainage period. Moreover, the post-drainage unit hydrographs are more "peaky" and have quicker recessions than the pre-drainage counterparts, thus confirming the findings of the earlier studies. It is also observed that, apart from the expected pre-to-post-drainage change, the nature of the
Schwab, Michael; Klaus, Julian; Pfister, Laurent; Weiler, Markus
2015-04-01
Over the past decades, stream sampling protocols for environmental tracers were often limited by logistical and technological constraints. Long-term sampling programs would typically rely on weekly sampling campaigns, while high-frequency sampling would remain restricted to a few days or hours at best. We stipulate that the currently predominant sampling protocols are too coarse to capture and understand the full amplitude of rainfall-runoff processes and its relation to water quality fluctuations. Weekly sampling protocols are not suited to get insights into the hydrological system during high flow conditions. Likewise, high frequency measurements of a few isolated events do not allow grasping inter-event variability in contributions and processes. Our working hypothesis is based on the potential of a new generation of field-deployable instruments for measuring environmental tracers at high temporal frequencies over an extended period. With this new generation of instruments we expect to gain new insights into rainfall-runoff dynamics, both at intra- and inter-event scales. Here, we present the results of one year of DOC and nitrate measurements with the field deployable UV-Vis spectrometer spectro::lyser (scan Messtechnik GmbH). The instrument measures the absorption spectrum from 220 to 720 nm in situ and at high frequencies and derives DOC and nitrate concentrations. The measurements were carried out at 15 minutes intervals in the Weierbach catchment (0.47 km2) in Luxemburg. This fully forested catchment is characterized by cambisol soils and fractured schist as underlying bedrock. The time series of DOC and nitrate give insights into the high frequency dynamics of stream water. Peaks in DOC concentrations are closely linked to discharge peaks that occur during or right after a rainfall event. Those first discharge peaks can be linked to fast near surface runoff processes and are responsible for a remarkable amount of DOC export. A special characterisation of
Kinoshita, A. M.; Hale, B.; Hogue, T. S.
2012-12-01
Post-fire management decisions are guided by rainfall-runoff predictions, which ultimately influence downstream treatment and mitigation costs. The current study investigates evolving rainfall-runoff partitioning at the watershed scale over a two-year period after the 2010 Bull Fire which occurred in the southern Sequoia National Forest in California. Stage height was measured at five-minute intervals using pressure transducers, tipping buckets were installed for rainfall duration and intensity, and channel cross-sections were measured approximately every two months to detail sediment deposition or scour. We also utilize remotely sensed vegetation data to evaluate vegetation recovery in the studied watersheds and the corresponding relationship to storm runoff. Normalized Difference Vegetation Index (NDVI), a measure of vegetation greenness, is evaluated for its potential use as a key recovery indicator. Preliminary results focus on alterations in annual and seasonal precipitation and discharge relationships using in-situ data and Landsat NDVI values for the period of study. NDVI values are consistent with a comprehensive burn, with an acute decrease observed in the initial post-fire period. However, vegetation recovery is highly variable in the studied systems and influenced by shorter-term biomass pulses (grasses) while longer-term recovery of other species (chaparral and pine) is ongoing. Runoff ratios are elevated during early storms and show some recovery in the later part of the study period. The ability to accurately and confidently predict post-fire runoff and longer-term recovery is critical for monitoring values-at-risk, reducing mitigation costs, and improving warnings to downstream public communities.
de Hamer, W.; Love, D.; Booij, Martijn J.; Hoekstra, Arjen Ysbert
2007-01-01
In semi‐arid regions, small artificial surface reservoirs are important to meet the domestic and agricultural water requirements of smallholder farmers. The research objective of the study was to determine the rainfall‐runoff relation of two ungauged rivers using the measured water levels of the
Suseno, Dwi Prabowo Yuga
2013-01-01
The availability of rainfall triggered hazard information such as flash flood is crucial in the flood disaster management and mitigation. However, providing that information is mainly hampered by the shortage of data because of the sparse, uneven or absence the hydrological or meteorological observation. Remote sensing techniques that make frequent observations with continuous spatial coverage provide useful information for detecting the hydrometeorological phenomena such as rainfall and floo...
Directory of Open Access Journals (Sweden)
Le Bihan Guillaume
2016-01-01
Full Text Available Flash floods monitoring systems developed up to now generally enable a real-time assessment of the potential flash-floods magnitudes based on highly distributed hydrological models and weather radar records. The approach presented here aims to go one step ahead by offering a direct assessment of the potential impacts of flash floods on inhabited areas. This approach is based on an a priori analysis of the considered area in order (1 to evaluate based on a semi-automatic hydraulic approach (Cartino method the potentially flooded areas for different discharge levels, and (2 to identify the associated buildings and/or population at risk based on geographic databases. This preliminary analysis enables to build a simplified impact model (discharge-impact curve for each river reach, which can be used to directly estimate the importance of potentially affected assets based on the outputs of a distributed rainfall-runoff model. This article presents a first case study conducted in the Gard region (south eastern France. The first validation results are presented in terms of (1 accuracy of the delineation of the flooded areas estimated based on the Cartino method and using a high resolution DTM, and (2 relevance and usefulness of the impact model obtained. The impacts estimated at the event scale will now be evaluated in a near future based on insurance claim data provided by CCR (Caisse Centrale de Réassurrance.
Laiolo, Paola; Gabellani, Simone; Campo, Lorenzo; Cenci, Luca; Silvestro, Francesco; Delogu, Fabio; Boni, Giorgio; Rudari, Roberto
2015-04-01
The reliable estimation of hydrological variables (e.g. soil moisture, evapotranspiration, surface temperature) in space and time is of fundamental importance in operational hydrology to improve the forecast of the rainfall-runoff response of catchments and, consequently, flood predictions. Nowadays remote sensing can offer a chance to provide good space-time estimates of several hydrological variables and then improve hydrological model performances especially in environments with scarce in-situ data. This work investigates the impact of the assimilation of different remote sensing products on the hydrological cycle by using a continuous physically based distributed hydrological model. Three soil moisture products derived by ASCAT (Advanced SCATterometer) are used to update the model state variables. The satellite-derived products are assimilated into the hydrological model using different assimilation techniques: a simple nudging and the Ensemble Kalman Filter. Moreover two assimilation strategies are evaluated to assess the impact of assimilating the satellite products at model spatial resolution or at the satellite scale. The experiments are carried out for three Italian catchments on multi year period. The benefits on the model predictions of discharge, LST, evapotranspiration and soil moisture dynamics are tested and discussed.
Worqlul, Abeyou W.; Ayana, Essayas K.; Maathuis, Ben H. P.; MacAlister, Charlotte; Philpot, William D.; Osorio Leyton, Javier M.; Steenhuis, Tammo S.
2018-01-01
In many developing countries and remote areas of important ecosystems, good quality precipitation data are neither available nor readily accessible. Satellite observations and processing algorithms are being extensively used to produce satellite rainfall products (SREs). Nevertheless, these products are prone to systematic errors and need extensive validation before to be usable for streamflow simulations. In this study, we investigated and corrected the bias of Multi-Sensor Precipitation Estimate-Geostationary (MPEG) data. The corrected MPEG dataset was used as input to a semi-distributed hydrological model Hydrologiska Byråns Vattenbalansavdelning (HBV) for simulation of discharge of the Gilgel Abay and Gumara watersheds in the Upper Blue Nile basin, Ethiopia. The result indicated that the MPEG satellite rainfall captured 81% and 78% of the gauged rainfall variability with a consistent bias of underestimating the gauged rainfall by 60%. A linear bias correction applied significantly reduced the bias while maintaining the coefficient of correlation. The simulated flow using bias corrected MPEG SRE resulted in a simulated flow comparable to the gauge rainfall for both watersheds. The study indicated the potential of MPEG SRE in water budget studies after applying a linear bias correction.
Puente, Celso; Atkins, John T.
1989-01-01
the water budget for Drawdy Creek basin indicate that total annual runoff during 1972-73 averaged only 43 percent of average annual precipitation--the lowest of all study basins; annual evapotranspiration losses averaged 49 percent, and interbasin transfer of ground-water losses averaged about 8 percent. Of the total annual runoff, approximately 74 percent was surface and subsurface flow and 26 percent was ground-water discharge. The low total annual runoff at Drawdy Creek probably reflects increased recharge of precipitation and surface and subsurface flow losses to ground water. Most of the increase in ground-water storage is, in turn, lost to a ground-water sink--namely, interbasin transfer of ground water by gravity drainage and (or) mine pumpage from underground mines that extend to adjacent basins. Hypothetical mining situations were posed for model analysis to determine the effects of increased mining on streamflow in the mined basins. Results of model simulations indicate that streamflow characteristics, the water budget, and the seasonal distribution of streamflow would be significantly modified in response to an increase in mining in the basins. Simulations indicate that (1) total annual runoff in the basins would decrease because of increased surface- and subsurface-flow losses and increased recharge of precipitation to ground water (these losses would tend to reduce medium to high flows mainly during winter and spring when losses would be greatest), (2) extreme high flows in response to intense rainstorms would be negligibly affected, regardless of the magnitude of mining in the basins, (3) ground-water discharge also would decrease during winter and spring, but the amount and duration of low flows during summer and fall would substantially increase in response to increased ground-water storage in rocks and in underground mines, and (4) the increase in ground-water storage in the basins would be depleted, mostly by increased losses to a grou
Guerrero, J.; Halldin, S.; Xu, C.; Lundin, L.
2011-12-01
Distributed hydrological models are important tools in water management as they account for the spatial variability of the hydrological data, as well as being able to produce spatially distributed outputs. They can directly incorporate and assess potential changes in the characteristics of our basins. A recognized problem for models in general is equifinality, which is only exacerbated for distributed models who tend to have a large number of parameters. We need to deal with the fundamentally ill-posed nature of the problem that such models force us to face, i.e. a large number of parameters and very few variables that can be used to constrain them, often only the catchment discharge. There is a growing but yet limited literature showing how the internal states of a distributed model can be used to calibrate/validate its predictions. In this paper, a distributed version of WASMOD, a conceptual rainfall runoff model with only three parameters, combined with a routing algorithm based on the high-resolution HydroSHEDS data was used to simulate the discharge in the Paso La Ceiba basin in Honduras. The parameter space was explored using Monte-Carlo simulations and the region of space containing the parameter-sets that were considered behavioral according to two different criteria was delimited using the geometric concept of alpha-shapes. The discharge data from five internal sub-basins was used to aid in the calibration of the model and to answer the following questions: Can this information improve the simulations at the outlet of the catchment, or decrease their uncertainty? Also, after reducing the number of model parameters needing calibration through sensitivity analysis: Is it possible to relate them to basin characteristics? The analysis revealed that in most cases the internal discharge data can be used to reduce the uncertainty in the discharge at the outlet, albeit with little improvement in the overall simulation results.
Directory of Open Access Journals (Sweden)
Hui Wan
2015-06-01
Full Text Available Sensitivity analysis is a fundamental approach to identify the most significant and sensitive parameters, helping us to understand complex hydrological models, particularly for time-consuming distributed flood forecasting models based on complicated theory with numerous parameters. Based on Sobol’ method, this study compared the sensitivity and interactions of distributed flood forecasting model parameters with and without accounting for correlation. Four objective functions: (1 Nash–Sutcliffe efficiency (ENS; (2 water balance coefficient (WB; (3 peak discharge efficiency (EP; and (4 time to peak efficiency (ETP were implemented to the Liuxihe model with hourly rainfall-runoff data collected in the Nanhua Creek catchment, Pearl River, China. Contrastive results for the sensitivity and interaction analysis were also illustrated among small, medium, and large flood magnitudes. Results demonstrated that the choice of objective functions had no effect on the sensitivity classification, while it had great influence on the sensitivity ranking for both uncorrelated and correlated cases. The Liuxihe model behaved and responded uniquely to various flood conditions. The results also indicated that the pairwise parameters interactions revealed a non-ignorable contribution to the model output variance. Parameters with high first or total order sensitivity indices presented a corresponding high second order sensitivity indices and correlation coefficients with other parameters. Without considering parameter correlations, the variance contributions of highly sensitive parameters might be underestimated and those of normally sensitive parameters might be overestimated. This research laid a basic foundation to improve the understanding of complex model behavior.
Krajewski, W. F.; Della Libera Zanchetta, A.; Mantilla, R.; Demir, I.
2017-12-01
This work explores the use of hydroinformatics tools to provide an user friendly and accessible interface for executing and assessing the output of realtime flood forecasts using distributed hydrological models. The main result is the implementation of a web system that uses an Iowa Flood Information System (IFIS)-based environment for graphical displays of rainfall-runoff simulation results for both real-time and past storm events. It communicates with ASYNCH ODE solver to perform large-scale distributed hydrological modeling based on segmentation of the terrain into hillslope-link hydrologic units. The cyber-platform also allows hindcast of model performance by testing multiple model configurations and assumptions of vertical flows in the soils. The scope of the currently implemented system is the entire set of contributing watersheds for the territory of the state of Iowa. The interface provides resources for visualization of animated maps for different water-related modeled states of the environment, including flood-waves propagation with classification of flood magnitude, runoff generation, surface soil moisture and total water column in the soil. Additional tools for comparing different model configurations and performing model evaluation by comparing to observed variables at monitored sites are also available. The user friendly interface has been published to the web under the URL http://ifis.iowafloodcenter.org/ifis/sc/modelplus/.
Deshmukh, Dhananjay Suresh; Chaube, Umesh Chandra; Ekube Hailu, Ambaye; Aberra Gudeta, Dida; Tegene Kassa, Melaku
2013-06-01
The CN represents runoff potential is estimated using three different methods for three watersheds namely Barureva, Sher and Umar watershed located in Narmada basin. Among three watersheds, Sher watershed has gauging site for the runoff measurements. The CN computed from the observed rainfall-runoff events is termed as CN(PQ), land use and land cover (LULC) is termed as CN(LU) and the CN based on land slope is termed as SACN2. The estimated annual CN(PQ) varies from 69 to 87 over the 26 years data period with median 74 and average 75. The range of CN(PQ) from 70 to 79 are most significant values and these truly represent the AMC II condition for the Sher watershed. The annual CN(LU) was computed for all three watersheds using GIS and the years are 1973, 1989 and 2000. Satellite imagery of MSS, TM and ETM+ sensors are available for these years and obtained from the Global Land Cover Facility Data Center of Maryland University USA. The computed CN(LU) values show rising trend with the time and this trend is attributed to expansion of agriculture area in all watersheds. The predicted values of CN(LU) with time (year) can be used to predict runoff potential under the effect of change in LULC. Comparison of CN(LU) and CN(PQ) values shows close agreement and it also validates the classification of LULC. The estimation of slope adjusted SA-CN2 shows the significant difference over conventional CN for the hilly forest lands. For the micro watershed planning, SCS-CN method should be modified to incorporate the effect of change in land use and land cover along with effect of land slope.
Flash flood modeling with the MARINE hydrological distributed model
Estupina-Borrell, V.; Dartus, D.; Ababou, R.
2006-11-01
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
Analysis of flood events on small river catchments using the KINFIL model
Czech Academy of Sciences Publication Activity Database
Kovář, P.; Cudlín, Pavel; Heřman, Michal; Zemek, František; Korytář, M.
2002-01-01
Roč. 50, č. 2 (2002), s. 157-171 ISSN 0042-790X Institutional research plan: CEZ:AV0Z6087904 Keywords : Infiltration Approach * Kinematic Wave * Rainfall-Runoff Models Subject RIV: DA - Hydrology ; Limnology
Oulad Naoui Noureddine; Cherif ELAmine; Djehiche Abdelkader
2017-01-01
Water resources management includes several disciplines; the modeling of rainfall-runoff relationship is the most important discipline to prevent natural risks. There are several models to study rainfall-runoff relationship in watersheds. However, the majority of these models are not applicable in all basins of the world. In this study, a new stochastic method called The Only Corresponding Competitor method (OCC) was used for the hydrological modeling of M’ZAB Watershed (South East of Alge...
Segura, C.; Nickolas, L. B.; Leshchinsky, B. A.
2015-12-01
Even though it is widely recognized that water quality and availability are crucial to society and wildlife sustainability, we are still not able to predict how much water is moved through a given catchment after a storm event nor what nutrients, solutes, and contaminates are mobilized. We will present preliminary results of a study incorporating of hydrometric information, water stable isotopes (δ18O), and concentrations of total nitrogen (TN), ammonia (NH3), and nitrate (NO3) within 4 sites in a nested framework at the HJ Andrews Experimental Forest (HJA), OR. Preliminary analysis of 2 storms (54mm and 145mm) indicate highly variable responses across space along with a positive relation between transit time of event water and storm magnitude in all catchments. In addition there appears to be a moisture threshold after which transit time scales with drainage area across the landscape likely related to higher degree of connectivity. We also found a strong correlation between transit times computed based on temporal variability of δ18O and electrical connectivity (EC). This lead to the analysis of over 50 storm across 10 catchments in the HJA during the last 3 years. In-stream NO3- during storm response are highest within the smaller catchments (1-5 km2) and tend to remain elevated throughout the response period. The larger catchments (15-64 km2) demonstrate smaller increases in NO3-, the response time lags behind that of the smaller catchments, and the concentration returns rapidly to baseflow conditions rather than remaining elevated. In contrast, in-stream NH3 show a higher degree of similarity between sites in terms of magnitude and timing of increases in concentration over the duration of the response period. Ultimately we found that fractions of inorganic nitrogen correlate with transit time and drainage area, opening the possibility of a catchment wide model of nutrient export prediction.
Estimating Runoff From Roadcuts With a Distributed Hydrologic Model
Cuhaciyan, C.; Luce, C.; Voisin, N.; Lettenmaier, D.; Black, T.
2008-12-01
Roads can have a substantial effect on hydrologic patterns of forested watersheds; the most noteworthy being the resurfacing of shallow groundwater at roadcuts. The influence of roads on hydrology has compelled hydrologists to include water routing and storage routines in rainfall-runoff models, such as those in the Distributed Hydrologic Soil Vegetation Model (DHSVM). We tested the ability of DHSVM to match observed runoff in roadcuts of a watershed in the Coast Range of Oregon. Eight roadcuts were instrumented using large tipping bucket gauges designed to capture only the water entering the roadside ditch from an 80-m long roadcut. The roadcuts were categorized by the topography of the upstream hillside as either swale, planar, or ridge. The simulation was run from December 2002 to December 2003 at a relatively fine spatial resolution (10-m). Average observed soil depths are 1.8-m across the watershed, below which there lies deep and highly weathered sandstone. DHSVM was designed for relatively impermeable bedrock and shallow soils; therefore it does not provide a mechanism for deep groundwater movement and storage. In the geologic setting of the study basin, however, water is routed through the sandstone allowing water to pass under roads through the parent material. For this reason a uniformly deep soil of 6.5-m with a decreased decay in conductivity with depth was used in the model to allow water to be routed beneath roadcuts that are up to 5.5-m in height. Up to three, typically shallow, soil layers can be modeled in DHSVM. We used the lowest of the three soil layers to mimic the hydraulically-well-connected sandstone exposed at deeper roadcuts. The model was calibrated against observed discharge at the outlet of the watershed. While model results closely matched the observed hydrograph at the watershed outlet, simulated runoff at an upstream gauge and the roadside ditches were varied and often higher than those observed in the field. The timing of the field
Bartlett, M. S.; Parolari, A. J.; McDonnell, J. J.; Porporato, A.
2016-09-01
Hydrologists and engineers may choose from a range of semidistributed rainfall-runoff models such as VIC, PDM, and TOPMODEL, all of which predict runoff from a distribution of watershed properties. However, these models are not easily compared to event-based data and are missing ready-to-use analytical expressions that are analogous to the SCS-CN method. The SCS-CN method is an event-based model that describes the runoff response with a rainfall-runoff curve that is a function of the cumulative storm rainfall and antecedent wetness condition. Here we develop an event-based probabilistic storage framework and distill semidistributed models into analytical, event-based expressions for describing the rainfall-runoff response. The event-based versions called VICx, PDMx, and TOPMODELx also are extended with a spatial description of the runoff concept of "prethreshold" and "threshold-excess" runoff, which occur, respectively, before and after infiltration exceeds a storage capacity threshold. For total storm rainfall and antecedent wetness conditions, the resulting ready-to-use analytical expressions define the source areas (fraction of the watershed) that produce runoff by each mechanism. They also define the probability density function (PDF) representing the spatial variability of runoff depths that are cumulative values for the storm duration, and the average unit area runoff, which describes the so-called runoff curve. These new event-based semidistributed models and the traditional SCS-CN method are unified by the same general expression for the runoff curve. Since the general runoff curve may incorporate different model distributions, it may ease the way for relating such distributions to land use, climate, topography, ecology, geology, and other characteristics.
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W. Castaings
2009-04-01
Full Text Available Variational methods are widely used for the analysis and control of computationally intensive spatially distributed systems. In particular, the adjoint state method enables a very efficient calculation of the derivatives of an objective function (response function to be analysed or cost function to be optimised with respect to model inputs.
In this contribution, it is shown that the potential of variational methods for distributed catchment scale hydrology should be considered. A distributed flash flood model, coupling kinematic wave overland flow and Green Ampt infiltration, is applied to a small catchment of the Thoré basin and used as a relatively simple (synthetic observations but didactic application case.
It is shown that forward and adjoint sensitivity analysis provide a local but extensive insight on the relation between the assigned model parameters and the simulated hydrological response. Spatially distributed parameter sensitivities can be obtained for a very modest calculation effort (~6 times the computing time of a single model run and the singular value decomposition (SVD of the Jacobian matrix provides an interesting perspective for the analysis of the rainfall-runoff relation.
For the estimation of model parameters, adjoint-based derivatives were found exceedingly efficient in driving a bound-constrained quasi-Newton algorithm. The reference parameter set is retrieved independently from the optimization initial condition when the very common dimension reduction strategy (i.e. scalar multipliers is adopted.
Furthermore, the sensitivity analysis results suggest that most of the variability in this high-dimensional parameter space can be captured with a few orthogonal directions. A parametrization based on the SVD leading singular vectors was found very promising but should be combined with another regularization strategy in order to prevent overfitting.
Guzmán, Enrique; Aguilar, Cristina; Taguas, Encarnación V.
2014-05-01
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.
Shokri, Ali
2017-04-01
The hydrological cycle contains a wide range of linked surface and subsurface flow processes. In spite of natural connections between surface water and groundwater, historically, these processes have been studied separately. The current trend in hydrological distributed physically based model development is to combine distributed surface water models with distributed subsurface flow models. This combination results in a better estimation of the temporal and spatial variability of the interaction between surface and subsurface flow. On the other hand, simple lumped models such as the Soil Conservation Service Curve Number (SCS-CN) are still quite common because of their simplicity. In spite of the popularity of the SCS-CN method, there have always been concerns about the ambiguity of the SCS-CN method in explaining physical mechanism of rainfall-runoff processes. The aim of this study is to minimize these ambiguity by establishing a method to find an equivalence of the SCS-CN solution to the DrainFlow model, which is a fully distributed physically based coupled surface-subsurface flow model. In this paper, two hypothetical v-catchment tests are designed and the direct runoff from a storm event are calculated by both SCS-CN and DrainFlow models. To find a comparable solution to runoff prediction through the SCS-CN and DrainFlow, the variance between runoff predictions by the two models are minimized by changing Curve Number (CN) and initial abstraction (Ia) values. Results of this study have led to a set of lumped model parameters (CN and Ia) for each catchment that is comparable to a set of physically based parameters including hydraulic conductivity, Manning roughness coefficient, ground surface slope, and specific storage. Considering the lack of physical interpretation in CN and Ia is often argued as a weakness of SCS-CN method, the novel method in this paper gives a physical explanation to CN and Ia.
Mockler, E. M.; Chun, K. P.; Sapriza-Azuri, G.; Bruen, M.; Wheater, H. S.
2016-11-01
Predictions of river flow dynamics provide vital information for many aspects of water management including water resource planning, climate adaptation, and flood and drought assessments. Many of the subjective choices that modellers make including model and criteria selection can have a significant impact on the magnitude and distribution of the output uncertainty. Hydrological modellers are tasked with understanding and minimising the uncertainty surrounding streamflow predictions before communicating the overall uncertainty to decision makers. Parameter uncertainty in conceptual rainfall-runoff models has been widely investigated, and model structural uncertainty and forcing data have been receiving increasing attention. This study aimed to assess uncertainties in streamflow predictions due to forcing data and the identification of behavioural parameter sets in 31 Irish catchments. By combining stochastic rainfall ensembles and multiple parameter sets for three conceptual rainfall-runoff models, an analysis of variance model was used to decompose the total uncertainty in streamflow simulations into contributions from (i) forcing data, (ii) identification of model parameters and (iii) interactions between the two. The analysis illustrates that, for our subjective choices, hydrological model selection had a greater contribution to overall uncertainty, while performance criteria selection influenced the relative intra-annual uncertainties in streamflow predictions. Uncertainties in streamflow predictions due to the method of determining parameters were relatively lower for wetter catchments, and more evenly distributed throughout the year when the Nash-Sutcliffe Efficiency of logarithmic values of flow (lnNSE) was the evaluation criterion.
Soulsby, C.; Kuppel, S.; Smith, A.; Tetzlaff, D.
2017-12-01
The dynamics of water storage in a catchment provides a fundamental insight into the interlinkages between input and output fluxes, and how these are affected by environmental change. Such dynamics also mediate, and help us understand, the fundamental difference of the rapid celerity of the rainfall-runoff (minutes to hours) response of catchments and the much slower velocity of water particles (months to decades) as they are transported through catchment systems. In this contribution we report an intensive, long-term (>10year), multi-scale isotope study in the Scottish Highlands that has sought to better understand these issues. We have integrated empirical data collection with diverse modelling approaches to quantify the dynamics and residence times of storage in different compartments of the hydrological system (vegetation canopies, soils, ground waters etc.) and their relationship between the magnitude and travel time distributions of output fluxes (stream flow, transpiration and evaporation). Use of conceptual, physically-based and probabilistic modelling approaches give broadly consistent perspectives on the storage-discharge relationships and the preferential selection of younger waters in runoff, evaporation and transpiration; while older waters predominate in groundwater. The work also highlighted the importance role vegetation plays in regulating fluxes in evaporation and transpiration and how this contributes to the differential ageing of water in mobile and bulk waters in the soil compartment. A separate case study shows how land use change can affect storage distributions in a catchment and radically change travel time distributions in output fluxes.
Caviedes-Voullième, Daniel; García-Navarro, Pilar; Murillo, Javier
2012-07-01
SummaryHydrological simulation of rain-runoff processes is often performed with lumped models which rely on calibration to generate storm hydrographs and study catchment response to rain. In this paper, a distributed, physically-based numerical model is used for runoff simulation in a mountain catchment. This approach offers two advantages. The first is that by using shallow-water equations for runoff flow, there is less freedom to calibrate routing parameters (as compared to, for example, synthetic hydrograph methods). The second, is that spatial distributions of water depth and velocity can be obtained. Furthermore, interactions among the various hydrological processes can be modeled in a physically-based approach which may depend on transient and spatially distributed factors. On the other hand, the undertaken numerical approach relies on accurate terrain representation and mesh selection, which also affects significantly the computational cost of the simulations. Hence, we investigate the response of a gauged catchment with this distributed approach. The methodology consists of analyzing the effects that the mesh has on the simulations by using a range of meshes. Next, friction is applied to the model and the response to variations and interaction with the mesh is studied. Finally, a first approach with the well-known SCS Curve Number method is studied to evaluate its behavior when coupled with a shallow-water model for runoff flow. The results show that mesh selection is of great importance, since it may affect the results in a magnitude as large as physical factors, such as friction. Furthermore, results proved to be less sensitive to roughness spatial distribution than to mesh properties. Finally, the results indicate that SCS-CN may not be suitable for simulating hydrological processes together with a shallow-water model.
Hierarchical species distribution models
Hefley, Trevor J.; Hooten, Mevin B.
2016-01-01
Determining the distribution pattern of a species is important to increase scientific knowledge, inform management decisions, and conserve biodiversity. To infer spatial and temporal patterns, species distribution models have been developed for use with many sampling designs and types of data. Recently, it has been shown that count, presence-absence, and presence-only data can be conceptualized as arising from a point process distribution. Therefore, it is important to understand properties of the point process distribution. We examine how the hierarchical species distribution modeling framework has been used to incorporate a wide array of regression and theory-based components while accounting for the data collection process and making use of auxiliary information. The hierarchical modeling framework allows us to demonstrate how several commonly used species distribution models can be derived from the point process distribution, highlight areas of potential overlap between different models, and suggest areas where further research is needed.
Surrogate modeling of joint flood risk across coastal watersheds
Bass, Benjamin; Bedient, Philip
2018-03-01
This study discusses the development and performance of a rapid prediction system capable of representing the joint rainfall-runoff and storm surge flood response of tropical cyclones (TCs) for probabilistic risk analysis. Due to the computational demand required for accurately representing storm surge with the high-fidelity ADvanced CIRCulation (ADCIRC) hydrodynamic model and its coupling with additional numerical models to represent rainfall-runoff, a surrogate or statistical model was trained to represent the relationship between hurricane wind- and pressure-field characteristics and their peak joint flood response typically determined from physics based numerical models. This builds upon past studies that have only evaluated surrogate models for predicting peak surge, and provides the first system capable of probabilistically representing joint flood levels from TCs. The utility of this joint flood prediction system is then demonstrated by improving upon probabilistic TC flood risk products, which currently account for storm surge but do not take into account TC associated rainfall-runoff. Results demonstrate the source apportionment of rainfall-runoff versus storm surge and highlight that slight increases in flood risk levels may occur due to the interaction between rainfall-runoff and storm surge as compared to the Federal Emergency Management Association's (FEMAs) current practices.
Ala-aho, P. O. A.; Tetzlaff, D.; Laudon, H.; McNamara, J. P.; Soulsby, C.
2016-12-01
We use the Spatially distributed Tracer-Aided Rainfall-Runoff (STARR) modelling framework to explore non-stationary flow and isotope response in three northern headwater catchments. The model simulates dynamic, spatially variable tracer concentration in different water stores and fluxes within a catchment, which can constrain internal catchment mixing processes, flow paths and associated water ages. To date, a major limitation in using such models in snow-dominated catchments has been the difficulties in paramaterising the isotopic transformations in snowpack accumulation and melt. We use high quality long term datasets for hydrometrics and stable water isotopes collected in three northern study catchments for model calibration and testing. The three catchments exhibit different hydroclimatic conditions, soil and vegetation types, and topographic relief, which brings about variable degree of snow dominance across the catchments. To account for the snow influence we develop novel formulations to estimate the isotope evolution in the snowpack and melt. Algorithms for the isotopic evolution parameterize an isotopic offset between snow evaporation and melt fluxes and the remaining snow storage. The model for each catchment is calibrated to match both streamflow and tracer concentration at the stream outlet to ensure internal consistency of the system behaviour. The model is able to reproduce the streamflow along with the spatio-temporal differences in tracer concentrations across the three studies catchments reasonably well. Incorporating the spatially distributed snowmelt processes and associated isotope transformations proved essential in capturing the stream tracer reponse for strongly snow-influenced cathments. This provides a transferrable tool which can be used to understand spatio-temporal variability of mixing and water ages for different storages and flow paths in other snow influenced, environments.
Porto, P.; Cogliandro, V.; Callegari, G.
2018-01-01
In this paper, long-term sediment yield data, collected in a small (1.38 ha) Calabrian catchment (W2), reafforested with eucalyptus trees (Eucalyptus occidentalis Engl.) are used to validate the performance of the SEdiment Delivery Distributed Model (SEDD) in areas with high erosion rates. At first step, the SEDD model was calibrated using field data collected in previous field campaigns undertaken during the period 1978-1994. This first phase allowed the model calibration parameter β to be calculated using direct measurements of rainfall, runoff, and sediment output. The model was then validated in its calibrated form for an independent period (2006-2016) for which new measurements of rainfall, runoff and sediment output are also available. The analysis, carried out at event and annual scale showed good agreement between measured and predicted values of sediment yield and suggested that the SEDD model can be seen as an appropriate means of evaluating erosion risk associated with manmade plantations in marginal areas. Further work is however required to test the performance of the SEDD model as a prediction tool in different geomorphic contexts.
Lee, H.; Seo, D.-J.; Liu, Y.; Koren, V.; McKee, P.; Corby, R.
2012-01-01
State updating of distributed rainfall-runoff models via streamflow assimilation is subject to overfitting because large dimensionality of the state space of the model may render the assimilation problem seriously under-determined. To examine the issue in the context of operational hydrology, we carry out a set of real-world experiments in which streamflow data is assimilated into gridded Sacramento Soil Moisture Accounting (SAC-SMA) and kinematic-wave routing models of the US National Weather Service (NWS) Research Distributed Hydrologic Model (RDHM) with the variational data assimilation technique. Study basins include four basins in Oklahoma and five basins in Texas. To assess the sensitivity of data assimilation performance to dimensionality reduction in the control vector, we used nine different spatiotemporal adjustment scales, where state variables are adjusted in a lumped, semi-distributed, or distributed fashion and biases in precipitation and potential evaporation (PE) are adjusted hourly, 6-hourly, or kept time-invariant. For each adjustment scale, three different streamflow assimilation scenarios are explored, where streamflow observations at basin interior points, at the basin outlet, or at both interior points and the outlet are assimilated. The streamflow assimilation experiments with nine different basins show that the optimum spatiotemporal adjustment scale varies from one basin to another and may be different for streamflow analysis and prediction in all of the three streamflow assimilation scenarios. The most preferred adjustment scale for seven out of nine basins is found to be the distributed, hourly scale, despite the fact that several independent validation results at this adjustment scale indicated the occurrence of overfitting. Basins with highly correlated interior and outlet flows tend to be less sensitive to the adjustment scale and could benefit more from streamflow assimilation. In comparison to outlet flow assimilation, interior flow
Bounding species distribution models
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Thomas J. STOHLGREN, Catherine S. JARNEVICH, Wayne E. ESAIAS,Jeffrey T. MORISETTE
2011-10-01
Full Text Available Species distribution models are increasing in popularity for mapping suitable habitat for species of management concern. Many investigators now recognize that extrapolations of these models with geographic information systems (GIS might be sensitive to the environmental bounds of the data used in their development, yet there is no recommended best practice for “clamping” model extrapolations. We relied on two commonly used modeling approaches: classification and regression tree (CART and maximum entropy (Maxent models, and we tested a simple alteration of the model extrapolations, bounding extrapolations to the maximum and minimum values of primary environmental predictors, to provide a more realistic map of suitable habitat of hybridized Africanized honey bees in the southwestern United States. Findings suggest that multiple models of bounding, and the most conservative bounding of species distribution models, like those presented here, should probably replace the unbounded or loosely bounded techniques currently used [Current Zoology 57 (5: 642–647, 2011].
Bounding Species Distribution Models
Stohlgren, Thomas J.; Jarnevich, Cahterine S.; Morisette, Jeffrey T.; Esaias, Wayne E.
2011-01-01
Species distribution models are increasing in popularity for mapping suitable habitat for species of management concern. Many investigators now recognize that extrapolations of these models with geographic information systems (GIS) might be sensitive to the environmental bounds of the data used in their development, yet there is no recommended best practice for "clamping" model extrapolations. We relied on two commonly used modeling approaches: classification and regression tree (CART) and maximum entropy (Maxent) models, and we tested a simple alteration of the model extrapolations, bounding extrapolations to the maximum and minimum values of primary environmental predictors, to provide a more realistic map of suitable habitat of hybridized Africanized honey bees in the southwestern United States. Findings suggest that multiple models of bounding, and the most conservative bounding of species distribution models, like those presented here, should probably replace the unbounded or loosely bounded techniques currently used [Current Zoology 57 (5): 642-647, 2011].
CSIR Research Space (South Africa)
Ayeni, AO
2012-11-01
Full Text Available literature (Adegbola, 1979; Oyenuga, 1967; Sobulo, 1985; Sonneveld, 1996; Iloeje, 2001; Aregheore, 2009). The monthly rainfall records of 28 years (1981 – 2008) for Asa, Owena, and Ogun basin were available for the study. As a result of challenges... is produced. The participation of the second author was made possible through the Young Researcher Establishment Fund (YREF), project number ECHS019, provided by the CSIR. References 1. Adegbola S. A. (1979): An Agricultural Atlas of Nigeria. University...
Vaginal drug distribution modeling.
Katz, David F; Yuan, Andrew; Gao, Yajing
2015-09-15
This review presents and applies fundamental mass transport theory describing the diffusion and convection driven mass transport of drugs to the vaginal environment. It considers sources of variability in the predictions of the models. It illustrates use of model predictions of microbicide drug concentration distribution (pharmacokinetics) to gain insights about drug effectiveness in preventing HIV infection (pharmacodynamics). The modeling compares vaginal drug distributions after different gel dosage regimens, and it evaluates consequences of changes in gel viscosity due to aging. It compares vaginal mucosal concentration distributions of drugs delivered by gels vs. intravaginal rings. Finally, the modeling approach is used to compare vaginal drug distributions across species with differing vaginal dimensions. Deterministic models of drug mass transport into and throughout the vaginal environment can provide critical insights about the mechanisms and determinants of such transport. This knowledge, and the methodology that obtains it, can be applied and translated to multiple applications, involving the scientific underpinnings of vaginal drug distribution and the performance evaluation and design of products, and their dosage regimens, that achieve it. Copyright © 2015 Elsevier B.V. All rights reserved.
Grimaldi, S.; Petroselli, A.; Romano, N.
2012-04-01
The Soil Conservation Service - Curve Number (SCS-CN) method is a popular rainfall-runoff model that is widely used to estimate direct runoff from small and ungauged basins. The SCS-CN is a simple and valuable approach to estimate the total stream-flow volume generated by a storm rainfall, but it was developed to be used with daily rainfall data. To overcome this drawback, we propose to include the Green-Ampt (GA) infiltration model into a mixed procedure, which is referred to as CN4GA (Curve Number for Green-Ampt), aiming to distribute in time the information provided by the SCS-CN method so as to provide estimation of sub-daily incremental rainfall excess. For a given storm, the computed SCS-CN total net rainfall amount is used to calibrate the soil hydraulic conductivity parameter of the Green-Ampt model. The proposed procedure was evaluated by analyzing 100 rainfall-runoff events observed in four small catchments of varying size. CN4GA appears an encouraging tool for predicting the net rainfall peak and duration values and has shown, at least for the test cases considered in this study, a better agreement with observed hydrographs than that of the classic SCS-CN method.
Coupling meteorological and hydrological models for flood forecasting
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Bartholmes
2005-01-01
Full Text Available This paper deals with the problem of analysing the coupling of meteorological meso-scale quantitative precipitation forecasts with distributed rainfall-runoff models to extend the forecasting horizon. Traditionally, semi-distributed rainfall-runoff models have been used for real time flood forecasting. More recently, increased computer capabilities allow the utilisation of distributed hydrological models with mesh sizes from tenths of metres to a few kilometres. On the other hand, meteorological models, providing the quantitative precipitation forecast, tend to produce average values on meshes ranging from slightly less than 10 to 200 kilometres. Therefore, to improve the quality of flood forecasts, the effects of coupling the meteorological and the hydrological models at different scales were analysed. A distributed hydrological model (TOPKAPI was developed and calibrated using a 1x1 km mesh for the case of the river Po closed at Ponte Spessa (catchment area c. 37000 km2. The model was then coupled with several other European meteorological models ranging from the Limited Area Models (provided by DMI and DWD with resolutions from 0.0625° * 0.0625°, to the ECMWF ensemble predictions with a resolution of 1.85° * 1.85°. Interesting results, describing the coupled model behaviour, are available for a meteorological extreme event in Northern Italy (Nov. 1994. The results demonstrate the poor reliability of the quantitative precipitation forecasts produced by meteorological models presently available; this is not resolved using the Ensemble Forecasting technique, when compared with results obtainable with measured rainfall.
International Nuclear Information System (INIS)
Stanzel, Ph; Haberl, U; Nachtnebel, H P
2008-01-01
Hydrological models for flood forecasting in Alpine basins need accurate representation of snow accumulation and snow melt processes. A continuous, semi-distributed rainfall-runoff model with snow modelling procedures using only precipitation and temperature as input is presented. Simulation results from an application in an Alpine Danube tributary watershed are shown and evaluated with snow depth measurements and MODIS remote sensing snow cover information. Seasonal variations of runoff due to snow melt were simulated accurately. Evaluation of simulated snow depth and snow covered area showed strengths and limitations of the model and allowed an assessment of input data quality. MODIS snow cover images were found to be valuable sources of information for hydrological modelling in alpine areas, where ground observations are scarce.
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Stanzel, Ph; Haberl, U; Nachtnebel, H P [Institute of Water Management, Hydrology and Hydraulic Engineering, University of Natural Resources and Applied Life Sciences, Muthgasse 18, 1190 Vienna (Austria)], E-mail: philipp.stanzel@boku.ac.at
2008-11-01
Hydrological models for flood forecasting in Alpine basins need accurate representation of snow accumulation and snow melt processes. A continuous, semi-distributed rainfall-runoff model with snow modelling procedures using only precipitation and temperature as input is presented. Simulation results from an application in an Alpine Danube tributary watershed are shown and evaluated with snow depth measurements and MODIS remote sensing snow cover information. Seasonal variations of runoff due to snow melt were simulated accurately. Evaluation of simulated snow depth and snow covered area showed strengths and limitations of the model and allowed an assessment of input data quality. MODIS snow cover images were found to be valuable sources of information for hydrological modelling in alpine areas, where ground observations are scarce.
Hydrological modelling in sandstone rocks watershed
Ponížilová, Iva; Unucka, Jan
2015-04-01
The contribution is focused on the modelling of surface and subsurface runoff in the Ploučnice basin. The used rainfall-runoff model is HEC-HMS comprising of the method of SCS CN curves and a recession method. The geological subsurface consisting of sandstone is characterised by reduced surface runoff and, on the contrary, it contributes to subsurface runoff. The aim of this paper is comparison of the rate of influence of sandstone on reducing surface runoff. The recession method for subsurface runoff was used to determine the subsurface runoff. The HEC-HMS model allows semi- and fully distributed approaches to schematisation of the watershed and rainfall situations. To determine the volume of runoff the method of SCS CN curves is used, which results depend on hydrological conditions of the soils. The rainfall-runoff model assuming selection of so-called methods of event of the SCS-CN type is used to determine the hydrograph and peak flow rate based on simulation of surface runoff in precipitation exceeding the infiltration capacity of the soil. The recession method is used to solve the baseflow (subsurface) runoff. The method is based on the separation of hydrograph to direct runoff and subsurface or baseflow runoff. The study area for the simulation of runoff using the method of SCS CN curves to determine the hydrological transformation is the Ploučnice basin. The Ploučnice is a hydrologically significant river in the northern part of the Czech Republic, it is a right tributary of the Elbe river with a total basin area of 1.194 km2. The average value of CN curves for the Ploučnice basin is 72. The geological structure of the Ploučnice basin is predominantly formed by Mesozoic sandstone. Despite significant initial loss of rainfall the basin response to the causal rainfall was demonstrated by a rapid rise of the surface runoff from the watershed and reached culmination flow. Basically, only surface runoff occures in the catchment during the initial phase of
Energy Technology Data Exchange (ETDEWEB)
Kivva, S.; Zheleznyak, M. [Institute of Environmental Radioactivity, Fukushima University (Japan)
2014-07-01
The distributed hydrological 'rainfall- runoff' models provide possibilities of the physically based simulation of surface and subsurface flow on watersheds based on the GIS processed data. The success of such modeling approaches for the predictions of the runoff and soil erosion provides a basis for the implementation of the distributed radionuclide transport watershed models. Two distributed watershed models of radionuclide transport - RUNTOX and DHSVM-R have been used to simulate the radionuclide transport in the basin of the Dnieper River, Ukraine and watersheds of Prefecture Fukushima. RUNTOX is used for the simulation of radionuclide wash off from the experimental plots and small watersheds, and DHSVM-R is used for medium and large watersheds RUNTOX is two dimensional distributed hydrological model based on the finite-difference solution of the coupled equations the surface flow, subsurface flow, groundwater flow and advection- dispersion equations of the sediments (eroded soil) and radionuclide transport in liquid and solid phases, taking into parameterize the radionuclide exchanges between liquid and solid phases.. This model has been applied to the experimental plots in Ukraine after the Chernobyl accident and experimental plots in the Fukushima Prefecture. The experience of RUNTOX development and application has been used for the extension of the distributed hydrological model DHSVM by the including of the module of the watershed radionuclide transport. The updated model was named by DHSMV-R. The original DHSVM (Distributed Hydrology Soil Vegetation Model) was developed in the University of Washington and Pacific Northwest National Laboratories. DHSVM is a physical distributed hydrology-vegetation model for complex terrain based on the numerical solution of the network of one dimensional equations. The model accounts explicitly for the spatial distribution of land-surface processes, and can be applied over a range of scales, from plot to large
Bitew, M. M.; Goodrich, D. C.; Demaria, E.; Heilman, P.; Kautz, M. A.
2017-12-01
Walnut Gulch is a semi-arid environment experimental watershed and Long Term Agro-ecosystem Research (LTAR) site managed by USDA-ARS Southwest Watershed Research Center for which high-resolution long-term hydro-climatic data are available across its 150 km2 drainage area. In this study, we present the analysis of 50 years of continuous hourly rainfall data to evaluate runoff control and generation processes for improving the QA-QC plans of Walnut Gulch to create high-quality data set that is critical for reducing water balance uncertainties. Multiple linear regression models were developed to relate rainfall properties, runoff characteristics and watershed properties. The rainfall properties were summarized to event based total depth, maximum intensity, duration, the location of the storm center with respect to the outlet, and storm size normalized to watershed area. We evaluated the interaction between the runoff and rainfall and runoff as antecedent moisture condition (AMC), antecedent runoff condition (ARC) and, runoff depth and duration for each rainfall events. We summarized each of the watershed properties such as contributing area, slope, shape, channel length, stream density, channel flow area, and percent of the area of retention stock ponds for each of the nested catchments in Walnut Gulch. The evaluation of the model using basic and categorical statistics showed good predictive skill throughout the watersheds. The model produced correlation coefficients ranging from 0.4-0.94, Nash efficiency coefficients up to 0.77, and Kling-Gupta coefficients ranging from 0.4 to 0.98. The model predicted 92% of all runoff generations and 98% of no-runoff across all sub-watersheds in Walnut Gulch. The regression model also indicated good potential to complement the QA-QC procedures in place for Walnut Gulch dataset publications developed over the years since the 1960s through identification of inconsistencies in rainfall and runoff relations.
Comparison of different uncertainty techniques in urban stormwater quantity and quality modelling
DEFF Research Database (Denmark)
Dotto, C. B.; Mannina, G.; Kleidorfer, M.
2012-01-01
-UA), an approach based on a multi-objective auto-calibration (a multialgorithm, genetically adaptive multiobjective method, AMALGAM) and a Bayesian approach based on a simplified Markov Chain Monte Carlo method (implemented in the software MICA). To allow a meaningful comparison among the different uncertainty...... techniques, common criteria have been set for the likelihood formulation, defining the number of simulations, and the measure of uncertainty bounds. Moreover, all the uncertainty techniques were implemented for the same case study, in which the same stormwater quantity and quality model was used alongside...... the same dataset. The comparison results for a well-posed rainfall/runoff model showed that the four methods provide similar probability distributions of model parameters, and model prediction intervals. For ill-posed water quality model the differences between the results were much wider; and the paper...
Scott W. Bailey; Patricia A. Brousseau; Kevin J. McGuire; Donald S. Ross
2014-01-01
Upland headwater catchments, such as those in the AppalachianMountain region, are typified by coarse textured soils, flashy hydrologic response, and low baseflow of streams, suggesting well drained soils and minimal groundwater storage. Model formulations of soil genesis, nutrient cycling, critical loads and rainfall/runoff response are typically based on vertical...
Towards large scale stochastic rainfall models for flood risk assessment in trans-national basins
Serinaldi, F.; Kilsby, C. G.
2012-04-01
and Shape (GAMLSS). This approach allows exploiting climate variables to improve the simulation of the spatio-temporal rainfall structure through dynamically varying marginal and joint distributions. The preliminary results of the spatio-temporal analysis and modelling of a large data set of daily rainfall time series from 15 countries in the Central Eastern Europe are shown. Finally, indications are given of how the model outputs will be used with rainfall runoff models for estimating collective flood risk across the Danube basin.
Modeling of Flood Risk for the Continental United States
Lohmann, D.; Li, S.; Katz, B.; Goteti, G.; Kaheil, Y. H.; Vojjala, R.
2011-12-01
The science of catastrophic risk modeling helps people to understand the physical and financial implications of natural catastrophes (hurricanes, flood, earthquakes, etc.), terrorism, and the risks associated with changes in life expectancy. As such it depends on simulation techniques that integrate multiple disciplines such as meteorology, hydrology, structural engineering, statistics, computer science, financial engineering, actuarial science, and more in virtually every field of technology. In this talk we will explain the techniques and underlying assumptions of building the RMS US flood risk model. We especially will pay attention to correlation (spatial and temporal), simulation and uncertainty in each of the various components in the development process. Recent extreme floods (e.g. US Midwest flood 2008, US Northeast flood, 2010) have increased the concern of flood risk. Consequently, there are growing needs to adequately assess the flood risk. The RMS flood hazard model is mainly comprised of three major components. (1) Stochastic precipitation simulation module based on a Monte-Carlo analogue technique, which is capable of producing correlated rainfall events for the continental US. (2) Rainfall-runoff and routing module. A semi-distributed rainfall-runoff model was developed to properly assess the antecedent conditions, determine the saturation area and runoff. The runoff is further routed downstream along the rivers by a routing model. Combined with the precipitation model, it allows us to correlate the streamflow and hence flooding from different rivers, as well as low and high return-periods across the continental US. (3) Flood inundation module. It transforms the discharge (output from the flow routing) into water level, which is further combined with a two-dimensional off-floodplain inundation model to produce comprehensive flood hazard map. The performance of the model is demonstrated by comparing to the observation and published data. Output from
International Nuclear Information System (INIS)
Latron, J.; Solar, M.; Nord, G.; Llorens, P.; Gallart, F.
2009-01-01
Hydrological response and runoff processes have been studied in the Vallcebre research basins (North Eastern Spain) for almost 20 years. Results obtained allowed to build a more complete perceptual model of the hydrological functioning of Mediterranean mountains basins. On a seasonal and monthly scale, there was no simple relationship between rainfall and runoff depths. Monthly rainfall and runoff values revealed the existence of a threshold in the relationship between rainfall and runoff depths. At the event scale, the storm-flow coefficient had a clear seasonal pattern. The effect of the water table position on how rainfall and runoff volumes relate was observed. Examination of soil water potential and water table dynamics during representative floods helped to identify 3 types of characteristic hydrological behaviour during the year. Under dry conditions, runoff was generated essentially as infiltration excess runoff in low permeable areas, whereas saturation excess runoff dominated during wetting-up and wet conditions. During wetting-up transition, saturated areas resulted from the development of scattered perched water tables, whereas in wet conditions they were linked to the rise of the shallow water table. (Author) 8 refs.
R-HyMOD: an R-package for the hydrological model HyMOD
Baratti, Emanuele; Montanari, Alberto
2015-04-01
A software code for the implementation of the HyMOD hydrological model [1] is presented. HyMOD is a conceptual lumped rainfall-runoff model that is based on the probability-distributed soil storage capacity principle introduced by R. J. Moore 1985 [2]. The general idea behind this model is to describe the spatial variability of some process parameters as, for instance, the soil structure or the water storage capacities, through probability distribution functions. In HyMOD, the rainfall-runoff process is represented through a nonlinear tank connected with three identical linear tanks in parallel representing the surface flow and a slow-flow tank representing groundwater flow. The model requires the optimization of five parameters: Cmax (the maximum storage capacity within the watershed), β (the degree of spatial variability of the soil moisture capacity within the watershed), α (a factor for partitioning the flow between two series of tanks) and the two residence time parameters of quick-flow and slow-flow tanks, kquick and kslow respectively. Given its relatively simplicity but robustness, the model is widely used in the literature. The input data consist of precipitation and potential evapotranspiration at the given time scale. The R-HyMOD package is composed by a 'canonical' R-function of HyMOD and a fast FORTRAN implementation. The first one can be easily modified and can be used, for instance, for educational purposes; the second part combines the R user friendly interface with a fast processing unit. [1] Boyle D.P. (2000), Multicriteria calibration of hydrological models, Ph.D. dissertation, Dep. of Hydrol. and Water Resour., Univ of Arizona, Tucson. [2] Moore, R.J., (1985), The probability-distributed principle and runoff production at point and basin scale, Hydrol. Sci. J., 30(2), 273-297.
Hydrograph simulation models of the Hillsborough and Alafia Rivers, Florida: a preliminary report
Turner, James F.
1972-01-01
Mathematical (digital) models that simulate flood hydrographs from rainfall records have been developed for the following gaging stations in the Hillsborough and Alafia River basins of west-central Florida: Hillsborough River near Tampa, Alafia River at Lithia, and north Prong Alafia River near Keysville. These models, which were developed from historical streamflow and and rainfall records, are based on rainfall-runoff and unit-hydrograph procedures involving an arbitrary separation of the flood hydrograph. These models assume the flood hydrograph to be composed of only two flow components, direct (storm) runoff, and base flow. Expressions describing these two flow components are derived from streamflow and rainfall records and are combined analytically to form algorithms (models), which are programmed for processing on a digital computing system. Most Hillsborough and Alafia River flood discharges can be simulated with expected relative errors less than or equal to 30 percent and flood peaks can be simulated with average relative errors less than 15 percent. Because of the inadequate rainfall network that is used in obtaining input data for the North Prong Alafia River model, simulated peaks are frequently in error by more than 40 percent, particularly for storms having highly variable areal rainfall distribution. Simulation errors are the result of rainfall sample errors and, to a lesser extent, model inadequacy. Data errors associated with the determination of mean basin precipitation are the result of the small number and poor areal distribution of rainfall stations available for use in the study. Model inadequacy, however, is attributed to the basic underlying theory, particularly the rainfall-runoff relation. These models broaden and enhance existing water-management capabilities within these basins by allowing the establishment and implementation of programs providing for continued development in these areas. Specifically, the models serve not only as a
STORM WATER MANAGEMENT MODEL USER'S MANUAL VERSION 5.0
The EPA Storm Water Management Model (SWMM) is a dynamic rainfall-runoff simulation model used for single event or long-term (continuous) simulation of runoff quantity and quality from primarily urban areas. SWMM was first developed in 1971 and has undergone several major upgrade...
Hydrological modeling in semi-arid region using HEC-HMS model ...
African Journals Online (AJOL)
The purpose of this study is to simulate rainfall-runoff in the semi-arid region of ... the frequency storm is used for the meteorological model, the SCS curve number is ... SCS unit hydrograph method have been applied to simulate the runoff rate.
Sakakibara, Koichi; Tsujimura, Maki; Onda, Yuichi; Iwagami, Sho; Konuma, Ryohei; Sato, Yutaro
2016-04-01
Time variant transit time of water in catchments can fundamentally describe catchment function, controlling rainfall-runoff generation, groundwater flow pathway and water storage. Though rainstorm event has been recognized as active phase on catchment hydrology, accurate and precise time variance of water transit time and related water dynamics during rainstorm have not been well clarified yet. Here, in order to reveal temporal variation of mean transit time of groundwater and related hydrological processes in a forested small catchment during rainstorm event, periodic and intensive field observations (15 - 17th July 2015, rainfall of 100.8 mm in total) were conducted in Yamakiya district (Fukushima, Japan) from September 2014 to December 2015. Discharge volume, groundwater table and precipitation amount were measured in 10 minutes interval. Water samples were taken from groundwater, discharge water, soil water and precipitation for determination of stable isotopic compositions (δ18O, δ2H), inorganic solutes concentration and dissolved noble gasses concentration (CFC11, CFC12, CFC113, SF6) in water. Storm hydrograph and groundwater table clearly responded to rainfall event especially with more than 30 mm per day throughout monitoring period. According to SF6 concentration in water, the mean transit time of discharge water (perennial spring) showed 3 - 6.5 years in the no-rainfall period (steady state), but fluctuated from zero to 12.5 years in the rainstorm event with totally 100.8 mm (unsteady state). The mean transit time of discharge water dramatically altered from zero to 12.5 years from before to after the tentative hydrograph peak in the rising limb, indicating new water components were dominant before tentative hydrograph peak, whereas deep groundwater component with longer residence time contributed much to discharge after the tentative hydrograph peak. On the other hand, mean residence time of groundwater (water in 5 m well) ranged from 0.5 to 11.5 years
From Logical to Distributional Models
Directory of Open Access Journals (Sweden)
Anne Preller
2014-12-01
Full Text Available The paper relates two variants of semantic models for natural language, logical functional models and compositional distributional vector space models, by transferring the logic and reasoning from the logical to the distributional models. The geometrical operations of quantum logic are reformulated as algebraic operations on vectors. A map from functional models to vector space models makes it possible to compare the meaning of sentences word by word.
Storm Water Management Model Reference Manual Volume II – Hydraulics
SWMM is a dynamic rainfall-runoff simulation model used for single event or long-term (continuous) simulation of runoff quantity and quality from primarily urban areas. The runoff component of SWMM operates on a collection of subcatchment areas that receive precipitation and gene...
Kandel, D. D.; Western, A. W.; Grayson, R. B.
2004-12-01
Mismatches in scale between the fundamental processes, the model and supporting data are a major limitation in hydrologic modelling. Surface runoff generation via infiltration excess and the process of soil erosion are fundamentally short time-scale phenomena and their average behaviour is mostly determined by the short time-scale peak intensities of rainfall. Ideally, these processes should be simulated using time-steps of the order of minutes to appropriately resolve the effect of rainfall intensity variations. However, sub-daily data support is often inadequate and the processes are usually simulated by calibrating daily (or even coarser) time-step models. Generally process descriptions are not modified but rather effective parameter values are used to account for the effect of temporal lumping, assuming that the effect of the scale mismatch can be counterbalanced by tuning the parameter values at the model time-step of interest. Often this results in parameter values that are difficult to interpret physically. A similar approach is often taken spatially. This is problematic as these processes generally operate or interact non-linearly. This indicates a need for better techniques to simulate sub-daily processes using daily time-step models while still using widely available daily information. A new method applicable to many rainfall-runoff-erosion models is presented. The method is based on temporal scaling using statistical distributions of rainfall intensity to represent sub-daily intensity variations in a daily time-step model. This allows the effect of short time-scale nonlinear processes to be captured while modelling at a daily time-step, which is often attractive due to the wide availability of daily forcing data. The approach relies on characterising the rainfall intensity variation within a day using a cumulative distribution function (cdf). This cdf is then modified by various linear and nonlinear processes typically represented in hydrological and
Le Bihan, Guillaume; Payrastre, Olivier; Gaume, Eric; Pons, Frederic; Moncoulon, David
2016-04-01
Hydrometeorological forecasting is an essential component of real-time flood management. The information it provides is of great help for crisis managers to anticipate the inundations and the associated risks. In the particular case of flash-floods, which may affect a large amount of small watersheds spread over the territory (up to 300 000 km of waterways considering a drained area of 5 km² minimum in France), appropriate flood forecasting systems are still under development. In France, highly distributed hydrological models have been implemented, enabling a real-time assessment of the potential intensity of flash-floods from the records of weather radars: AIGA-hydro system (Lavabre et al., 2005; Javelle et al., 2014), PreDiFlood project (Naulin et al., 2013). The approach presented here aims to go one step further by offering a direct assessment of the potential impacts of the simulated floods on inhabited areas. This approach is based on an a priori analysis of the study area in order (1) to evaluate with a simplified hydraulic approach (DTM treatment) the potentially flooded areas for different discharge levels, and (2) to identify the associated buildings and/or population at risk from geographic databases. This preliminary analysis enables to build an impact model (discharge-impact curve) on each river reach, which is then used to directly estimate the potentially affected assets based on a distributed rainfall runoff model. The overall principle of this approach was already presented at the 8th Hymex workshop. Therefore, the presentation will be here focused on the first validation results in terms of (1) accuracy of flooded areas simulated from DTM treatments, and (2) relevance of estimated impacts. The inundated areas simulated were compared to the European Directive cartography results (where available), showing an overall good correspondence in a large majority of cases, but also very significant errors for approximatively 10% of the river reaches
Directory of Open Access Journals (Sweden)
A. Elshorbagy
2010-10-01
Full Text Available In this second part of the two-part paper, the data driven modeling (DDM experiment, presented and explained in the first part, is implemented. Inputs for the five case studies (half-hourly actual evapotranspiration, daily peat soil moisture, daily till soil moisture, and two daily rainfall-runoff datasets are identified, either based on previous studies or using the mutual information content. Twelve groups (realizations were randomly generated from each dataset by randomly sampling without replacement from the original dataset. Neural networks (ANNs, genetic programming (GP, evolutionary polynomial regression (EPR, Support vector machines (SVM, M5 model trees (M5, K-nearest neighbors (K-nn, and multiple linear regression (MLR techniques are implemented and applied to each of the 12 realizations of each case study. The predictive accuracy and uncertainties of the various techniques are assessed using multiple average overall error measures, scatter plots, frequency distribution of model residuals, and the deterioration rate of prediction performance during the testing phase. Gamma test is used as a guide to assist in selecting the appropriate modeling technique. Unlike two nonlinear soil moisture case studies, the results of the experiment conducted in this research study show that ANNs were a sub-optimal choice for the actual evapotranspiration and the two rainfall-runoff case studies. GP is the most successful technique due to its ability to adapt the model complexity to the modeled data. EPR performance could be close to GP with datasets that are more linear than nonlinear. SVM is sensitive to the kernel choice and if appropriately selected, the performance of SVM can improve. M5 performs very well with linear and semi linear data, which cover wide range of hydrological situations. In highly nonlinear case studies, ANNs, K-nn, and GP could be more successful than other modeling techniques. K-nn is also successful in linear situations, and it
Elshorbagy, A.; Corzo, G.; Srinivasulu, S.; Solomatine, D. P.
2010-10-01
In this second part of the two-part paper, the data driven modeling (DDM) experiment, presented and explained in the first part, is implemented. Inputs for the five case studies (half-hourly actual evapotranspiration, daily peat soil moisture, daily till soil moisture, and two daily rainfall-runoff datasets) are identified, either based on previous studies or using the mutual information content. Twelve groups (realizations) were randomly generated from each dataset by randomly sampling without replacement from the original dataset. Neural networks (ANNs), genetic programming (GP), evolutionary polynomial regression (EPR), Support vector machines (SVM), M5 model trees (M5), K-nearest neighbors (K-nn), and multiple linear regression (MLR) techniques are implemented and applied to each of the 12 realizations of each case study. The predictive accuracy and uncertainties of the various techniques are assessed using multiple average overall error measures, scatter plots, frequency distribution of model residuals, and the deterioration rate of prediction performance during the testing phase. Gamma test is used as a guide to assist in selecting the appropriate modeling technique. Unlike two nonlinear soil moisture case studies, the results of the experiment conducted in this research study show that ANNs were a sub-optimal choice for the actual evapotranspiration and the two rainfall-runoff case studies. GP is the most successful technique due to its ability to adapt the model complexity to the modeled data. EPR performance could be close to GP with datasets that are more linear than nonlinear. SVM is sensitive to the kernel choice and if appropriately selected, the performance of SVM can improve. M5 performs very well with linear and semi linear data, which cover wide range of hydrological situations. In highly nonlinear case studies, ANNs, K-nn, and GP could be more successful than other modeling techniques. K-nn is also successful in linear situations, and it should
Distributed Parameter Modelling Applications
DEFF Research Database (Denmark)
Sales-Cruz, Mauricio; Cameron, Ian; Gani, Rafiqul
2011-01-01
and the development of a short-path evaporator. The oil shale processing problem illustrates the interplay amongst particle flows in rotating drums, heat and mass transfer between solid and gas phases. The industrial application considers the dynamics of an Alberta-Taciuk processor, commonly used in shale oil and oil...... the steady state, distributed behaviour of a short-path evaporator....
Wainwright, et al. (Earth Surface Processes and Landforms; 2008a, b, c) propose a new model (MAHLERAN) for simulating catchment-scale erosion resulting from rainfall-runoff events. In justification for this new model, several existing process-based models are criticized in regard to their theoretic...
Distribution system modeling and analysis
Kersting, William H
2001-01-01
For decades, distribution engineers did not have the sophisticated tools developed for analyzing transmission systems-often they had only their instincts. Things have changed, and we now have computer programs that allow engineers to simulate, analyze, and optimize distribution systems. Powerful as these programs are, however, without a real understanding of the operating characteristics of a distribution system, engineers using the programs can easily make serious errors in their designs and operating procedures. Distribution System Modeling and Analysis helps prevent those errors. It gives readers a basic understanding of the modeling and operating characteristics of the major components of a distribution system. One by one, the author develops and analyzes each component as a stand-alone element, then puts them all together to analyze a distribution system comprising the various shunt and series devices for power-flow and short-circuit studies. He includes the derivation of all models and includes many num...
Schoups, G.; Vrugt, J. A.; Fenicia, F.; van de Giesen, N. C.
2010-10-01
Conceptual rainfall-runoff models have traditionally been applied without paying much attention to numerical errors induced by temporal integration of water balance dynamics. Reliance on first-order, explicit, fixed-step integration methods leads to computationally cheap simulation models that are easy to implement. Computational speed is especially desirable for estimating parameter and predictive uncertainty using Markov chain Monte Carlo (MCMC) methods. Confirming earlier work of Kavetski et al. (2003), we show here that the computational speed of first-order, explicit, fixed-step integration methods comes at a cost: for a case study with a spatially lumped conceptual rainfall-runoff model, it introduces artificial bimodality in the marginal posterior parameter distributions, which is not present in numerically accurate implementations of the same model. The resulting effects on MCMC simulation include (1) inconsistent estimates of posterior parameter and predictive distributions, (2) poor performance and slow convergence of the MCMC algorithm, and (3) unreliable convergence diagnosis using the Gelman-Rubin statistic. We studied several alternative numerical implementations to remedy these problems, including various adaptive-step finite difference schemes and an operator splitting method. Our results show that adaptive-step, second-order methods, based on either explicit finite differencing or operator splitting with analytical integration, provide the best alternative for accurate and efficient MCMC simulation. Fixed-step or adaptive-step implicit methods may also be used for increased accuracy, but they cannot match the efficiency of adaptive-step explicit finite differencing or operator splitting. Of the latter two, explicit finite differencing is more generally applicable and is preferred if the individual hydrologic flux laws cannot be integrated analytically, as the splitting method then loses its advantage.
Description of the G-A Infiltration Model Using Chu and Chow ...
African Journals Online (AJOL)
The soil infiltration process is one of the hydrological cycle processes, attracting the attention of the hydrologists more than any other process. This process provides conversion of the raw rainfall into the excess rainfall; and ultimately the excess rainfall is used for describing the rainfall-runoff models. In most of the infiltration ...
Storm Water Management Model Reference Manual Volume III – Water Quality
SWMM is a dynamic rainfall-runoff simulation model used for single event or long-term (continuous) simulation of runoff quantity and quality from primarily urban areas. The runoff component of SWMM operates on a collection of subcatchment areas that receive precipitation and gene...
Analysis of rainfall distribution in Kelantan river basin, Malaysia
Che Ros, Faizah; Tosaka, Hiroyuki
2018-03-01
Using rainfall gauge on its own as input carries great uncertainties regarding runoff estimation, especially when the area is large and the rainfall is measured and recorded at irregular spaced gauging stations. Hence spatial interpolation is the key to obtain continuous and orderly rainfall distribution at unknown points to be the input to the rainfall runoff processes for distributed and semi-distributed numerical modelling. It is crucial to study and predict the behaviour of rainfall and river runoff to reduce flood damages of the affected area along the Kelantan river. Thus, a good knowledge on rainfall distribution is essential in early flood prediction studies. Forty six rainfall stations and their daily time-series were used to interpolate gridded rainfall surfaces using inverse-distance weighting (IDW), inverse-distance and elevation weighting (IDEW) methods and average rainfall distribution. Sensitivity analysis for distance and elevation parameters were conducted to see the variation produced. The accuracy of these interpolated datasets was examined using cross-validation assessment.
Kobayashi, Kenichiro; Otsuka, Shigenori; Apip; Saito, Kazuo
2016-08-01
This paper presents a study on short-term ensemble flood forecasting specifically for small dam catchments in Japan. Numerical ensemble simulations of rainfall from the Japan Meteorological Agency nonhydrostatic model (JMA-NHM) are used as the input data to a rainfall-runoff model for predicting river discharge into a dam. The ensemble weather simulations use a conventional 10 km and a high-resolution 2 km spatial resolutions. A distributed rainfall-runoff model is constructed for the Kasahori dam catchment (approx. 70 km2) and applied with the ensemble rainfalls. The results show that the hourly maximum and cumulative catchment-average rainfalls of the 2 km resolution JMA-NHM ensemble simulation are more appropriate than the 10 km resolution rainfalls. All the simulated inflows based on the 2 and 10 km rainfalls become larger than the flood discharge of 140 m3 s-1, a threshold value for flood control. The inflows with the 10 km resolution ensemble rainfall are all considerably smaller than the observations, while at least one simulated discharge out of 11 ensemble members with the 2 km resolution rainfalls reproduces the first peak of the inflow at the Kasahori dam with similar amplitude to observations, although there are spatiotemporal lags between simulation and observation. To take positional lags into account of the ensemble discharge simulation, the rainfall distribution in each ensemble member is shifted so that the catchment-averaged cumulative rainfall of the Kasahori dam maximizes. The runoff simulation with the position-shifted rainfalls shows much better results than the original ensemble discharge simulations.
Uncertainty Analysis of Multi-Model Flood Forecasts
Directory of Open Access Journals (Sweden)
Erich J. Plate
2015-12-01
Full Text Available This paper demonstrates, by means of a systematic uncertainty analysis, that the use of outputs from more than one model can significantly improve conditional forecasts of discharges or water stages, provided the models are structurally different. Discharge forecasts from two models and the actual forecasted discharge are assumed to form a three-dimensional joint probability density distribution (jpdf, calibrated on long time series of data. The jpdf is decomposed into conditional probability density distributions (cpdf by means of Bayes formula, as suggested and explored by Krzysztofowicz in a series of papers. In this paper his approach is simplified to optimize conditional forecasts for any set of two forecast models. Its application is demonstrated by means of models developed in a study of flood forecasting for station Stung Treng on the middle reach of the Mekong River in South-East Asia. Four different forecast models were used and pairwise combined: forecast with no model, with persistence model, with a regression model, and with a rainfall-runoff model. Working with cpdfs requires determination of dependency among variables, for which linear regressions are required, as was done by Krzysztofowicz. His Bayesian approach based on transforming observed probability distributions of discharges and forecasts into normal distributions is also explored. Results obtained with his method for normal prior and likelihood distributions are identical to results from direct multiple regressions. Furthermore, it is shown that in the present case forecast accuracy is only marginally improved, if Weibull distributed basic data were converted into normally distributed variables.
Biondi, Daniela; De Luca, Davide Luciano
2015-04-01
The use of rainfall-runoff models represents an alternative to statistical approaches (such as at-site or regional flood frequency analysis) for design flood estimation, and constitutes an answer to the increasing need for synthetic design hydrographs (SDHs) associated to a specific return period. However, the lack of streamflow observations and the consequent high uncertainty associated with parameter estimation, usually pose serious limitations to the use of process-based approaches in ungauged catchments, which in contrast represent the majority in practical applications. This work presents the application of a Bayesian procedure that, for a predefined rainfall-runoff model, allows for the assessment of posterior parameters distribution, using the limited and uncertain information available for the response of an ungauged catchment (Bulygina et al. 2009; 2011). The use of regional estimates of river flow statistics, interpreted as hydrological signatures that measure theoretically relevant system process behaviours (Gupta et al. 2008), within this framework represents a valuable option and has shown significant developments in recent literature to constrain the plausible model response and to reduce the uncertainty in ungauged basins. In this study we rely on the first three L-moments of annual streamflow maxima, for which regressions are available from previous studies (Biondi et al. 2012; Laio et al. 2011). The methodology was carried out for a catchment located in southern Italy, and used within a Monte Carlo scheme (MCs) considering both event-based and continuous simulation approaches for design flood estimation. The applied procedure offers promising perspectives to perform model calibration and uncertainty analysis in ungauged basins; moreover, in the context of design flood estimation, process-based methods coupled with MCs approach have the advantage of providing simulated floods uncertainty analysis that represents an asset in risk-based decision
Moving horizon estimation for assimilating H-SAF remote sensing data into the HBV hydrological model
Montero, Rodolfo Alvarado; Schwanenberg, Dirk; Krahe, Peter; Lisniak, Dmytro; Sensoy, Aynur; Sorman, A. Arda; Akkol, Bulut
2016-06-01
Remote sensing information has been extensively developed over the past few years including spatially distributed data for hydrological applications at high resolution. The implementation of these products in operational flow forecasting systems is still an active field of research, wherein data assimilation plays a vital role on the improvement of initial conditions of streamflow forecasts. We present a novel implementation of a variational method based on Moving Horizon Estimation (MHE), in application to the conceptual rainfall-runoff model HBV, to simultaneously assimilate remotely sensed snow covered area (SCA), snow water equivalent (SWE), soil moisture (SM) and in situ measurements of streamflow data using large assimilation windows of up to one year. This innovative application of the MHE approach allows to simultaneously update precipitation, temperature, soil moisture as well as upper and lower zones water storages of the conceptual model, within the assimilation window, without an explicit formulation of error covariance matrixes and it enables a highly flexible formulation of distance metrics for the agreement of simulated and observed variables. The framework is tested in two data-dense sites in Germany and one data-sparse environment in Turkey. Results show a potential improvement of the lead time performance of streamflow forecasts by using perfect time series of state variables generated by the simulation of the conceptual rainfall-runoff model itself. The framework is also tested using new operational data products from the Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF) of EUMETSAT. This study is the first application of H-SAF products to hydrological forecasting systems and it verifies their added value. Results from assimilating H-SAF observations lead to a slight reduction of the streamflow forecast skill in all three cases compared to the assimilation of streamflow data only. On the other hand
ERM model analysis for adaptation to hydrological model errors
Baymani-Nezhad, M.; Han, D.
2018-05-01
Hydrological conditions are changed continuously and these phenomenons generate errors on flood forecasting models and will lead to get unrealistic results. Therefore, to overcome these difficulties, a concept called model updating is proposed in hydrological studies. Real-time model updating is one of the challenging processes in hydrological sciences and has not been entirely solved due to lack of knowledge about the future state of the catchment under study. Basically, in terms of flood forecasting process, errors propagated from the rainfall-runoff model are enumerated as the main source of uncertainty in the forecasting model. Hence, to dominate the exciting errors, several methods have been proposed by researchers to update the rainfall-runoff models such as parameter updating, model state updating, and correction on input data. The current study focuses on investigations about the ability of rainfall-runoff model parameters to cope with three types of existing errors, timing, shape and volume as the common errors in hydrological modelling. The new lumped model, the ERM model, has been selected for this study to evaluate its parameters for its use in model updating to cope with the stated errors. Investigation about ten events proves that the ERM model parameters can be updated to cope with the errors without the need to recalibrate the model.
Modeled ground water age distributions
Woolfenden, Linda R.; Ginn, Timothy R.
2009-01-01
The age of ground water in any given sample is a distributed quantity representing distributed provenance (in space and time) of the water. Conventional analysis of tracers such as unstable isotopes or anthropogenic chemical species gives discrete or binary measures of the presence of water of a given age. Modeled ground water age distributions provide a continuous measure of contributions from different recharge sources to aquifers. A numerical solution of the ground water age equation of Ginn (1999) was tested both on a hypothetical simplified one-dimensional flow system and under real world conditions. Results from these simulations yield the first continuous distributions of ground water age using this model. Complete age distributions as a function of one and two space dimensions were obtained from both numerical experiments. Simulations in the test problem produced mean ages that were consistent with the expected value at the end of the model domain for all dispersivity values tested, although the mean ages for the two highest dispersivity values deviated slightly from the expected value. Mean ages in the dispersionless case also were consistent with the expected mean ages throughout the physical model domain. Simulations under real world conditions for three dispersivity values resulted in decreasing mean age with increasing dispersivity. This likely is a consequence of an edge effect. However, simulations for all three dispersivity values tested were mass balanced and stable demonstrating that the solution of the ground water age equation can provide estimates of water mass density distributions over age under real world conditions.
Video distribution system cost model
Gershkoff, I.; Haspert, J. K.; Morgenstern, B.
1980-01-01
A cost model that can be used to systematically identify the costs of procuring and operating satellite linked communications systems is described. The user defines a network configuration by specifying the location of each participating site, the interconnection requirements, and the transmission paths available for the uplink (studio to satellite), downlink (satellite to audience), and voice talkback (between audience and studio) segments of the network. The model uses this information to calculate the least expensive signal distribution path for each participating site. Cost estimates are broken downy by capital, installation, lease, operations and maintenance. The design of the model permits flexibility in specifying network and cost structure.
Turboelectric Distributed Propulsion System Modelling
Liu, Chengyuan
2013-01-01
The Blended-Wing-Body is a conceptual aircraft design with rear-mounted, over wing engines. Turboelectric distributed propulsion system with boundary layer ingestion has been considered for this aircraft. It uses electricity to transmit power from the core turbine to the fans, therefore dramatically increases bypass ratio to reduce fuel consumption and noise. This dissertation presents methods on designing the TeDP system, evaluating effects of boundary layer ingestion, modelling engine perfo...
Water Distribution and Removal Model
International Nuclear Information System (INIS)
Y. Deng; N. Chipman; E.L. Hardin
2005-01-01
The design of the Yucca Mountain high level radioactive waste repository depends on the performance of the engineered barrier system (EBS). To support the total system performance assessment (TSPA), the Engineered Barrier System Degradation, Flow, and Transport Process Model Report (EBS PMR) is developed to describe the thermal, mechanical, chemical, hydrological, biological, and radionuclide transport processes within the emplacement drifts, which includes the following major analysis/model reports (AMRs): (1) EBS Water Distribution and Removal (WD and R) Model; (2) EBS Physical and Chemical Environment (P and CE) Model; (3) EBS Radionuclide Transport (EBS RNT) Model; and (4) EBS Multiscale Thermohydrologic (TH) Model. Technical information, including data, analyses, models, software, and supporting documents will be provided to defend the applicability of these models for their intended purpose of evaluating the postclosure performance of the Yucca Mountain repository system. The WD and R model ARM is important to the site recommendation. Water distribution and removal represents one component of the overall EBS. Under some conditions, liquid water will seep into emplacement drifts through fractures in the host rock and move generally downward, potentially contacting waste packages. After waste packages are breached by corrosion, some of this seepage water will contact the waste, dissolve or suspend radionuclides, and ultimately carry radionuclides through the EBS to the near-field host rock. Lateral diversion of liquid water within the drift will occur at the inner drift surface, and more significantly from the operation of engineered structures such as drip shields and the outer surface of waste packages. If most of the seepage flux can be diverted laterally and removed from the drifts before contacting the wastes, the release of radionuclides from the EBS can be controlled, resulting in a proportional reduction in dose release at the accessible environment
Water Distribution and Removal Model
Energy Technology Data Exchange (ETDEWEB)
Y. Deng; N. Chipman; E.L. Hardin
2005-08-26
The design of the Yucca Mountain high level radioactive waste repository depends on the performance of the engineered barrier system (EBS). To support the total system performance assessment (TSPA), the Engineered Barrier System Degradation, Flow, and Transport Process Model Report (EBS PMR) is developed to describe the thermal, mechanical, chemical, hydrological, biological, and radionuclide transport processes within the emplacement drifts, which includes the following major analysis/model reports (AMRs): (1) EBS Water Distribution and Removal (WD&R) Model; (2) EBS Physical and Chemical Environment (P&CE) Model; (3) EBS Radionuclide Transport (EBS RNT) Model; and (4) EBS Multiscale Thermohydrologic (TH) Model. Technical information, including data, analyses, models, software, and supporting documents will be provided to defend the applicability of these models for their intended purpose of evaluating the postclosure performance of the Yucca Mountain repository system. The WD&R model ARM is important to the site recommendation. Water distribution and removal represents one component of the overall EBS. Under some conditions, liquid water will seep into emplacement drifts through fractures in the host rock and move generally downward, potentially contacting waste packages. After waste packages are breached by corrosion, some of this seepage water will contact the waste, dissolve or suspend radionuclides, and ultimately carry radionuclides through the EBS to the near-field host rock. Lateral diversion of liquid water within the drift will occur at the inner drift surface, and more significantly from the operation of engineered structures such as drip shields and the outer surface of waste packages. If most of the seepage flux can be diverted laterally and removed from the drifts before contacting the wastes, the release of radionuclides from the EBS can be controlled, resulting in a proportional reduction in dose release at the accessible environment. The purposes
Integration of a Three-Dimensional Process-Based Hydrological Model into the Object Modeling System
Directory of Open Access Journals (Sweden)
Giuseppe Formetta
2016-01-01
Full Text Available The integration of a spatial process model into an environmental modeling framework can enhance the model’s capabilities. This paper describes a general methodology for integrating environmental models into the Object Modeling System (OMS regardless of the model’s complexity, the programming language, and the operating system used. We present the integration of the GEOtop model into the OMS version 3.0 and illustrate its application in a small watershed. OMS is an environmental modeling framework that facilitates model development, calibration, evaluation, and maintenance. It provides innovative techniques in software design such as multithreading, implicit parallelism, calibration and sensitivity analysis algorithms, and cloud-services. GEOtop is a physically based, spatially distributed rainfall-runoff model that performs three-dimensional finite volume calculations of water and energy budgets. Executing GEOtop as an OMS model component allows it to: (1 interact directly with the open-source geographical information system (GIS uDig-JGrass to access geo-processing, visualization, and other modeling components; and (2 use OMS components for automatic calibration, sensitivity analysis, or meteorological data interpolation. A case study of the model in a semi-arid agricultural catchment is presented for illustration and proof-of-concept. Simulated soil water content and soil temperature results are compared with measured data, and model performance is evaluated using goodness-of-fit indices. This study serves as a template for future integration of process models into OMS.
Kivva, Sergei; Zheleznyak, Mark; Konoplev, Alexei; Nanba, Kenji; Onda, Yuichi; Wakiyama Yoshifumi Wakiyama, Yoshifumi
2015-04-01
The distributed hydrological "rainfall- runoff" models provide possibilities of the physically based simulation of surface and subsurface flow on watersheds based on the GIS processed data. The success of such modeling approaches for the predictions of the runoff and soil erosion provides a basis for the implementation of the distributed models of the radionuclide washoff from the watersheds. The field studies provided on the Chernobyl and Fukushima catchments provides a unique data sets for the comparative testing and improvements of the modeling tools for the watersheds located in the areas of the very different geographical and hydro-meteorological condition The set of USLE experimental plots has been established by CRIED, University of Tsukuba after the Fukushima accident to study soil erosion and 137Cs wash off from the watersheds (Onda et al, 2014). The distributed watershed models of surface and subsurface flow, sediment and radionuclide transport has been used to simulate the radionuclide transport in the basin Dnieper River, Ukraine and the watersheds of Prefecture Fuksuhima. DHSVM-R is extension of the distributed hydrological model DHSVM (Lettenmayer, Wigmosta et al, 1996-2014) by the including into it the module of the watershed radionuclide transport. DHSVM is a physically based, distributed hydrology-vegetation model for complex terrain based on the numerical solution of the network of one-dimensional equations. The surface flow submodel of DHSMV has been modified: four-directions schematization for the model's cells has been replaced by the eight-directions scheme, more numerically efficient finite -differences scheme was implemented. The new module of radionuclide wash-off from catchment and transport via stream network in soluble phase and on suspended sediments including bottom-water exchange processes was developed for DHSMV-R. DHSVM-R was implemented recently within Swedish- Ukrainian ENSURE project for the modeling of 234U wash-off from the
Real-time modeling of heat distributions
Hamann, Hendrik F.; Li, Hongfei; Yarlanki, Srinivas
2018-01-02
Techniques for real-time modeling temperature distributions based on streaming sensor data are provided. In one aspect, a method for creating a three-dimensional temperature distribution model for a room having a floor and a ceiling is provided. The method includes the following steps. A ceiling temperature distribution in the room is determined. A floor temperature distribution in the room is determined. An interpolation between the ceiling temperature distribution and the floor temperature distribution is used to obtain the three-dimensional temperature distribution model for the room.
DEFF Research Database (Denmark)
Del Giudice, Dario; Löwe, Roland; Madsen, Henrik
2015-01-01
from different fields and have not yet been compared in environmental modeling. To compare the two approaches, we develop a unifying terminology, evaluate them theoretically, and apply them to conceptual rainfall-runoff modeling in the same drainage system. Our results show that both approaches can......In urban rainfall-runoff, commonly applied statistical techniques for uncertainty quantification mostly ignore systematic output errors originating from simplified models and erroneous inputs. Consequently, the resulting predictive uncertainty is often unreliable. Our objective is to present two...... approaches which use stochastic processes to describe systematic deviations and to discuss their advantages and drawbacks for urban drainage modeling. The two methodologies are an external bias description (EBD) and an internal noise description (IND, also known as stochastic gray-box modeling). They emerge...
Modelling Inland Flood Events for Hazard Maps in Taiwan
Ghosh, S.; Nzerem, K.; Sassi, M.; Hilberts, A.; Assteerawatt, A.; Tillmanns, S.; Mathur, P.; Mitas, C.; Rafique, F.
2015-12-01
Taiwan experiences significant inland flooding, driven by torrential rainfall from plum rain storms and typhoons during summer and fall. From last 13 to 16 years data, 3,000 buildings were damaged by such floods annually with a loss US$0.41 billion (Water Resources Agency). This long, narrow island nation with mostly hilly/mountainous topography is located at tropical-subtropical zone with annual average typhoon-hit-frequency of 3-4 (Central Weather Bureau) and annual average precipitation of 2502mm (WRA) - 2.5 times of the world's average. Spatial and temporal distributions of countrywide precipitation are uneven, with very high local extreme rainfall intensities. Annual average precipitation is 3000-5000mm in the mountainous regions, 78% of it falls in May-October, and the 1-hour to 3-day maximum rainfall are about 85 to 93% of the world records (WRA). Rivers in Taiwan are short with small upstream areas and high runoff coefficients of watersheds. These rivers have the steepest slopes, the shortest response time with rapid flows, and the largest peak flows as well as specific flood peak discharge (WRA) in the world. RMS has recently developed a countrywide inland flood model for Taiwan, producing hazard return period maps at 1arcsec grid resolution. These can be the basis for evaluating and managing flood risk, its economic impacts, and insured flood losses. The model is initiated with sub-daily historical meteorological forcings and calibrated to daily discharge observations at about 50 river gauges over the period 2003-2013. Simulations of hydrologic processes, via rainfall-runoff and routing models, are subsequently performed based on a 10000 year set of stochastic forcing. The rainfall-runoff model is physically based continuous, semi-distributed model for catchment hydrology. The 1-D wave propagation hydraulic model considers catchment runoff in routing and describes large-scale transport processes along the river. It also accounts for reservoir storage
Zhu, Gaofeng; Li, Xin; Ma, Jinzhu; Wang, Yunquan; Liu, Shaomin; Huang, Chunlin; Zhang, Kun; Hu, Xiaoli
2018-04-01
Sequential Monte Carlo (SMC) samplers have become increasing popular for estimating the posterior parameter distribution with the non-linear dependency structures and multiple modes often present in hydrological models. However, the explorative capabilities and efficiency of the sampler depends strongly on the efficiency in the move step of SMC sampler. In this paper we presented a new SMC sampler entitled the Particle Evolution Metropolis Sequential Monte Carlo (PEM-SMC) algorithm, which is well suited to handle unknown static parameters of hydrologic model. The PEM-SMC sampler is inspired by the works of Liang and Wong (2001) and operates by incorporating the strengths of the genetic algorithm, differential evolution algorithm and Metropolis-Hasting algorithm into the framework of SMC. We also prove that the sampler admits the target distribution to be a stationary distribution. Two case studies including a multi-dimensional bimodal normal distribution and a conceptual rainfall-runoff hydrologic model by only considering parameter uncertainty and simultaneously considering parameter and input uncertainty show that PEM-SMC sampler is generally superior to other popular SMC algorithms in handling the high dimensional problems. The study also indicated that it may be important to account for model structural uncertainty by using multiplier different hydrological models in the SMC framework in future study.
Comparative Distributions of Hazard Modeling Analysis
Directory of Open Access Journals (Sweden)
Rana Abdul Wajid
2006-07-01
Full Text Available In this paper we present the comparison among the distributions used in hazard analysis. Simulation technique has been used to study the behavior of hazard distribution modules. The fundamentals of Hazard issues are discussed using failure criteria. We present the flexibility of the hazard modeling distribution that approaches to different distributions.
FLASH-FLOOD MODELLING WITH ARTIFICIAL NEURAL NETWORKS USING RADAR RAINFALL ESTIMATES
Directory of Open Access Journals (Sweden)
Dinu Cristian
2017-09-01
Full Text Available The use of artificial neural networks (ANNs in modelling the hydrological processes has become a common approach in the last two decades, among side the traditional methods. In regard to the rainfall-runoff modelling, in both traditional and ANN models the use of ground rainfall measurements is prevalent, which can be challenging in areas with low rain gauging station density, especially in catchments where strong focused rainfall can generate flash-floods. The weather radar technology can prove to be a solution for such areas by providing rain estimates with good time and space resolution. This paper presents a comparison between different ANN setups using as input both ground and radar observations for modelling the rainfall-runoff process for Bahluet catchment, with focus on a flash-flood observed in the catchment.
Adaptation of the HBV model for the study of drought propagation in European catchments
van Loon, A. F.; van Lanen, H. A. J.; Seibert, J.; Torfs, P. J. J. F.
2009-04-01
Drought propagation is the conversion of a meteorological drought signal into a hydrological drought (e.g. groundwater and streamflow) as it moves through the subsurface part of the hydrological cycle. The lag, attenuation and possibly pooling of parts of the signal are dependent on climate and catchment characteristics. The understanding of processes underlying drought propagation is still very limited. Our aim is to study these processes in small catchments across Europe with different climate conditions and physical structures (e.g. hard rock, porous rock, flat areas, steep slopes, snow, lakes). As measurements of soil moisture and groundwater storage are normally scarce, simulation of these variables using a lumped hydrological model is needed. However, although a simple model is preferable, many conceptual rainfall-runoff models are not suitable for this purpose because of their focus on fast reactions and therefore unrealistic black box approach of the soil moisture and groundwater system. We studied the applicability of the well-known semi-distributed rainfall-runoff model HBV for drought propagation research. The results show that HBV reproduces observed discharges fairly well. However, in simulating groundwater storage in dry periods, HBV has some conceptual weaknesses: 1) surface runoff is approximated by a quick flow component through the upper groundwater box; 2) the storage in the upper groundwater box has no upper limit; 3) lakes are simulated as part of the lower groundwater box; 4) the percolation from the upper to the lower groundwater box is not continuous, but either zero or constant. So, adaptation of the HBV model structure was needed to be able to simulate realistic groundwater storage in dry periods. The HBV Light model (Seibert et al., 2000) was used as basis for this work. As the snow and soil routines of this model have proven their value in previous (drought) studies, these routines are left unchanged. The lower part of HBV Light, the
Odry, Jean; Arnaud, Patrick
2016-04-01
The SHYREG method (Aubert et al., 2014) associates a stochastic rainfall generator and a rainfall-runoff model to produce rainfall and flood quantiles on a 1 km2 mesh covering the whole French territory. The rainfall generator is based on the description of rainy events by descriptive variables following probability distributions and is characterised by a high stability. This stochastic generator is fully regionalised, and the rainfall-runoff transformation is calibrated with a single parameter. Thanks to the stability of the approach, calibration can be performed against only flood quantiles associated with observated frequencies which can be extracted from relatively short time series. The aggregation of SHYREG flood quantiles to the catchment scale is performed using an areal reduction factor technique unique on the whole territory. Past studies demonstrated the accuracy of SHYREG flood quantiles estimation for catchments where flow data are available (Arnaud et al., 2015). Nevertheless, the parameter of the rainfall-runoff model is independently calibrated for each target catchment. As a consequence, this parameter plays a corrective role and compensates approximations and modelling errors which makes difficult to identify its proper spatial pattern. It is an inherent objective of the SHYREG approach to be completely regionalised in order to provide a complete and accurate flood quantiles database throughout France. Consequently, it appears necessary to identify the model configuration in which the calibrated parameter could be regionalised with acceptable performances. The revaluation of some of the method hypothesis is a necessary step before the regionalisation. Especially the inclusion or the modification of the spatial variability of imposed parameters (like production and transfer reservoir size, base flow addition and quantiles aggregation function) should lead to more realistic values of the only calibrated parameter. The objective of the work presented
Distributions with given marginals and statistical modelling
Fortiana, Josep; Rodriguez-Lallena, José
2002-01-01
This book contains a selection of the papers presented at the meeting `Distributions with given marginals and statistical modelling', held in Barcelona (Spain), July 17-20, 2000. In 24 chapters, this book covers topics such as the theory of copulas and quasi-copulas, the theory and compatibility of distributions, models for survival distributions and other well-known distributions, time series, categorical models, definition and estimation of measures of dependence, monotonicity and stochastic ordering, shape and separability of distributions, hidden truncation models, diagonal families, orthogonal expansions, tests of independence, and goodness of fit assessment. These topics share the use and properties of distributions with given marginals, this being the fourth specialised text on this theme. The innovative aspect of the book is the inclusion of statistical aspects such as modelling, Bayesian statistics, estimation, and tests.
The effect of coupling hydrologic and hydrodynamic models on probable maximum flood estimation
Felder, Guido; Zischg, Andreas; Weingartner, Rolf
2017-07-01
Deterministic rainfall-runoff modelling usually assumes stationary hydrological system, as model parameters are calibrated with and therefore dependant on observed data. However, runoff processes are probably not stationary in the case of a probable maximum flood (PMF) where discharge greatly exceeds observed flood peaks. Developing hydrodynamic models and using them to build coupled hydrologic-hydrodynamic models can potentially improve the plausibility of PMF estimations. This study aims to assess the potential benefits and constraints of coupled modelling compared to standard deterministic hydrologic modelling when it comes to PMF estimation. The two modelling approaches are applied using a set of 100 spatio-temporal probable maximum precipitation (PMP) distribution scenarios. The resulting hydrographs, the resulting peak discharges as well as the reliability and the plausibility of the estimates are evaluated. The discussion of the results shows that coupling hydrologic and hydrodynamic models substantially improves the physical plausibility of PMF modelling, although both modelling approaches lead to PMF estimations for the catchment outlet that fall within a similar range. Using a coupled model is particularly suggested in cases where considerable flood-prone areas are situated within a catchment.
A Distributional Representation Model For Collaborative Filtering
Junlin, Zhang; Heng, Cai; Tongwen, Huang; Huiping, Xue
2015-01-01
In this paper, we propose a very concise deep learning approach for collaborative filtering that jointly models distributional representation for users and items. The proposed framework obtains better performance when compared against current state-of-art algorithms and that made the distributional representation model a promising direction for further research in the collaborative filtering.
Rapid Prototyping of Formally Modelled Distributed Systems
Buchs, Didier; Buffo, Mathieu; Titsworth, Frances M.
1999-01-01
This paper presents various kinds of prototypes, used in the prototyping of formally modelled distributed systems. It presents the notions of prototyping techniques and prototype evolution, and shows how to relate them to the software life-cycle. It is illustrated through the use of the formal modelling language for distributed systems CO-OPN/2.
Business Models and Regulation | Distributed Generation Interconnection
Collaborative | NREL Business Models and Regulation Business Models and Regulation Subscribe to new business models and approaches. The growing role of distributed resources in the electricity system is leading to a shift in business models and regulation for electric utilities. These
Methodology and application of combined watershed and ground-water models in Kansas
Sophocleous, M.; Perkins, S.P.
2000-01-01
Increased irrigation in Kansas and other regions during the last several decades has caused serious water depletion, making the development of comprehensive strategies and tools to resolve such problems increasingly important. This paper makes the case for an intermediate complexity, quasi-distributed, comprehensive, large-watershed model, which falls between the fully distributed, physically based hydrological modeling system of the type of the SHE model and the lumped, conceptual rainfall-runoff modeling system of the type of the Stanford watershed model. This is achieved by integrating the quasi-distributed watershed model SWAT with the fully-distributed ground-water model MODFLOW. The advantage of this approach is the appreciably smaller input data requirements and the use of readily available data (compared to the fully distributed, physically based models), the statistical handling of watershed heterogeneities by employing the hydrologic-response-unit concept, and the significantly increased flexibility in handling stream-aquifer interactions, distributed well withdrawals, and multiple land uses. The mechanics of integrating the component watershed and ground-water models are outlined, and three real-world management applications of the integrated model from Kansas are briefly presented. Three different aspects of the integrated model are emphasized: (1) management applications of a Decision Support System for the integrated model (Rattlesnake Creek subbasin); (2) alternative conceptual models of spatial heterogeneity related to the presence or absence of an underlying aquifer with shallow or deep water table (Lower Republican River basin); and (3) the general nature of the integrated model linkage by employing a watershed simulator other than SWAT (Wet Walnut Creek basin). These applications demonstrate the practicality and versatility of this relatively simple and conceptually clear approach, making public acceptance of the integrated watershed modeling
Impact of modelling scale on probabilistic flood risk assessment: the Malawi case
Directory of Open Access Journals (Sweden)
Rudari Roberto
2016-01-01
Full Text Available In the early months of 2015, destructive floods hit Malawi, causing deaths and economic losses. Flood risk assessment outcomes can be used to increase scientific-supported awareness of risk. The recent increase in availability of high resolution data such as TanDEM-X at 12m resolution makes possible the use of detailed physical based flood hazard models in risk assessment. Nonetheless the scale of hazard modelling still remains an issue, which requires a compromise between level of detail and computational efforts. This work presents two different approaches on hazard modelling. Both methods rely on 32-years of numeric weather re-analysis and rainfall-runoff transformation through a fully distributed WFLOW-type hydrological model. The first method, applied at national scale, uses fast post-processing routines, which estimate flood water depth at a resolution of about 1×1km. The second method applies a full 2D hydraulic model to propagate water discharge into the flood plains and best suites for small areas where assets are concentrated. At the 12m resolution, three hot spots with a model area of approximately 10×10 km are analysed. Flood hazard maps obtained with both approaches are combined with flood impact models at the same resolution to generate indicators for flood risk. A quantitative comparison of the two approaches is presented in order to show the effects of modelling scale on both hazard and impact losses.
Habaieb, Hamadi; Hermassi, Taoufik; Moncef Masmoudi, Mohamed; Ben Mechlia, Nétij
2015-04-01
Northern Tunisia is characterized by a semi-arid climate with an irregular and high spatial variability of rainfall. This situation is expected to aggravate under the expected increase of temperature and modification of rainfall regime predicted by most climate models for the Mediterranean region. Water is a major limiting factor for agriculture in Tunisia and mobilization of surface water resources is approaching its maximum. Dams are installed on almost all large watersheds and concerned also medium size and small ones. Hydrological functioning of such structures and their capacity to satisfy user's demand under the changing climate will be addressed using simple models and results will be discussed in this paper. The small catchment of Wadi Rmel is considered here for methodological development. This watershed (675 Km2) is situated in North-East Tunisia with average annual rainfall of 420 mm and was equipped in 1998 with a small dam. Data on rainfall collected at 12 rainfall stations during the period 1908 - 2012 are analyzed and used to build a coherent series of monthly rainfalls and spatially averaged on the watershed by the Thiessen method. In a second step, rainfall-runoff modeling was used to estimate runoff and water budget of the dam. Tow rainfall-runoff models GR2M and SWAT were considered and evaluated when using i) the rainfall observed at the dam and ii) the average rainfall on the watershed. The observed and simulated level in the dam were compared for both models and situations. Results showed that taking into account the spatial distribution of rainfall improved the simulation of stream flows and that SWAT model performs better than GR2M. The use of such models to make prediction of stream flow using downscaled climatic data from GCM will be discussed. Analysis of the results considering tow standardized sets of future greenhouse gas emissions used by the General Circulation Models for the IPCC 5th approximation RCP4.5 and RCP8.5 and three future
Distributed modeling for road authorities
Luiten, G.T.; Bõhms, H.M.; Nederveen, S. van; Bektas, E.
2013-01-01
A great challenge for road authorities is to improve the effectiveness and efficiency of their core processes by improving data exchange and sharing using new technologies such as building information modeling (BIM). BIM has already been successfully implemented in other sectors, such as
Hydrologic behaviour of the Lake of Monate (Italy): a parsimonious modelling strategy
Tomesani, Giulia; Soligno, Irene; Castellarin, Attilio; Baratti, Emanuele; Cervi, Federico; Montanari, Alberto
2016-04-01
The Lake of Monate (province of Varese, Northern Italy), is a unique example of ecosystem in equilibrium. The lake water quality is deemed excellent notwithstanding the intensive agricultural cultivation, industrial assets and mining activities characterising the surrounding areas. The lake has a true touristic vocation and is the only swimmable water body of the province of Varese, which counts several natural lakes. Lake of Monate has no tributary and its overall watershed area is equal to c.a. 6.6 km2 including the lake surface (i.e. 2.6 km2), of which 3.3 out of c.a. 4.0 km2 belong to the topographical watershed, while the remaining 0.7 km2 belong to the underground watershed. The latter is larger than the topographical watershed due to the presence of moraine formations on top of the limestone bedrock. The local administration recently promoted an intensive environmental monitoring campaign that aims to reach a better understanding of the hydrology of the lake and the subsurface water fluxes. The monitoring campaign started in October 2013 and, as a result, several meteoclimatic and hydrologic data have been collected up to now at daily and hourly timescales. Our study focuses on a preliminary representation of the hydrological behaviour of the lake through a modified version of HyMOD, a conceptual 5-parameter lumped rainfall-runoff model based on the probability-distributed soil storage capacity. The modified model is a semi-distributed application of HyMOD that uses the same five parameters of the original version and simulates the rainfall-runoff transformation for the whole lake watershed at daily time scale in terms of: direct precipitation on, and evaporation from, the lake surface; overall lake inflow, by separating the runoff component (topographic watershed) from the groundwater component (overall watershed); lake water-level oscillation; streamflow at the lake outlet. We used the first year of hydrometeorological observations as calibration data and
New trends in species distribution modelling
Zimmermann, Niklaus E.; Edwards, Thomas C.; Graham, Catherine H.; Pearman, Peter B.; Svenning, Jens-Christian
2010-01-01
Species distribution modelling has its origin in the late 1970s when computing capacity was limited. Early work in the field concentrated mostly on the development of methods to model effectively the shape of a species' response to environmental gradients (Austin 1987, Austin et al. 1990). The methodology and its framework were summarized in reviews 10–15 yr ago (Franklin 1995, Guisan and Zimmermann 2000), and these syntheses are still widely used as reference landmarks in the current distribution modelling literature. However, enormous advancements have occurred over the last decade, with hundreds – if not thousands – of publications on species distribution model (SDM) methodologies and their application to a broad set of conservation, ecological and evolutionary questions. With this special issue, originating from the third of a set of specialized SDM workshops (2008 Riederalp) entitled 'The Utility of Species Distribution Models as Tools for Conservation Ecology', we reflect on current trends and the progress achieved over the last decade.
Salinas, J. L.; Nester, T.; Komma, J.; Bloeschl, G.
2017-12-01
Generation of realistic synthetic spatial rainfall is of pivotal importance for assessing regional hydroclimatic hazard as the input for long term rainfall-runoff simulations. The correct reproduction of observed rainfall characteristics, such as regional intensity-duration-frequency curves, and spatial and temporal correlations is necessary to adequately model the magnitude and frequency of the flood peaks, by reproducing antecedent soil moisture conditions before extreme rainfall events, and joint probability of flood waves at confluences. In this work, a modification of the model presented by Bardossy and Platte (1992), where precipitation is first modeled on a station basis as a multivariate autoregressive model (mAr) in a Normal space. The spatial and temporal correlation structures are imposed in the Normal space, allowing for a different temporal autocorrelation parameter for each station, and simultaneously ensuring the positive-definiteness of the correlation matrix of the mAr errors. The Normal rainfall is then transformed to a Gamma-distributed space, with parameters varying monthly according to a sinusoidal function, in order to adapt to the observed rainfall seasonality. One of the main differences with the original model is the simulation time-step, reduced from 24h to 6h. Due to a larger availability of daily rainfall data, as opposite to sub-daily (e.g. hourly), the parameters of the Gamma distributions are calibrated to reproduce simultaneously a series of daily rainfall characteristics (mean daily rainfall, standard deviations of daily rainfall, and 24h intensity-duration-frequency [IDF] curves), as well as other aggregated rainfall measures (mean annual rainfall, and monthly rainfall). The calibration of the spatial and temporal correlation parameters is performed in a way that the catchment-averaged IDF curves aggregated at different temporal scales fit the measured ones. The rainfall model is used to generate 10.000 years of synthetic
Economic Models and Algorithms for Distributed Systems
Neumann, Dirk; Altmann, Jorn; Rana, Omer F
2009-01-01
Distributed computing models for sharing resources such as Grids, Peer-to-Peer systems, or voluntary computing are becoming increasingly popular. This book intends to discover fresh avenues of research and amendments to existing technologies, aiming at the successful deployment of commercial distributed systems
Distributed simulation a model driven engineering approach
Topçu, Okan; Oğuztüzün, Halit; Yilmaz, Levent
2016-01-01
Backed by substantive case studies, the novel approach to software engineering for distributed simulation outlined in this text demonstrates the potent synergies between model-driven techniques, simulation, intelligent agents, and computer systems development.
Incorporating uncertainty in predictive species distribution modelling.
Beale, Colin M; Lennon, Jack J
2012-01-19
Motivated by the need to solve ecological problems (climate change, habitat fragmentation and biological invasions), there has been increasing interest in species distribution models (SDMs). Predictions from these models inform conservation policy, invasive species management and disease-control measures. However, predictions are subject to uncertainty, the degree and source of which is often unrecognized. Here, we review the SDM literature in the context of uncertainty, focusing on three main classes of SDM: niche-based models, demographic models and process-based models. We identify sources of uncertainty for each class and discuss how uncertainty can be minimized or included in the modelling process to give realistic measures of confidence around predictions. Because this has typically not been performed, we conclude that uncertainty in SDMs has often been underestimated and a false precision assigned to predictions of geographical distribution. We identify areas where development of new statistical tools will improve predictions from distribution models, notably the development of hierarchical models that link different types of distribution model and their attendant uncertainties across spatial scales. Finally, we discuss the need to develop more defensible methods for assessing predictive performance, quantifying model goodness-of-fit and for assessing the significance of model covariates.
Quantifying rainfall-runoff relationships on the Mieso Hypo Calcic ...
African Journals Online (AJOL)
2012-04-17
Apr 17, 2012 ... and 2004 on 2 m x 2 m plots provided with a runoff measuring system, and replicated 3 times for each treatment. There were 2 treatments: .... a Tukulu form soil (Soil Classification Working Group, 1991) at. Glen. Details about the .... intervals by an automatic tipping-bucket rain gauge (Hobo. Event (C) Onset ...
Sample sizes and model comparison metrics for species distribution models
B.B. Hanberry; H.S. He; D.C. Dey
2012-01-01
Species distribution models use small samples to produce continuous distribution maps. The question of how small a sample can be to produce an accurate model generally has been answered based on comparisons to maximum sample sizes of 200 observations or fewer. In addition, model comparisons often are made with the kappa statistic, which has become controversial....
Modelling refrigerant distribution in minichannel evaporators
DEFF Research Database (Denmark)
Brix, Wiebke
of the liquid and vapour in the inlet manifold. Combining non-uniform airflow and non-uniform liquid and vapour distribution shows that a non-uniform airflow distribution to some degree can be compensated by a suitable liquid and vapour distribution. Controlling the superheat out of the individual channels...... to be equal, results in a cooling capacity very close to the optimum. A sensitivity study considering parameter changes shows that the course of the pressure gradient in the channel is significant, considering the magnitude of the capacity reductions due to non-uniform liquid and vapour distribution and non......This thesis is concerned with numerical modelling of flow distribution in a minichannel evaporator for air-conditioning. The study investigates the impact of non-uniform airflow and non-uniform distribution of the liquid and vapour phases in the inlet manifold on the refrigerant mass flow...
An Approach for Generating Precipitation Input for Worst-Case Flood Modelling
Felder, Guido; Weingartner, Rolf
2015-04-01
There is a lack of suitable methods for creating precipitation scenarios that can be used to realistically estimate peak discharges with very low probabilities. On the one hand, existing methods are methodically questionable when it comes to physical system boundaries. On the other hand, the spatio-temporal representativeness of precipitation patterns as system input is limited. In response, this study proposes a method of deriving representative spatio-temporal precipitation patterns and presents a step towards making methodically correct estimations of infrequent floods by using a worst-case approach. A Monte-Carlo rainfall-runoff model allows for the testing of a wide range of different spatio-temporal distributions of an extreme precipitation event and therefore for the generation of a hydrograph for each of these distributions. Out of these numerous hydrographs and their corresponding peak discharges, the worst-case catchment reactions on the system input can be derived. The spatio-temporal distributions leading to the highest peak discharges are identified and can eventually be used for further investigations.
GIS-Based KW-GIUH hydrological model of semiarid catchments: The case of Faria Catchment, Palestine
International Nuclear Information System (INIS)
Shadeed, S.; Shaheen, H.; Jayyousi, A.
2007-01-01
Among the most basic challenges of hydrology are the quantitative understanding of the processes of runoff generation and prediction of flow hydrographs. Traditional techniques have been widely applied for the estimation of runoff hydrographs of gauged catchments using historical rainfall-runoff data and unit hydrographs. Such procedures are questioned as to their reliability and their application to ungauged, arid and semiarid catchments. To overcome such difficulties, the use of physically based rainfall-runoff process of Faria Catchment using the lately developed KW-GIUH. Faria catchment, located in the northeastern part of the West Bank, Palestine, is characterized as a semiarid region with annual rainfall depths ranging on average from 150 to 640 mm at both ends of the catchment. The Geographical Information System (GIS) techniques were used to shape the geomorphological features of the catchment. A GIS based KW-GIUH hydrological model was used to stimulate the rainfall-runoff process in the three sub-catchments of Faria, namely: Al-Badan, Al-Faria and Al-Malaqi. The simulated runoff hydrographs proved that the GIS-based KW-GIUH model is applicable to semiarid regions and can be used to estimate the unit hydrographs in the West Bank catchments. (author)
HYSOGs250m, global gridded hydrologic soil groups for curve-number-based runoff modeling.
Ross, C Wade; Prihodko, Lara; Anchang, Julius; Kumar, Sanath; Ji, Wenjie; Hanan, Niall P
2018-05-15
Hydrologic soil groups (HSGs) are a fundamental component of the USDA curve-number (CN) method for estimation of rainfall runoff; yet these data are not readily available in a format or spatial-resolution suitable for regional- and global-scale modeling applications. We developed a globally consistent, gridded dataset defining HSGs from soil texture, bedrock depth, and groundwater. The resulting data product-HYSOGs250m-represents runoff potential at 250 m spatial resolution. Our analysis indicates that the global distribution of soil is dominated by moderately high runoff potential, followed by moderately low, high, and low runoff potential. Low runoff potential, sandy soils are found primarily in parts of the Sahara and Arabian Deserts. High runoff potential soils occur predominantly within tropical and sub-tropical regions. No clear pattern could be discerned for moderately low runoff potential soils, as they occur in arid and humid environments and at both high and low elevations. Potential applications of this data include CN-based runoff modeling, flood risk assessment, and as a covariate for biogeographical analysis of vegetation distributions.
Mathematical Models for Room Air Distribution
DEFF Research Database (Denmark)
Nielsen, Peter V.
1982-01-01
A number of different models on the air distribution in rooms are introduced. This includes the throw model, a model on penetration length of a cold wall jet and a model for maximum velocity in the dimensioning of an air distribution system in highly loaded rooms and shows that the amount of heat...... removed from the room at constant penetration length is proportional to the cube of the velocities in the occupied zone. It is also shown that a large number of diffusers increases the amount of heat which may be removed without affecting the thermal conditions. Control strategies for dual duct and single...... duct systems are given and the paper is concluded by mentioning a computer-based prediction method which gives the velocity and temperature distribution in the whole room....
Mathematical Models for Room Air Distribution - Addendum
DEFF Research Database (Denmark)
Nielsen, Peter V.
1982-01-01
A number of different models on the air distribution in rooms are introduced. This includes the throw model, a model on penetration length of a cold wall jet and a model for maximum velocity in the dimensioning of an air distribution system in highly loaded rooms and shows that the amount of heat...... removed from the room at constant penetration length is proportional to the cube of the velocities in the occupied zone. It is also shown that a large number of diffusers increases the amount of heat which may be removed without affecting the thermal conditions. Control strategies for dual duct and single...... duct systems are given and the paper is concluded by mentioning a computer-based prediction method which gives the velocity and temperature distribution in the whole room....
A Hierarchy Model of Income Distribution
Fix, Blair
2018-01-01
Based on worldly experience, most people would agree that firms are hierarchically organized, and that pay tends to increase as one moves up the hierarchy. But how this hierarchical structure affects income distribution has not been widely studied. To remedy this situation, this paper presents a new model of income distribution that explores the effects of social hierarchy. This ‘hierarchy model’ takes the limited available evidence on the structure of firm hierarchies and generalizes it to c...
International Nuclear Information System (INIS)
Stanzel, Ph; Kahl, B; Haberl, U; Herrnegger, M; Nachtnebel, H P
2008-01-01
A hydrological modelling framework applied within operational flood forecasting systems in three alpine Danube tributary basins, Traisen, Salzach and Enns, is presented. A continuous, semi-distributed rainfall-runoff model, accounting for the main hydrological processes of snow accumulation and melt, interception, evapotranspiration, infiltration, runoff generation and routing is set up. Spatial discretization relies on the division of watersheds into subbasins and subsequently into hydrologic response units based on spatial information on soil types, land cover and elevation bands. The hydrological models are calibrated with meteorological ground measurements and with meteorological analyses incorporating radar information. Operationally, each forecasting sequence starts with the re-calculation of the last 24 to 48 hours. Errors between simulated and observed runoff are minimized by optimizing a correction factor for the input to provide improved system states. For the hydrological forecast quantitative 48 or 72 hour forecast grids of temperature and precipitation - deterministic and probabilistic - are used as input. The forecasted hydrograph is corrected with an autoregressive model. The forecasting sequences are repeated each 15 minutes. First evaluations of resulting hydrological forecasts are presented and reliability of forecasts with different lead times is discussed.
Modeling a Distribution of Mortgage Credit Losses
Czech Academy of Sciences Publication Activity Database
Gapko, Petr; Šmíd, Martin
2012-01-01
Roč. 60, č. 10 (2012), s. 1005-1023 ISSN 0013-3035 R&D Projects: GA ČR GD402/09/H045; GA ČR(CZ) GBP402/12/G097 Grant - others:Univerzita Karlova(CZ) 46108 Institutional research plan: CEZ:AV0Z10750506 Institutional support: RVO:67985556 Keywords : credit risk * mortgage * delinquency rate * generalized hyperbolic distribution * normal distribution Subject RIV: AH - Economics Impact factor: 0.194, year: 2012 http://library.utia.cas.cz/separaty/2013/E/smid-modeling a distribution of mortgage credit losses.pdf
Modeling a Distribution of Mortgage Credit Losses
Czech Academy of Sciences Publication Activity Database
Gapko, Petr; Šmíd, Martin
2010-01-01
Roč. 23, č. 23 (2010), s. 1-23 R&D Projects: GA ČR GA402/09/0965; GA ČR GD402/09/H045 Grant - others:Univerzita Karlova - GAUK(CZ) 46108 Institutional research plan: CEZ:AV0Z10750506 Keywords : Credit Risk * Mortgage * Delinquency Rate * Generalized Hyperbolic Distribution * Normal Distribution Subject RIV: AH - Economics http://library.utia.cas.cz/separaty/2010/E/gapko-modeling a distribution of mortgage credit losses-ies wp.pdf
Advanced Distribution Network Modelling with Distributed Energy Resources
O'Connell, Alison
The addition of new distributed energy resources, such as electric vehicles, photovoltaics, and storage, to low voltage distribution networks means that these networks will undergo major changes in the future. Traditionally, distribution systems would have been a passive part of the wider power system, delivering electricity to the customer and not needing much control or management. However, the introduction of these new technologies may cause unforeseen issues for distribution networks, due to the fact that they were not considered when the networks were originally designed. This thesis examines different types of technologies that may begin to emerge on distribution systems, as well as the resulting challenges that they may impose. Three-phase models of distribution networks are developed and subsequently utilised as test cases. Various management strategies are devised for the purposes of controlling distributed resources from a distribution network perspective. The aim of the management strategies is to mitigate those issues that distributed resources may cause, while also keeping customers' preferences in mind. A rolling optimisation formulation is proposed as an operational tool which can manage distributed resources, while also accounting for the uncertainties that these resources may present. Network sensitivities for a particular feeder are extracted from a three-phase load flow methodology and incorporated into an optimisation. Electric vehicles are the focus of the work, although the method could be applied to other types of resources. The aim is to minimise the cost of electric vehicle charging over a 24-hour time horizon by controlling the charge rates and timings of the vehicles. The results demonstrate the advantage that controlled EV charging can have over an uncontrolled case, as well as the benefits provided by the rolling formulation and updated inputs in terms of cost and energy delivered to customers. Building upon the rolling optimisation, a
Dynamic models for distributed generation resources
Energy Technology Data Exchange (ETDEWEB)
Morched, A.S. [BPR Energie, Sherbrooke, PQ (Canada)
2010-07-01
Distributed resources can impact the performance of host power systems during both normal and abnormal system conditions. This PowerPoint presentation discussed the use of dynamic models for identifying potential interaction problems between interconnected systems. The models were designed to simulate steady state behaviour as well as transient responses to system disturbances. The distributed generators included directly coupled and electronically coupled generators. The directly coupled generator was driven by wind turbines. Simplified models of grid-side inverters, electronically coupled wind generators and doubly-fed induction generators (DFIGs) were presented. The responses of DFIGs to wind variations were evaluated. Synchronous machine and electronically coupled generator responses were compared. The system model components included load models, generators, protection systems, and system equivalents. Frequency responses to islanding events were reviewed. The study demonstrated that accurate simulations are needed to predict the impact of distributed generation resources on the performance of host systems. Advances in distributed generation technology have outpaced the development of models needed for integration studies. tabs., figs.
Itzï (version 17.1): an open-source, distributed GIS model for dynamic flood simulation
Guillaume Courty, Laurent; Pedrozo-Acuña, Adrián; Bates, Paul David
2017-05-01
Worldwide, floods are acknowledged as one of the most destructive hazards. In human-dominated environments, their negative impacts are ascribed not only to the increase in frequency and intensity of floods but also to a strong feedback between the hydrological cycle and anthropogenic development. In order to advance a more comprehensive understanding of this complex interaction, this paper presents the development of a new open-source tool named Itzï that enables the 2-D numerical modelling of rainfall-runoff processes and surface flows integrated with the open-source geographic information system (GIS) software known as GRASS. Therefore, it takes advantage of the ability given by GIS environments to handle datasets with variations in both temporal and spatial resolutions. Furthermore, the presented numerical tool can handle datasets from different sources with varied spatial resolutions, facilitating the preparation and management of input and forcing data. This ability reduces the preprocessing time usually required by other models. Itzï uses a simplified form of the shallow water equations, the damped partial inertia equation, for the resolution of surface flows, and the Green-Ampt model for the infiltration. The source code is now publicly available online, along with complete documentation. The numerical model is verified against three different tests cases: firstly, a comparison with an analytic solution of the shallow water equations is introduced; secondly, a hypothetical flooding event in an urban area is implemented, where results are compared to those from an established model using a similar approach; and lastly, the reproduction of a real inundation event that occurred in the city of Kingston upon Hull, UK, in June 2007, is presented. The numerical approach proved its ability at reproducing the analytic and synthetic test cases. Moreover, simulation results of the real flood event showed its suitability at identifying areas affected by flooding
Laiolo, Paola; Gabellani, Simone; Rudari, Roberto; Boni, Giorgio; Puca, Silvia
2013-04-01
Soil moisture plays a fundamental role in the partitioning of mass and energy fluxes between land surface and atmosphere, thereby influencing climate and weather, and it is important in determining the rainfall-runoff response of catchments; moreover, in hydrological modelling and flood forecasting, a correct definition of moisture conditions is a key factor for accurate predictions. Different sources of information for the estimation of the soil moisture state are currently available: satellite data, point measurements and model predictions. All are affected by intrinsic uncertainty. Among different satellite sensors that can be used for soil moisture estimation three major groups can be distinguished: passive microwave sensors (e.g., SSMI), active sensors (e.g. SAR, Scatterometers), and optical sensors (e.g. Spectroradiometers). The last two families, mainly because of their temporal and spatial resolution seem the most suitable for hydrological applications In this work soil moisture point measurements from 10 sensors in the Italian territory are compared of with the satellite products both from the HSAF project SM-OBS-2, derived from the ASCAT scatterometer, and from ACHAB, an operative energy balance model that assimilate LST data derived from MSG and furnishes daily an evaporative fraction index related to soil moisture content for all the Italian region. Distributed comparison of the ACHAB and SM-OBS-2 on the whole Italian territory are performed too.
Distributed model predictive control made easy
Negenborn, Rudy
2014-01-01
The rapid evolution of computer science, communication, and information technology has enabled the application of control techniques to systems beyond the possibilities of control theory just a decade ago. Critical infrastructures such as electricity, water, traffic and intermodal transport networks are now in the scope of control engineers. The sheer size of such large-scale systems requires the adoption of advanced distributed control approaches. Distributed model predictive control (MPC) is one of the promising control methodologies for control of such systems. This book provides a state-of-the-art overview of distributed MPC approaches, while at the same time making clear directions of research that deserve more attention. The core and rationale of 35 approaches are carefully explained. Moreover, detailed step-by-step algorithmic descriptions of each approach are provided. These features make the book a comprehensive guide both for those seeking an introduction to distributed MPC as well as for those ...
Applications of species distribution modeling to paleobiology
DEFF Research Database (Denmark)
Svenning, Jens-Christian; Fløjgaard, Camilla; Marske, Katharine Ann
2011-01-01
-Pleistocene megafaunal extinctions, past community assembly, human paleobiogeography, Holocene paleoecology, and even deep-time biogeography (notably, providing insights into biogeographic dynamics >400 million years ago). We discuss important assumptions and uncertainties that affect the SDM approach to paleobiology......Species distribution modeling (SDM: statistical and/or mechanistic approaches to the assessment of range determinants and prediction of species occurrence) offers new possibilities for estimating and studying past organism distributions. SDM complements fossil and genetic evidence by providing (i......) quantitative and potentially high-resolution predictions of the past organism distributions, (ii) statistically formulated, testable ecological hypotheses regarding past distributions and communities, and (iii) statistical assessment of range determinants. In this article, we provide an overview...
Modeling Word Burstiness Using the Dirichlet Distribution
DEFF Research Database (Denmark)
Madsen, Rasmus Elsborg; Kauchak, David; Elkan, Charles
2005-01-01
Multinomial distributions are often used to model text documents. However, they do not capture well the phenomenon that words in a document tend to appear in bursts: if a word appears once, it is more likely to appear again. In this paper, we propose the Dirichlet compound multinomial model (DCM......) as an alternative to the multinomial. The DCM model has one additional degree of freedom, which allows it to capture burstiness. We show experimentally that the DCM is substantially better than the multinomial at modeling text data, measured by perplexity. We also show using three standard document collections...
Overhead distribution line models for harmonics studies
Energy Technology Data Exchange (ETDEWEB)
Nagpal, M.; Xu, W.; Dommel, H.W.
1994-01-01
Carson's formulae and Maxwell's potential coefficients are used for calculating the per unit length series impedances and shunt capacitances of the overhead lines. The per unit length values are then used for building the models, nominal pi-circuit, and equivalent pi-circuit at the harmonic frequencies. This paper studies the accuracy of these models for presenting the overhead distribution lines in steady-state harmonic solutions at frequencies up to 5 kHz. The models are verified with a field test on a 25 kV distribution line and the sensitivity of the models to ground resistivity, skin effect, and multiple grounding is reported.
A DISTRIBUTED HYPERMAP MODEL FOR INTERNET GIS
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
The rapid development of Internet technology makes it possible to integrate GIS with the Internet,forming Internet GIS.Internet GIS is based on a distributed client/server architecture and TCP/IP & IIOP.When constructing and designing Internet GIS,we face the problem of how to express information units of Internet GIS.In order to solve this problem,this paper presents a distributed hypermap model for Internet GIS.This model provides a solution to organize and manage Internet GIS information units.It also illustrates relations between two information units and in an internal information unit both on clients and servers.On the basis of this model,the paper contributes to the expressions of hypermap relations and hypermap operations.The usage of this model is shown in the implementation of a prototype system.
Programming model for distributed intelligent systems
Sztipanovits, J.; Biegl, C.; Karsai, G.; Bogunovic, N.; Purves, B.; Williams, R.; Christiansen, T.
1988-01-01
A programming model and architecture which was developed for the design and implementation of complex, heterogeneous measurement and control systems is described. The Multigraph Architecture integrates artificial intelligence techniques with conventional software technologies, offers a unified framework for distributed and shared memory based parallel computational models and supports multiple programming paradigms. The system can be implemented on different hardware architectures and can be adapted to strongly different applications.
Modelling Dynamic Forgetting in Distributed Information Systems
N.F. Höning (Nicolas); M.C. Schut
2010-01-01
htmlabstractWe describe and model a new aspect in the design of distributed information systems. We build upon a previously described problem on the microlevel, which asks how quickly agents should discount (forget) their experience: If they cherish their memories, they can build their reports on
Comparison of sparse point distribution models
DEFF Research Database (Denmark)
Erbou, Søren Gylling Hemmingsen; Vester-Christensen, Martin; Larsen, Rasmus
2010-01-01
This paper compares several methods for obtaining sparse and compact point distribution models suited for data sets containing many variables. These are evaluated on a database consisting of 3D surfaces of a section of the pelvic bone obtained from CT scans of 33 porcine carcasses. The superior m...
A Distributive Model of Treatment Acceptability
Carter, Stacy L.
2008-01-01
A model of treatment acceptability is proposed that distributes overall treatment acceptability into three separate categories of influence. The categories are comprised of societal influences, consultant influences, and influences associated with consumers of treatments. Each of these categories are defined and their inter-relationships within…
Finessing atlas data for species distribution models
Niamir, A.; Skidmore, A.K.; Toxopeus, A.G.; Munoz, A.R.; Real, R.
2011-01-01
Aim The spatial resolution of species atlases and therefore resulting model predictions are often too coarse for local applications. Collecting distribution data at a finer resolution for large numbers of species requires a comprehensive sampling effort, making it impractical and expensive. This
Modelling simple helically delivered dose distributions
International Nuclear Information System (INIS)
Fenwick, John D; Tome, Wolfgang A; Kissick, Michael W; Mackie, T Rock
2005-01-01
In a previous paper, we described quality assurance procedures for Hi-Art helical tomotherapy machines. Here, we develop further some ideas discussed briefly in that paper. Simple helically generated dose distributions are modelled, and relationships between these dose distributions and underlying characteristics of Hi-Art treatment systems are elucidated. In particular, we describe the dependence of dose levels along the central axis of a cylinder aligned coaxially with a Hi-Art machine on fan beam width, couch velocity and helical delivery lengths. The impact on these dose levels of angular variations in gantry speed or output per linear accelerator pulse is also explored
A void distribution model-flashing flow
International Nuclear Information System (INIS)
Riznic, J.; Ishii, M.; Afgan, N.
1987-01-01
A new model for flashing flow based on wall nucleations is proposed here and the model predictions are compared with some experimental data. In order to calculate the bubble number density, the bubble number transport equation with a distributed source from the wall nucleation sites was used. Thus it was possible to avoid the usual assumption of a constant bubble number density. Comparisons of the model with the data shows that the model based on the nucleation site density correlation appears to be acceptable to describe the vapor generation in the flashing flow. For the limited data examined, the comparisons show rather satisfactory agreement without using a floating parameter to adjust the model. This result indicated that, at least for the experimental conditions considered here, the mechanistic predictions of the flashing phenomenon is possible on the present wall nucleation based model
Modeling error distributions of growth curve models through Bayesian methods.
Zhang, Zhiyong
2016-06-01
Growth curve models are widely used in social and behavioral sciences. However, typical growth curve models often assume that the errors are normally distributed although non-normal data may be even more common than normal data. In order to avoid possible statistical inference problems in blindly assuming normality, a general Bayesian framework is proposed to flexibly model normal and non-normal data through the explicit specification of the error distributions. A simulation study shows when the distribution of the error is correctly specified, one can avoid the loss in the efficiency of standard error estimates. A real example on the analysis of mathematical ability growth data from the Early Childhood Longitudinal Study, Kindergarten Class of 1998-99 is used to show the application of the proposed methods. Instructions and code on how to conduct growth curve analysis with both normal and non-normal error distributions using the the MCMC procedure of SAS are provided.
Modelling refrigerant distribution in microchannel evaporators
DEFF Research Database (Denmark)
Brix, Wiebke; Kærn, Martin Ryhl; Elmegaard, Brian
2009-01-01
of the refrigerant distribution is carried out for two channels in parallel and for two different cases. In the first case maldistribution of the inlet quality into the channels is considered, and in the second case a non-uniform airflow on the secondary side is considered. In both cases the total mixed superheat...... out of the evaporator is kept constant. It is shown that the cooling capacity of the evaporator is reduced significantly, both in the case of unevenly distributed inlet quality and for the case of non-uniform airflow on the outside of the channels.......The effects of refrigerant maldistribution in parallel evaporator channels on the heat exchanger performance are investigated numerically. For this purpose a 1D steady state model of refrigerant R134a evaporating in a microchannel tube is built and validated against other evaporator models. A study...
Statistical models based on conditional probability distributions
International Nuclear Information System (INIS)
Narayanan, R.S.
1991-10-01
We present a formulation of statistical mechanics models based on conditional probability distribution rather than a Hamiltonian. We show that it is possible to realize critical phenomena through this procedure. Closely linked with this formulation is a Monte Carlo algorithm, in which a configuration generated is guaranteed to be statistically independent from any other configuration for all values of the parameters, in particular near the critical point. (orig.)
Equifinality and process-based modelling
Khatami, S.; Peel, M. C.; Peterson, T. J.; Western, A. W.
2017-12-01
Equifinality is understood as one of the fundamental difficulties in the study of open complex systems, including catchment hydrology. A review of the hydrologic literature reveals that the term equifinality has been widely used, but in many cases inconsistently and without coherent recognition of the various facets of equifinality, which can lead to ambiguity but also methodological fallacies. Therefore, in this study we first characterise the term equifinality within the context of hydrological modelling by reviewing the genesis of the concept of equifinality and then presenting a theoretical framework. During past decades, equifinality has mainly been studied as a subset of aleatory (arising due to randomness) uncertainty and for the assessment of model parameter uncertainty. Although the connection between parameter uncertainty and equifinality is undeniable, we argue there is more to equifinality than just aleatory parameter uncertainty. That is, the importance of equifinality and epistemic uncertainty (arising due to lack of knowledge) and their implications is overlooked in our current practice of model evaluation. Equifinality and epistemic uncertainty in studying, modelling, and evaluating hydrologic processes are treated as if they can be simply discussed in (or often reduced to) probabilistic terms (as for aleatory uncertainty). The deficiencies of this approach to conceptual rainfall-runoff modelling are demonstrated for selected Australian catchments by examination of parameter and internal flux distributions and interactions within SIMHYD. On this basis, we present a new approach that expands equifinality concept beyond model parameters to inform epistemic uncertainty. The new approach potentially facilitates the identification and development of more physically plausible models and model evaluation schemes particularly within the multiple working hypotheses framework, and is generalisable to other fields of environmental modelling as well.
Petroselli, A.; Grimaldi, S.; Romano, N.
2012-12-01
The Soil Conservation Service - Curve Number (SCS-CN) method is a popular rainfall-runoff model widely used to estimate losses and direct runoff from a given rainfall event, but its use is not appropriate at sub-daily time resolution. To overcome this drawback, a mixed procedure, referred to as CN4GA (Curve Number for Green-Ampt), was recently developed including the Green-Ampt (GA) infiltration model and aiming to distribute in time the information provided by the SCS-CN method. The main concept of the proposed mixed procedure is to use the initial abstraction and the total volume given by the SCS-CN to calibrate the Green-Ampt soil hydraulic conductivity parameter. The procedure is here applied on a real case study and a sensitivity analysis concerning the remaining parameters is presented; results show that CN4GA approach is an ideal candidate for the rainfall excess analysis at sub-daily time resolution, in particular for ungauged basin lacking of discharge observations.
A distributed snow-evolution modeling system (SnowModel)
Glen E. Liston; Kelly. Elder
2006-01-01
SnowModel is a spatially distributed snow-evolution modeling system designed for application in landscapes, climates, and conditions where snow occurs. It is an aggregation of four submodels: MicroMet defines meteorological forcing conditions, EnBal calculates surface energy exchanges, SnowPack simulates snow depth and water-equivalent evolution, and SnowTran-3D...
Application of a baseflow filter for evaluating model structure suitability of the IHACRES CMD
Kim, H. S.
2015-02-01
The main objective of this study was to assess the predictive uncertainty from the rainfall-runoff model structure coupling a conceptual module (non-linear module) with a metric transfer function module (linear module). The methodology was primarily based on the comparison between the outputs of the rainfall-runoff model and those from an alternative model approach. An alternative model approach was used to minimise uncertainties arising from data and the model structure. A baseflow filter was adopted to better understand deficiencies in the forms of the rainfall-runoff model by avoiding the uncertainties related to data and the model structure. The predictive uncertainty from the model structure was investigated for representative groups of catchments having similar hydrological response characteristics in the upper Murrumbidgee Catchment. In the assessment of model structure suitability, the consistency (or variability) of catchment response over time and space in model performance and parameter values has been investigated to detect problems related to the temporal and spatial variability of the model accuracy. The predictive error caused by model uncertainty was evaluated through analysis of the variability of the model performance and parameters. A graphical comparison of model residuals, effective rainfall estimates and hydrographs was used to determine a model's ability related to systematic model deviation between simulated and observed behaviours and general behavioural differences in the timing and magnitude of peak flows. The model's predictability was very sensitive to catchment response characteristics. The linear module performs reasonably well in the wetter catchments but has considerable difficulties when applied to the drier catchments where a hydrologic response is dominated by quick flow. The non-linear module has a potential limitation in its capacity to capture non-linear processes for converting observed rainfall into effective rainfall in
Sworn testimony of the model evidence: Gaussian Mixture Importance (GAME) sampling
Volpi, Elena; Schoups, Gerrit; Firmani, Giovanni; Vrugt, Jasper A.
2017-07-01
What is the "best" model? The answer to this question lies in part in the eyes of the beholder, nevertheless a good model must blend rigorous theory with redeeming qualities such as parsimony and quality of fit. Model selection is used to make inferences, via weighted averaging, from a set of K candidate models, Mk; k=>(1,…,K>), and help identify which model is most supported by the observed data, Y>˜=>(y˜1,…,y˜n>). Here, we introduce a new and robust estimator of the model evidence, p>(Y>˜|Mk>), which acts as normalizing constant in the denominator of Bayes' theorem and provides a single quantitative measure of relative support for each hypothesis that integrates model accuracy, uncertainty, and complexity. However, p>(Y>˜|Mk>) is analytically intractable for most practical modeling problems. Our method, coined GAussian Mixture importancE (GAME) sampling, uses bridge sampling of a mixture distribution fitted to samples of the posterior model parameter distribution derived from MCMC simulation. We benchmark the accuracy and reliability of GAME sampling by application to a diverse set of multivariate target distributions (up to 100 dimensions) with known values of p>(Y>˜|Mk>) and to hypothesis testing using numerical modeling of the rainfall-runoff transformation of the Leaf River watershed in Mississippi, USA. These case studies demonstrate that GAME sampling provides robust and unbiased estimates of the evidence at a relatively small computational cost outperforming commonly used estimators. The GAME sampler is implemented in the MATLAB package of DREAM and simplifies considerably scientific inquiry through hypothesis testing and model selection.
Reconsideration of mass-distribution models
Directory of Open Access Journals (Sweden)
Ninković S.
2014-01-01
Full Text Available The mass-distribution model proposed by Kuzmin and Veltmann (1973 is revisited. It is subdivided into two models which have a common case. Only one of them is subject of the present study. The study is focused on the relation between the density ratio (the central one to that corresponding to the core radius and the total-mass fraction within the core radius. The latter one is an increasing function of the former one, but it cannot exceed one quarter, which takes place when the density ratio tends to infinity. Therefore, the model is extended by representing the density as a sum of two components. The extension results into possibility of having a correspondence between the infinite density ratio and 100% total-mass fraction. The number of parameters in the extended model exceeds that of the original model. Due to this, in the extended model, the correspondence between the density ratio and total-mass fraction is no longer one-to-one; several values of the total-mass fraction can correspond to the same value for the density ratio. In this way, the extended model could explain the contingency of having two, or more, groups of real stellar systems (subsystems in the diagram total-mass fraction versus density ratio. [Projekat Ministarstva nauke Republike Srbije, br. 176011: Dynamics and Kinematics of Celestial Bodies and Systems
Ballistic model to estimate microsprinkler droplet distribution
Directory of Open Access Journals (Sweden)
Conceição Marco Antônio Fonseca
2003-01-01
Full Text Available Experimental determination of microsprinkler droplets is difficult and time-consuming. This determination, however, could be achieved using ballistic models. The present study aimed to compare simulated and measured values of microsprinkler droplet diameters. Experimental measurements were made using the flour method, and simulations using a ballistic model adopted by the SIRIAS computational software. Drop diameters quantified in the experiment varied between 0.30 mm and 1.30 mm, while the simulated between 0.28 mm and 1.06 mm. The greatest differences between simulated and measured values were registered at the highest radial distance from the emitter. The model presented a performance classified as excellent for simulating microsprinkler drop distribution.
Rodríguez-Rincón, J. P.; Pedrozo-Acuña, A.; Breña-Naranjo, J. A.
2015-07-01
This investigation aims to study the propagation of meteorological uncertainty within a cascade modelling approach to flood prediction. The methodology was comprised of a numerical weather prediction (NWP) model, a distributed rainfall-runoff model and a 2-D hydrodynamic model. The uncertainty evaluation was carried out at the meteorological and hydrological levels of the model chain, which enabled the investigation of how errors that originated in the rainfall prediction interact at a catchment level and propagate to an estimated inundation area and depth. For this, a hindcast scenario is utilised removing non-behavioural ensemble members at each stage, based on the fit with observed data. At the hydrodynamic level, an uncertainty assessment was not incorporated; instead, the model was setup following guidelines for the best possible representation of the case study. The selected extreme event corresponds to a flood that took place in the southeast of Mexico during November 2009, for which field data (e.g. rain gauges; discharge) and satellite imagery were available. Uncertainty in the meteorological model was estimated by means of a multi-physics ensemble technique, which is designed to represent errors from our limited knowledge of the processes generating precipitation. In the hydrological model, a multi-response validation was implemented through the definition of six sets of plausible parameters from past flood events. Precipitation fields from the meteorological model were employed as input in a distributed hydrological model, and resulting flood hydrographs were used as forcing conditions in the 2-D hydrodynamic model. The evolution of skill within the model cascade shows a complex aggregation of errors between models, suggesting that in valley-filling events hydro-meteorological uncertainty has a larger effect on inundation depths than that observed in estimated flood inundation extents.
Distributed Bayesian Networks for User Modeling
DEFF Research Database (Denmark)
Tedesco, Roberto; Dolog, Peter; Nejdl, Wolfgang
2006-01-01
The World Wide Web is a popular platform for providing eLearning applications to a wide spectrum of users. However – as users differ in their preferences, background, requirements, and goals – applications should provide personalization mechanisms. In the Web context, user models used by such ada......The World Wide Web is a popular platform for providing eLearning applications to a wide spectrum of users. However – as users differ in their preferences, background, requirements, and goals – applications should provide personalization mechanisms. In the Web context, user models used...... by such adaptive applications are often partial fragments of an overall user model. The fragments have then to be collected and merged into a global user profile. In this paper we investigate and present algorithms able to cope with distributed, fragmented user models – based on Bayesian Networks – in the context...... of Web-based eLearning platforms. The scenario we are tackling assumes learners who use several systems over time, which are able to create partial Bayesian Networks for user models based on the local system context. In particular, we focus on how to merge these partial user models. Our merge mechanism...
Broadband model of the distribution network
DEFF Research Database (Denmark)
Jensen, Martin Høgdahl
for circular conductors involving Bessel series. The two methods show equal values of resistance, but there is considerable difference in the values of internal inductance. A method for calculation of proximity effect is derived for a two-conductor configuration. This method is expanded to the use...... of frequency up to 200 kHz. The square wave measurements reveal the complete capacitance matrice at a frequency of approximately 12.5 MHz as well as the series inductance between the four conductors. The influence of non-ideal ground could not be measured due to the high impedance of the grounding device...... measurement and simulation, once the Phase model is used. No explanation is found on why the new material properties cause error in the Phase model. At the kyndby 10 kV test site a non-linear load is inserted on the secondary side of normal distribution transformer and the phase voltage and current...
How can model comparison help improving species distribution models?
Directory of Open Access Journals (Sweden)
Emmanuel Stephan Gritti
Full Text Available Today, more than ever, robust projections of potential species range shifts are needed to anticipate and mitigate the impacts of climate change on biodiversity and ecosystem services. Such projections are so far provided almost exclusively by correlative species distribution models (correlative SDMs. However, concerns regarding the reliability of their predictive power are growing and several authors call for the development of process-based SDMs. Still, each of these methods presents strengths and weakness which have to be estimated if they are to be reliably used by decision makers. In this study we compare projections of three different SDMs (STASH, LPJ and PHENOFIT that lie in the continuum between correlative models and process-based models for the current distribution of three major European tree species, Fagussylvatica L., Quercusrobur L. and Pinussylvestris L. We compare the consistency of the model simulations using an innovative comparison map profile method, integrating local and multi-scale comparisons. The three models simulate relatively accurately the current distribution of the three species. The process-based model performs almost as well as the correlative model, although parameters of the former are not fitted to the observed species distributions. According to our simulations, species range limits are triggered, at the European scale, by establishment and survival through processes primarily related to phenology and resistance to abiotic stress rather than to growth efficiency. The accuracy of projections of the hybrid and process-based model could however be improved by integrating a more realistic representation of the species resistance to water stress for instance, advocating for pursuing efforts to understand and formulate explicitly the impact of climatic conditions and variations on these processes.
Koskela, J. J.; Croke, B. W. F.; Koivusalo, H.; Jakeman, A. J.; Kokkonen, T.
2012-11-01
Bayesian inference is used to study the effect of precipitation and model structural uncertainty on estimates of model parameters and confidence limits of predictive variables in a conceptual rainfall-runoff model in the snow-fed Rudbäck catchment (142 ha) in southern Finland. The IHACRES model is coupled with a simple degree day model to account for snow accumulation and melt. The posterior probability distribution of the model parameters is sampled by using the Differential Evolution Adaptive Metropolis (DREAM(ZS)) algorithm and the generalized likelihood function. Precipitation uncertainty is taken into account by introducing additional latent variables that were used as multipliers for individual storm events. Results suggest that occasional snow water equivalent (SWE) observations together with daily streamflow observations do not contain enough information to simultaneously identify model parameters, precipitation uncertainty and model structural uncertainty in the Rudbäck catchment. The addition of an autoregressive component to account for model structure error and latent variables having uniform priors to account for input uncertainty lead to dubious posterior distributions of model parameters. Thus our hypothesis that informative priors for latent variables could be replaced by additional SWE data could not be confirmed. The model was found to work adequately in 1-day-ahead simulation mode, but the results were poor in the simulation batch mode. This was caused by the interaction of parameters that were used to describe different sources of uncertainty. The findings may have lessons for other cases where parameterizations are similarly high in relation to available prior information.
An urban runoff model designed to inform stormwater management decisions.
Beck, Nicole G; Conley, Gary; Kanner, Lisa; Mathias, Margaret
2017-05-15
We present an urban runoff model designed for stormwater managers to quantify runoff reduction benefits of mitigation actions that has lower input data and user expertise requirements than most commonly used models. The stormwater tool to estimate load reductions (TELR) employs a semi-distributed approach, where landscape characteristics and process representation are spatially-lumped within urban catchments on the order of 100 acres (40 ha). Hydrologic computations use a set of metrics that describe a 30-year rainfall distribution, combined with well-tested algorithms for rainfall-runoff transformation and routing to generate average annual runoff estimates for each catchment. User inputs include the locations and specifications for a range of structural best management practice (BMP) types. The model was tested in a set of urban catchments within the Lake Tahoe Basin of California, USA, where modeled annual flows matched that of the observed flows within 18% relative error for 5 of the 6 catchments and had good regional performance for a suite of performance metrics. Comparisons with continuous simulation models showed an average of 3% difference from TELR predicted runoff for a range of hypothetical urban catchments. The model usually identified the dominant BMP outflow components within 5% relative error of event-based measured flow data and simulated the correct proportionality between outflow components. TELR has been implemented as a web-based platform for use by municipal stormwater managers to inform prioritization, report program benefits and meet regulatory reporting requirements (www.swtelr.com). Copyright © 2017. Published by Elsevier Ltd.
Jain, Ashu; Srinivasulu, Sanaga
2006-02-01
This paper presents the findings of a study aimed at decomposing a flow hydrograph into different segments based on physical concepts in a catchment, and modelling different segments using different technique viz. conceptual and artificial neural networks (ANNs). An integrated modelling framework is proposed capable of modelling infiltration, base flow, evapotranspiration, soil moisture accounting, and certain segments of the decomposed flow hydrograph using conceptual techniques and the complex, non-linear, and dynamic rainfall-runoff process using ANN technique. Specifically, five different multi-layer perceptron (MLP) and two self-organizing map (SOM) models have been developed. The rainfall and streamflow data derived from the Kentucky River catchment were employed to test the proposed methodology and develop all the models. The performance of all the models was evaluated using seven different standard statistical measures. The results obtained in this study indicate that (a) the rainfall-runoff relationship in a large catchment consists of at least three or four different mappings corresponding to different dynamics of the underlying physical processes, (b) an integrated approach that models the different segments of the decomposed flow hydrograph using different techniques is better than a single ANN in modelling the complex, dynamic, non-linear, and fragmented rainfall runoff process, (c) a simple model based on the concept of flow recession is better than an ANN to model the falling limb of a flow hydrograph, and (d) decomposing a flow hydrograph into the different segments corresponding to the different dynamics based on the physical concepts is better than using the soft decomposition employed using SOM.
A Distributed Snow Evolution Modeling System (SnowModel)
Liston, G. E.; Elder, K.
2004-12-01
A spatially distributed snow-evolution modeling system (SnowModel) has been specifically designed to be applicable over a wide range of snow landscapes, climates, and conditions. To reach this goal, SnowModel is composed of four sub-models: MicroMet defines the meteorological forcing conditions, EnBal calculates surface energy exchanges, SnowMass simulates snow depth and water-equivalent evolution, and SnowTran-3D accounts for snow redistribution by wind. While other distributed snow models exist, SnowModel is unique in that it includes a well-tested blowing-snow sub-model (SnowTran-3D) for application in windy arctic, alpine, and prairie environments where snowdrifts are common. These environments comprise 68% of the seasonally snow-covered Northern Hemisphere land surface. SnowModel also accounts for snow processes occurring in forested environments (e.g., canopy interception related processes). SnowModel is designed to simulate snow-related physical processes occurring at spatial scales of 5-m and greater, and temporal scales of 1-hour and greater. These include: accumulation from precipitation; wind redistribution and sublimation; loading, unloading, and sublimation within forest canopies; snow-density evolution; and snowpack ripening and melt. To enhance its wide applicability, SnowModel includes the physical calculations required to simulate snow evolution within each of the global snow classes defined by Sturm et al. (1995), e.g., tundra, taiga, alpine, prairie, maritime, and ephemeral snow covers. The three, 25-km by 25-km, Cold Land Processes Experiment (CLPX) mesoscale study areas (MSAs: Fraser, North Park, and Rabbit Ears) are used as SnowModel simulation examples to highlight model strengths, weaknesses, and features in forested, semi-forested, alpine, and shrubland environments.
Hierarchical Model Predictive Control for Resource Distribution
DEFF Research Database (Denmark)
Bendtsen, Jan Dimon; Trangbæk, K; Stoustrup, Jakob
2010-01-01
units. The approach is inspired by smart-grid electric power production and consumption systems, where the flexibility of a large number of power producing and/or power consuming units can be exploited in a smart-grid solution. The objective is to accommodate the load variation on the grid, arising......This paper deals with hierarchichal model predictive control (MPC) of distributed systems. A three level hierachical approach is proposed, consisting of a high level MPC controller, a second level of so-called aggregators, controlled by an online MPC-like algorithm, and a lower level of autonomous...... on one hand from varying consumption, on the other hand by natural variations in power production e.g. from wind turbines. The approach presented is based on quadratic optimization and possess the properties of low algorithmic complexity and of scalability. In particular, the proposed design methodology...
Using genetic algorithm and TOPSIS for Xinanjiang model calibration with a single procedure
Cheng, Chun-Tian; Zhao, Ming-Yan; Chau, K. W.; Wu, Xin-Yu
2006-01-01
Genetic Algorithm (GA) is globally oriented in searching and thus useful in optimizing multiobjective problems, especially where the objective functions are ill-defined. Conceptual rainfall-runoff models that aim at predicting streamflow from the knowledge of precipitation over a catchment have become a basic tool for flood forecasting. The parameter calibration of a conceptual model usually involves the multiple criteria for judging the performances of observed data. However, it is often difficult to derive all objective functions for the parameter calibration problem of a conceptual model. Thus, a new method to the multiple criteria parameter calibration problem, which combines GA with TOPSIS (technique for order performance by similarity to ideal solution) for Xinanjiang model, is presented. This study is an immediate further development of authors' previous research (Cheng, C.T., Ou, C.P., Chau, K.W., 2002. Combining a fuzzy optimal model with a genetic algorithm to solve multi-objective rainfall-runoff model calibration. Journal of Hydrology, 268, 72-86), whose obvious disadvantages are to split the whole procedure into two parts and to become difficult to integrally grasp the best behaviors of model during the calibration procedure. The current method integrates the two parts of Xinanjiang rainfall-runoff model calibration together, simplifying the procedures of model calibration and validation and easily demonstrated the intrinsic phenomenon of observed data in integrity. Comparison of results with two-step procedure shows that the current methodology gives similar results to the previous method, is also feasible and robust, but simpler and easier to apply in practice.
APPROXIMATION OF PROBABILITY DISTRIBUTIONS IN QUEUEING MODELS
Directory of Open Access Journals (Sweden)
T. I. Aliev
2013-03-01
Full Text Available For probability distributions with variation coefficient, not equal to unity, mathematical dependences for approximating distributions on the basis of first two moments are derived by making use of multi exponential distributions. It is proposed to approximate distributions with coefficient of variation less than unity by using hypoexponential distribution, which makes it possible to generate random variables with coefficient of variation, taking any value in a range (0; 1, as opposed to Erlang distribution, having only discrete values of coefficient of variation.
Kinouchi, T.; Omata, T.; Wei, L.; Liu, T.; Araya, M.
2013-12-01
Due to the accident of the Fukushima Dai-ichi Nuclear Power Plant on March 2011, a huge amount of radionuclides including Cesium-134 and Cesium-137 was deposited over the main island of Japan and the Pacific Ocean, resulting in further transfer and diffusion of Cesium through the atmospheric flow, watershed hydrological processes, and terrestrial ecosystem. Particularly, for the transfer of Cesium-134 and Cesium-137, sediments eroded and transported by the rainfall-runoff processes play an important role as Cesium tends to be strongly adsorbed to soil particles such as clay and silt. In this study, we focus on the transport of sediment and adsorbed Cesium in the watershed-scale hydrologic system to predict the long-term change of distribution of Cesium and its discharge to rivers and ocean. We coupled a physically-based distributed hydrological model with the modules of erosion and transport of sediments and adsorbed Cesium, and applied the coupled model to the Abukuma River watershed, which is located over the area of higher deposition of Cesium. In the model, complex land use and land cover distributions, and the effect of human activities such as irrigation, dam control and urban drainage system are taken into accounts. Simulation was conducted for the period of March 2011 until August 2012, with initial spatial distribution of Cesium-134 and Cesium-137 obtained by the airborne survey. Simulated flow rates and sediment concentrations agreed well with observed, and found that since the accident, two major storms in July and September 2011 transported about 50% of total sediments transported during the simulated periods. Cesium concentration in the sediment was reproduced well except for the difference in the initial periods. This difference is attributable to the uncertainty arisen from the initial distribution of Cesium in the soil and the transfer of Cesium from the forest canopy.
A simple topography-driven, calibration-free runoff generation model
Gao, H.; Birkel, C.; Hrachowitz, M.; Tetzlaff, D.; Soulsby, C.; Savenije, H. H. G.
2017-12-01
Determining the amount of runoff generation from rainfall occupies a central place in rainfall-runoff modelling. Moreover, reading landscapes and developing calibration-free runoff generation models that adequately reflect land surface heterogeneities remains the focus of much hydrological research. In this study, we created a new method to estimate runoff generation - HAND-based Storage Capacity curve (HSC) which uses a topographic index (HAND, Height Above the Nearest Drainage) to identify hydrological similarity and partially the saturated areas of catchments. We then coupled the HSC model with the Mass Curve Technique (MCT) method to estimate root zone storage capacity (SuMax), and obtained the calibration-free runoff generation model HSC-MCT. Both the two models (HSC and HSC-MCT) allow us to estimate runoff generation and simultaneously visualize the spatial dynamic of saturated area. We tested the two models in the data-rich Bruntland Burn (BB) experimental catchment in Scotland with an unusual time series of the field-mapped saturation area extent. The models were subsequently tested in 323 MOPEX (Model Parameter Estimation Experiment) catchments in the United States. HBV and TOPMODEL were used as benchmarks. We found that the HSC performed better in reproducing the spatio-temporal pattern of the observed saturated areas in the BB catchment compared with TOPMODEL which is based on the topographic wetness index (TWI). The HSC also outperformed HBV and TOPMODEL in the MOPEX catchments for both calibration and validation. Despite having no calibrated parameters, the HSC-MCT model also performed comparably well with the calibrated HBV and TOPMODEL, highlighting the robustness of the HSC model to both describe the spatial distribution of the root zone storage capacity and the efficiency of the MCT method to estimate the SuMax. Moreover, the HSC-MCT model facilitated effective visualization of the saturated area, which has the potential to be used for broader
Haris, H.; Chow, M. F.; Usman, F.; Sidek, L. M.; Roseli, Z. A.; Norlida, M. D.
2016-03-01
Urbanization is growing rapidly in Malaysia. Rapid urbanization has known to have several negative impacts towards hydrological cycle due to decreasing of pervious area and deterioration of water quality in stormwater runoff. One of the negative impacts of urbanization is the congestion of the stormwater drainage system and this situation leading to flash flood problem and water quality degradation. There are many urban stormwater management softwares available in the market such as Storm Water Drainage System design and analysis program (DRAINS), Urban Drainage and Sewer Model (MOUSE), InfoWorks River Simulation (InfoWork RS), Hydrological Simulation Program-Fortran (HSPF), Distributed Routing Rainfall-Runoff Model (DR3M), Storm Water Management Model (SWMM), XP Storm Water Management Model (XPSWMM), MIKE-SWMM, Quality-Quantity Simulators (QQS), Storage, Treatment, Overflow, Runoff Model (STORM), and Hydrologic Engineering Centre-Hydrologic Modelling System (HEC-HMS). In this paper, we are going to discuss briefly about several softwares and their functionality, accessibility, characteristics and components in the quantity analysis of the hydrological design software and compare it with MSMA Design Aid and Database. Green Infrastructure (GI) is one of the main topics that has widely been discussed all over the world. Every development in the urban area is related to GI. GI can be defined as green area build in the develop area such as forest, park, wetland or floodway. The role of GI is to improve life standard such as water filtration or flood control. Among the twenty models that have been compared to MSMA SME, ten models were selected to conduct a comprehensive review for this study. These are known to be widely accepted by water resource researchers. These ten tools are further classified into three major categories as models that address the stormwater management ability of GI in terms of quantity and quality, models that have the capability of conducting the
Dynamical Models For Prices With Distributed Delays
Directory of Open Access Journals (Sweden)
Mircea Gabriela
2015-06-01
Full Text Available In the present paper we study some models for the price dynamics of a single commodity market. The quantities of supplied and demanded are regarded as a function of time. Nonlinearities in both supply and demand functions are considered. The inventory and the level of inventory are taken into consideration. Due to the fact that the consumer behavior affects commodity demand, and the behavior is influenced not only by the instantaneous price, but also by the weighted past prices, the distributed time delay is introduced. The following kernels are taken into consideration: demand price weak kernel and demand price Dirac kernel. Only one positive equilibrium point is found and its stability analysis is presented. When the demand price kernel is weak, under some conditions of the parameters, the equilibrium point is locally asymptotically stable. When the demand price kernel is Dirac, the existence of the local oscillations is investigated. A change in local stability of the equilibrium point, from stable to unstable, implies a Hopf bifurcation. A family of periodic orbits bifurcates from the positive equilibrium point when the time delay passes through a critical value. The last part contains some numerical simulations to illustrate the effectiveness of our results and conclusions.
Modeling transport of nutrients & sediment loads into Lake Tahoe under climate change
Riverson, John; Coats, Robert; Costa-Cabral, Mariza; Dettinger, Mike; Reuter, John; Sahoo, Goloka; Schladow, Geoffrey
2013-01-01
The outputs from two General Circulation Models (GCMs) with two emissions scenarios were downscaled and bias-corrected to develop regional climate change projections for the Tahoe Basin. For one model—the Geophysical Fluid Dynamics Laboratory or GFDL model—the daily model results were used to drive a distributed hydrologic model. The watershed model used an energy balance approach for computing evapotranspiration and snowpack dynamics so that the processes remain a function of the climate change projections. For this study, all other aspects of the model (i.e. land use distribution, routing configuration, and parameterization) were held constant to isolate impacts of climate change projections. The results indicate that (1) precipitation falling as rain rather than snow will increase, starting at the current mean snowline, and moving towards higher elevations over time; (2) annual accumulated snowpack will be reduced; (3) snowpack accumulation will start later; and (4) snowmelt will start earlier in the year. Certain changes were masked (or counter-balanced) when summarized as basin-wide averages; however, spatial evaluation added notable resolution. While rainfall runoff increased at higher elevations, a drop in total precipitation volume decreased runoff and fine sediment load from the lower elevation meadow areas and also decreased baseflow and nitrogen loads basin-wide. This finding also highlights the important role that the meadow areas could play as high-flow buffers under climatic change. Because the watershed model accounts for elevation change and variable meteorological patterns, it provided a robust platform for evaluating the impacts of projected climate change on hydrology and water quality.
Model simulations of flood and debris flow timing in steep catchments after wildfire
Rengers, Francis K.; McGuire, Luke; Kean, Jason W.; Staley, Dennis M.; Hobley, D.E.J
2016-01-01
Debris flows are a typical hazard on steep slopes after wildfire, but unlike debris flows that mobilize from landslides, most post-wildfire debris flows are generated from water runoff. The majority of existing debris-flow modeling has focused on landslide-triggered debris flows. In this study we explore the potential for using process-based rainfall-runoff models to simulate the timing of water flow and runoff-generated debris flows in recently burned areas. Two different spatially distributed hydrologic models with differing levels of complexity were used: the full shallow water equations and the kinematic wave approximation. Model parameter values were calibrated in two different watersheds, spanning two orders of magnitude in drainage area. These watersheds were affected by the 2009 Station Fire in the San Gabriel Mountains, CA, USA. Input data for the numerical models were constrained by time series of soil moisture, flow stage, and rainfall collected at field sites, as well as high-resolution lidar-derived digital elevation models. The calibrated parameters were used to model a third watershed in the burn area, and the results show a good match with observed timing of flow peaks. The calibrated roughness parameter (Manning's $n$) was generally higher when using the kinematic wave approximation relative to the shallow water equations, and decreased with increasing spatial scale. The calibrated effective watershed hydraulic conductivity was low for both models, even for storms occurring several months after the fire, suggesting that wildfire-induced changes to soil-water infiltration were retained throughout that time. Overall the two model simulations were quite similar suggesting that a kinematic wave model, which is simpler and more computationally efficient, is a suitable approach for predicting flood and debris flow timing in steep, burned watersheds.
Model simulations of flood and debris flow timing in steep catchments after wildfire
Rengers, F. K.; McGuire, L. A.; Kean, J. W.; Staley, D. M.; Hobley, D. E. J.
2016-08-01
Debris flows are a typical hazard on steep slopes after wildfire, but unlike debris flows that mobilize from landslides, most postwildfire debris flows are generated from water runoff. The majority of existing debris flow modeling has focused on landslide-triggered debris flows. In this study we explore the potential for using process-based rainfall-runoff models to simulate the timing of water flow and runoff-generated debris flows in recently burned areas. Two different spatially distributed hydrologic models with differing levels of complexity were used: the full shallow water equations and the kinematic wave approximation. Model parameter values were calibrated in two different watersheds, spanning two orders of magnitude in drainage area. These watersheds were affected by the 2009 Station Fire in the San Gabriel Mountains, CA, USA. Input data for the numerical models were constrained by time series of soil moisture, flow stage, and rainfall collected at field sites, as well as high-resolution lidar-derived digital elevation models. The calibrated parameters were used to model a third watershed in the burn area, and the results show a good match with observed timing of flow peaks. The calibrated roughness parameter (Manning's n) was generally higher when using the kinematic wave approximation relative to the shallow water equations, and decreased with increasing spatial scale. The calibrated effective watershed hydraulic conductivity was low for both models, even for storms occurring several months after the fire, suggesting that wildfire-induced changes to soil-water infiltration were retained throughout that time. Overall, the two model simulations were quite similar suggesting that a kinematic wave model, which is simpler and more computationally efficient, is a suitable approach for predicting flood and debris flow timing in steep, burned watersheds.
A Variance Distribution Model of Surface EMG Signals Based on Inverse Gamma Distribution.
Hayashi, Hideaki; Furui, Akira; Kurita, Yuichi; Tsuji, Toshio
2017-11-01
Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this variance. Variance distribution estimation based on marginal likelihood maximization is also outlined in this paper. The procedure can be approximated using rectified and smoothed EMG signals, thereby allowing the determination of distribution parameters in real time at low computational cost. Results: A simulation experiment was performed to evaluate the accuracy of distribution estimation using artificially generated EMG signals, with results demonstrating that the proposed model's accuracy is higher than that of maximum-likelihood-based estimation. Analysis of variance distribution using real EMG data also suggested a relationship between variance distribution and signal-dependent noise. Conclusion: The study reported here was conducted to examine the performance of a proposed surface EMG model capable of representing variance distribution and a related distribution parameter estimation method. Experiments using artificial and real EMG data demonstrated the validity of the model. Significance: Variance distribution estimated using the proposed model exhibits potential in the estimation of muscle force. Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this
Correlation Structures of Correlated Binomial Models and Implied Default Distribution
S. Mori; K. Kitsukawa; M. Hisakado
2006-01-01
We show how to analyze and interpret the correlation structures, the conditional expectation values and correlation coefficients of exchangeable Bernoulli random variables. We study implied default distributions for the iTraxx-CJ tranches and some popular probabilistic models, including the Gaussian copula model, Beta binomial distribution model and long-range Ising model. We interpret the differences in their profiles in terms of the correlation structures. The implied default distribution h...
Deterministic Properties of Serially Connected Distributed Lag Models
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Piotr Nowak
2013-01-01
Full Text Available Distributed lag models are an important tool in modeling dynamic systems in economics. In the analysis of composite forms of such models, the component models are ordered in parallel (with the same independent variable and/or in series (where the independent variable is also the dependent variable in the preceding model. This paper presents an analysis of certain deterministic properties of composite distributed lag models composed of component distributed lag models arranged in sequence, and their asymptotic properties in particular. The models considered are in discrete form. Even though the paper focuses on deterministic properties of distributed lag models, the derivations are based on analytical tools commonly used in probability theory such as probability distributions and the central limit theorem. (original abstract
Representing macropore flow at the catchment scale: a comparative modeling study
Liu, D.; Li, H. Y.; Tian, F.; Leung, L. R.
2017-12-01
Macropore flow is an important hydrological process that generally enhances the soil infiltration capacity and velocity of subsurface water. Up till now, macropore flow is mostly simulated with high-resolution models. One possible drawback of this modeling approach is the difficulty to effectively represent the overall typology and connectivity of the macropore networks. We hypothesize that modeling macropore flow directly at the catchment scale may be complementary to the existing modeling strategy and offer some new insights. Tsinghua Representative Elementary Watershed model (THREW model) is a semi-distributed hydrology model, where the fundamental building blocks are representative elementary watersheds (REW) linked by the river channel network. In THREW, all the hydrological processes are described with constitutive relationships established directly at the REW level, i.e., catchment scale. In this study, the constitutive relationship of macropore flow drainage is established as part of THREW. The enhanced THREW model is then applied at two catchments with deep soils but distinct climates, the humid Asu catchment in the Amazon River basin, and the arid Wei catchment in the Yellow River basin. The Asu catchment has an area of 12.43km2 with mean annual precipitation of 2442mm. The larger Wei catchment has an area of 24800km2 but with mean annual precipitation of only 512mm. The rainfall-runoff processes are simulated at a hourly time step from 2002 to 2005 in the Asu catchment and from 2001 to 2012 in the Wei catchment. The role of macropore flow on the catchment hydrology will be analyzed comparatively over the Asu and Wei catchments against the observed streamflow, evapotranspiration and other auxiliary data.
Multiplicity distributions in the dual parton model
International Nuclear Information System (INIS)
Batunin, A.V.; Tolstenkov, A.N.
1985-01-01
Multiplicity distributions are calculated by means of a new mechanism of production of hadrons in a string, which was proposed previously by the authors and takes into account explicitly the valence character of the ends of the string. It is shown that allowance for this greatly improves the description of the low-energy multiplicity distributions. At superhigh energies, the contribution of the ends of the strings becomes negligibly small, but in this case multi-Pomeron contributions must be taken into account
Electricity distribution management Smart Grid system model
Directory of Open Access Journals (Sweden)
Wiesław Nowak
2012-06-01
Full Text Available This paper presents issues concerning the implementation of Smart Grid solutions in a real distribution network. The main components possible to quick implementation were presented. Realization of these ideas should bring tangible benefi ts to both customers and distribution system operators. Moreover the paper shows selected research results which examine proposed solutions in area of improving supply reliability and reducing energy losses in analysed network.
A model for the distribution channels planning process
Neves, M.F.; Zuurbier, P.; Campomar, M.C.
2001-01-01
Research of existing literature reveals some models (sequence of steps) for companies that want to plan distribution channels. None of these models uses strong contributions from transaction cost economics, bringing a possibility to elaborate on a "distribution channels planning model", with these
Experimental measurement and modeling of snow accumulation and snowmelt in a mountain microcatchment
Danko, Michal; Krajčí, Pavel; Hlavčo, Jozef; Kostka, Zdeněk; Holko, Ladislav
2016-04-01
Fieldwork is a very useful source of data in all geosciences. This naturally applies also to the snow hydrology. Snow accumulation and snowmelt are spatially very heterogeneous especially in non-forested, mountain environments. Direct field measurements provide the most accurate information about it. Quantification and understanding of processes, that cause these spatial differences are crucial in prediction and modelling of runoff volumes in spring snowmelt period. This study presents possibilities of detailed measurement and modeling of snow cover characteristics in a mountain experimental microcatchment located in northern part of Slovakia in Western Tatra mountains. Catchment area is 0.059 km2 and mean altitude is 1500 m a.s.l. Measurement network consists of 27 snow poles, 3 small snow lysimeters, discharge measurement device and standard automatic weather station. Snow depth and snow water equivalent (SWE) were measured twice a month near the snow poles. These measurements were used to estimate spatial differences in accumulation of SWE. Snowmelt outflow was measured by small snow lysimeters. Measurements were performed in winter 2014/2015. Snow water equivalent variability was very high in such a small area. Differences between particular measuring points reached 600 mm in time of maximum SWE. The results indicated good performance of a snow lysimeter in case of snowmelt timing identification. Increase of snowmelt measured by the snow lysimeter had the same timing as increase in discharge at catchment's outlet and the same timing as the increase in air temperature above the freezing point. Measured data were afterwards used in distributed rainfall-runoff model MIKE-SHE. Several methods were used for spatial distribution of precipitation and snow water equivalent. The model was able to simulate snow water equivalent and snowmelt timing in daily step reasonably well. Simulated discharges were slightly overestimated in later spring.
A space-time hybrid hourly rainfall model for derived flood frequency analysis
Directory of Open Access Journals (Sweden)
U. Haberlandt
2008-12-01
Full Text Available For derived flood frequency analysis based on hydrological modelling long continuous precipitation time series with high temporal resolution are needed. Often, the observation network with recording rainfall gauges is poor, especially regarding the limited length of the available rainfall time series. Stochastic precipitation synthesis is a good alternative either to extend or to regionalise rainfall series to provide adequate input for long-term rainfall-runoff modelling with subsequent estimation of design floods. Here, a new two step procedure for stochastic synthesis of continuous hourly space-time rainfall is proposed and tested for the extension of short observed precipitation time series.
First, a single-site alternating renewal model is presented to simulate independent hourly precipitation time series for several locations. The alternating renewal model describes wet spell durations, dry spell durations and wet spell intensities using univariate frequency distributions separately for two seasons. The dependence between wet spell intensity and duration is accounted for by 2-copulas. For disaggregation of the wet spells into hourly intensities a predefined profile is used. In the second step a multi-site resampling procedure is applied on the synthetic point rainfall event series to reproduce the spatial dependence structure of rainfall. Resampling is carried out successively on all synthetic event series using simulated annealing with an objective function considering three bivariate spatial rainfall characteristics. In a case study synthetic precipitation is generated for some locations with short observation records in two mesoscale catchments of the Bode river basin located in northern Germany. The synthetic rainfall data are then applied for derived flood frequency analysis using the hydrological model HEC-HMS. The results show good performance in reproducing average and extreme rainfall characteristics as well as in
The κ-generalized distribution: A new descriptive model for the size distribution of incomes
Clementi, F.; Di Matteo, T.; Gallegati, M.; Kaniadakis, G.
2008-05-01
This paper proposes the κ-generalized distribution as a model for describing the distribution and dispersion of income within a population. Formulas for the shape, moments and standard tools for inequality measurement-such as the Lorenz curve and the Gini coefficient-are given. A method for parameter estimation is also discussed. The model is shown to fit extremely well the data on personal income distribution in Australia and in the United States.
Analysis and Comparison of Typical Models within Distribution Network Design
DEFF Research Database (Denmark)
Jørgensen, Hans Jacob; Larsen, Allan; Madsen, Oli B.G.
This paper investigates the characteristics of typical optimisation models within Distribution Network Design. During the paper fourteen models known from the literature will be thoroughly analysed. Through this analysis a schematic approach to categorisation of distribution network design models...... for educational purposes. Furthermore, the paper can be seen as a practical introduction to network design modelling as well as a being an art manual or recipe when constructing such a model....
Vischel, Théo; Lebel, Thierry
2007-01-01
As in many other semi-arid regions in the world, the Sahelian hydrological environment is characterized by a mosaic of small endoreic catchments with dry soil surface conditions producing mostly Hortonian runoff. Using an SCS-type event based rainfall-runoff model, an idealized modeling experiment of a Sahelian environment is set up to study the sensitivity of runoff to small scale rainfall variability. A set of 548 observed rain events is used to force the hydrological model to study the sen...
Deterioration and optimal rehabilitation modelling for urban water distribution systems
Zhou, Y.
2018-01-01
Pipe failures in water distribution systems can have a serious impact and hence it’s important to maintain the condition and integrity of the distribution system. This book presents a whole-life cost optimisation model for the rehabilitation of water distribution systems. It combines a pipe breakage
Bayesian Nonparametric Model for Estimating Multistate Travel Time Distribution
Directory of Open Access Journals (Sweden)
Emmanuel Kidando
2017-01-01
Full Text Available Multistate models, that is, models with more than two distributions, are preferred over single-state probability models in modeling the distribution of travel time. Literature review indicated that the finite multistate modeling of travel time using lognormal distribution is superior to other probability functions. In this study, we extend the finite multistate lognormal model of estimating the travel time distribution to unbounded lognormal distribution. In particular, a nonparametric Dirichlet Process Mixture Model (DPMM with stick-breaking process representation was used. The strength of the DPMM is that it can choose the number of components dynamically as part of the algorithm during parameter estimation. To reduce computational complexity, the modeling process was limited to a maximum of six components. Then, the Markov Chain Monte Carlo (MCMC sampling technique was employed to estimate the parameters’ posterior distribution. Speed data from nine links of a freeway corridor, aggregated on a 5-minute basis, were used to calculate the corridor travel time. The results demonstrated that this model offers significant flexibility in modeling to account for complex mixture distributions of the travel time without specifying the number of components. The DPMM modeling further revealed that freeway travel time is characterized by multistate or single-state models depending on the inclusion of onset and offset of congestion periods.
Radar meteors range distribution model. I. Theory
Czech Academy of Sciences Publication Activity Database
Pecinová, Drahomíra; Pecina, Petr
2007-01-01
Roč. 37, č. 2 (2007), s. 83-106 ISSN 1335-1842 R&D Projects: GA ČR GA205/03/1405 Institutional research plan: CEZ:AV0Z10030501 Keywords : physics of meteors * radar meteors * range distribution Subject RIV: BN - Astronomy, Celestial Mechanics, Astrophysics
International Nuclear Information System (INIS)
Sambou, Soussou
2004-01-01
In flood forecasting modelling, large basins are often considered as hydrological systems with multiple inputs and one output. Inputs are hydrological variables such rainfall, runoff and physical characteristics of basin; output is runoff. Relating inputs to output can be achieved using deterministic, conceptual, or stochastic models. Rainfall runoff models generally lack of accuracy. Physical hydrological processes based models, either deterministic or conceptual are highly data requirement demanding and by the way very complex. Stochastic multiple input-output models, using only historical chronicles of hydrological variables particularly runoff are by the way very popular among the hydrologists for large river basin flood forecasting. Application is made on the Senegal River upstream of Bakel, where the River is formed by the main branch, Bafing, and two tributaries, Bakoye and Faleme; Bafing being regulated by Manantaly Dam. A three inputs and one output model has been used for flood forecasting on Bakel. Influence of the lead forecasting, and of the three inputs taken separately, then associated two by two, and altogether has been verified using a dimensionless variance as criterion of quality. Inadequacies occur generally between model output and observations; to put model in better compliance with current observations, we have compared four parameter updating procedure, recursive least squares, Kalman filtering, stochastic gradient method, iterative method, and an AR errors forecasting model. A combination of these model updating have been used in real time flood forecasting.(Author)
Modelling the distribution of pig production and diseases in Thailand
Thanapongtharm, Weerapong
2015-01-01
This thesis, entitled “Modelling the distribution of pig production and diseases in Thailand”, presents many aspects of pig production in Thailand including the characteristics of pig farming system, distribution of pig population and pig farms, spatio-temporal distribution and risk of most important diseases in pig at present, and the suitability area for pig farming. Spatial distribution and characteristics of pig farming in Thailand were studied using time-series pig population data to des...
Modeling and optimization of an electric power distribution network ...
African Journals Online (AJOL)
Modeling and optimization of an electric power distribution network planning system using ... of the network was modelled with non-linear mathematical expressions. ... given feasible locations, re-conductoring of existing feeders in the network, ...
Bilinear reduced order approximate model of parabolic distributed solar collectors
Elmetennani, Shahrazed; Laleg-Kirati, Taous-Meriem
2015-01-01
This paper proposes a novel, low dimensional and accurate approximate model for the distributed parabolic solar collector, by means of a modified gaussian interpolation along the spatial domain. The proposed reduced model, taking the form of a low
Chowdhury, S.; Sharma, A.
2005-12-01
present. SIMEX is based on theory that the trend in alternate parameters can be extrapolated back to the notional error free zone. We illustrate the utility of SIMEX in a synthetic rainfall-runoff modelling scenario and an application to study the dependence of uncertain distributed sea surface temperature anomalies with an indicator of the El Nino Southern Oscillation, the Southern Oscillation Index (SOI). The errors in rainfall data and its affect is explored using Sacramento rainfall runoff model. The rainfall uncertainty is assumed to be multiplicative and temporally invariant. The model used to relate the sea surface temperature anomalies (SSTA) to the SOI is assumed to be of a linear form. The nature of uncertainty in the SSTA is additive and varies with time. The SIMEX framework allows assessment of the relationship between the error free inputs and response. Cook, J.R., Stefanski, L. A., Simulation-Extrapolation Estimation in Parametric Measurement Error Models, Journal of the American Statistical Association, 89 (428), 1314-1328, 1994.
Designing the Distributed Model Integration Framework – DMIF
Belete, Getachew F.; Voinov, Alexey; Morales, Javier
2017-01-01
We describe and discuss the design and prototype of the Distributed Model Integration Framework (DMIF) that links models deployed on different hardware and software platforms. We used distributed computing and service-oriented development approaches to address the different aspects of
A Modeling Framework for Schedulability Analysis of Distributed Avionics Systems
DEFF Research Database (Denmark)
Han, Pujie; Zhai, Zhengjun; Nielsen, Brian
2018-01-01
This paper presents a modeling framework for schedulability analysis of distributed integrated modular avionics (DIMA) systems that consist of spatially distributed ARINC-653 modules connected by a unified AFDX network. We model a DIMA system as a set of stopwatch automata (SWA) in UPPAAL...
The sensitivity of catchment runoff models to rainfall data at different spatial scales
Directory of Open Access Journals (Sweden)
V. A. Bell
2000-01-01
model is explored. The need to recalibrate the model for use with rainfall data of a given resolution, particularly for periods of convective rain, is highlighted. Again, best performance is obtained using lower resolution rainfall data. This is interpreted as evidence for the need to improve the distributed model structure to make better use of the higher resolution information on rainfall and topographic controls on runoff. Degrading the resolution of rainfall data, model or both to achieve the smoothing apparently needed is not seen as wholly appropriate. Keywords: rainfall, runoff, sensitivity, scale, model, flood
Modeling Hydrologic Processes after Vegetation Restoration in an Urban Watershed with HEC-HMS
Stevenson, K.; Kinoshita, A. M.
2017-12-01
The San Diego River Watershed in California (USA) is highly urbanized, where stream channel geomorphology are directly affected by anthropogenic disturbances. Flooding and water quality concerns have led to an increased interest in improving the condition of urban waterways. Alvarado Creek, a 1200-meter section of a tributary to the San Diego River will be used as a case study to understand the degree to which restoration efforts reduce the impacts of climate change and anthropogenic activities on hydrologic processes and water quality in urban stream ecosystems. In 2016, non-native vegetation (i.e. Washingtonia spp. (fan palm), Phoenix canariensis (Canary Island palm)) and approximately 7257 kilograms of refuse were removed from the study reach. This research develops the United States Army Corp of Engineers Hydrologic Engineering Center's Hydraulic Modeling System (USACE HEC-HMS) using field-based data to model and predict the short- and long-term impacts of restoration on geomorphic and hydrologic processes. Observations include cross-sectional area, grain-size distributions, water quality, and continuous measurements of streamflow, temperature, and precipitation. Baseline and design storms are simulated before and after restoration. The model will be calibrated and validated using field observations. The design storms represent statistical likelihoods of storms occurrences, and the pre- and post-restoration hydrologic responses will be compared to evaluate the impact of vegetation and waste removal on runoff processes. Ultimately model parameters will be transferred to other urban creeks in San Diego that may potentially undergo restoration. Modeling will be used to learn about the response trajectory of rainfall-runoff processes following restoration efforts in urban streams and guide future management and restoration activities.
A generalized statistical model for the size distribution of wealth
International Nuclear Information System (INIS)
Clementi, F; Gallegati, M; Kaniadakis, G
2012-01-01
In a recent paper in this journal (Clementi et al 2009 J. Stat. Mech. P02037), we proposed a new, physically motivated, distribution function for modeling individual incomes, having its roots in the framework of the κ-generalized statistical mechanics. The performance of the κ-generalized distribution was checked against real data on personal income for the United States in 2003. In this paper we extend our previous model so as to be able to account for the distribution of wealth. Probabilistic functions and inequality measures of this generalized model for wealth distribution are obtained in closed form. In order to check the validity of the proposed model, we analyze the US household wealth distributions from 1984 to 2009 and conclude an excellent agreement with the data that is superior to any other model already known in the literature. (paper)
A generalized statistical model for the size distribution of wealth
Clementi, F.; Gallegati, M.; Kaniadakis, G.
2012-12-01
In a recent paper in this journal (Clementi et al 2009 J. Stat. Mech. P02037), we proposed a new, physically motivated, distribution function for modeling individual incomes, having its roots in the framework of the κ-generalized statistical mechanics. The performance of the κ-generalized distribution was checked against real data on personal income for the United States in 2003. In this paper we extend our previous model so as to be able to account for the distribution of wealth. Probabilistic functions and inequality measures of this generalized model for wealth distribution are obtained in closed form. In order to check the validity of the proposed model, we analyze the US household wealth distributions from 1984 to 2009 and conclude an excellent agreement with the data that is superior to any other model already known in the literature.
Electric Power Distribution System Model Simplification Using Segment Substitution
Energy Technology Data Exchange (ETDEWEB)
Reiman, Andrew P.; McDermott, Thomas E.; Akcakaya, Murat; Reed, Gregory F.
2018-05-01
Quasi-static time-series (QSTS) simulation is used to simulate the behavior of distribution systems over long periods of time (typically hours to years). The technique involves repeatedly solving the load-flow problem for a distribution system model and is useful for distributed energy resource (DER) planning. When a QSTS simulation has a small time step and a long duration, the computational burden of the simulation can be a barrier to integration into utility workflows. One way to relieve the computational burden is to simplify the system model. The segment substitution method of simplifying distribution system models introduced in this paper offers model bus reduction of up to 98% with a simplification error as low as 0.2% (0.002 pu voltage). In contrast to existing methods of distribution system model simplification, which rely on topological inspection and linearization, the segment substitution method uses black-box segment data and an assumed simplified topology.
Electric Power Distribution System Model Simplification Using Segment Substitution
International Nuclear Information System (INIS)
Reiman, Andrew P.; McDermott, Thomas E.; Akcakaya, Murat; Reed, Gregory F.
2017-01-01
Quasi-static time-series (QSTS) simulation is used to simulate the behavior of distribution systems over long periods of time (typically hours to years). The technique involves repeatedly solving the load-flow problem for a distribution system model and is useful for distributed energy resource (DER) planning. When a QSTS simulation has a small time step and a long duration, the computational burden of the simulation can be a barrier to integration into utility workflows. One way to relieve the computational burden is to simplify the system model. The segment substitution method of simplifying distribution system models introduced in this paper offers model bus reduction of up to 98% with a simplification error as low as 0.2% (0.002 pu voltage). Finally, in contrast to existing methods of distribution system model simplification, which rely on topological inspection and linearization, the segment substitution method uses black-box segment data and an assumed simplified topology.
Robustness of a Distributed Knowledge Management Model
DEFF Research Database (Denmark)
Pedersen, Mogens Kühn; Larsen, Michael Holm
1999-01-01
Knowledge management based on symmetric incentives is rarely found in literature. A knowledge exchange model relies upon a double loop knowledge conversion with symmetric incentives in a network. The model merges specific knowledge with knowledge from other actors into a decision support system...
Karmeshu; Gupta, Varun; Kadambari, K V
2011-06-01
A single neuronal model incorporating distributed delay (memory)is proposed. The stochastic model has been formulated as a Stochastic Integro-Differential Equation (SIDE) which results in the underlying process being non-Markovian. A detailed analysis of the model when the distributed delay kernel has exponential form (weak delay) has been carried out. The selection of exponential kernel has enabled the transformation of the non-Markovian model to a Markovian model in an extended state space. For the study of First Passage Time (FPT) with exponential delay kernel, the model has been transformed to a system of coupled Stochastic Differential Equations (SDEs) in two-dimensional state space. Simulation studies of the SDEs provide insight into the effect of weak delay kernel on the Inter-Spike Interval(ISI) distribution. A measure based on Jensen-Shannon divergence is proposed which can be used to make a choice between two competing models viz. distributed delay model vis-á-vis LIF model. An interesting feature of the model is that the behavior of (CV(t))((ISI)) (Coefficient of Variation) of the ISI distribution with respect to memory kernel time constant parameter η reveals that neuron can switch from a bursting state to non-bursting state as the noise intensity parameter changes. The membrane potential exhibits decaying auto-correlation structure with or without damped oscillatory behavior depending on the choice of parameters. This behavior is in agreement with empirically observed pattern of spike count in a fixed time window. The power spectral density derived from the auto-correlation function is found to exhibit single and double peaks. The model is also examined for the case of strong delay with memory kernel having the form of Gamma distribution. In contrast to fast decay of damped oscillations of the ISI distribution for the model with weak delay kernel, the decay of damped oscillations is found to be slower for the model with strong delay kernel.
Velez, Carlos; Maroy, Edith; Rocabado, Ivan; Pereira, Fernando
2017-04-01
. 40 years of records. This paper investigates the capacity of the three hydrological models to project the impacts of climate change scenarios. It is proposed a general testing framework which combine the use of the existing information through an adapted form of DSST with the approach proposed by Van Steenbergen and Willems, (2012) adapted to assess statistical properties of flows useful in the context of water allocation. To assess the model we use robustness criteria based on a Log Nash-Sutcliffe, BIAS on cummulative volumes and relative changes based on Q50/Q90 estimated from the duration curve. The three conceptual rainfall-runoff models yielded different results per sub-catchments. A relation was found between robustness criteria and changes in mean rainfall and changes in mean potential evapotranspiration. Biases are greatly affected by changes in precipitation, especially when the climate scenarios involve changes in precipitation volume beyond the range used for calibration. Using the combine approach we were able to classify the modelling tools per sub-catchments and create an ensemble of best models to project the impacts of climate variability for the catchments of 10 main rivers in Flanders. Thus, managers could understand better the usability of the modelling tools and the credibility of its outputs for water allocation applications. References Refsgaard, J.C., Madsen, H., Andréassian, V., Arnbjerg-Nielsen, K., Davidson, T.A., Drews, M., Hamilton, D.P., Jeppesen, E., Kjellström, E., Olesen, J.E., Sonnenborg, T.O., Trolle, D., Willems, P., Christensen, J.H., 2014. A framework for testing the ability of models to project climate change and its impacts. Clim. Change. Van Steenbergen, N., Willems, P., 2012. Method for testing the accuracy of rainfall - runoff models in predicting peak flow changes due to rainfall changes , in a climate changing context. J. Hydrol. 415, 425-434.
A distributed computing model for telemetry data processing
Barry, Matthew R.; Scott, Kevin L.; Weismuller, Steven P.
1994-05-01
We present a new approach to distributing processed telemetry data among spacecraft flight controllers within the control centers at NASA's Johnson Space Center. This approach facilitates the development of application programs which integrate spacecraft-telemetered data and ground-based synthesized data, then distributes this information to flight controllers for analysis and decision-making. The new approach combines various distributed computing models into one hybrid distributed computing model. The model employs both client-server and peer-to-peer distributed computing models cooperating to provide users with information throughout a diverse operations environment. Specifically, it provides an attractive foundation upon which we are building critical real-time monitoring and control applications, while simultaneously lending itself to peripheral applications in playback operations, mission preparations, flight controller training, and program development and verification. We have realized the hybrid distributed computing model through an information sharing protocol. We shall describe the motivations that inspired us to create this protocol, along with a brief conceptual description of the distributed computing models it employs. We describe the protocol design in more detail, discussing many of the program design considerations and techniques we have adopted. Finally, we describe how this model is especially suitable for supporting the implementation of distributed expert system applications.
A distributed computing model for telemetry data processing
Barry, Matthew R.; Scott, Kevin L.; Weismuller, Steven P.
1994-01-01
We present a new approach to distributing processed telemetry data among spacecraft flight controllers within the control centers at NASA's Johnson Space Center. This approach facilitates the development of application programs which integrate spacecraft-telemetered data and ground-based synthesized data, then distributes this information to flight controllers for analysis and decision-making. The new approach combines various distributed computing models into one hybrid distributed computing model. The model employs both client-server and peer-to-peer distributed computing models cooperating to provide users with information throughout a diverse operations environment. Specifically, it provides an attractive foundation upon which we are building critical real-time monitoring and control applications, while simultaneously lending itself to peripheral applications in playback operations, mission preparations, flight controller training, and program development and verification. We have realized the hybrid distributed computing model through an information sharing protocol. We shall describe the motivations that inspired us to create this protocol, along with a brief conceptual description of the distributed computing models it employs. We describe the protocol design in more detail, discussing many of the program design considerations and techniques we have adopted. Finally, we describe how this model is especially suitable for supporting the implementation of distributed expert system applications.
Analysis of Jingdong Mall Logistics Distribution Model
Shao, Kang; Cheng, Feng
In recent years, the development of electronic commerce in our country to speed up the pace. The role of logistics has been highlighted, more and more electronic commerce enterprise are beginning to realize the importance of logistics in the success or failure of the enterprise. In this paper, the author take Jingdong Mall for example, performing a SWOT analysis of their current situation of self-built logistics system, find out the problems existing in the current Jingdong Mall logistics distribution and give appropriate recommendations.
Tempered stable distributions stochastic models for multiscale processes
Grabchak, Michael
2015-01-01
This brief is concerned with tempered stable distributions and their associated Levy processes. It is a good text for researchers interested in learning about tempered stable distributions. A tempered stable distribution is one which takes a stable distribution and modifies its tails to make them lighter. The motivation for this class comes from the fact that infinite variance stable distributions appear to provide a good fit to data in a variety of situations, but the extremely heavy tails of these models are not realistic for most real world applications. The idea of using distributions that modify the tails of stable models to make them lighter seems to have originated in the influential paper of Mantegna and Stanley (1994). Since then, these distributions have been extended and generalized in a variety of ways. They have been applied to a wide variety of areas including mathematical finance, biostatistics,computer science, and physics.
Photovoltaic subsystem marketing and distribution model: programming manual. Final report
Energy Technology Data Exchange (ETDEWEB)
1982-07-01
Complete documentation of the marketing and distribution (M and D) computer model is provided. The purpose is to estimate the costs of selling and transporting photovoltaic solar energy products from the manufacturer to the final customer. The model adjusts for the inflation and regional differences in marketing and distribution costs. The model consists of three major components: the marketing submodel, the distribution submodel, and the financial submodel. The computer program is explained including the input requirements, output reports, subprograms and operating environment. The program specifications discuss maintaining the validity of the data and potential improvements. An example for a photovoltaic concentrator collector demonstrates the application of the model.
Correlation Structures of Correlated Binomial Models and Implied Default Distribution
Mori, Shintaro; Kitsukawa, Kenji; Hisakado, Masato
2008-11-01
We show how to analyze and interpret the correlation structures, the conditional expectation values and correlation coefficients of exchangeable Bernoulli random variables. We study implied default distributions for the iTraxx-CJ tranches and some popular probabilistic models, including the Gaussian copula model, Beta binomial distribution model and long-range Ising model. We interpret the differences in their profiles in terms of the correlation structures. The implied default distribution has singular correlation structures, reflecting the credit market implications. We point out two possible origins of the singular behavior.
Species Distribution modeling as a tool to unravel determinants of palm distribution in Thailand
DEFF Research Database (Denmark)
Tovaranonte, Jantrararuk; Barfod, Anders S.; Balslev, Henrik
2011-01-01
As a consequence of the decimation of the forest cover in Thailand from 50% to ca. 20 % since the 1950ies, it is difficult to gain insight in the drivers behind past, present and future distribution ranges of plant species. Species distribution modeling allows visualization of potential species...... distribution under specific sets of assumptions. In this study we used maximum entropy to map potential distributions of 103 species of palms for which more than 5 herbarium records exist. Palms constitute key-stone plant group from both an ecological, economical and conservation perspective. The models were......) and the Area Under the Curve (AUC). All models performed well with AUC scores above 0.95. The predicted distribution ranges showed high suitability for palms in the southern region of Thailand. It also shows that spatial predictor variables are important in cases where historical processes may explain extant...
Distributed Prognostics Based on Structural Model Decomposition
National Aeronautics and Space Administration — Within systems health management, prognostics focuses on predicting the remaining useful life of a system. In the model-based prognostics paradigm, physics-based...
Building a generalized distributed system model
Mukkamala, R.
1993-01-01
The key elements in the 1992-93 period of the project are the following: (1) extensive use of the simulator to implement and test - concurrency control algorithms, interactive user interface, and replica control algorithms; and (2) investigations into the applicability of data and process replication in real-time systems. In the 1993-94 period of the project, we intend to accomplish the following: (1) concentrate on efforts to investigate the effects of data and process replication on hard and soft real-time systems - especially we will concentrate on the impact of semantic-based consistency control schemes on a distributed real-time system in terms of improved reliability, improved availability, better resource utilization, and reduced missed task deadlines; and (2) use the prototype to verify the theoretically predicted performance of locking protocols, etc.
Spreadsheet Modeling of Electron Distributions in Solids
Glassy, Wingfield V.
2006-01-01
A series of spreadsheet modeling exercises constructed as part of a new upper-level elective course on solid state materials and surface chemistry is described. The spreadsheet exercises are developed to provide students with the opportunity to interact with the conceptual framework where the role of the density of states and the Fermi-Dirac…
Distributed Model Predictive Control via Dual Decomposition
DEFF Research Database (Denmark)
Biegel, Benjamin; Stoustrup, Jakob; Andersen, Palle
2014-01-01
This chapter presents dual decomposition as a means to coordinate a number of subsystems coupled by state and input constraints. Each subsystem is equipped with a local model predictive controller while a centralized entity manages the subsystems via prices associated with the coupling constraints...
Garcia, Tanya P; Ma, Yanyuan
2017-10-01
We develop consistent and efficient estimation of parameters in general regression models with mismeasured covariates. We assume the model error and covariate distributions are unspecified, and the measurement error distribution is a general parametric distribution with unknown variance-covariance. We construct root- n consistent, asymptotically normal and locally efficient estimators using the semiparametric efficient score. We do not estimate any unknown distribution or model error heteroskedasticity. Instead, we form the estimator under possibly incorrect working distribution models for the model error, error-prone covariate, or both. Empirical results demonstrate robustness to different incorrect working models in homoscedastic and heteroskedastic models with error-prone covariates.
Directory of Open Access Journals (Sweden)
G. Seiller
2015-03-01
Full Text Available Study region: Twenty diversified U.S. watersheds. Study focus: Identifying optimal parameter sets for hydrological modeling on a specific catchment remains an important challenge for numerous applied and research projects. This is particularly the case when working under contrasted climate conditions that question the temporal transposability of the parameters. Methodologies exist, mainly based on Differential Split Sample Tests, to examine this concern. This work assesses the improved temporal transposability of a multimodel implementation, based on twenty dissimilar lumped conceptual structures and on twenty U.S. watersheds, over the performance of the individual models. New hydrological insights for the region: Individual and collective temporal transposabilities are analyzed and compared on the twenty studied watersheds. Results show that individual models performances on contrasted climate conditions are very dissimilar depending on test period and watershed, without the possibility to identify a best solution in all circumstances. They also confirm that performance and robustness are clearly enhanced using an ensemble of rainfall-runoff models instead of individual ones. The use of (calibrated weight averaged multimodels further improves temporal transposability over simple averaged ensemble, in most instances, confirming added-value of this approach but also the need to evaluate how individual models compensate each other errors. Keywords: Rainfall-runoff modeling, Multimodel approach, Differential Split Sample Test, Deterministic combination, Outputs averaging
Ragettli, S.; Zhou, J.; Wang, H.; Liu, C.; Guo, L.
2017-12-01
Flash floods in small mountain catchments are one of the most frequent causes of loss of life and property from natural hazards in China. Hydrological models can be a useful tool for the anticipation of these events and the issuing of timely warnings. One of the main challenges of setting up such a system is finding appropriate model parameter values for ungauged catchments. Previous studies have shown that the transfer of parameter sets from hydrologically similar gauged catchments is one of the best performing regionalization methods. However, a remaining key issue is the identification of suitable descriptors of similarity. In this study, we use decision tree learning to explore parameter set transferability in the full space of catchment descriptors. For this purpose, a semi-distributed rainfall-runoff model is set up for 35 catchments in ten Chinese provinces. Hourly runoff data from in total 858 storm events are used to calibrate the model and to evaluate the performance of parameter set transfers between catchments. We then present a novel technique that uses the splitting rules of classification and regression trees (CART) for finding suitable donor catchments for ungauged target catchments. The ability of the model to detect flood events in assumed ungauged catchments is evaluated in series of leave-one-out tests. We show that CART analysis increases the probability of detection of 10-year flood events in comparison to a conventional measure of physiographic-climatic similarity by up to 20%. Decision tree learning can outperform other regionalization approaches because it generates rules that optimally consider spatial proximity and physical similarity. Spatial proximity can be used as a selection criteria but is skipped in the case where no similar gauged catchments are in the vicinity. We conclude that the CART regionalization concept is particularly suitable for implementation in sparsely gauged and topographically complex environments where a proximity
Candela, Lucila; Tamoh, Karim; Olivares, Gonzalo; Gomez, Manuel
2012-12-01
Gaining knowledge on potential climate change impacts on water resources is a complex process which depends on numerical models capable of describing these processes in quantitative terms. Under limited data or ungauged basin conditions, which constrain the modelling approach, a physically based coherent methodological approach is required. The traditional approach to assess flow regime and groundwater recharge impacts, based on coupling general atmosphere-ocean circulation models (GCM) and hydrologic models, has been investigated in the Siurana ungauged catchment (NE Spain). The future A2 (medium-high) and B1 (medium-low) greenhouse gas scenarios and time slices 2013-2037 (2025) and 2038-2062 (2050), developed by the Intergovernmental Panel on Climate Change (IPCC, 2001), have been selected. For scenario simulations, coupled GCM ECHAM5 scenarios, stochastically downscaled outputs and surface-subsurface modelling to simulate changes in water resources were applied to the catchment. Flow regime analysis was assessed by HEC-HMS, a physically based hydrologic model to assess rainfall-runoff in a catchment, while recharge was estimated with VisualBALAN, a distributed model for natural recharge estimation. Simulations show that the projected climate change at the catchment will affect the entire hydrological system with a maximum of 56% reduction of water resources. While subtle changes are observed for the 2025 time slice, the temperature and precipitation forecast for 2050 shows a maximum increase of 2.2 °C and a decreased precipitation volume of 11.3% in relation to historical values. Regarding historical values, runoff output shows a maximum 20% decrease, and 18% decrease of natural recharge with a certain delay in relation to runoff and rainfall data. According to the results, the most important parameters conditioning future water resources are changes in climatic parameters, but they are highly dependent on soil moisture conditions. Copyright © 2012 Elsevier B
Braga, Ana Cláudia F. Medeiros; Silva, Richarde Marques da; Santos, Celso Augusto Guimarães; Galvão, Carlos de Oliveira; Nobre, Paulo
2013-08-01
The coastal zone of northeastern Brazil is characterized by intense human activities and by large settlements and also experiences high soil losses that can contribute to environmental damage. Therefore, it is necessary to build an integrated modeling-forecasting system for rainfall-runoff erosion that assesses plans for water availability and sediment yield that can be conceived and implemented. In this work, we present an evaluation of an integrated modeling system for a basin located in this region with a relatively low predictability of seasonal rainfall and a small area (600 km2). The National Center for Environmental Predictions - NCEP’s Regional Spectral Model (RSM) nested within the Center for Weather Forecasting and Climate Studies - CPTEC’s Atmospheric General Circulation Model (AGCM) were investigated in this study, and both are addressed in the simulation work. The rainfall analysis shows that: (1) the dynamic downscaling carried out by the regional RSM model approximates the frequency distribution of the daily observed data set although errors were detected in the magnitude and timing (anticipation of peaks, for example) at the daily scale, (2) an unbiased precipitation forecast seemed to be essential for use of the results in hydrological models, and (3) the information directly extracted from the global model may also be useful. The simulated runoff and reservoir-stored volumes are strongly linked to rainfall, and their estimation accuracy was significantly improved at the monthly scale, thus rendering the results useful for management purposes. The runoff-erosion forecasting displayed a large sediment yield that was consistent with the predicted rainfall.
Charge distribution in an two-chain dual model
International Nuclear Information System (INIS)
Fialkowski, K.; Kotanski, A.
1983-01-01
Charge distributions in the multiple production processes are analysed using the dual chain model. A parametrisation of charge distributions for single dual chains based on the νp and anti vp data is proposed. The rapidity charge distributions are then calculated for pp and anti pp collisions and compared with the previous calculations based on the recursive cascade model of single chains. The results differ at the SPS collider energies and in the energy dependence of the net forward charge supplying the useful tests of the dual chain model. (orig.)
Quantifying Distributional Model Risk via Optimal Transport
Blanchet, Jose; Murthy, Karthyek R. A.
2016-01-01
This paper deals with the problem of quantifying the impact of model misspecification when computing general expected values of interest. The methodology that we propose is applicable in great generality, in particular, we provide examples involving path dependent expectations of stochastic processes. Our approach consists in computing bounds for the expectation of interest regardless of the probability measure used, as long as the measure lies within a prescribed tolerance measured in terms ...
DEFF Research Database (Denmark)
Soares, Tiago; Pereira, Fábio; Morais, Hugo
2015-01-01
The high penetration of distributed energy resources (DER) in distribution networks and the competitive environment of electricity markets impose the use of new approaches in several domains. The network cost allocation, traditionally used in transmission networks, should be adapted and used...... in the distribution networks considering the specifications of the connected resources. The main goal is to develop a fairer methodology trying to distribute the distribution network use costs to all players which are using the network in each period. In this paper, a model considering different type of costs (fixed......, losses, and congestion costs) is proposed comprising the use of a large set of DER, namely distributed generation (DG), demand response (DR) of direct load control type, energy storage systems (ESS), and electric vehicles with capability of discharging energy to the network, which is known as vehicle...
Rationalisation of distribution functions for models of nanoparticle magnetism
International Nuclear Information System (INIS)
El-Hilo, M.; Chantrell, R.W.
2012-01-01
A formalism is presented which reconciles the use of different distribution functions of particle diameter in analytical models of the magnetic properties of nanoparticle systems. For the lognormal distribution a transformation is derived which shows that a distribution of volume fraction transforms into a lognormal distribution of particle number albeit with a modified median diameter. This transformation resolves an apparent discrepancy reported in Tournus and Tamion [Journal of Magnetism and Magnetic Materials 323 (2011) 1118]. - Highlights: ► We resolve a problem resulting from the misunderstanding of the nature. ► The nature of dispersion functions in models of nanoparticle magnetism. ► The derived transformation between distributions will be of benefit in comparing models and experimental results.
Linear Power-Flow Models in Multiphase Distribution Networks: Preprint
Energy Technology Data Exchange (ETDEWEB)
Bernstein, Andrey; Dall' Anese, Emiliano
2017-05-26
This paper considers multiphase unbalanced distribution systems and develops approximate power-flow models where bus-voltages, line-currents, and powers at the point of common coupling are linearly related to the nodal net power injections. The linearization approach is grounded on a fixed-point interpretation of the AC power-flow equations, and it is applicable to distribution systems featuring (i) wye connections; (ii) ungrounded delta connections; (iii) a combination of wye-connected and delta-connected sources/loads; and, (iv) a combination of line-to-line and line-to-grounded-neutral devices at the secondary of distribution transformers. The proposed linear models can facilitate the development of computationally-affordable optimization and control applications -- from advanced distribution management systems settings to online and distributed optimization routines. Performance of the proposed models is evaluated on different test feeders.
Distributed modelling of shallow landslides triggered by intense rainfall
Directory of Open Access Journals (Sweden)
G. B. Crosta
2003-01-01
Full Text Available Hazard assessment of shallow landslides represents an important aspect of land management in mountainous areas. Among all the methods proposed in the literature, physically based methods are the only ones that explicitly includes the dynamic factors that control landslide triggering (rainfall pattern, land-use. For this reason, they allow forecasting both the temporal and the spatial distribution of shallow landslides. Physically based methods for shallow landslides are based on the coupling of the infinite slope stability analysis with hydrological models. Three different grid-based distributed hydrological models are presented in this paper: a steady state model, a transient "piston-flow" wetting front model, and a transient diffusive model. A comparative test of these models was performed to simulate landslide occurred during a rainfall event (27–28 June 1997 that triggered hundreds of shallow landslides within Lecco province (central Southern Alps, Italy. In order to test the potential for a completely distributed model for rainfall-triggered landslides, radar detected rainfall intensity has been used. A new procedure for quantitative evaluation of distributed model performance is presented and used in this paper. The diffusive model results in the best model for the simulation of shallow landslide triggering after a rainfall event like the one that we have analysed. Finally, radar data available for the June 1997 event permitted greatly improving the simulation. In particular, radar data allowed to explain the non-uniform distribution of landslides within the study area.
Distributed MAP in the SpinJa Model Checker
Directory of Open Access Journals (Sweden)
Stefan Vijzelaar
2011-10-01
Full Text Available Spin in Java (SpinJa is an explicit state model checker for the Promela modelling language also used by the SPIN model checker. Designed to be extensible and reusable, the implementation of SpinJa follows a layered approach in which each new layer extends the functionality of the previous one. While SpinJa has preliminary support for shared-memory model checking, it did not yet support distributed-memory model checking. This tool paper presents a distributed implementation of a maximal accepting predecessors (MAP search algorithm on top of SpinJa.
Overland erosion of uranium-mill-tailings impoundments: physical processes and computational methods
International Nuclear Information System (INIS)
Walters, M.H.
1983-03-01
The surface runoff and erosional processes of watersheds caused by rainfall-runoff are reviewed. Soil properties, topography, and rainstorm distribution are discussed with respect to their effects on soil erosion. The effects of climate and vegetation are briefly presented. Regression models and physical process simulation models are reviewed
Grey Box Modelling of Hydrological Systems
DEFF Research Database (Denmark)
Thordarson, Fannar Ørn
of two papers where the stochastic differential equation based model is used for sewer runoff from a drainage system. A simple model is used to describe a complex rainfall-runoff process in a catchment, but the stochastic part of the system is formulated to include the increasing uncertainty when...... rainwater flows through the system, as well as describe the lower limit of the uncertainty when the flow approaches zero. The first paper demonstrates in detail the grey box model and all related transformations required to obtain a feasible model for the sewer runoff. In the last paper this model is used......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...
Modeling and analysis of solar distributed generation
Ortiz Rivera, Eduardo Ivan
Recent changes in the global economy are creating a big impact in our daily life. The price of oil is increasing and the number of reserves are less every day. Also, dramatic demographic changes are impacting the viability of the electric infrastructure and ultimately the economic future of the industry. These are some of the reasons that many countries are looking for alternative energy to produce electric energy. The most common form of green energy in our daily life is solar energy. To convert solar energy into electrical energy is required solar panels, dc-dc converters, power control, sensors, and inverters. In this work, a photovoltaic module, PVM, model using the electrical characteristics provided by the manufacturer data sheet is presented for power system applications. Experimental results from testing are showed, verifying the proposed PVM model. Also in this work, three maximum power point tracker, MPPT, algorithms would be presented to obtain the maximum power from a PVM. The first MPPT algorithm is a method based on the Rolle's and Lagrange's Theorems and can provide at least an approximate answer to a family of transcendental functions that cannot be solved using differential calculus. The second MPPT algorithm is based on the approximation of the proposed PVM model using fractional polynomials where the shape, boundary conditions and performance of the proposed PVM model are satisfied. The third MPPT algorithm is based in the determination of the optimal duty cycle for a dc-dc converter and the previous knowledge of the load or load matching conditions. Also, four algorithms to calculate the effective irradiance level and temperature over a photovoltaic module are presented in this work. The main reasons to develop these algorithms are for monitoring climate conditions, the elimination of temperature and solar irradiance sensors, reductions in cost for a photovoltaic inverter system, and development of new algorithms to be integrated with maximum
Idealized models of the joint probability distribution of wind speeds
Monahan, Adam H.
2018-05-01
The joint probability distribution of wind speeds at two separate locations in space or points in time completely characterizes the statistical dependence of these two quantities, providing more information than linear measures such as correlation. In this study, we consider two models of the joint distribution of wind speeds obtained from idealized models of the dependence structure of the horizontal wind velocity components. The bivariate Rice distribution follows from assuming that the wind components have Gaussian and isotropic fluctuations. The bivariate Weibull distribution arises from power law transformations of wind speeds corresponding to vector components with Gaussian, isotropic, mean-zero variability. Maximum likelihood estimates of these distributions are compared using wind speed data from the mid-troposphere, from different altitudes at the Cabauw tower in the Netherlands, and from scatterometer observations over the sea surface. While the bivariate Rice distribution is more flexible and can represent a broader class of dependence structures, the bivariate Weibull distribution is mathematically simpler and may be more convenient in many applications. The complexity of the mathematical expressions obtained for the joint distributions suggests that the development of explicit functional forms for multivariate speed distributions from distributions of the components will not be practical for more complicated dependence structure or more than two speed variables.
Model Checking Geographically Distributed Interlocking Systems Using UMC
DEFF Research Database (Denmark)
Fantechi, Alessandro; Haxthausen, Anne Elisabeth; Nielsen, Michel Bøje Randahl
2017-01-01
the relevant distributed protocols. By doing that we obey the safety guidelines of the railway signalling domain, that require formal methods to support the certification of such products. We also show how formal modelling can help designing alternative distributed solutions, while maintaining adherence...
Modelling aspects of distributed processing in telecommunication networks
Tomasgard, A; Audestad, JA; Dye, S; Stougie, L; van der Vlerk, MH; Wallace, SW
1998-01-01
The purpose of this paper is to formally describe new optimization models for telecommunication networks with distributed processing. Modem distributed networks put more focus on the processing of information and less on the actual transportation of data than we are traditionally used to in
Modified Normal Demand Distributions in (R,S)-Inventory Models
Strijbosch, L.W.G.; Moors, J.J.A.
2003-01-01
To model demand, the normal distribution is by far the most popular; the disadvantage that it takes negative values is taken for granted.This paper proposes two modi.cations of the normal distribution, both taking non-negative values only.Safety factors and order-up-to-levels for the familiar (R,
Income Distribution Over Educational Levels: A Simple Model.
Tinbergen, Jan
An econometric model is formulated that explains income per person in various compartments of the labor market defined by three main levels of education and by education required. The model enables an estimation of the effect of increased access to education on that distribution. The model is based on a production for the economy as a whole; a…
Distributed Generation Market Demand Model (dGen): Documentation
Energy Technology Data Exchange (ETDEWEB)
Sigrin, Benjamin [National Renewable Energy Lab. (NREL), Golden, CO (United States); Gleason, Michael [National Renewable Energy Lab. (NREL), Golden, CO (United States); Preus, Robert [National Renewable Energy Lab. (NREL), Golden, CO (United States); Baring-Gould, Ian [National Renewable Energy Lab. (NREL), Golden, CO (United States); Margolis, Robert [National Renewable Energy Lab. (NREL), Golden, CO (United States)
2016-02-01
The Distributed Generation Market Demand model (dGen) is a geospatially rich, bottom-up, market-penetration model that simulates the potential adoption of distributed energy resources (DERs) for residential, commercial, and industrial entities in the continental United States through 2050. The National Renewable Energy Laboratory (NREL) developed dGen to analyze the key factors that will affect future market demand for distributed solar, wind, storage, and other DER technologies in the United States. The new model builds off, extends, and replaces NREL's SolarDS model (Denholm et al. 2009a), which simulates the market penetration of distributed PV only. Unlike the SolarDS model, dGen can model various DER technologies under one platform--it currently can simulate the adoption of distributed solar (the dSolar module) and distributed wind (the dWind module) and link with the ReEDS capacity expansion model (Appendix C). The underlying algorithms and datasets in dGen, which improve the representation of customer decision making as well as the spatial resolution of analyses (Figure ES-1), also are improvements over SolarDS.
Development of vortex model with realistic axial velocity distribution
International Nuclear Information System (INIS)
Ito, Kei; Ezure, Toshiki; Ohshima, Hiroyuki
2014-01-01
A vortex is considered as one of significant phenomena which may cause gas entrainment (GE) and/or vortex cavitation in sodium-cooled fast reactors. In our past studies, the vortex is assumed to be approximated by the well-known Burgers vortex model. However, the Burgers vortex model has a simple but unreal assumption that the axial velocity component is horizontally constant, while in real the free surface vortex has the axial velocity distribution which shows large gradient in radial direction near the vortex center. In this study, a new vortex model with realistic axial velocity distribution is proposed. This model is derived from the steady axisymmetric Navier-Stokes equation as well as the Burgers vortex model, but the realistic axial velocity distribution in radial direction is considered, which is defined to be zero at the vortex center and to approach asymptotically to zero at infinity. As the verification, the new vortex model is applied to the evaluation of a simple vortex experiment, and shows good agreements with the experimental data in terms of the circumferential velocity distribution and the free surface shape. In addition, it is confirmed that the Burgers vortex model fails to calculate accurate velocity distribution with the assumption of uniform axial velocity. However, the calculation accuracy of the Burgers vortex model can be enhanced close to that of the new vortex model in consideration of the effective axial velocity which is calculated as the average value only in the vicinity of the vortex center. (author)
Regularized multivariate regression models with skew-t error distributions
Chen, Lianfu; Pourahmadi, Mohsen; Maadooliat, Mehdi
2014-01-01
We consider regularization of the parameters in multivariate linear regression models with the errors having a multivariate skew-t distribution. An iterative penalized likelihood procedure is proposed for constructing sparse estimators of both
Modelling distributed energy resources in energy service networks
Acha, Salvador
2013-01-01
Focuses on modelling two key infrastructures (natural gas and electrical) in urban energy systems with embedded technologies (cogeneration and electric vehicles) to optimise the operation of natural gas and electrical infrastructures under the presence of distributed energy resources
A phenomenological retention tank model using settling velocity distributions.
Maruejouls, T; Vanrolleghem, P A; Pelletier, G; Lessard, P
2012-12-15
Many authors have observed the influence of the settling velocity distribution on the sedimentation process in retention tanks. However, the pollutants' behaviour in such tanks is not well characterized, especially with respect to their settling velocity distribution. This paper presents a phenomenological modelling study dealing with the way by which the settling velocity distribution of particles in combined sewage changes between entering and leaving an off-line retention tank. The work starts from a previously published model (Lessard and Beck, 1991) which is first implemented in a wastewater management modelling software, to be then tested with full-scale field data for the first time. Next, its performance is improved by integrating the particle settling velocity distribution and adding a description of the resuspension due to pumping for emptying the tank. Finally, the potential of the improved model is demonstrated by comparing the results for one more rain event. Copyright © 2011 Elsevier Ltd. All rights reserved.
Modeling of Drift Effects on Solar Tower Concentrated Flux Distributions
Directory of Open Access Journals (Sweden)
Luis O. Lara-Cerecedo
2016-01-01
Full Text Available A novel modeling tool for calculation of central receiver concentrated flux distributions is presented, which takes into account drift effects. This tool is based on a drift model that includes different geometrical error sources in a rigorous manner and on a simple analytic approximation for the individual flux distribution of a heliostat. The model is applied to a group of heliostats of a real field to obtain the resulting flux distribution and its variation along the day. The distributions differ strongly from those obtained assuming the ideal case without drift or a case with a Gaussian tracking error function. The time evolution of peak flux is also calculated to demonstrate the capabilities of the model. The evolution of this parameter also shows strong differences in comparison to the case without drift.
A Framework for Modeling and Analyzing Complex Distributed Systems
National Research Council Canada - National Science Library
Lynch, Nancy A; Shvartsman, Alex Allister
2005-01-01
Report developed under STTR contract for topic AF04-T023. This Phase I project developed a modeling language and laid a foundation for computational support tools for specifying, analyzing, and verifying complex distributed system designs...
Beauregard, Frieda; de Blois, Sylvie
2014-01-01
Both climatic and edaphic conditions determine plant distribution, however many species distribution models do not include edaphic variables especially over large geographical extent. Using an exceptional database of vegetation plots (n = 4839) covering an extent of ∼55,000 km2, we tested whether the inclusion of fine scale edaphic variables would improve model predictions of plant distribution compared to models using only climate predictors. We also tested how well these edaphic variables could predict distribution on their own, to evaluate the assumption that at large extents, distribution is governed largely by climate. We also hypothesized that the relative contribution of edaphic and climatic data would vary among species depending on their growth forms and biogeographical attributes within the study area. We modelled 128 native plant species from diverse taxa using four statistical model types and three sets of abiotic predictors: climate, edaphic, and edaphic-climate. Model predictive accuracy and variable importance were compared among these models and for species' characteristics describing growth form, range boundaries within the study area, and prevalence. For many species both the climate-only and edaphic-only models performed well, however the edaphic-climate models generally performed best. The three sets of predictors differed in the spatial information provided about habitat suitability, with climate models able to distinguish range edges, but edaphic models able to better distinguish within-range variation. Model predictive accuracy was generally lower for species without a range boundary within the study area and for common species, but these effects were buffered by including both edaphic and climatic predictors. The relative importance of edaphic and climatic variables varied with growth forms, with trees being more related to climate whereas lower growth forms were more related to edaphic conditions. Our study identifies the potential
Directory of Open Access Journals (Sweden)
Frieda Beauregard
Full Text Available Both climatic and edaphic conditions determine plant distribution, however many species distribution models do not include edaphic variables especially over large geographical extent. Using an exceptional database of vegetation plots (n = 4839 covering an extent of ∼55,000 km2, we tested whether the inclusion of fine scale edaphic variables would improve model predictions of plant distribution compared to models using only climate predictors. We also tested how well these edaphic variables could predict distribution on their own, to evaluate the assumption that at large extents, distribution is governed largely by climate. We also hypothesized that the relative contribution of edaphic and climatic data would vary among species depending on their growth forms and biogeographical attributes within the study area. We modelled 128 native plant species from diverse taxa using four statistical model types and three sets of abiotic predictors: climate, edaphic, and edaphic-climate. Model predictive accuracy and variable importance were compared among these models and for species' characteristics describing growth form, range boundaries within the study area, and prevalence. For many species both the climate-only and edaphic-only models performed well, however the edaphic-climate models generally performed best. The three sets of predictors differed in the spatial information provided about habitat suitability, with climate models able to distinguish range edges, but edaphic models able to better distinguish within-range variation. Model predictive accuracy was generally lower for species without a range boundary within the study area and for common species, but these effects were buffered by including both edaphic and climatic predictors. The relative importance of edaphic and climatic variables varied with growth forms, with trees being more related to climate whereas lower growth forms were more related to edaphic conditions. Our study
Umgiesser, Georg; Bellafiore, Debora; De Pascalis, Francesca; Icke, Joost; Stanica, Adrian
2017-04-01
The DANUBIUS Research Infrastructure (DANUBIUS-RI) is a new initiative to address the challenges and opportunities of research on large river- sea (RS) systems. DANUBIUS-RI is a distributed pan-European RI that will provide a platform for interdisciplinary research. It will deal with RS investigation through facilities and expertise from a large number of European institutions becoming a 'one-stop shop' for knowledge exchange in managing RS systems, ranging from freshwater to marine research. Globally, RS systems are complex and dynamic, with huge environmental, social and economic value. They are poorly understood but under increasing pressure through pollution, hydraulic engineering, water supply, energy, flood control and erosion. RS systems in Europe are among the most impacted globally, after centuries of industrialisation, urbanisation and agricultural intensification. Improved understanding is essential to avoid irreversible degradation and for restoration. DANUBIUS-RI will provide, among a number of other facilities concerning observations, analyses, impacts' evaluation, a modeling node that will provide integrated up-to-date tools, at locations of high scientific importance and opportunity, covering the RS systems - from source (upper parts of rivers - mountain lakes) to the transition with coastal seas. Modeling will be one of the major services provided by DANUBIUS-RI, relying on the inputs from the whole RI. RS systems are challenging from a modelling point of view, because of the complex morphology and the wide temporal and spatial range of processes occurring. Scale interaction plays a central role, considering the different hydro-eco-morphological processes on the large (basin) and small (local, coast, rivers, lagoons) scale. Currently, different model applications are made for the different geographical domains, and also for subsets of the processes. For instance there are separate models for rainfall runoff in the catchment, a sewer model for the
A Complex Network Approach to Distributional Semantic Models.
Directory of Open Access Journals (Sweden)
Akira Utsumi
Full Text Available A number of studies on network analysis have focused on language networks based on free word association, which reflects human lexical knowledge, and have demonstrated the small-world and scale-free properties in the word association network. Nevertheless, there have been very few attempts at applying network analysis to distributional semantic models, despite the fact that these models have been studied extensively as computational or cognitive models of human lexical knowledge. In this paper, we analyze three network properties, namely, small-world, scale-free, and hierarchical properties, of semantic networks created by distributional semantic models. We demonstrate that the created networks generally exhibit the same properties as word association networks. In particular, we show that the distribution of the number of connections in these networks follows the truncated power law, which is also observed in an association network. This indicates that distributional semantic models can provide a plausible model of lexical knowledge. Additionally, the observed differences in the network properties of various implementations of distributional semantic models are consistently explained or predicted by considering the intrinsic semantic features of a word-context matrix and the functions of matrix weighting and smoothing. Furthermore, to simulate a semantic network with the observed network properties, we propose a new growing network model based on the model of Steyvers and Tenenbaum. The idea underlying the proposed model is that both preferential and random attachments are required to reflect different types of semantic relations in network growth process. We demonstrate that this model provides a better explanation of network behaviors generated by distributional semantic models.
Flash flood modelling for ungauged catchments
Garambois, P.-A.; Roux, H.; Larnier, K.; Dartus, D.
2012-04-01
Flash flood is a very intense and quick hydrologic response of a catchment to rainfall. This phenomenon has a high spatial-temporal variability as its generating storm, often hitting small catchments (few km2). Data collected by (Gaume et al. 2009) about 500 flash floods over the last 50 years showed that they could occur everywhere in Europe and more often in the Mediterranean regions, Alpine regions and continental Europe. Given the small spatial-temporal scales and high variability of flash floods, their prediction remains a hard exercise as the necessary data are often scarce. Flash flood prediction on ungauged catchments is one of the challenges of hydrological modelling as defined by (Sivapalan et al. 2003). Several studies have been headed up with the MARINE model (Modélisation de l'Anticipation du Ruissellement et des Inondations pour des évèNements Extrêmes) for the Gard region (France), (Roux et al. 2011), (Castaings et al. 2009). This physically based spatially distributed rainfall runoff model is dedicated to flash flood prediction. The study aims at finding a methodology for flash flood prediction at ungauged locations in the Cévennes-Vivarais region in particular. The regionalization method is based on multiple calibrations on gauged catchments in order to extract model structures (model + parameter values) for each catchment. Several mathematical methods (multiple regressions, transfer functions, krigging…) will then be tested to calculate a regional parameter set. The study also investigates the usability of additional hydrologic indices at different time scales to constrain model predictions from parameters obtained using these indices, and this independently of the model considered. These hydrologic indices gather information on hydrograph shape or catchment dynamic for instance. Results explaining global catchments behaviour are expected that way. The spatial-temporal variability of storms is also described through indices and linked with
Software reliability growth models with normal failure time distributions
International Nuclear Information System (INIS)
Okamura, Hiroyuki; Dohi, Tadashi; Osaki, Shunji
2013-01-01
This paper proposes software reliability growth models (SRGM) where the software failure time follows a normal distribution. The proposed model is mathematically tractable and has sufficient ability of fitting to the software failure data. In particular, we consider the parameter estimation algorithm for the SRGM with normal distribution. The developed algorithm is based on an EM (expectation-maximization) algorithm and is quite simple for implementation as software application. Numerical experiment is devoted to investigating the fitting ability of the SRGMs with normal distribution through 16 types of failure time data collected in real software projects
Maxent modelling for predicting the potential distribution of Thai Palms
DEFF Research Database (Denmark)
Tovaranonte, Jantrararuk; Barfod, Anders S.; Overgaard, Anne Blach
2011-01-01
on presence data. The aim was to identify potential hot spot areas, assess the determinants of palm distribution ranges, and provide a firmer knowledge base for future conservation actions. We focused on a relatively small number of climatic, environmental and spatial variables in order to avoid...... overprediction of species distribution ranges. The models with the best predictive power were found by calculating the area under the curve (AUC) of receiver-operating characteristic (ROC). Here, we provide examples of contrasting predicted species distribution ranges as well as a map of modeled palm diversity...
Modeling, robust and distributed model predictive control for freeway networks
Liu, S.
2016-01-01
In Model Predictive Control (MPC) for traffic networks, traffic models are crucial since they are used as prediction models for determining the optimal control actions. In order to reduce the computational complexity of MPC for traffic networks, macroscopic traffic models are often used instead of
The Distributed Geothermal Market Demand Model (dGeo): Documentation
Energy Technology Data Exchange (ETDEWEB)
McCabe, Kevin [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Mooney, Meghan E [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Sigrin, Benjamin O [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Gleason, Michael [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Liu, Xiaobing [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
2017-11-06
The National Renewable Energy Laboratory (NREL) developed the Distributed Geothermal Market Demand Model (dGeo) as a tool to explore the potential role of geothermal distributed energy resources (DERs) in meeting thermal energy demands in the United States. The dGeo model simulates the potential for deployment of geothermal DERs in the residential and commercial sectors of the continental United States for two specific technologies: ground-source heat pumps (GHP) and geothermal direct use (DU) for district heating. To quantify the opportunity space for these technologies, dGeo leverages a highly resolved geospatial database and robust bottom-up, agent-based modeling framework. This design is consistent with others in the family of Distributed Generation Market Demand models (dGen; Sigrin et al. 2016), including the Distributed Solar Market Demand (dSolar) and Distributed Wind Market Demand (dWind) models. dGeo is intended to serve as a long-term scenario-modeling tool. It has the capability to simulate the technical potential, economic potential, market potential, and technology deployment of GHP and DU through the year 2050 under a variety of user-defined input scenarios. Through these capabilities, dGeo can provide substantial analytical value to various stakeholders interested in exploring the effects of various techno-economic, macroeconomic, financial, and policy factors related to the opportunity for GHP and DU in the United States. This report documents the dGeo modeling design, methodology, assumptions, and capabilities.
Working toward integrated models of alpine plant distribution.
Carlson, Bradley Z; Randin, Christophe F; Boulangeat, Isabelle; Lavergne, Sébastien; Thuiller, Wilfried; Choler, Philippe
2013-10-01
Species distribution models (SDMs) have been frequently employed to forecast the response of alpine plants to global changes. Efforts to model alpine plant distribution have thus far been primarily based on a correlative approach, in which ecological processes are implicitly addressed through a statistical relationship between observed species occurrences and environmental predictors. Recent evidence, however, highlights the shortcomings of correlative SDMs, especially in alpine landscapes where plant species tend to be decoupled from atmospheric conditions in micro-topographic habitats and are particularly exposed to geomorphic disturbances. While alpine plants respond to the same limiting factors as plants found at lower elevations, alpine environments impose a particular set of scale-dependent and hierarchical drivers that shape the realized niche of species and that require explicit consideration in a modelling context. Several recent studies in the European Alps have successfully integrated both correlative and process-based elements into distribution models of alpine plants, but for the time being a single integrative modelling framework that includes all key drivers remains elusive. As a first step in working toward a comprehensive integrated model applicable to alpine plant communities, we propose a conceptual framework that structures the primary mechanisms affecting alpine plant distributions. We group processes into four categories, including multi-scalar abiotic drivers, gradient dependent species interactions, dispersal and spatial-temporal plant responses to disturbance. Finally, we propose a methodological framework aimed at developing an integrated model to better predict alpine plant distribution.
Orbital angular momentum parton distributions in quark models
International Nuclear Information System (INIS)
Scopetta, S.; Vento, V.
2000-01-01
At the low energy, hadronic, scale we calculate Orbital Angular Momentum (OAM) twist-two parton distributions for the relativistic MIT bag model and for nonrelativistic quark models. We reach the scale of the data by leading order evolution in perturbative QCD. We confirm that the contribution of quarks and gluons OAM to the nucleon spin grows with Q 2 , and it can be relevant at the experimental scale, even if it is negligible at the hadronic scale, irrespective of the model used. The sign and shape of the quark OAM distribution at high Q 2 may depend strongly on the relative size of the OAM and spin distributions at the hadronic scale. Sizeable quark OAM distributions at the hadronic scale, as proposed by several authors, can produce the dominant contribution to the nucleon spin at high Q 2 . (author)
Modelling and analysis of distributed simulation protocols with distributed graph transformation
Lara, Juan de; Taentzer, Gabriele
2005-01-01
Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. J. de Lara, and G. Taentzer, "Modelling and analysis of distributed simulation protocols with distributed graph transformation...
Directory of Open Access Journals (Sweden)
Christian Vögeli
2016-12-01
Full Text Available Accurate knowledge on snow distribution in alpine terrain is crucial for various applicationssuch as flood risk assessment, avalanche warning or managing water supply and hydro-power.To simulate the seasonal snow cover development in alpine terrain, the spatially distributed,physics-based model Alpine3D is suitable. The model is typically driven by spatial interpolationsof observations from automatic weather stations (AWS, leading to errors in the spatial distributionof atmospheric forcing. With recent advances in remote sensing techniques, maps of snowdepth can be acquired with high spatial resolution and accuracy. In this work, maps of the snowdepth distribution, calculated from summer and winter digital surface models based on AirborneDigital Sensors (ADS, are used to scale precipitation input data, with the aim to improve theaccuracy of simulation of the spatial distribution of snow with Alpine3D. A simple method toscale and redistribute precipitation is presented and the performance is analysed. The scalingmethod is only applied if it is snowing. For rainfall the precipitation is distributed by interpolation,with a simple air temperature threshold used for the determination of the precipitation phase.It was found that the accuracy of spatial snow distribution could be improved significantly forthe simulated domain. The standard deviation of absolute snow depth error is reduced up toa factor 3.4 to less than 20 cm. The mean absolute error in snow distribution was reducedwhen using representative input sources for the simulation domain. For inter-annual scaling, themodel performance could also be improved, even when using a remote sensing dataset from adifferent winter. In conclusion, using remote sensing data to process precipitation input, complexprocesses such as preferential snow deposition and snow relocation due to wind or avalanches,can be substituted and modelling performance of spatial snow distribution is improved.
Modeling highway travel time distribution with conditional probability models
Energy Technology Data Exchange (ETDEWEB)
Oliveira Neto, Francisco Moraes [ORNL; Chin, Shih-Miao [ORNL; Hwang, Ho-Ling [ORNL; Han, Lee [University of Tennessee, Knoxville (UTK)
2014-01-01
ABSTRACT Under the sponsorship of the Federal Highway Administration's Office of Freight Management and Operations, the American Transportation Research Institute (ATRI) has developed performance measures through the Freight Performance Measures (FPM) initiative. Under this program, travel speed information is derived from data collected using wireless based global positioning systems. These telemetric data systems are subscribed and used by trucking industry as an operations management tool. More than one telemetric operator submits their data dumps to ATRI on a regular basis. Each data transmission contains truck location, its travel time, and a clock time/date stamp. Data from the FPM program provides a unique opportunity for studying the upstream-downstream speed distributions at different locations, as well as different time of the day and day of the week. This research is focused on the stochastic nature of successive link travel speed data on the continental United States Interstates network. Specifically, a method to estimate route probability distributions of travel time is proposed. This method uses the concepts of convolution of probability distributions and bivariate, link-to-link, conditional probability to estimate the expected distributions for the route travel time. Major contribution of this study is the consideration of speed correlation between upstream and downstream contiguous Interstate segments through conditional probability. The established conditional probability distributions, between successive segments, can be used to provide travel time reliability measures. This study also suggests an adaptive method for calculating and updating route travel time distribution as new data or information is added. This methodology can be useful to estimate performance measures as required by the recent Moving Ahead for Progress in the 21st Century Act (MAP 21).
Modelling the potential distribution of Betula utilis in the Himalaya
Directory of Open Access Journals (Sweden)
Maria Bobrowski
2017-07-01
Full Text Available Developing sustainable adaptation pathways under climate change conditions in mountain regions requires accurate predictions of treeline shifts and future distribution ranges of treeline species. Here, we model for the first time the potential distribution of Betula utilis, a principal Himalayan treeline species, to provide a basis for the analysis of future range shifts. Our target species Betula utilis is widespread at alpine treelines in the Himalayan mountains, the distribution range extends across the Himalayan mountain range. Our objective is to model the potential distribution of B. utilis in relation to current climate conditions. We generated a dataset of 590 occurrence records and used 24 variables for ecological niche modelling. We calibrated Generalized Linear Models using the Akaike Information Criterion (AIC and evaluated model performance using threshold-independent (AUC, Area Under the Curve and threshold-dependent (TSS, True Skill Statistics characteristics as well as visual assessments of projected distribution maps. We found two temperature-related (Mean Temperature of the Wettest Quarter, Temperature Annual Range and three precipitation-related variables (Precipitation of the Coldest Quarter, Average Precipitation of March, April and May and Precipitation Seasonality to be useful for predicting the potential distribution of B. utilis. All models had high predictive power (AUC ≥ 0.98 and TSS ≥ 0.89. The projected suitable area in the Himalayan mountains varies considerably, with most extensive distribution in the western and central Himalayan region. A substantial difference between potential and real distribution in the eastern Himalaya points to decreasing competitiveness of B. utilis under more oceanic conditions in the eastern part of the mountain system. A comparison between the vegetation map of Schweinfurth (1957 and our current predictions suggests that B. utilis does not reach the upper elevational limit in
Estimating Predictive Variance for Statistical Gas Distribution Modelling
International Nuclear Information System (INIS)
Lilienthal, Achim J.; Asadi, Sahar; Reggente, Matteo
2009-01-01
Recent publications in statistical gas distribution modelling have proposed algorithms that model mean and variance of a distribution. This paper argues that estimating the predictive concentration variance entails not only a gradual improvement but is rather a significant step to advance the field. This is, first, since the models much better fit the particular structure of gas distributions, which exhibit strong fluctuations with considerable spatial variations as a result of the intermittent character of gas dispersal. Second, because estimating the predictive variance allows to evaluate the model quality in terms of the data likelihood. This offers a solution to the problem of ground truth evaluation, which has always been a critical issue for gas distribution modelling. It also enables solid comparisons of different modelling approaches, and provides the means to learn meta parameters of the model, to determine when the model should be updated or re-initialised, or to suggest new measurement locations based on the current model. We also point out directions of related ongoing or potential future research work.
Real Rainfall Time Series for Storm Sewer Design
DEFF Research Database (Denmark)
Larsen, Torben
1981-01-01
to a storm sewer system. The output of the simulation is the frequency distribution of the peak flow, overflow volume etc. from the overflow or the retention storage. The parameters in the transfer model are found either from rainfall/runoff measurements in the catchment or from one or more simulations...
Assigning probability distributions to input parameters of performance assessment models
Energy Technology Data Exchange (ETDEWEB)
Mishra, Srikanta [INTERA Inc., Austin, TX (United States)
2002-02-01
This study presents an overview of various approaches for assigning probability distributions to input parameters and/or future states of performance assessment models. Specifically,three broad approaches are discussed for developing input distributions: (a) fitting continuous distributions to data, (b) subjective assessment of probabilities, and (c) Bayesian updating of prior knowledge based on new information. The report begins with a summary of the nature of data and distributions, followed by a discussion of several common theoretical parametric models for characterizing distributions. Next, various techniques are presented for fitting continuous distributions to data. These include probability plotting, method of moments, maximum likelihood estimation and nonlinear least squares analysis. The techniques are demonstrated using data from a recent performance assessment study for the Yucca Mountain project. Goodness of fit techniques are also discussed, followed by an overview of how distribution fitting is accomplished in commercial software packages. The issue of subjective assessment of probabilities is dealt with in terms of the maximum entropy distribution selection approach, as well as some common rules for codifying informal expert judgment. Formal expert elicitation protocols are discussed next, and are based primarily on the guidance provided by the US NRC. The Bayesian framework for updating prior distributions (beliefs) when new information becomes available is discussed. A simple numerical approach is presented for facilitating practical applications of the Bayes theorem. Finally, a systematic framework for assigning distributions is presented: (a) for the situation where enough data are available to define an empirical CDF or fit a parametric model to the data, and (b) to deal with the situation where only a limited amount of information is available.
Assigning probability distributions to input parameters of performance assessment models
International Nuclear Information System (INIS)
Mishra, Srikanta
2002-02-01
This study presents an overview of various approaches for assigning probability distributions to input parameters and/or future states of performance assessment models. Specifically,three broad approaches are discussed for developing input distributions: (a) fitting continuous distributions to data, (b) subjective assessment of probabilities, and (c) Bayesian updating of prior knowledge based on new information. The report begins with a summary of the nature of data and distributions, followed by a discussion of several common theoretical parametric models for characterizing distributions. Next, various techniques are presented for fitting continuous distributions to data. These include probability plotting, method of moments, maximum likelihood estimation and nonlinear least squares analysis. The techniques are demonstrated using data from a recent performance assessment study for the Yucca Mountain project. Goodness of fit techniques are also discussed, followed by an overview of how distribution fitting is accomplished in commercial software packages. The issue of subjective assessment of probabilities is dealt with in terms of the maximum entropy distribution selection approach, as well as some common rules for codifying informal expert judgment. Formal expert elicitation protocols are discussed next, and are based primarily on the guidance provided by the US NRC. The Bayesian framework for updating prior distributions (beliefs) when new information becomes available is discussed. A simple numerical approach is presented for facilitating practical applications of the Bayes theorem. Finally, a systematic framework for assigning distributions is presented: (a) for the situation where enough data are available to define an empirical CDF or fit a parametric model to the data, and (b) to deal with the situation where only a limited amount of information is available
Modeling the probability distribution of peak discharge for infiltrating hillslopes
Baiamonte, Giorgio; Singh, Vijay P.
2017-07-01
Hillslope response plays a fundamental role in the prediction of peak discharge at the basin outlet. The peak discharge for the critical duration of rainfall and its probability distribution are needed for designing urban infrastructure facilities. This study derives the probability distribution, denoted as GABS model, by coupling three models: (1) the Green-Ampt model for computing infiltration, (2) the kinematic wave model for computing discharge hydrograph from the hillslope, and (3) the intensity-duration-frequency (IDF) model for computing design rainfall intensity. The Hortonian mechanism for runoff generation is employed for computing the surface runoff hydrograph. Since the antecedent soil moisture condition (ASMC) significantly affects the rate of infiltration, its effect on the probability distribution of peak discharge is investigated. Application to a watershed in Sicily, Italy, shows that with the increase of probability, the expected effect of ASMC to increase the maximum discharge diminishes. Only for low values of probability, the critical duration of rainfall is influenced by ASMC, whereas its effect on the peak discharge seems to be less for any probability. For a set of parameters, the derived probability distribution of peak discharge seems to be fitted by the gamma distribution well. Finally, an application to a small watershed, with the aim to test the possibility to arrange in advance the rational runoff coefficient tables to be used for the rational method, and a comparison between peak discharges obtained by the GABS model with those measured in an experimental flume for a loamy-sand soil were carried out.
Stand diameter distribution modelling and prediction based on Richards function.
Directory of Open Access Journals (Sweden)
Ai-guo Duan
Full Text Available The objective of this study was to introduce application of the Richards equation on modelling and prediction of stand diameter distribution. The long-term repeated measurement data sets, consisted of 309 diameter frequency distributions from Chinese fir (Cunninghamia lanceolata plantations in the southern China, were used. Also, 150 stands were used as fitting data, the other 159 stands were used for testing. Nonlinear regression method (NRM or maximum likelihood estimates method (MLEM were applied to estimate the parameters of models, and the parameter prediction method (PPM and parameter recovery method (PRM were used to predict the diameter distributions of unknown stands. Four main conclusions were obtained: (1 R distribution presented a more accurate simulation than three-parametric Weibull function; (2 the parameters p, q and r of R distribution proved to be its scale, location and shape parameters, and have a deep relationship with stand characteristics, which means the parameters of R distribution have good theoretical interpretation; (3 the ordinate of inflection point of R distribution has significant relativity with its skewness and kurtosis, and the fitted main distribution range for the cumulative diameter distribution of Chinese fir plantations was 0.4∼0.6; (4 the goodness-of-fit test showed diameter distributions of unknown stands can be well estimated by applying R distribution based on PRM or the combination of PPM and PRM under the condition that only quadratic mean DBH or plus stand age are known, and the non-rejection rates were near 80%, which are higher than the 72.33% non-rejection rate of three-parametric Weibull function based on the combination of PPM and PRM.
Directory of Open Access Journals (Sweden)
Nobuaki Kimura
2014-01-01
Full Text Available Severe rainstorms have occurred more frequently in Taiwan over the last decade. To understand the flood characteristics of a local region under climate change, a hydrological model simulation was conducted for the Tsengwen Reservoir watershed. The model employed was the Integrated Flood Analysis System (IFAS, which has a conceptual, distributed rainfall-runoff analysis module and a GIS data-input function. The high-resolution rainfall data for flood simulation was categorized into three terms: 1979 - 2003 (Present, 2015 - 2039 (Near-future, and 2075 - 2099 (Future, provided by the Meteorological Research Institute atmospheric general circulation model (MRI-AGCM. Ten extreme rainfall (top ten events were selected for each term in descending order of total precipitation volume. Due to the small watershed area the MRI-AGCM3.2S data was downsized into higher resolution data using the Weather Research and Forecasting Model. The simulated discharges revealed that most of the Near-future and Future peaks caused by extreme rainfall increased compared to the Present peak. These ratios were 0.8 - 1.6 (Near-future/Present and 0.9 - 2.2 (Future/Present, respectively. Additionally, we evaluated how these future discharges would affect the reservoir¡¦s flood control capacity, specifically the excess water volume required to be stored while maintaining dam releases up to the dam¡¦s spillway capacity or the discharge peak design for flood prevention. The results for the top ten events show that the excess water for the Future term exceeded the reservoir¡¦s flood control capacity and was approximately 79.6 - 87.5% of the total reservoir maximum capacity for the discharge peak design scenario.
A Discrete Model for HIV Infection with Distributed Delay
Directory of Open Access Journals (Sweden)
Brahim EL Boukari
2014-01-01
Full Text Available We give a consistent discretization of a continuous model of HIV infection, with distributed time delays to express the lag between the times when the virus enters a cell and when the cell becomes infected. The global stability of the steady states of the model is determined and numerical simulations are presented to illustrate our theoretical results.
Optimal dimensioning model of water distribution systems | Gomes ...
African Journals Online (AJOL)
This study is aimed at developing a pipe-sizing model for a water distribution system. The optimal solution minimises the system's total cost, which comprises the hydraulic network capital cost, plus the capitalised cost of pumping energy. The developed model, called Lenhsnet, may also be used for economical design when ...
Five (or so) challenges for species distribution modelling
DEFF Research Database (Denmark)
Bastos Araujo, Miguel; Guisan, Antoine
2006-01-01
Species distribution modelling is central to both fundamental and applied research in biogeography. Despite widespread use of models, there are still important conceptual ambiguities as well as biotic and algorithmic uncertainties that need to be investigated in order to increase confidence in mo...
Degree distribution of a new model for evolving networks
Indian Academy of Sciences (India)
on intuitive but realistic consideration that nodes are added to the network with both preferential and random attachments. The degree distribution of the model is between a power-law and an exponential decay. Motivated by the features of network evolution, we introduce a new model of evolving networks, incorporating the ...
Diffusion approximation for modeling of 3-D radiation distributions
International Nuclear Information System (INIS)
Zardecki, A.; Gerstl, S.A.W.; De Kinder, R.E. Jr.
1985-01-01
A three-dimensional transport code DIF3D, based on the diffusion approximation, is used to model the spatial distribution of radiation energy arising from volumetric isotropic sources. Future work will be concerned with the determination of irradiances and modeling of realistic scenarios, relevant to the battlefield conditions. 8 refs., 4 figs
Occam factors and model independent Bayesian learning of continuous distributions
International Nuclear Information System (INIS)
Nemenman, Ilya; Bialek, William
2002-01-01
Learning of a smooth but nonparametric probability density can be regularized using methods of quantum field theory. We implement a field theoretic prior numerically, test its efficacy, and show that the data and the phase space factors arising from the integration over the model space determine the free parameter of the theory ('smoothness scale') self-consistently. This persists even for distributions that are atypical in the prior and is a step towards a model independent theory for learning continuous distributions. Finally, we point out that a wrong parametrization of a model family may sometimes be advantageous for small data sets
Spatial distribution of emissions to air - the SPREAD model
Energy Technology Data Exchange (ETDEWEB)
Plejdrup, M S; Gyldenkaerne, S
2011-04-15
The National Environmental Research Institute (NERI), Aarhus University, completes the annual national emission inventories for greenhouse gases and air pollutants according to Denmark's obligations under international conventions, e.g. the climate convention, UNFCCC and the convention on long-range transboundary air pollution, CLRTAP. NERI has developed a model to distribute emissions from the national emission inventories on a 1x1 km grid covering the Danish land and sea territory. The new spatial high resolution distribution model for emissions to air (SPREAD) has been developed according to the requirements for reporting of gridded emissions to CLRTAP. Spatial emission data is e.g. used as input for air quality modelling, which again serves as input for assessment and evaluation of health effects. For these purposes distributions with higher spatial resolution have been requested. Previously, a distribution on the 17x17 km EMEP grid has been set up and used in research projects combined with detailed distributions for a few sectors or sub-sectors e.g. a distribution for emissions from road traffic on 1x1 km resolution. SPREAD is developed to generate improved spatial emission data for e.g. air quality modelling in exposure studies. SPREAD includes emission distributions for each sector in the Danish inventory system; stationary combustion, mobile sources, fugitive emissions from fuels, industrial processes, solvents and other product use, agriculture and waste. This model enables generation of distributions for single sectors and for a number of sub-sectors and single sources as well. This report documents the methodologies in this first version of SPREAD and presents selected results. Further, a number of potential improvements for later versions of SPREAD are addressed and discussed. (Author)
Spatial distribution of emissions to air - the SPREAD model
Energy Technology Data Exchange (ETDEWEB)
Plejdrup, M.S.; Gyldenkaerne, S.
2011-04-15
The National Environmental Research Institute (NERI), Aarhus University, completes the annual national emission inventories for greenhouse gases and air pollutants according to Denmark's obligations under international conventions, e.g. the climate convention, UNFCCC and the convention on long-range transboundary air pollution, CLRTAP. NERI has developed a model to distribute emissions from the national emission inventories on a 1x1 km grid covering the Danish land and sea territory. The new spatial high resolution distribution model for emissions to air (SPREAD) has been developed according to the requirements for reporting of gridded emissions to CLRTAP. Spatial emission data is e.g. used as input for air quality modelling, which again serves as input for assessment and evaluation of health effects. For these purposes distributions with higher spatial resolution have been requested. Previously, a distribution on the 17x17 km EMEP grid has been set up and used in research projects combined with detailed distributions for a few sectors or sub-sectors e.g. a distribution for emissions from road traffic on 1x1 km resolution. SPREAD is developed to generate improved spatial emission data for e.g. air quality modelling in exposure studies. SPREAD includes emission distributions for each sector in the Danish inventory system; stationary combustion, mobile sources, fugitive emissions from fuels, industrial processes, solvents and other product use, agriculture and waste. This model enables generation of distributions for single sectors and for a number of sub-sectors and single sources as well. This report documents the methodologies in this first version of SPREAD and presents selected results. Further, a number of potential improvements for later versions of SPREAD are addressed and discussed. (Author)
Smoluchowski coagulation models of sea ice thickness distribution dynamics
Godlovitch, D.; Illner, R.; Monahan, A.
2011-12-01
Sea ice thickness distributions display a ubiquitous exponential decrease with thickness. This tail characterizes the range of ice thickness produced by mechanical redistribution of ice through the process of ridging, rafting, and shearing. We investigate how well the thickness distribution can be simulated by representing mechanical redistribution as a generalized stacking process. Such processes are naturally described by a well-studied class of models known as Smoluchowski Coagulation Models (SCMs), which describe the dynamics of a population of fixed-mass "particles" which combine in pairs to form a "particle" with the combined mass of the constituent pair at a rate which depends on the mass of the interacting particles. Like observed sea ice thickness distributions, the mass distribution of the populations generated by SCMs has an exponential or quasi-exponential form. We use SCMs to model sea ice, identifying mass-increasing particle combinations with thickness-increasing ice redistribution processes. Our model couples an SCM component with a thermodynamic component and generates qualitatively accurate thickness distributions with a variety of rate kernels. Our results suggest that the exponential tail of the sea ice thickness distribution arises from the nature of the ridging process, rather than specific physical properties of sea ice or the spatial arrangement of floes, and that the relative strengths of the dynamic and thermodynamic processes are key in accurately simulating the rate at which the sea ice thickness tail drops off with thickness.
Guo, B.
2017-12-01
Mountain watershed in Western China is prone to flash floods. The Wenchuan earthquake on May 12, 2008 led to the destruction of surface, and frequent landslides and debris flow, which further exacerbated the flash flood hazards. Two giant torrent and debris flows occurred due to heavy rainfall after the earthquake, one was on August 13 2010, and the other on August 18 2010. Flash floods reduction and risk assessment are the key issues in post-disaster reconstruction. Hydrological prediction models are important and cost-efficient mitigation tools being widely applied. In this paper, hydrological observations and simulation using remote sensing data and the WMS model are carried out in the typical flood-hit area, Longxihe watershed, Dujiangyan City, Sichuan Province, China. The hydrological response of rainfall runoff is discussed. The results show that: the WMS HEC-1 model can well simulate the runoff process of small watershed in mountainous area. This methodology can be used in other earthquake-affected areas for risk assessment and to predict the magnitude of flash floods. Key Words: Rainfall-runoff modeling. Remote Sensing. Earthquake. WMS.
Directory of Open Access Journals (Sweden)
Asma Foughali
2015-07-01
Full Text Available This work aims to evaluate the performance of a hydrological balance model in a watershed located in northern Tunisia (wadi Sejnane, 378 km2 in present climate conditions using input variables provided by four regional climate models. A modified version (MBBH of the lumped and single layer surface model BBH (Bucket with Bottom Hole model, in which pedo-transfer parameters estimated using watershed physiographic characteristics are introduced is adopted to simulate the water balance components. Only two parameters representing respectively the water retention capacity of the soil and the vegetation resistance to evapotranspiration are calibrated using rainfall-runoff data. The evaluation criterions for the MBBH model calibration are: relative bias, mean square error and the ratio of mean actual evapotranspiration to mean potential evapotranspiration. Daily air temperature, rainfall and runoff observations are available from 1960 to 1984. The period 1960–1971 is selected for calibration while the period 1972–1984 is chosen for validation. Air temperature and precipitation series are provided by four regional climate models (DMI, ARP, SMH and ICT from the European program ENSEMBLES, forced by two global climate models (GCM: ECHAM and ARPEGE. The regional climate model outputs (precipitation and air temperature are compared to the observations in terms of statistical distribution. The analysis was performed at the seasonal scale for precipitation. We found out that RCM precipitation must be corrected before being introduced as MBBH inputs. Thus, a non-parametric quantile-quantile bias correction method together with a dry day correction is employed. Finally, simulated runoff generated using corrected precipitation from the regional climate model SMH is found the most acceptable by comparison with runoff simulated using observed precipitation data, to reproduce the temporal variability of mean monthly runoff. The SMH model is the most accurate to
Distributing Correlation Coefficients of Linear Structure-Activity/Property Models
Directory of Open Access Journals (Sweden)
Sorana D. BOLBOACA
2011-12-01
Full Text Available Quantitative structure-activity/property relationships are mathematical relationships linking chemical structure and activity/property in a quantitative manner. These in silico approaches are frequently used to reduce animal testing and risk-assessment, as well as to increase time- and cost-effectiveness in characterization and identification of active compounds. The aim of our study was to investigate the pattern of correlation coefficients distribution associated to simple linear relationships linking the compounds structure with their activities. A set of the most common ordnance compounds found at naval facilities with a limited data set with a range of toxicities on aquatic ecosystem and a set of seven properties was studied. Statistically significant models were selected and investigated. The probability density function of the correlation coefficients was investigated using a series of possible continuous distribution laws. Almost 48% of the correlation coefficients proved fit Beta distribution, 40% fit Generalized Pareto distribution, and 12% fit Pert distribution.
Kaon quark distribution functions in the chiral constituent quark model
Watanabe, Akira; Sawada, Takahiro; Kao, Chung Wen
2018-04-01
We investigate the valence u and s ¯ quark distribution functions of the K+ meson, vK (u )(x ,Q2) and vK (s ¯)(x ,Q2), in the framework of the chiral constituent quark model. We judiciously choose the bare distributions at the initial scale to generate the dressed distributions at the higher scale, considering the meson cloud effects and the QCD evolution, which agree with the phenomenologically satisfactory valence quark distribution of the pion and the experimental data of the ratio vK (u )(x ,Q2)/vπ (u )(x ,Q2) . We show how the meson cloud effects affect the bare distribution functions in detail. We find that a smaller S U (3 ) flavor symmetry breaking effect is observed, compared with results of the preceding studies based on other approaches.
Bilinear reduced order approximate model of parabolic distributed solar collectors
Elmetennani, Shahrazed
2015-07-01
This paper proposes a novel, low dimensional and accurate approximate model for the distributed parabolic solar collector, by means of a modified gaussian interpolation along the spatial domain. The proposed reduced model, taking the form of a low dimensional bilinear state representation, enables the reproduction of the heat transfer dynamics along the collector tube for system analysis. Moreover, presented as a reduced order bilinear state space model, the well established control theory for this class of systems can be applied. The approximation efficiency has been proven by several simulation tests, which have been performed considering parameters of the Acurex field with real external working conditions. Model accuracy has been evaluated by comparison to the analytical solution of the hyperbolic distributed model and its semi discretized approximation highlighting the benefits of using the proposed numerical scheme. Furthermore, model sensitivity to the different parameters of the gaussian interpolation has been studied.
Hydrological catchment modelling: past, present and future
Directory of Open Access Journals (Sweden)
2007-01-01
Full Text Available This paper discusses basic issues in hydrological modelling and flood forecasting, ranging from the roles of physically-based and data-driven rainfall runoff models, to the concepts of predictive uncertainty and equifinality and their implications. The evolution of a wide range of hydrological catchment models employing the physically meaningful and data-driven approaches introduces the need for objective test beds or benchmarks to assess the merits of the different models in reconciling the alternative approaches. In addition, the paper analyses uncertainty in models and predictions by clarifying the meaning of uncertainty, by distinguishing between parameter and predictive uncertainty and by demonstrating how the concept of equifinality must be addressed by appropriate and robust inference approaches. Finally, the importance of predictive uncertainty in the decision making process is highlighted together with possible approaches aimed at overcoming the diffidence of end-users.
Actors: A Model of Concurrent Computation in Distributed Systems.
1985-06-01
Artificial Intelligence Labora- tory of the Massachusetts Institute of Technology. Support for the labora- tory’s aritificial intelligence research is...RD-A157 917 ACTORS: A MODEL OF CONCURRENT COMPUTATION IN 1/3- DISTRIBUTED SYTEMS(U) MASSACHUSETTS INST OF TECH CRMBRIDGE ARTIFICIAL INTELLIGENCE ...Computation In Distributed Systems Gui A. Aghai MIT Artificial Intelligence Laboratory Thsdocument ha. been cipp-oved I= pblicrelease and sale; itsI
DEFF Research Database (Denmark)
Han, Xue; Sandels, Claes; Zhu, Kun
2013-01-01
There has been a large body of statements claiming that the large-scale deployment of Distributed Energy Resources (DERs) could eventually reshape the future distribution grid operation in numerous ways. Thus, it is necessary to introduce a framework to measure to what extent the power system......, comprising distributed generation, active demand and electric vehicles. Subsequently, quantitative analysis was made on the basis of the current and envisioned DER deployment scenarios proposed for Sweden. Simulations are performed in two typical distribution network models for four seasons. The simulation...... results show that in general the DER deployment brings in the possibilities to reduce the power losses and voltage drops by compensating power from the local generation and optimizing the local load profiles....
Reservoir theory, groundwater transit time distributions, and lumped parameter models
International Nuclear Information System (INIS)
Etcheverry, D.; Perrochet, P.
1999-01-01
The relation between groundwater residence times and transit times is given by the reservoir theory. It allows to calculate theoretical transit time distributions in a deterministic way, analytically, or on numerical models. Two analytical solutions validates the piston flow and the exponential model for simple conceptual flow systems. A numerical solution of a hypothetical regional groundwater flow shows that lumped parameter models could be applied in some cases to large-scale, heterogeneous aquifers. (author)
Quantification Model for Estimating Temperature Field Distributions of Apple Fruit
Zhang , Min; Yang , Le; Zhao , Huizhong; Zhang , Leijie; Zhong , Zhiyou; Liu , Yanling; Chen , Jianhua
2009-01-01
International audience; A quantification model of transient heat conduction was provided to simulate apple fruit temperature distribution in the cooling process. The model was based on the energy variation of apple fruit of different points. It took into account, heat exchange of representative elemental volume, metabolism heat and external heat. The following conclusions could be obtained: first, the quantification model can satisfactorily describe the tendency of apple fruit temperature dis...
Distributional Language Learning: Mechanisms and Models of ategory Formation.
Aslin, Richard N; Newport, Elissa L
2014-09-01
In the past 15 years, a substantial body of evidence has confirmed that a powerful distributional learning mechanism is present in infants, children, adults and (at least to some degree) in nonhuman animals as well. The present article briefly reviews this literature and then examines some of the fundamental questions that must be addressed for any distributional learning mechanism to operate effectively within the linguistic domain. In particular, how does a naive learner determine the number of categories that are present in a corpus of linguistic input and what distributional cues enable the learner to assign individual lexical items to those categories? Contrary to the hypothesis that distributional learning and category (or rule) learning are separate mechanisms, the present article argues that these two seemingly different processes---acquiring specific structure from linguistic input and generalizing beyond that input to novel exemplars---actually represent a single mechanism. Evidence in support of this single-mechanism hypothesis comes from a series of artificial grammar-learning studies that not only demonstrate that adults can learn grammatical categories from distributional information alone, but that the specific patterning of distributional information among attested utterances in the learning corpus enables adults to generalize to novel utterances or to restrict generalization when unattested utterances are consistently absent from the learning corpus. Finally, a computational model of distributional learning that accounts for the presence or absence of generalization is reviewed and the implications of this model for linguistic-category learning are summarized.
Using the Weibull distribution reliability, modeling and inference
McCool, John I
2012-01-01
Understand and utilize the latest developments in Weibull inferential methods While the Weibull distribution is widely used in science and engineering, most engineers do not have the necessary statistical training to implement the methodology effectively. Using the Weibull Distribution: Reliability, Modeling, and Inference fills a gap in the current literature on the topic, introducing a self-contained presentation of the probabilistic basis for the methodology while providing powerful techniques for extracting information from data. The author explains the use of the Weibull distribution
Shell model test of the Porter-Thomas distribution
International Nuclear Information System (INIS)
Grimes, S.M.; Bloom, S.D.
1981-01-01
Eigenvectors have been calculated for the A=18, 19, 20, 21, and 26 nuclei in an sd shell basis. The decomposition of these states into their shell model components shows, in agreement with other recent work, that this distribution is not a single Gaussian. We find that the largest amplitudes are distributed approximately in a Gaussian fashion. Thus, many experimental measurements should be consistent with the Porter-Thomas predictions. We argue that the non-Gaussian form of the complete distribution can be simply related to the structure of the Hamiltonian
Distributed model based control of multi unit evaporation systems
International Nuclear Information System (INIS)
Yudi Samyudia
2006-01-01
In this paper, we present a new approach to the analysis and design of distributed control systems for multi-unit plants. The approach is established after treating the effect of recycled dynamics as a gap metric uncertainty from which a distributed controller can be designed sequentially for each unit to tackle the uncertainty. We then use a single effect multi-unit evaporation system to illustrate how the proposed method is used to analyze different control strategies and to systematically achieve a better closed-loop performance using a distributed model-based controller
Transversity quark distributions in a covariant quark-diquark model
Energy Technology Data Exchange (ETDEWEB)
Cloet, I.C. [Physics Division, Argonne National Laboratory, Argonne, IL 60439-4843 (United States)], E-mail: icloet@anl.gov; Bentz, W. [Department of Physics, School of Science, Tokai University, Hiratsuka-shi, Kanagawa 259-1292 (Japan)], E-mail: bentz@keyaki.cc.u-tokai.ac.jp; Thomas, A.W. [Jefferson Lab, 12000 Jefferson Avenue, Newport News, VA 23606 (United States); College of William and Mary, Williamsburg, VA 23187 (United States)], E-mail: awthomas@jlab.org
2008-01-17
Transversity quark light-cone momentum distributions are calculated for the nucleon. We utilize a modified Nambu-Jona-Lasinio model in which confinement is simulated by eliminating unphysical thresholds for nucleon decay into quarks. The nucleon bound state is obtained by solving the relativistic Faddeev equation in the quark-diquark approximation, where both scalar and axial-vector diquark channels are included. Particular attention is paid to comparing our results with the recent experimental extraction of the transversity distributions by Anselmino et al. We also compare our transversity results with earlier spin-independent and helicity quark distributions calculated in the same approach.
Analysis and Comparison of Typical Models within Distribution Network Design
DEFF Research Database (Denmark)
Jørgensen, Hans Jacob; Larsen, Allan; Madsen, Oli B.G.
Efficient and cost effective transportation and logistics plays a vital role in the supply chains of the modern world’s manufacturers. Global distribution of goods is a very complicated matter as it involves many different distinct planning problems. The focus of this presentation is to demonstrate...... a number of important issues which have been identified when addressing the Distribution Network Design problem from a modelling angle. More specifically, we present an analysis of the research which has been performed in utilizing operational research in developing and optimising distribution systems....
Confronting species distribution model predictions with species functional traits.
Wittmann, Marion E; Barnes, Matthew A; Jerde, Christopher L; Jones, Lisa A; Lodge, David M
2016-02-01
Species distribution models are valuable tools in studies of biogeography, ecology, and climate change and have been used to inform conservation and ecosystem management. However, species distribution models typically incorporate only climatic variables and species presence data. Model development or validation rarely considers functional components of species traits or other types of biological data. We implemented a species distribution model (Maxent) to predict global climate habitat suitability for Grass Carp (Ctenopharyngodon idella). We then tested the relationship between the degree of climate habitat suitability predicted by Maxent and the individual growth rates of both wild (N = 17) and stocked (N = 51) Grass Carp populations using correlation analysis. The Grass Carp Maxent model accurately reflected the global occurrence data (AUC = 0.904). Observations of Grass Carp growth rate covered six continents and ranged from 0.19 to 20.1 g day(-1). Species distribution model predictions were correlated (r = 0.5, 95% CI (0.03, 0.79)) with observed growth rates for wild Grass Carp populations but were not correlated (r = -0.26, 95% CI (-0.5, 0.012)) with stocked populations. Further, a review of the literature indicates that the few studies for other species that have previously assessed the relationship between the degree of predicted climate habitat suitability and species functional traits have also discovered significant relationships. Thus, species distribution models may provide inferences beyond just where a species may occur, providing a useful tool to understand the linkage between species distributions and underlying biological mechanisms.
A distributed dynamic model of a monolith hydrogen membrane reactor
International Nuclear Information System (INIS)
Michelsen, Finn Are; Wilhelmsen, Øivind; Zhao, Lei; Aasen, Knut Ingvar
2013-01-01
Highlights: ► We model a rigorous distributed dynamic model for a HMR unit. ► The model includes enough complexity for steady-state and dynamic analysis. ► Simulations show that the model is non-linear within the normal operating range. ► The model is useful for studying and handling disturbances such as inlet changes and membrane leakage. - Abstract: This paper describes a distributed mechanistic dynamic model of a hydrogen membrane reformer unit (HMR) used for methane steam reforming. The model is based on a square channel monolith structure concept, where air flows adjacent to a mix of natural gas and water distributed in a chess pattern of channels. Combustion of hydrogen gives energy to the endothermic steam reforming reactions. The model is used for both steady state and dynamic analyses. It therefore needs to be computationally attractive, but still include enough complexity to study the important steady state and dynamic features of the process. Steady-state analysis of the model gives optimum for the steam to carbon and steam to oxygen ratios, where the conversion of methane is 92% and the hydrogen used as energy for the endothermic reactions is 28% at the nominal optimum. The dynamic analysis shows that non-linear control schemes may be necessary for satisfactory control performance
Joint Distributed Surf Zone Environmental Model: FY96 Modeling Procedure
National Research Council Canada - National Science Library
Allard, Richard
1997-01-01
... to the modeling and simulation community. To test this proof of concept, a suite of models were identified and tested for Camp Pendelton, CA, during two 7 day periods in January and August 1995, in which data from the Coupled Ocean...
Energy Technology Data Exchange (ETDEWEB)
NONE
1995-02-17
The Natural Gas Transmission and Distribution Model (NGTDM) is the component of the National Energy Modeling System (NEMS) that is used to represent the domestic natural gas transmission and distribution system. NEMS was developed in the Office of integrated Analysis and Forecasting of the Energy information Administration (EIA). NEMS is the third in a series of computer-based, midterm energy modeling systems used since 1974 by the EIA and its predecessor, the Federal Energy Administration, to analyze domestic energy-economy markets and develop projections. The NGTDM is the model within the NEMS that represents the transmission, distribution, and pricing of natural gas. The model also includes representations of the end-use demand for natural gas, the production of domestic natural gas, and the availability of natural gas traded on the international market based on information received from other NEMS models. The NGTDM determines the flow of natural gas in an aggregate, domestic pipeline network, connecting domestic and foreign supply regions with 12 demand regions. The methodology employed allows the analysis of impacts of regional capacity constraints in the interstate natural gas pipeline network and the identification of pipeline capacity expansion requirements. There is an explicit representation of core and noncore markets for natural gas transmission and distribution services, and the key components of pipeline tariffs are represented in a pricing algorithm. Natural gas pricing and flow patterns are derived by obtaining a market equilibrium across the three main elements of the natural gas market: the supply element, the demand element, and the transmission and distribution network that links them. The NGTDM consists of four modules: the Annual Flow Module, the Capacity F-expansion Module, the Pipeline Tariff Module, and the Distributor Tariff Module. A model abstract is provided in Appendix A.
International Nuclear Information System (INIS)
1995-01-01
The Natural Gas Transmission and Distribution Model (NGTDM) is the component of the National Energy Modeling System (NEMS) that is used to represent the domestic natural gas transmission and distribution system. NEMS was developed in the Office of integrated Analysis and Forecasting of the Energy information Administration (EIA). NEMS is the third in a series of computer-based, midterm energy modeling systems used since 1974 by the EIA and its predecessor, the Federal Energy Administration, to analyze domestic energy-economy markets and develop projections. The NGTDM is the model within the NEMS that represents the transmission, distribution, and pricing of natural gas. The model also includes representations of the end-use demand for natural gas, the production of domestic natural gas, and the availability of natural gas traded on the international market based on information received from other NEMS models. The NGTDM determines the flow of natural gas in an aggregate, domestic pipeline network, connecting domestic and foreign supply regions with 12 demand regions. The methodology employed allows the analysis of impacts of regional capacity constraints in the interstate natural gas pipeline network and the identification of pipeline capacity expansion requirements. There is an explicit representation of core and noncore markets for natural gas transmission and distribution services, and the key components of pipeline tariffs are represented in a pricing algorithm. Natural gas pricing and flow patterns are derived by obtaining a market equilibrium across the three main elements of the natural gas market: the supply element, the demand element, and the transmission and distribution network that links them. The NGTDM consists of four modules: the Annual Flow Module, the Capacity F-expansion Module, the Pipeline Tariff Module, and the Distributor Tariff Module. A model abstract is provided in Appendix A
Directory of Open Access Journals (Sweden)
Penny Masuoka
2010-11-01
Full Text Available Over 35,000 cases of Japanese encephalitis (JE are reported worldwide each year. Culex tritaeniorhynchus is the primary vector of the JE virus, while wading birds are natural reservoirs and swine amplifying hosts. As part of a JE risk analysis, the ecological niche modeling programme, Maxent, was used to develop a predictive model for the distribution of Cx. tritaeniorhynchus in the Republic of Korea, using mosquito collection data, temperature, precipitation, elevation, land cover and the normalized difference vegetation index (NDVI. The resulting probability maps from the model were consistent with the known environmental limitations of the mosquito with low probabilities predicted for forest covered mountains. July minimum temperature and land cover were the most important variables in the model. Elevation, summer NDVI (July-September, precipitation in July, summer minimum temperature (May-August and maximum temperature for fall and winter months also contributed to the model. Comparison of the Cx. tritaeniorhynchus model to the distribution of JE cases in the Republic of Korea from 2001 to 2009 showed that cases among a highly vaccinated Korean population were located in high-probability areas for Cx. tritaeniorhynchus. No recent JE cases were reported from the eastern coastline, where higher probabilities of mosquitoes were predicted, but where only small numbers of pigs are raised. The geographical distribution of reported JE cases corresponded closely with the predicted high-probability areas for Cx. tritaeniorhynchus, making the map a useful tool for health risk analysis that could be used for planning preventive public health measures.
Dynamical Analysis of SIR Epidemic Models with Distributed Delay
Directory of Open Access Journals (Sweden)
Wencai Zhao
2013-01-01
Full Text Available SIR epidemic models with distributed delay are proposed. Firstly, the dynamical behaviors of the model without vaccination are studied. Using the Jacobian matrix, the stability of the equilibrium points of the system without vaccination is analyzed. The basic reproduction number R is got. In order to study the important role of vaccination to prevent diseases, the model with distributed delay under impulsive vaccination is formulated. And the sufficient conditions of globally asymptotic stability of “infection-free” periodic solution and the permanence of the model are obtained by using Floquet’s theorem, small-amplitude perturbation skills, and comparison theorem. Lastly, numerical simulation is presented to illustrate our main conclusions that vaccination has significant effects on the dynamical behaviors of the model. The results can provide effective tactic basis for the practical infectious disease prevention.
Model for the angular distribution of sky radiance
Energy Technology Data Exchange (ETDEWEB)
Hooper, F C; Brunger, A P
1979-08-01
A flexible mathematical model is introduced which describes the radiance of the dome of the sky under various conditions. This three-component continuous distribution (TCCD) model is compounded by the superposition of three separate terms, the isotropic, circumsolar and horizon brightening terms, each representing the contribution of a particular sky characteristic. In use a particular sky condition is characterized by the values of the coefficients of each of these three terms, defining the distribution of the total diffuse component. The TCCD model has been demonstrated to fit both the normalized clear sky data and the normalized overcast sky data with an RMS error of about ten percent of the man overall sky radiance. By extension the model could describe variable or partly clouded sky conditions. The model can aid in improving the prediction of solar collector performance.
Distributed models coupling soakaways, urban drainage and groundwater
DEFF Research Database (Denmark)
Roldin, Maria Kerstin
in receiving waters, urban flooding etc. WSUD structures are generally small, decentralized systems intended to manage stormwater near the source. Many of these alternative techniques are based on infiltration which can affect both the urban sewer system and urban groundwater levels if widely implemented......Alternative methods for stormwater management in urban areas, also called Water Sensitive Urban Design (WSUD) methods, have become increasingly important for the mitigation of urban stormwater management problems such as high runoff volumes, combined sewage overflows, poor water quality......, and how these can be modeled in an integrated environment with distributed urban drainage and groundwater flow models. The thesis: 1. Identifies appropriate models of soakaways for use in an integrated and distributed urban water and groundwater modeling system 2. Develops a modeling concept that is able...
UV Stellar Distribution Model for the Derivation of Payload
Directory of Open Access Journals (Sweden)
Young-Jun Choi
1999-12-01
Full Text Available We present the results of a model calculation of the stellar distribution in a UV and centered at 2175Å corresponding to the well-known bump in the interstellar extinction curve. The stellar distribution model used here is based on the Bahcall-Soneira galaxy model (1980. The source code for model calculation was designed by Brosch (1991 and modified to investigate various designing factors for UV satellite payload. The model predicts UV stellar densities in different sky directions, and its results are compared with the TD-1 star counts for a number of sky regions. From this study, we can determine the field of view, size of optics, angular resolution, and number of stars in one orbit. There will provide the basic constrains in designing a satellite payload for UV observations.
Species distribution models of tropical deep-sea snappers.
Directory of Open Access Journals (Sweden)
Céline Gomez
Full Text Available Deep-sea fisheries provide an important source of protein to Pacific Island countries and territories that are highly dependent on fish for food security. However, spatial management of these deep-sea habitats is hindered by insufficient data. We developed species distribution models using spatially limited presence data for the main harvested species in the Western Central Pacific Ocean. We used bathymetric and water temperature data to develop presence-only species distribution models for the commercially exploited deep-sea snappers Etelis Cuvier 1828, Pristipomoides Valenciennes 1830, and Aphareus Cuvier 1830. We evaluated the performance of four different algorithms (CTA, GLM, MARS, and MAXENT within the BIOMOD framework to obtain an ensemble of predicted distributions. We projected these predictions across the Western Central Pacific Ocean to produce maps of potential deep-sea snapper distributions in 32 countries and territories. Depth was consistently the best predictor of presence for all species groups across all models. Bathymetric slope was consistently the poorest predictor. Temperature at depth was a good predictor of presence for GLM only. Model precision was highest for MAXENT and CTA. There were strong regional patterns in predicted distribution of suitable habitat, with the largest areas of suitable habitat (> 35% of the Exclusive Economic Zone predicted in seven South Pacific countries and territories (Fiji, Matthew & Hunter, Nauru, New Caledonia, Tonga, Vanuatu and Wallis & Futuna. Predicted habitat also varied among species, with the proportion of predicted habitat highest for Aphareus and lowest for Etelis. Despite data paucity, the relationship between deep-sea snapper presence and their environments was sufficiently strong to predict their distribution across a large area of the Pacific Ocean. Our results therefore provide a strong baseline for designing monitoring programs that balance resource exploitation and
Mathematical modelling of flooding at Magela Creek
International Nuclear Information System (INIS)
Vardavas, I.
1989-01-01
The extent and frequency of the flooding at Magela Creek can be predicted from a mathematical/computer model describing the hydrological phases of surface runoff. Surface runoff involves complex water transfer processes over very inhomogeneous terrain. A simple mathematical model of these has been developed which includes the interception of rainfall by the plant canopy, evapotranspiration, infiltration of surface water into the soil, the storage of water in surface depressions, and overland and subsurface water flow. The rainfall-runoff model has then been incorporated into a more complex computer model to predict the amount of water that enters and leaves the Magela Creek flood plain, downstream of the mine. 2 figs., ills
Real-time modeling and simulation of distribution feeder and distributed resources
Singh, Pawan
The analysis of the electrical system dates back to the days when analog network analyzers were used. With the advent of digital computers, many programs were written for power-flow and short circuit analysis for the improvement of the electrical system. Real-time computer simulations can answer many what-if scenarios in the existing or the proposed power system. In this thesis, the standard IEEE 13-Node distribution feeder is developed and validated on a real-time platform OPAL-RT. The concept and the challenges of the real-time simulation are studied and addressed. Distributed energy resources include some of the commonly used distributed generation and storage devices like diesel engine, solar photovoltaic array, and battery storage system are modeled and simulated on a real-time platform. A microgrid encompasses a portion of an electric power distribution which is located downstream of the distribution substation. Normally, the microgrid operates in paralleled mode with the grid; however, scheduled or forced isolation can take place. In such conditions, the microgrid must have the ability to operate stably and autonomously. The microgrid can operate in grid connected and islanded mode, both the operating modes are studied in the last chapter. Towards the end, a simple microgrid controller modeled and simulated on the real-time platform is developed for energy management and protection for the microgrid.
Fitting the Probability Distribution Functions to Model Particulate Matter Concentrations
International Nuclear Information System (INIS)
El-Shanshoury, Gh.I.
2017-01-01
The main objective of this study is to identify the best probability distribution and the plotting position formula for modeling the concentrations of Total Suspended Particles (TSP) as well as the Particulate Matter with an aerodynamic diameter<10 μm (PM 10 ). The best distribution provides the estimated probabilities that exceed the threshold limit given by the Egyptian Air Quality Limit value (EAQLV) as well the number of exceedance days is estimated. The standard limits of the EAQLV for TSP and PM 10 concentrations are 24-h average of 230 μg/m 3 and 70 μg/m 3 , respectively. Five frequency distribution functions with seven formula of plotting positions (empirical cumulative distribution functions) are compared to fit the average of daily TSP and PM 10 concentrations in year 2014 for Ain Sokhna city. The Quantile-Quantile plot (Q-Q plot) is used as a method for assessing how closely a data set fits a particular distribution. A proper probability distribution that represents the TSP and PM 10 has been chosen based on the statistical performance indicator values. The results show that Hosking and Wallis plotting position combined with Frechet distribution gave the highest fit for TSP and PM 10 concentrations. Burr distribution with the same plotting position follows Frechet distribution. The exceedance probability and days over the EAQLV are predicted using Frechet distribution. In 2014, the exceedance probability and days for TSP concentrations are 0.052 and 19 days, respectively. Furthermore, the PM 10 concentration is found to exceed the threshold limit by 174 days
STOCHASTIC MODEL OF THE SPIN DISTRIBUTION OF DARK MATTER HALOS
Energy Technology Data Exchange (ETDEWEB)
Kim, Juhan [Center for Advanced Computation, Korea Institute for Advanced Study, Heogiro 85, Seoul 130-722 (Korea, Republic of); Choi, Yun-Young [Department of Astronomy and Space Science, Kyung Hee University, Gyeonggi 446-701 (Korea, Republic of); Kim, Sungsoo S.; Lee, Jeong-Eun [School of Space Research, Kyung Hee University, Gyeonggi 446-701 (Korea, Republic of)
2015-09-15
We employ a stochastic approach to probing the origin of the log-normal distributions of halo spin in N-body simulations. After analyzing spin evolution in halo merging trees, it was found that a spin change can be characterized by a stochastic random walk of angular momentum. Also, spin distributions generated by random walks are fairly consistent with those directly obtained from N-body simulations. We derived a stochastic differential equation from a widely used spin definition and measured the probability distributions of the derived angular momentum change from a massive set of halo merging trees. The roles of major merging and accretion are also statistically analyzed in evolving spin distributions. Several factors (local environment, halo mass, merging mass ratio, and redshift) are found to influence the angular momentum change. The spin distributions generated in the mean-field or void regions tend to shift slightly to a higher spin value compared with simulated spin distributions, which seems to be caused by the correlated random walks. We verified the assumption of randomness in the angular momentum change observed in the N-body simulation and detected several degrees of correlation between walks, which may provide a clue for the discrepancies between the simulated and generated spin distributions in the voids. However, the generated spin distributions in the group and cluster regions successfully match the simulated spin distribution. We also demonstrated that the log-normality of the spin distribution is a natural consequence of the stochastic differential equation of the halo spin, which is well described by the Geometric Brownian Motion model.
International Nuclear Information System (INIS)
1996-01-01
The Natural Gas Transmission and Distribution Model (NGTDM) of the National Energy Modeling System is developed and maintained by the Energy Information Administration (EIA), Office of Integrated Analysis and Forecasting. This report documents the archived version of the NGTDM that was used to produce the natural gas forecasts presented in the Annual Energy Outlook 1996, (DOE/EIA-0383(96)). The purpose of this report is to provide a reference document for model analysts, users, and the public that defines the objectives of the model, describes its basic approach, and provides detail on the methodology employed. Previously this report represented Volume I of a two-volume set. Volume II reported on model performance, detailing convergence criteria and properties, results of sensitivity testing, comparison of model outputs with the literature and/or other model results, and major unresolved issues
Energy Technology Data Exchange (ETDEWEB)
NONE
1996-02-26
The Natural Gas Transmission and Distribution Model (NGTDM) of the National Energy Modeling System is developed and maintained by the Energy Information Administration (EIA), Office of Integrated Analysis and Forecasting. This report documents the archived version of the NGTDM that was used to produce the natural gas forecasts presented in the Annual Energy Outlook 1996, (DOE/EIA-0383(96)). The purpose of this report is to provide a reference document for model analysts, users, and the public that defines the objectives of the model, describes its basic approach, and provides detail on the methodology employed. Previously this report represented Volume I of a two-volume set. Volume II reported on model performance, detailing convergence criteria and properties, results of sensitivity testing, comparison of model outputs with the literature and/or other model results, and major unresolved issues.
A simplified model of saltcake moisture distribution. Letter report
International Nuclear Information System (INIS)
Simmons, C.S.
1995-09-01
This letter report describes the formulation of a simplified model for finding the moisture distribution in a saltcake waste profile that has been stabilized by pumping out the drainable interstitial liquid. The model is based on assuming that capillarity mainly governs the distribution of moisture in the porous saltcake waste. A stead upward flow of moisture driven by evaporation from the waste surface is conceptualized to occur for isothermal conditions. To obtain hydraulic parameters for unsaturated conditions, the model is calibrated or matched to the relative saturation distribution as measured by neutron probe scans. The model is demonstrated on Tanks 104-BY and 105-TX as examples. A value of the model is that it identifies the key physical parameters that control the surface moisture content in a waste profile. Moreover, the model can be used to estimate the brine application rate at the waste surface that would raise the moisture content there to a safe level. Thus, the model can be applied to help design a strategy for correcting the moisture conditions in a saltcake waste tank
Nucleon parton distributions in a light-front quark model
International Nuclear Information System (INIS)
Gutsche, Thomas; Lyubovitskij, Valery E.; Schmidt, Ivan
2017-01-01
Continuing our analysis of parton distributions in the nucleon, we extend our light-front quark model in order to obtain both the helicity-independent and the helicity-dependent parton distributions, analytically matching the results of global fits at the initial scale μ∝ 1 GeV; they also contain the correct Dokshitzer-Gribov-Lipatov-Altarelli-Parisi evolution. We also calculate the transverse parton, Wigner and Husimi distributions from a unified point of view, using our light-front wave functions and expressing them in terms of the parton distributions q_v(x) and δq_v(x). Our results are very relevant for the current and future program of the COMPASS experiment at SPS (CERN). (orig.)
Nucleon parton distributions in a light-front quark model
Energy Technology Data Exchange (ETDEWEB)
Gutsche, Thomas [Universitaet Tuebingen, Institut fuer Theoretische Physik, Kepler Center for Astro and Particle Physics, Tuebingen (Germany); Lyubovitskij, Valery E. [Universitaet Tuebingen, Institut fuer Theoretische Physik, Kepler Center for Astro and Particle Physics, Tuebingen (Germany); Tomsk State University, Department of Physics, Tomsk (Russian Federation); Tomsk Polytechnic University, Laboratory of Particle Physics, Mathematical Physics Department, Tomsk (Russian Federation); Universidad Tecnica Federico Santa Maria, Departamento de Fisica y Centro Cientifico Tecnologico de Valparaiso (CCTVal), Valparaiso (Chile); Schmidt, Ivan [Universidad Tecnica Federico Santa Maria, Departamento de Fisica y Centro Cientifico Tecnologico de Valparaiso (CCTVal), Valparaiso (Chile)
2017-02-15
Continuing our analysis of parton distributions in the nucleon, we extend our light-front quark model in order to obtain both the helicity-independent and the helicity-dependent parton distributions, analytically matching the results of global fits at the initial scale μ∝ 1 GeV; they also contain the correct Dokshitzer-Gribov-Lipatov-Altarelli-Parisi evolution. We also calculate the transverse parton, Wigner and Husimi distributions from a unified point of view, using our light-front wave functions and expressing them in terms of the parton distributions q{sub v}(x) and δq{sub v}(x). Our results are very relevant for the current and future program of the COMPASS experiment at SPS (CERN). (orig.)
Cho, Jae Heon; Lee, Jong Ho
2015-11-01
Manual calibration is common in rainfall-runoff model applications. However, rainfall-runoff models include several complicated parameters; thus, significant time and effort are required to manually calibrate the parameters individually and repeatedly. Automatic calibration has relative merit regarding time efficiency and objectivity but shortcomings regarding understanding indigenous processes in the basin. In this study, a watershed model calibration framework was developed using an influence coefficient algorithm and genetic algorithm (WMCIG) to automatically calibrate the distributed models. The optimization problem used to minimize the sum of squares of the normalized residuals of the observed and predicted values was solved using a genetic algorithm (GA). The final model parameters were determined from the iteration with the smallest sum of squares of the normalized residuals of all iterations. The WMCIG was applied to a Gomakwoncheon watershed located in an area that presents a total maximum daily load (TMDL) in Korea. The proportion of urbanized area in this watershed is low, and the diffuse pollution loads of nutrients such as phosphorus are greater than the point-source pollution loads because of the concentration of rainfall that occurs during the summer. The pollution discharges from the watershed were estimated for each land-use type, and the seasonal variations of the pollution loads were analyzed. Consecutive flow measurement gauges have not been installed in this area, and it is difficult to survey the flow and water quality in this area during the frequent heavy rainfall that occurs during the wet season. The Hydrological Simulation Program-Fortran (HSPF) model was used to calculate the runoff flow and water quality in this basin. Using the water quality results, a load duration curve was constructed for the basin, the exceedance frequency of the water quality standard was calculated for each hydrologic condition class, and the percent reduction
Spatio-temporal modeling of nonlinear distributed parameter systems
Li, Han-Xiong
2011-01-01
The purpose of this volume is to provide a brief review of the previous work on model reduction and identifi cation of distributed parameter systems (DPS), and develop new spatio-temporal models and their relevant identifi cation approaches. In this book, a systematic overview and classifi cation on the modeling of DPS is presented fi rst, which includes model reduction, parameter estimation and system identifi cation. Next, a class of block-oriented nonlinear systems in traditional lumped parameter systems (LPS) is extended to DPS, which results in the spatio-temporal Wiener and Hammerstein s
Distributionally Robust Return-Risk Optimization Models and Their Applications
Directory of Open Access Journals (Sweden)
Li Yang
2014-01-01
Full Text Available Based on the risk control of conditional value-at-risk, distributionally robust return-risk optimization models with box constraints of random vector are proposed. They describe uncertainty in both the distribution form and moments (mean and covariance matrix of random vector. It is difficult to solve them directly. Using the conic duality theory and the minimax theorem, the models are reformulated as semidefinite programming problems, which can be solved by interior point algorithms in polynomial time. An important theoretical basis is therefore provided for applications of the models. Moreover, an application of the models to a practical example of portfolio selection is considered, and the example is evaluated using a historical data set of four stocks. Numerical results show that proposed methods are robust and the investment strategy is safe.
Coupling Radar Rainfall to Hydrological Models for Water Abstraction Management
Asfaw, Alemayehu; Shucksmith, James; Smith, Andrea; MacDonald, Ken
2015-04-01
The impacts of climate change and growing water use are likely to put considerable pressure on water resources and the environment. In the UK, a reform to surface water abstraction policy has recently been proposed which aims to increase the efficiency of using available water resources whilst minimising impacts on the aquatic environment. Key aspects to this reform include the consideration of dynamic rather than static abstraction licensing as well as introducing water trading concepts. Dynamic licensing will permit varying levels of abstraction dependent on environmental conditions (i.e. river flow and quality). The practical implementation of an effective dynamic abstraction strategy requires suitable flow forecasting techniques to inform abstraction asset management. Potentially the predicted availability of water resources within a catchment can be coupled to predicted demand and current storage to inform a cost effective water resource management strategy which minimises environmental impacts. The aim of this work is to use a historical analysis of UK case study catchment to compare potential water resource availability using modelled dynamic abstraction scenario informed by a flow forecasting model, against observed abstraction under a conventional abstraction regime. The work also demonstrates the impacts of modelling uncertainties on the accuracy of predicted water availability over range of forecast lead times. The study utilised a conceptual rainfall-runoff model PDM - Probability-Distributed Model developed by Centre for Ecology & Hydrology - set up in the Dove River catchment (UK) using 1km2 resolution radar rainfall as inputs and 15 min resolution gauged flow data for calibration and validation. Data assimilation procedures are implemented to improve flow predictions using observed flow data. Uncertainties in the radar rainfall data used in the model are quantified using artificial statistical error model described by Gaussian distribution and
Linear Model for Optimal Distributed Generation Size Predication
Directory of Open Access Journals (Sweden)
Ahmed Al Ameri
2017-01-01
Full Text Available This article presents a linear model predicting optimal size of Distributed Generation (DG that addresses the minimum power loss. This method is based fundamentally on strong coupling between active power and voltage angle as well as between reactive power and voltage magnitudes. This paper proposes simplified method to calculate the total power losses in electrical grid for different distributed generation sizes and locations. The method has been implemented and tested on several IEEE bus test systems. The results show that the proposed method is capable of predicting approximate optimal size of DG when compared with precision calculations. The method that linearizes a complex model showed a good result, which can actually reduce processing time required. The acceptable accuracy with less time and memory required can help the grid operator to assess power system integrated within large-scale distribution generation.
International Nuclear Information System (INIS)
Abrahamse, Augusta; Knox, Lloyd; Schmidt, Samuel; Thorman, Paul; Anthony Tyson, J.; Zhan Hu
2011-01-01
The uncertainty in the redshift distributions of galaxies has a significant potential impact on the cosmological parameter values inferred from multi-band imaging surveys. The accuracy of the photometric redshifts measured in these surveys depends not only on the quality of the flux data, but also on a number of modeling assumptions that enter into both the training set and spectral energy distribution (SED) fitting methods of photometric redshift estimation. In this work we focus on the latter, considering two types of modeling uncertainties: uncertainties in the SED template set and uncertainties in the magnitude and type priors used in a Bayesian photometric redshift estimation method. We find that SED template selection effects dominate over magnitude prior errors. We introduce a method for parameterizing the resulting ignorance of the redshift distributions, and for propagating these uncertainties to uncertainties in cosmological parameters.
From microscopic taxation and redistribution models to macroscopic income distributions
Bertotti, Maria Letizia; Modanese, Giovanni
2011-10-01
We present here a general framework, expressed by a system of nonlinear differential equations, suitable for the modeling of taxation and redistribution in a closed society. This framework allows one to describe the evolution of income distribution over the population and to explain the emergence of collective features based on knowledge of the individual interactions. By making different choices of the framework parameters, we construct different models, whose long-time behavior is then investigated. Asymptotic stationary distributions are found, which enjoy similar properties as those observed in empirical distributions. In particular, they exhibit power law tails of Pareto type and their Lorenz curves and Gini indices are consistent with some real world ones.
Spatial distribution of emissions to air – the SPREAD model
DEFF Research Database (Denmark)
Plejdrup, Marlene Schmidt; Gyldenkærne, Steen
The National Environmental Research Institute (NERI), Aarhus University, completes the annual national emission inventories for greenhouse gases and air pollutants according to Denmark’s obligations under international conventions, e.g. the climate convention, UNFCCC and the convention on long...... quality modelling in exposure studies. SPREAD includes emission distributions for each sector in the Danish inventory system; stationary combustion, mobile sources, fugitive emissions from fuels, industrial processes, solvents and other product use, agriculture and waste. This model enables generation...
Nucleon quark distributions in a covariant quark-diquark model
Energy Technology Data Exchange (ETDEWEB)
Cloet, I.C. [Special Research Centre for the Subatomic Structure of Matter and Department of Physics and Mathematical Physics, University of Adelaide, SA 5005 (Australia) and Jefferson Lab, 12000 Jefferson Avenue, Newport News, VA 23606 (United States)]. E-mail: icloet@physics.adelaide.edu.au; Bentz, W. [Department of Physics, School of Science, Tokai University, Hiratsuka-shi, Kanagawa 259-1292 (Japan)]. E-mail: bentz@keyaki.cc.u-tokai.ac.jp; Thomas, A.W. [Jefferson Lab, 12000 Jefferson Avenue, Newport News, VA 23606 (United States)]. E-mail: awthomas@jlab.org
2005-08-18
Spin-dependent and spin-independent quark light-cone momentum distributions and structure functions are calculated for the nucleon. We utilize a modified Nambu-Jona-Lasinio model in which confinement is simulated by eliminating unphysical thresholds for nucleon decay into quarks. The nucleon bound state is obtained by solving the Faddeev equation in the quark-diquark approximation, where both scalar and axial-vector diquark channels are included. We find excellent agreement between our model results and empirical data.
Improved Testing of Distributed Lag Model in Presence of ...
African Journals Online (AJOL)
The finite distributed lag models (DLM) are often used in econometrics and statistics. Application of the ordinary least square (OLS) directly on the DLM for estimation may have serious problems. To overcome these problems, some alternative estimation procedures are available in the literature. One popular method to ...
A Species Distribution Modeling Informed Conservation Assessment of Bog Spicebush
2016-09-14
Adhikari, Barik , and Upadhaya 2012). These results sug- gest there are many locations potentially suitable for (re)introducing L. subcoriacea across its...References Adhikari, D., S. K. Barik , K. Upadhaya. 2012. Habitat distribution modelling for reintroduction of Ilex khasiana Purk., a critically
Using WNTR to Model Water Distribution System Resilience
The Water Network Tool for Resilience (WNTR) is a new open source Python package developed by the U.S. Environmental Protection Agency and Sandia National Laboratories to model and evaluate resilience of water distribution systems. WNTR can be used to simulate a wide range of di...
Modelling flow dynamics in water distribution networks using ...
African Journals Online (AJOL)
One such approach is the Artificial Neural Networks (ANNs) technique. The advantage of ANNs is that they are robust and can be used to model complex linear and non-linear systems without making implicit assumptions. ANNs can be trained to forecast flow dynamics in a water distribution network. Such flow dynamics ...
A Game-Theoretic Model for Distributed Programming by Contract
DEFF Research Database (Denmark)
Henriksen, Anders Starcke; Hvitved, Tom; Filinski, Andrzej
2009-01-01
We present an extension of the programming-by-contract (PBC) paradigm to a concurrent and distributed environment. Classical PBC is characterized by absolute conformance of code to its specification, assigning blame in case of failures, and a hierarchical, cooperative decomposition model – none...
Airport acoustics: Aircraft noise distribution and modelling of some ...
African Journals Online (AJOL)
Airport acoustics: Aircraft noise distribution and modelling of some aircraft parameters. MU Onuu, EO Obisung. Abstract. No Abstract. Nigerian Journal of Physics Vol. 17 (Supplement) 2005: pp. 177-186. Full Text: EMAIL FREE FULL TEXT EMAIL FREE FULL TEXT · DOWNLOAD FULL TEXT DOWNLOAD FULL TEXT.
Noise Residual Learning for Noise Modeling in Distributed Video Coding
DEFF Research Database (Denmark)
Luong, Huynh Van; Forchhammer, Søren
2012-01-01
Distributed video coding (DVC) is a coding paradigm which exploits the source statistics at the decoder side to reduce the complexity at the encoder. The noise model is one of the inherently difficult challenges in DVC. This paper considers Transform Domain Wyner-Ziv (TDWZ) coding and proposes...
Business models for distributed generation in a liberalized market environment
International Nuclear Information System (INIS)
Gordijn, Jaap; Akkermans, Hans
2007-01-01
The analysis of the potential of emerging innovative technologies calls for a systems-theoretic approach that takes into account technical as well as socio-economic factors. This paper reports the main findings of several business case studies of different future applications in various countries of distributed power generation technologies, all based on a common methodology for networked business modeling and analysis. (author)
Performance prediction model for distributed applications on multicore clusters
CSIR Research Space (South Africa)
Khanyile, NP
2012-07-01
Full Text Available discusses some of the short comings of this law in the current age. We propose a theoretical model for predicting the behavior of a distributed algorithm given the network restrictions of the cluster used. The paper focuses on the impact of latency...
Hasan, Husna; Radi, Noor Fadhilah Ahmad; Kassim, Suraiya
2012-05-01
Extreme share return in Malaysia is studied. The monthly, quarterly, half yearly and yearly maximum returns are fitted to the Generalized Extreme Value (GEV) distribution. The Augmented Dickey Fuller (ADF) and Phillips Perron (PP) tests are performed to test for stationarity, while Mann-Kendall (MK) test is for the presence of monotonic trend. Maximum Likelihood Estimation (MLE) is used to estimate the parameter while L-moments estimate (LMOM) is used to initialize the MLE optimization routine for the stationary model. Likelihood ratio test is performed to determine the best model. Sherman's goodness of fit test is used to assess the quality of convergence of the GEV distribution by these monthly, quarterly, half yearly and yearly maximum. Returns levels are then estimated for prediction and planning purposes. The results show all maximum returns for all selection periods are stationary. The Mann-Kendall test indicates the existence of trend. Thus, we ought to model for non-stationary model too. Model 2, where the location parameter is increasing with time is the best for all selection intervals. Sherman's goodness of fit test shows that monthly, quarterly, half yearly and yearly maximum converge to the GEV distribution. From the results, it seems reasonable to conclude that yearly maximum is better for the convergence to the GEV distribution especially if longer records are available. Return level estimates, which is the return level (in this study return amount) that is expected to be exceeded, an average, once every t time periods starts to appear in the confidence interval of T = 50 for quarterly, half yearly and yearly maximum.
Lee, Serena B.; Birch, Gavin F.
2012-10-01
Estuarine health is affected by contamination from stormwater, particularly in highly-urbanised environments. For systems where catchment monitoring is insufficient, novel techniques must be employed to determine the impact of