A Web‐Based Decision Support System for Assessing Regional Water‐Quality Conditions and Management Actions1

Booth, Nathaniel L., Eric J. Everman, I‐Lin Kuo, Lori Sprague, and Lorraine Murphy, 2011. A Web‐Based Decision Support System for Assessing Regional Water‐Quality Conditions and Management Actions. Journal of the American Water Resources Association (JAWRA) 47(5):1136‐1150. DOI: 10.1111/j.1752‐1688.2011.00573.x Abstract: The U.S. Geological Survey National Water Quality Assessment Program has completed a number of water‐quality prediction models for nitrogen and phosphorus for the conterminous United States as well as for regional areas of the nation. In addition to estimating water‐quality conditions at unmonitored streams, the calibrated SPAtially Referenced Regressions On Watershed attributes (SPARROW) models can be used to produce estimates of yield, flow‐weighted concentration, or load of constituents in water under various land‐use condition, change, or resource management scenarios. A web‐based decision support infrastructure has been developed to provide access to SPARROW simulation results on stream water‐quality conditions and to offer sophisticated scenario testing capabilities for research and water‐quality planning via a graphical user interface with familiar controls. The SPARROW decision support system (DSS) is delivered through a web browser over an Internet connection, making it widely accessible to the public in a format that allows users to easily display water‐quality conditions and to describe, test, and share modeled scenarios of future conditions. SPARROW models currently supported by the DSS are based on the modified digital versions of the 1:500,000‐scale River Reach File (RF1) and 1:100,000‐scale National Hydrography Dataset (medium‐resolution, NHDPlus) stream networks.     

Application of SPARROW Modeling to Understanding Contaminant Fate and Transport from Uplands to Streams

Understanding spatial variability in contaminant fate and transport is critical to efficient regional water‐quality restoration. An approach to capitalize on previously calibrated spatially referenced regression (SPARROW) models to improve the understanding of contaminant fate and transport was developed and applied to the case of nitrogen in the 166,000 km² Chesapeake Bay watershed. A continuous function of four hydrogeologic, soil, and other landscape properties significant (α = 0.10) to nitrogen transport from uplands to streams was evaluated and compared among each of the more than 80,000 individual catchments (mean area, 2.1 km²) in the watershed. Budgets (including inputs, losses or net change in storage in uplands and stream corridors, and delivery to tidal waters) were also estimated for nitrogen applied to these catchments from selected upland sources. Most (81%) of such inputs are removed, retained, or otherwise processed in uplands rather than transported to surface waters. Combining SPARROW results with previous budget estimates suggests 55% of this processing is attributable to denitrification, 23% to crop or timber harvest, and 6% to volatilization. Remaining upland inputs represent a net annual increase in landscape storage in soils or biomass exceeding 10 kg per hectare in some areas. Such insights are important for planning watershed restoration and for improving future watershed models.     

Calibration and Uncertainty Analysis Using the Sparrow Model for Dissolved‐Solids Transport in the Upper Colorado River Basin

Salinity in the Upper Colorado River Basin (UCRB) is due to both natural sources and processes, and anthropogenic activities. Given economic damage due to salinity of $295 million in 2010, understanding salinity sources and production together with transport are of great importance. SPAtially Referenced Regressions On Watershed (SPARROW) is a nonlinear regression water quality model that simulates sources and transport of contaminants such as dissolved‐solids. However, SPARROW simulations of dissolved‐solids in the UCRB only represent conditions through 1998 due to limited data availability. More importantly, prior simulations focused on a single year calibration and its transferability to other years, and the validity of this approach is questionable, given the changing hydrologic and climatic conditions. This study presents different calibration approaches to assess the best approach for reducing model uncertainty. This study conducted simulations from 1999 to 2011, and the results showed good model accuracy. However, the number of monitoring stations decreased significantly in recent years resulting in higher model uncertainty. The uncertainty analysis was conducted using SPARROW results and bootstrapping. The results suggest that the watershed rankings based on salinity yields changed due to the uncertainty analysis and therefore, uncertainty consideration should be an important part of the management strategy.     

Source and Delivery of Nutrients to Receiving Waters in the Northeastern and Mid‐Atlantic Regions of the United States1

Moore, Richard B., Craig M. Johnston, Richard A. Smith, and Bryan Milstead, 2011. Source and Delivery of Nutrients to Receiving Waters in the Northeastern and Mid‐Atlantic Regions of the United States. Journal of the American Water Resources Association (JAWRA) 47(5):965‐990. DOI: 10.1111/j.1752‐1688.2011.00582.x Abstract: This study investigates nutrient sources and transport to receiving waters, in order to provide spatially detailed information to aid water‐resources managers concerned with eutrophication and nutrient management strategies. SPAtially Referenced Regressions On Watershed attributes (SPARROW) nutrient models were developed for the Northeastern and Mid‐Atlantic (NE US) regions of the United States to represent source conditions for the year 2002. The model developed to examine the source and delivery of nitrogen to the estuaries of nine large rivers along the NE US Seaboard indicated that agricultural sources contribute the largest percentage (37%) of the total nitrogen load delivered to the estuaries. Point sources account for 28% while atmospheric deposition accounts for 20%. A second SPARROW model was used to examine the sources and delivery of phosphorus to lakes and reservoirs throughout the NE US. The greatest attenuation of phosphorus occurred in lakes that were large relative to the size of their watershed. Model results show that, within the NE US, aquatic decay of nutrients is quite limited on an annual basis and that we especially cannot rely on natural attenuation to remove nutrients within the larger rivers nor within lakes with large watersheds relative to the size of the lake.     

A Multi‐Agency Nutrient Dataset Used to Estimate Loads,Improve Monitoring Design,and Calibrate Regional Nutrient SPARROW Models1

Saad, David A., Gregory E. Schwarz, Dale M. Robertson, and Nathaniel L. Booth, 2011. A Multi‐Agency Nutrient Dataset Used to Estimate Loads, Improve Monitoring Design, and Calibrate Regional Nutrient SPARROW Models. Journal of the American Water Resources Association (JAWRA) 47(5):933‐949. DOI: 10.1111/j.1752‐1688. 2011.00575.x Abstract: Stream‐loading information was compiled from federal, state, and local agencies, and selected universities as part of an effort to develop regional SPAtially Referenced Regressions On Watershed attributes (SPARROW) models to help describe the distribution, sources, and transport of nutrients in streams throughout much of the United States. After screening, 2,739 sites, sampled by 73 agencies, were identified as having suitable data for calculating long‐term mean annual nutrient loads required for SPARROW model calibration. These sites had a wide range in nutrient concentrations, loads, and yields, and environmental characteristics in their basins. An analysis of the accuracy in load estimates relative to site attributes indicated that accuracy in loads improve with increases in the number of observations, the proportion of uncensored data, and the variability in flow on observation days, whereas accuracy declines with increases in the root mean square error of the water‐quality model, the flow‐bias ratio, the number of days between samples, the variability in daily streamflow for the prediction period, and if the load estimate has been detrended. Based on compiled data, all areas of the country had recent declines in the number of sites with sufficient water‐quality data to compute accurate annual loads and support regional modeling analyses. These declines were caused by decreases in the number of sites being sampled and data not being entered in readily accessible databases.     

DEM AGGREGATION FOR WATERSHED MODELING1

ABSTRACT: The widely available USGS 7.5‐minute Digital Elevation Model (DEM) has a cell size of approximately 30 m × 30 m. This high resolution topographic information is impractical for many applications of distributed hydrologic and water quality models. In this study, cells were aggregated into coarse‐resolution areal units, termed grids, and a method to approximate flow direction for coarse‐resolution grids from 30 m DEM cells was developed. The method considers the flow path defined from the fine‐resolution DEM in determining a grid's flow direction and makes flow directions for grids closely follow the flow pattern suggested by the DEM. The aggregation method was applied to a DEM of Goodwater Creek, a nearly flat watershed that is located in central Missouri. The drainage networks derived for different levels of cell aggregations showed that grid aggregates of the Goodwater Creek watershed provided an adequate representation of the landscape topography.     

The Road to NHDPlus — Advancements in Digital Stream Networks and Associated Catchments

A progression of advancements in Geographic Information Systems techniques for hydrologic network and associated catchment delineation has led to the production of the National Hydrography Dataset Plus (NHDPlus). NHDPlus is a digital stream network for hydrologic modeling with catchments and a suite of related geospatial data. Digital stream networks with associated catchments provide a geospatial framework for linking and integrating water‐related data. Advancements in the development of NHDPlus are expected to continue to improve the capabilities of this national geospatial hydrologic framework. NHDPlus is built upon the medium‐resolution NHD and, like NHD, was developed by the U.S. Environmental Protection Agency and U.S. Geological Survey to support the estimation of streamflow and stream velocity used in fate‐and‐transport modeling. Catchments included with NHDPlus were created by integrating vector information from the NHD and from the Watershed Boundary Dataset with the gridded land surface elevation as represented by the National Elevation Dataset. NHDPlus is an actively used and continually improved dataset. Users recognize the importance of a reliable stream network and associated catchments. The NHDPlus spatial features and associated data tables will continue to be improved to support regional water quality and streamflow models and other user‐defined applications.     

STORMFLOW SIMULATION USING A GEOGRAPHICAL INFORMATION SYSTEM WITH A DISTRIBUTED APPROACH1

ABSTRACT: With the increasing availability of digital and remotely sensed data such as land use, soil texture, and digital elevation models (DEMs), geographic information systems (GIS) have become an indispensable tool in preprocessing data sets for watershed hydrologic modeling and post processing simulation results. However, model inputs and outputs must be transferred between the model and the GIS. These transfers can be greatly simplified by incorporating the model itself into the GIS environment. To this end, a simple hydrologic model, which incorporates the curve number method of rainfall‐runoff partitioning, the ground‐water base‐flow routine, and the Muskingum flow routing procedure, was implemented on the GIS. The model interfaces directly with stream network, flow direction, and watershed boundary data generated using standard GIS terrain analysis tools; and while the model is running, various data layers may be viewed at each time step using the full display capabilities. The terrain analysis tools were first used to delineate the drainage basins and stream networks for the Susquehanna River. Then the model was used to simulate the hydrologic response of the Upper West Branch of the Susquehanna to two different storms. The simulated streamflow hydrographs compare well with the observed hydrographs at the basin outlet.     

SPATIALLY EXPLICIT HYDROLOGIC MODELING OF LAND USE CHANGE1

ABSTRACT: Using a Geographic Information System (GIS), a method is presented to develop a spatially explicit time series of land use in an urbanizing watershed. The method is prefaced on the existence of independent observations of land use at different times and data that describes the spatial‐temporal land use transition characteristics of the watershed between these two points in time. A method is then presented to generalize the TR‐55 graphical method, a common lumped hydrologic model for estimating peak discharge, for use in a spatially explicit scheme. This scheme predicts peak discharge throughout a watershed, rather than at a single selected watershed outlet. Coupling these two methods allows the engineer to model both the temporal and spatial evolution of peak discharge for the watershed. An illustrative watershed in a suburban area of Washington, DC is selected to demonstrate the methods. The model results from these analyses are presented graphically to highlight the complex features in peak discharge behavior that exist both spatially, as a function of position within the watershed drainage network, and temporally, as the watershed undergoes urbanization. These features are not commonly noted in most hydrologic analyses but are captured in these analyses because of the high spatial and temporal resolution of the methods presented. The physical implications of the modeled results are discussed in the context of the information content of a stream gauge located at the overall outlet of the illustrative watershed. This work shows that the common practice of transposition of gauge information to locations internal to the watershed would neglect internal variability in peak discharge behavior, and could potentially lead to the determination of inappropriate design discharges.     

Analyses of Urban Drainage Network Structure and its Impact on Hydrologic Response1

Meierdiercks, Katherine L., James A. Smith, Mary Lynn Baeck, and Andrew J. Miller, 2010. Analyses of Urban Drainage Network Structure and Its Impact on Hydrologic Response. Journal of the American Water Resources Association (JAWRA) 1-12. DOI: 10.1111/j.1752-1688.2010.00465.x Abstract: Urban flood studies have linked the severity of flooding to the percent imperviousness or land use classifications of a watershed, but relatively little attention has been given to the impact of urban drainage networks on hydrologic response. The drainage network, which can include storm pipes, surface channels, street gutters, and stormwater management ponds, is examined in the Dead Run watershed (14.3 km²). Comprehensive digital representations of the urban drainage network in Dead Run were developed and provide a key observational resource for analyses of urban drainage networks and their impact on hydrologic response. Analyses in this study focus on three headwater subbasins with drainage areas ranging from 1.3 to 1.9 km² and that exhibit striking contrasts in their patterns and history of development. It is shown that the drainage networks of the three subbasins, like natural river networks, exhibit characteristic structures and that these features play critical roles in determining urban hydrologic response. Hydrologic modeling analyses utilize the Environmental Protection Agency’s Stormwater Management Model (SWMM), which provides a flexible platform for examining the impacts of drainage network structure on hydrologic response. Results of SWMM modeling analyses suggest that drainage density and presence of stormwater ponds impact peak discharge more significantly in the Dead Run subbasins than the percent impervious or land use type of the subbasins.     

Predicting the Fate and Transport of E. coli in Two Texas River Basins Using a Spatially Referenced Regression Model1

Abstract: The two main rivers of southeast Texas: Guadalupe and San Antonio have shown high temporal increase in bacteria concentration during the last decade. The SPAtially Referenced Regression On Watershed (SPARROW) attributes model, developed by the U.S. Geological Survey (USGS), has been applied to predict the fluxes and concentrations of contaminants in unmonitored streams and to identify the sources of these contaminants. This model identifies every reach as a basic network unit to distribute the sources, delivery, and attenuation factors. The model is data intensive and implements nonlinear regression to solve the parsimonious relations for describing various watershed processes. This study explored watershed and hydrological characteristics (land uses, precipitation, human and animal population, point sources, areal hydraulic load and drainage density, etc.) as the probable sources and delivery mechanisms of waterborne pathogens and their indicator (Escherichia coli [E. coli]) in the Guadalupe and San Antonio River basins. The effect of using various statistical indices for model selection on the final model’s ability to explain the various E. coli sources and transport processes was also analyzed.     

Evolution and Application of Urban Watershed Management Planning

The development of Watershed Management Plans (WMPs) in urban areas aids municipalities in allocating resources, engaging the public and stakeholders, addressing water quality regulations, and mitigating issues related to stormwater runoff and flooding. In this study, 124 urban WMPs across the United States were reviewed to characterize historic approaches and identify emerging trends in watershed planning. Planning methods and tools were qualitatively evaluated, followed by statistical analyses of a subset of 63 WMPs to identify relationships between planning factors. Plans developed by a municipality or consultant were associated with more occurrences of hydrologic modeling and site‐specific recommendations, and fewer occurrences of characterizing social watershed factors, than plans authored by agencies, organizations, or universities. WMPs in the past decade exhibited greater frequency in the use of pollutant load models and spatially explicit hydrologic and hydraulic models. Project prioritization was found to increasingly focus on feasibility to implement proposed strategies. More recent plans additionally exhibited greater consideration for water quality, ecological health, and public participation. Innovation in planning methods and consideration of future watershed conditions are primary areas that were found to be deficient in the study WMPs, although analysis methods and tools continue to improve in the wake of advancing technology and data availability.     

The Watershed Flow and Allocation Model: An NHDPlus‐Based Watershed Modeling Approach for Multiple Scales and Conditions

The Watershed Flow and Allocation model (WaterFALL^®) provides segment‐specific, daily streamflow at both gaged and ungaged locations to generate the hydrologic foundation for a variety of water resources management applications. The model is designed to apply across the spatially explicit and enhanced National Hydrography Dataset (NHDPlus) stream and catchment network. To facilitate modeling at the NHDPlus catchment scale, we use an intermediate‐level rainfall‐runoff model rather than a complex process‐based model. The hydrologic model within WaterFALL simulates rainfall‐runoff processes for each catchment within a watershed and routes streamflow between catchments, while accounting for withdrawals, discharges, and onstream reservoirs within the network. The model is therefore distributed among each NHDPlus catchment within the larger selected watershed. Input parameters including climate, land use, soils, and water withdrawals and discharges are georeferenced to each catchment. The WaterFALL system includes a centralized database and server‐based environment for storing all model code, input parameters, and results in a single instance for all simulations allowing for rapid comparison between multiple scenarios. We demonstrate and validate WaterFALL within North Carolina at a variety of scales using observed streamflows to inform quantitative and qualitative measures, including hydrologic flow metrics relevant to the study of ecological flow management decisions.     

A STRIP MODEL APPROACH TO PARAMETERIZE A COUPLED GREEN‐AMPT KINEMATIC WAVE MODEL1

ABSTRACT: Infiltration processes at the plot scale are often described and modeled using a single effective hydraulic conductivity (Kg) value. This can lead to errors in runoff and erosion prediction. An integrated field measurement and modeling study was conducted to evaluate: (1) the relationship among rainfall intensity, spatially variable soil and vegetation characteristics, and infiltration processes; and (2) how this relationship could be modeled using Green and Ampt and a spatially distributed hydrologic model. Experiments were conducted using a newly developed variable intensity rainfall simulator on 2 m by 6 m plots in a rangeland watershed in southeastern Arizona. Rainfall application rates varied between 50 and 200 mm/hr. Results of the rainfall simulator experiments showed that the observed hydrologic response changed with changes in rainfall intensity and that the response varied with antecedent moisture condition. A distributed process based hydrologic simulation model was used to model the plots at different levels of hydrologic complexity. The measurement and simulation model results show that the rainfall runoff relationship cannot be accurately described or modeled using a single Kg value at the plot scale. Multi‐plane model configurations with infiltration parameters based on soil and plot characteristics resulted in a significant improvement over single‐plane configurations.     

“Nutrient Inputs to the Laurentian Great Lakes by Source and Watershed Estimated Using SPARROW Watershed Models” by Dale M. Robertson and David A. Saad2

Richards, R. Peter, Ibrahim Alameddine, J. David Allan, David B. Baker, Nathan S. Bosch, Remegio Confesor, Joseph V. DePinto, David M. Dolan, Jeffrey M. Reutter, and Donald Scavia, 2012. Discussion –“Nutrient Inputs to the Laurentian Great Lakes by Source and Watershed Estimated Using SPARROW Watershed Models” by Dale M. Robertson and David A. Saad. Journal of the American Water Resources Association (JAWRA) 1‐10. DOI: 10.1111/jawr.12006 Abstract: Results from the Upper Midwest Major River Basin (MRB3) SPARROW model and underlying Fluxmaster load estimates were compared with detailed data available in the Lake Erie and Ohio River watersheds. Fluxmaster and SPARROW estimates of tributary loads tend to be biased low for total phosphorus and high for total nitrogen. These and other limitations of the application led to an overestimation of the relative contribution of point sources vs. nonpoint sources of phosphorus to eutrophication conditions in Lake Erie, when compared with direct estimates for data‐rich Ohio tributaries. These limitations include the use of a decade‐old reference point (2002), lack of modeling of dissolved phosphorus, lack of inclusion of inputs from the Canadian Lake Erie watersheds and from Lake Huron, and the choice to summarize results for the entire United States Lake Erie watershed, as opposed to the key Western and Central Basin watersheds that drive Lake Erie’s eutrophication processes. Although the MRB3 SPARROW model helps to meet a critical need by modeling unmonitored watersheds and ranking rivers by their estimated relative contributions, we recommend caution in use of the MRB3 SPARRROW model for Lake Erie management, and argue that the management of agricultural nonpoint sources should continue to be the primary focus for the Western and Central Basins of Lake Erie.     

Modeling the Spatially Varying Water Balance Processes in a Semiarid Mountainous Watershed of Idaho1

Stratton, Benjamin T., Venakataramana Sridhar, Molly M. Gribb, James P. McNamara, and Balaji Narasimhan, 2009. Modeling the Spatially Varying Water Balance Processes in a Semiarid Mountainous Watershed of Idaho. Journal of the American Water Resources Association (JAWRA) 45(6):1390‐1408. Abstract: The distributed Soil Water Assessment Tool (SWAT) hydrologic model was applied to a research watershed, the Dry Creek Experimental Watershed, near Boise Idaho to investigate its water balance components both temporally and spatially. Calibrating and validating SWAT is necessary to enable our understanding of the water balance components in this semiarid watershed. Daily streamflow data from four streamflow gages were used for calibration and validation of the model. Monthly estimates of streamflow during the calibration phase by SWAT produced satisfactory results with a Nash Sutcliffe coefficient of model efficiency 0.79. Since it is a continuous simulation model, as opposed to an event‐based model, it demonstrated the limited ability in capturing both streamflow and soil moisture for selected rain‐on‐snow (ROS) events during the validation period between 2005 and 2007. Especially, soil moisture was generally underestimated compared with observations from two monitoring pits. However, our implementation of SWAT showed that seasonal and annual water balance partitioning of precipitation into evapotranspiration, streamflow, soil moisture, and drainage was not only possible but closely followed the trends of a typical semiarid watershed in the intermountain west. This study highlights the necessity for better techniques to precisely identify and drive the model with commonly observed climatic inversion‐related snowmelt or ROS weather events. Estimation of key parameters pertaining to soil (e.g., available water content and saturated hydraulic conductivity), snow (e.g., lapse rates, melting), and vegetation (e.g., leaf area index and maximum canopy index) using additional field observations in the watershed is critical for better prediction.     

COMPARISON OF PROCESS‐BASED AND ARTIFICIAL NEURAL NETWORK APPROACHES FOR STREAMFLOW MODELING IN AN AGRICULTURAL WATERSHED1

ABSTRACT: The performance of the Soil and Water Assessment Tool (SWAT) and artificial neural network (ANN) models in simulating hydrologic response was assessed in an agricultural watershed in southeastern Pennsylvania. All of the performance evaluation measures including Nash‐Sutcliffe coefficient of efficiency (E) and coefficient of determination (R²) suggest that the ANN monthly predictions were closer to the observed flows than the monthly predictions from the SWAT model. More specifically, monthly streamflow E and R² were 0.54 and 0.57, respectively, for the SWAT model calibration period, and 0.71 and 0.75, respectively, for the ANN model training period. For the validation period, these values were ?0.17 and 0.34 for the SWAT and 0.43 and 0.45 for the ANN model. SWAT model performance was affected by snowmelt events during winter months and by the model's inability to adequately simulate base flows. Even though this and other studies using ANN models suggest that these models provide a viable alternative approach for hydrologic and water quality modeling, ANN models in their current form are not spatially distributed watershed modeling systems. However, considering the promising performance of the simple ANN model, this study suggests that the ANN approach warrants further development to explicitly address the spatial distribution of hydrologic/water quality processes within watersheds.     

Integrating Modeling and Field Experiments to Evaluate Impacts of Vegetative Practices on Ponderosa Pine Watersheds1

Abstract: Determining watershed response to vegetation treatment has been the subject of numerous hydrologic studies over the years. However, generalizing the information obtained from traditional paired‐watershed studies to other watersheds in a region is problematic because of the empirical nature of such studies and the context dependence of hydrologic responses. This paper addresses the issue of generalizing hydrologic information through integration of process‐based modeling and field observations from small‐scale watershed experiments. To this end, the results from application of a process‐based model were compared with the results from small‐scale watershed experiments in ponderosa pine forests of Arizona. The model simulated treatment impacts reasonably well when compared to the traditional paired‐watershed approach. However, the model tended to overestimate water yields during periods of low flow, and there was a significant difference between the two approaches in the estimation of treatment impacts during the first four years following treatment. The results indicate that the lumped‐parameter modeling approach used here may be limited in its ability to detect small changes, and tends to overestimate changes that occur immediately following treatment. It is concluded that watershed experiments can be highly informative due to their direct examination of cause‐effect relationships, while process‐based models are useful for their processing power and focus on functional relationships. The integrated use of both watershed experiments and process‐based models provides a way to generalize hydrologic information, illuminate the processes behind landscape treatment effects, and to generate and test hypotheses.     

Evaluation of Three Watershed‐Scale Pesticide Environmental Transport and Fate Models1

Abstract: The U.S. Environmental Protection Agency (USEPA) Office of Pesticide Programs (OPP) has completed an evaluation of three watershed‐scale simulation models for potential use in Food Quality Protection Act pesticide drinking water exposure assessments. The evaluation may also guide OPP in identifying computer simulation tools that can be used in performing aquatic ecological exposure assessments. Models selected for evaluation were the Soil Water Assessment Tool (SWAT), the Nonpoint Source Model (NPSM), a modified version of the Hydrologic Simulation Program‐Fortran (HSPF), and the Pesticide Root Zone Model‐Riverine Water Quality (PRZM‐RIVWQ) model. Simulated concentrations of the pesticides atrazine, metolachlor, and trifluralin in surface water were compared with field data monitored in the Sugar Creek watershed of Indiana’s White River basin by the National Water Quality Assessment (NAWQA) program. The evaluation not only provided USEPA with experience in using watershed models for estimating pesticide concentration in flowing water but also led to the development of improved statistical techniques for assessing model accuracy. Further, it demonstrated the difficulty of representing spatially and temporally variable soil, weather, and pesticide applications with relatively infrequent, spatially fixed, point estimates. It also demonstrated the value of using monitoring and modeling as mutually supporting tools and pointed to the need to design monitoring programs that support modeling.     

Using SWAT to Model Streamflow in Two River Basins With Ground and Satellite Precipitation Data1

Abstract: Both ground rain gauge and remotely sensed precipitation (Next Generation Weather Radar – NEXRAD Stage III) data have been used to support spatially distributed hydrological modeling. This study is unique in that it utilizes and compares the performance of National Weather Service (NWS) rain gauge, NEXRAD Stage III, and Tropical Rainfall Measurement Mission (TRMM) 3B42 (Version 6) data for the hydrological modeling of the Middle Nueces River Watershed in South Texas and Middle Rio Grande Watershed in South Texas and northern Mexico. The hydrologic model chosen for this study is the Soil and Water Assessment Tool (SWAT), which is a comprehensive, physical‐based tool that models watershed hydrology and water quality within stream reaches. Minor adjustments to selected model parameters were applied to make parameter values more realistic based on results from previous studies. In both watersheds, NEXRAD Stage III data yields results with low mass balance error between simulated and actual streamflow (±13%) and high monthly Nash‐Sutcliffe efficiency coefficients (NS > 0.60) for both calibration (July 1, 2003 to December 31, 2006) and validation (2007) periods. In the Middle Rio Grande Watershed NEXRAD Stage III data also yield robust daily results (time averaged over a three‐day period) with NS values of (0.60‐0.88). TRMM 3B42 data generate simulations for the Middle Rio Grande Watershed of variable qualtiy (MBE = +13 to ?16%; NS = 0.38‐0.94; RMSE = 0.07‐0.65), but greatly overestimates streamflow during the calibration period in the Middle Nueces Watershed. During the calibration period use of NWS rain gauge data does not generate acceptable simulations in both watersheds. Significantly, our study is the first to successfully demonstrate the utility of satellite‐estimated precipitation (TRMM 3B42) in supporting hydrologic modeling with SWAT; thereby, potentially extending the realm (between 50°N and 50°S) where remotely sensed precipitation data can support hydrologic modeling outside of regions that have modern, ground‐based radar networks (i.e., much of the third world).