Better Assessment Science Integrating Point And Nonpoint Sources Research Articles

Review of Watershed-Scale Water Quality and Nonpoint Source Pollution Models.

Watershed-scale nonpoint source (NPS) pollution models have become important tools to understand, evaluate, and predict the negative impacts of NPS pollution on water quality. Today, there are many NPS models available for users. However, different types of models possess different form and structure as well as complexity of computation. It is difficult for users to select an appropriate model for a specific application without a clear understanding of the limitations or strengths for each model or tool. This review evaluates 14 more commonly used watershed-scale NPS pollution models to explain how and when the application of these different models are appropriate for a given effort. The models that are assessed have a wide range of capacities that include simple models used as rapid screening tools (e.g., Long-Term Hydrologic Impact Assessment (L-THIA) and Nonpoint Source Pollution and Erosion Comparison Tool (N-SPECT/OpenNSPECT)), medium-complexity models that require detail data input and limited calibration (e.g., Generalized Watershed Loading Function (GWLF), Loading Simulation Program C (LSPC), Source Loading and Management Model (SLAMM), and Watershed Analysis Risk Management Frame (WARMF)), complex models that provide sophisticated simulation for NPS pollution processes with intensive data and rigorous calibration (e.g., Agricultural Nonpoint Source pollution model (AGNPS/AnnAGNPS), Soil and Water Assessment Tool (SWAT), Stormwater Management Model (SWMM), and Hydrologic Simulation Program Fortran (HSPF)), and modeling systems that integrate various sub-models and tools, and contain the highest complexity to solve all phases of hydrologic, hydraulic, and chemical dynamic processes (e.g., Automated Geospatial Watershed Assessment Tool (AGWA), Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) and Watershed Modeling System (WMS)). This assessment includes model intended use, components or capabilities, suitable land-use type, input parameter type, spatial and temporal scale, simulated pollutants, strengths and limitations, and software availability. Understanding the strengths and weaknesses of each watershed-scale NPS model will lead to better model selection for suitability and help to avoid misinterpretation or misapplication in practice. The article further explains the crucial criteria for model selection, including spatial and temporal considerations, calibration and validation, uncertainty analysis, and future research direction of NPS pollution models. The goal of this work is to provide accurate and concise insight for watershed managers and planners to select the best-suited model to reduce the harm of NPS pollution to watershed ecosystems.

Estimating impact of rainfall change on hydrological processes in Jianfengling rainforest watershed, China using BASINS-HSPF-CAT modeling system

Climate change over the past several decades has resulted in shifting rainfall pattern and modifying rainfall intensity, which has exacerbated hydrological processes and added the uncertainty and instability to these processes. This study ascertained impacts of potential future rainfall change on hydrological processes at the Jianfengling (JFL) tropical mountain rainforest watershed in Hainan Island, China using the BASINS (Better Assessment Science Integrating Point and Nonpoint Sources)-HSPF (Hydrological Simulation Program-FORTRAN)-CAT (Climate Assessment Tool) modeling system. The HSPF model was calibrated and validated with available measured data prior to its applications. Three simulation scenarios were then performed to gain a better understanding of the impacts of different rainfall rates and storm intensities on stream discharge, surface water runoff from forest land, and water outflow from the JFL watershed outlet. Results showed that a 10% increase in rainfall rate could result in 1.3 times increase in stream discharge, surface runoff, and water outflow. A potential future wet climate could have profound impacts on hydrological processes at the JFL watershed, whereas a potential future dry climate could result less impacts on stream discharge, surface runoff, and water outflow at the same watershed. Our simulation further revealed that climate change driven by extreme rain storms had greater impacts on annual surface runoff than on annual stream discharge. The coupled CAT-HSPF model is a useful tool to modify historical rainfall data for projecting future rainfall variation impacts on forest hydrological processes due to climate change. This approach would be able to extend to other regions around the world.

Assessing a fuzzy model and HSPF to supplement rainfall data for nonpoint source water quality in the Feitsui reservoir watershed

The objective of this study was to improve the use of a fuzzy model to supplement rainfall data when the watershed's meteorological station is either far away or suffers a loss of rainfall data. The fuzzy model can also supplement rainfall data when the station is nearby. The accuracy of rainfall data in the EPA's (Environmental Protection Agency) BASINS (Better Assessment Science Integrating Point and Nonpoint Sources) decision support tool is affected by the sparse meteorological data contained in BASINS. This study also assessed the improvement in stream flow prediction with the Hydrological Simulation Program-FORTRAN (HSPF) model contained within BASINS, using the hourly precipitation estimates for the Feitsui reservoir watershed. This study demonstrates that using a fuzzy model to supplement rainfall data has the potential to improve stream flow predictions, thus aiding water quality assessment in the nonpoint water quality assessment decision tool.

Assessing the Hydrologic Performance of the Nonpoint Source Water Quality Assessment Decision Support Tool Using HSPF in Feitsui Reservoir Watershed

The accuracy of rainfall predictions in the EPA’s BASINS (Better Assessment Science Integrating Point and Nonpoint Sources) decision support tool is affected by the sparse meteorological data contained in BASINS. The objectives of this study were improvement of using the entropy theory to supplement the precipitation data are significant when the watershed’s meteorological station is either far away or not in a similar climatic region. When the station is nearby, using entropy theory to supplement the precipitation data produces similar results. And this study assessed the improvement of stream flow prediction of the Hydrological Simulation Program-FORTRAN (HSPF) model contained within BASINS using the hourly precipitation estimates in Feitsui reservoir watershed. Our results demonstrated consistent improvements of daily stream flow predictions in Feitsui reservoir watershed when precipitation data was incorporated into BASINS. Our analyses also showed that the stream flow improvements were mainly contributed by entropy theory to supplement precipitation data; partially due to the constraints of current BASINS-HSPF settings. However, entropy theory to supplement precipitation data did improve the base flow prediction. The entropy theory method showed 10.17 to 25.51 percent less error than the Thiessen polygon method and Arithmetic to supplement the rainfall data. And used entropy theory supplement the rainfall data to simulate stream flow that RMSE values between 58 and 182. This study demonstrates entropy theory to supplement precipitation has the potential to improve stream flow predictions, thus aid the water quality assessment in the nonpoint water quality assessment decision tool.

Estimation of dynamic load of mercury in a river with BASINS-HSPF model

Purpose Mercury (Hg) is a naturally occurring element and a pervasive toxic pollutant. This study investigated the dynamic loads of Hg from the Cedar–Ortega Rivers watershed into the Lower St. Johns River (LSJR), Florida, USA, using the better assessment science integrating point and nonpoint sources (BASINS)-hydrologic simulation program—FORTRAN (HSPF) model.

Evaluating Hydrologic Response of an Agricultural Watershed for Watershed Analysis

This paper describes the hydrological assessment of an agricultural watershed in the Midwestern United States through the use of a watershed scale hydrologic model. The Soil and Water Assessment Tool (SWAT) model was applied to the Maquoketa River watershed, located in northeast Iowa, draining an agriculture intensive area of about 5,000 km2. The inputs to the model were obtained from the Environmental Protection Agency’s geographic information/database system called Better Assessment Science Integrating Point and Nonpoint Sources (BASINS). Meteorological input, including precipitation and temperature from six weather stations located in and around the watershed, and measured streamflow data at the watershed outlet, were used in the simulation. A sensitivity analysis was performed using an influence coefficient method to evaluate surface runoff and baseflow variations in response to changes in model input hydrologic parameters. The curve number, evaporation compensation factor, and soil available water capacity were found to be the most sensitive parameters among eight selected parameters. Model calibration, facilitated by the sensitivity analysis, was performed for the period 1988 through 1993, and validation was performed for 1982 through 1987. The model was found to explain at least 86% and 69% of the variability in the measured streamflow data for calibration and validation periods, respectively. This initial hydrologic assessment will facilitate future modeling applications using SWAT to the Maquoketa River watershed for various watershed analyses, including watershed assessment for water quality management, such as total maximum daily loads, impacts of land use and climate change, and impacts of alternate management practices.

Impacts of Climate Change and Urban Development on Water Resources in the Tualatin River Basin, Oregon

We investigated the relative importance of future climate change and land use change in determining the quantity and quality of freshwater resources in northwestern Oregon's Tualatin River Basin using the U.S. Environmental Protection Agency's Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) modeling system. Models were calibrated and validated using historic flow and water quality data between 1990 and 2006. The goodness of fit for the calibrated models was high, with coefficients of determination ranging from 0.72 to 0.93 in the calibration period. The calibrated models were run under a range of eight statistically downscaled climate change, two regional land use change, and four combined scenarios. Results included average increases in winter flows of 10 percent, decreases in summer flows of 37 percent, and increases in fifth-percentile flows of up to 80 percent as a result of climate change in the Tualatin River Basin. For land use change, the results included an increase in annual flows of 21 percent for the development-oriented scenario and a decrease of 16 percent for the conservation-oriented scenario. For combined scenarios of high climate change and high urban development, there is a projected increase in winter flows of up to 71 percent and decrease in summer flows of up to 48 percent. Climate change scenarios were more significant than urban development scenarios in determining basin hydrological response. The results are relevant to regional planners interested in the long-term response of water resources to climate change and land use change at the basin scale.

Phosphorus Budget and Remediation Plan for Big Platte Lake, Michigan

This paper presents a phosphorus budget and modeling case study for Big Platte Lake Michigan and the Platte River watershed. These analyses are a necessary component of a credible total maximum daily load (TMDL) for Big Platte Lake and may be more broadly applicable to similar systems and other water quality management issues. A calibrated Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) model is used to simulate total phosphorus loads from the watershed. A nonsteady state lake model is developed to predict total phosphorus concentrations in both the water column and the sediments. Temperature and dissolved oxygen models are used to predict the anoxic periods in the lake hypolimnion to facilitate calculation of the internal phosphorus loading due to sediment release. Following calibration, the models were used to determine allowable total phosphorus loads for Big Platte Lake for typical hydraulic conditions. Current measured total phosphorus loads exceed model calculated allowable...

Assessing the hydrologic performance of the EPA’s nonpoint source water quality assessment decision support tool using North American Land Data Assimilation System (NLDAS) products

The accuracy of streamflow predictions in the EPA’s BASINS (Better Assessment Science Integrating Point and Nonpoint Sources) decision support tool is affected by the sparse meteorological data contained in BASINS. The North American Land Data Assimilation System (NLDAS) data with high spatial and temporal resolutions provide an alternative to the NOAA National Climatic Data Center (NCDC)’s station data. This study assessed the improvement of streamflow prediction of the Hydrological Simulation Program-FORTRAN (HSPF) model contained within BASINS using the NLDAS 1/8 degree hourly precipitation and evapotranspiration estimates in seven watersheds of the Chesapeake Bay region. Our results demonstrated consistent improvements of daily streamflow predictions in five of the seven watersheds when NLDAS precipitation and evapotranspiration data was incorporated into BASINS. The improvement of using NLDAS data is significant when the watershed’s meteorological station is either far away or not in a similar climatic region. When the station is nearby, using NLDAS data produces similar results. The correlation coefficients of the analyses using NLDAS data were greater than 0.8, the Nash–Sutcliffe (NS) model fit efficiency greater than 0.6, and the error in the water balance was less than 5%. Our analyses also showed that the streamflow improvements were mainly contributed by NLDAS precipitation data and that the improvement from using NLDAS evapotranspiration data was not significant; partially due to the constraints of current BASINS-HSPF settings. However, NLDAS evapotranspiration data did improve the baseflow prediction. This study demonstrates NLDAS data has the potential to improve stream flow predictions, thus aid the water quality assessment in the EPA nonpoint water quality assessment decision tool.

Multicriteria Review of Nonpoint Source Water Quality Models for Nutrients, Sediments, and Pathogens

Abstract There now exists a large number of nonpoint source models that have been developed for watershed management issues. As part of the National Agri-Environmental Standards Initiative (NAESI), it was necessary to evaluate which model or models would be the best choice for examining various best management practices for nutrients, sediments, and pathogens in test watersheds. Environment Canada has committed to the development of environmental performance standards that will guide environmentally sustainable agricultural practices and management. A literature review was carried out and a short list of 13 models was selected that met the basic needs of the project. These models were subsequently evaluated based on a multicriteria analysis that considered 21 model characteristics. A weight and a total score quantify the relative importance of each criterion. The top six models were SWAT (Soil and Water Assessment Tool), AnnAGNPS (Annualized Agricultural Nonpoint Source), BASINS (Better Assessment Science Integrating Point and Nonpoint Sources), GIBSI (Gestion Intégrée des Bassins versants á l'aide d'un Systéme Informatisé), AGNPS (Agricultural Nonpoint Source), and HSPF (Hydrologic Simulation Program - Fortran).

Effects of Land-Use Changes on Saint Louis Bay Watershed Modeling

Abstract Saint Louis Bay Watershed is a coastal watershed located in southern Mississippi, which composes two basins: Jordan River Basin and Wolf River Basin. Two land use/land cover (LULC) datasets: the Geographic Information Retrieval and Analysis System (GIRAS) and the National Land Cover Data (NLCD) are applied on these two basins to simulate the hydrologic and water quality parameters by using the Hydrological Simulation Program - FORTRAN (HSPF) and the Better Assessment Science Integrating Point and Nonpoint Sources (BASINS). The difference of GIRAS dataset and NLCD dataset for the Saint Louis Bay represents the LULC change from 1977 to 1992. The area percentages of Forest Land and Urban or Built-up Land decrease for both these two basins. However, the area percentages of Wetlands and Barren Land increase. The Rate of Soil Erosion has a great increase in the area changing from other LULC classifications to Barren Land. As a result of the loss of vegetation and the aggravation of soil erosion, the To...

Hydrology and Sediment Modeling Using BASINS/HSPF in a Tropical Island Watershed

The Hydrological Simulation Program - FORTRAN (HSPF) in interface with Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) v.3.0 was used to study hydrology, soil erosion, and sediment transport of the Rio Caonillas watershed in Puerto Rico. The HSPF model has been used widely since 1980; however, little is known about the model's performance in tropical island watersheds that have extreme environmental conditions, such as rainfall intensity more than 25 mm h-1 and average soil slope of 38%. Three years (1999-2001) of continuous meteorological, flow, and suspended sediments data were used for model evaluation. The study found that the groundwater recession rate coefficient (AGWRC) was the most sensitive model parameter for both streamflow and sediment transport modeling. The calibrated model explained more than 85% of the monthly variability of streamflows and 70% of the monthly variability of suspended sediment concentrations. Agricultural and barren areas yielded the highest soil losses, contributing 55% and 20% of annual soil erosion, respectively. These results demonstrate that HSPF is capable of simulating hydrology and suspended sediment in the river for tropical island watersheds, principally for analysis on a monthly basis.

Enhancing Hyrdological Simulation Program – FORTRAN Model Channel Hydraulic Representation1

Abstract: The hydrological simulation program – FORTRAN (HSPF) is a comprehensive watershed model that employs depth‐area‐volume‐flow relationships known as the hydraulic function table (FTABLE) to represent the hydraulic characteristics of stream channel cross‐sections and reservoirs. An accurate FTABLE determination for a stream cross‐section site requires an accurate determination of mean flow depth, mean flow width, roughness coefficient, longitudinal bed slope, and length of stream reach. A method that uses regional regression equations to estimate mean flow depth, mean flow width, and roughness coefficient is presented herein. FTABLES generated by the proposed method (Alternative Method) and FTABLES generated by Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) were compared. As a result, the Alternative Method was judged to be an enhancement over the BASINS method. First, the Alternative Method employs a spatially variable roughness coefficient, whereas BASINS employs an arbitrarily selected spatially uniform roughness coefficient. Second, the Alternative Method uses mean flow width and mean flow depth estimated from regional regression equations whereas BASINS uses mean flow width and depth extracted from the National Hydrography Dataset (NHD). Third, the Alternative Method offers an option to use separate roughness coefficients for the in‐channel and floodplain sections of compound channels. Fourth, the Alternative Method has higher resolution in the sense that area, volume, and flow data are calculated at smaller depth intervals than the BASINS method. To test whether the Alternative Method enhances channel hydraulic representation over the BASINS method, comparisons of observed and simulated streamflow, flow velocity, and suspended sediment were made for four test watersheds. These comparisons revealed that the method used to estimate the FTABLE has little influence on hydrologic calibration, but greatly influences hydraulic and suspended sediment calibration. The hydrologic calibration results showed that observed versus simulated daily streamflow comparisons had Nash‐Sutcliffe efficiencies ranging from 0.50 to 0.61 and monthly comparisons had efficiencies ranging from 0.61 to 0.84. Comparisons of observed and simulated suspended sediments concentrations had model efficiencies ranging from 0.48 to 0.56 for the daily, and 0.28 to 0.70 for the monthly comparisons. The overall results of the hydrological, hydraulic, and suspended sediment concentration comparisons show that the Alternative Method yielded a relatively more accurate FTABLE than the BASINS method. This study concludes that hydraulic calibration enhances suspended sediment simulation performance, but even greater improvement in suspended sediment calibration can be achieved when hydrological simulation performance is improved. Any improvements in hydrological simulation performance are subject to improvements in the temporal and spatial representation of the precipitation data.

Coupling of hydrologic and hydraulic models for the Illinois River Basin

The Hydrologic Simulation Program – Fortran (HSPF) was applied to the Illinois River Basin using the U.S. Environmental Protection Agency’s (USEPA) Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) system. Values of the HSPF model parameters were based on the calibrations of three representative watersheds within the basin. Over the 1985–1995 simulation period, monthly and annual mass balances correlated well with observed discharges at three gaging stations along the Illinois River. However, poor correlation of daily flows was due largely to the weakness of the HSPF model in routing dynamic flows through the complicated Illinois River system. To address this problem, a one-dimensional unsteady state flow model (UNET) developed for the main stem of the Illinois River was coupled with the HSPF model to perform the flow routing. Comparison of hydrographs showed much closer correlation between coupled HSPF–UNET model simulations of daily flows and observed flow hydrographs. This study also showed that peak flows simulated by the HSPF model occurred several days before the actual observations. However, the coupled HSPF–UNET model simulated peak flow time more closely to the observations. The Nash-Sutcliffe efficiency (NSE) computed using observed and simulated daily flows from HSPF and HSPF–UNET models was 0.72 and 0.79 at Marseilles, 0.63 and 0.82 at Kingston Mines, and 0.40 and 0.85 at Valley City, respectively. As expected, the NSE computed using mean monthly flows was also slightly better from HSPF–UNET than from HSPF, but the annual NSE values were nearly same from both models.

Application of Non‐Linear Automatic Optimization Techniques for Calibration of HSPF

Development of TMDLs (total maximum daily loads) is often facilitated by using the software system BASINS (Better Assessment Science Integrating point and Nonpoint Sources). One of the key elements of BASINS is the watershed model HSPF (Hydrological Simulation Program Fortran) developed by USEPA. Calibration of HSPF is a very tedious and time consuming task, more than 100 parameters are involved in the calibration process. In the current research, three non-linear automatic optimization techniques are applied and compared, as well an efficient way to calibrate HSPF is suggested. Parameter optimization using local and global optimization techniques for the watershed model is discussed. Approaches to automatic calibration of HSPF using the nonlinear parameter estimator PEST (Parameter Estimation Tool) with its Gauss-Marquardt-Levenberg (GML) method, Random multiple Search Method (RSM), and Shuffled Complex Evolution method developed at the University of Arizona (SCE-UA) are presented. Sensitivity analysis was conducted and the most and the least sensitive parameters were identified. It was noted that sensitivity depends on number of adjustable parameters. As more parameters were optimized simultaneously--a wider range of parameter values can maintain the model in the calibrated state. Impact of GML, RSM, and SCE-UA variables on ability to find the global minimum of the objective function (OF) was studied and the best variables are suggested. All three methods proved to be more efficient than manual HSPF calibration. Optimization results obtained by these methods are very similar, although in most cases RSM outperforms GML and SCE-UA outperforms RSM. GML is a very fast method, it can perform as well as SCE-UA when the variables are properly adjusted, initial guess is good and insensitive parameters are eliminated from the optimization process. SCE-UA is very robust and convenient to use. Logical definition of key variables in most cases leads to the global minimum.

Exploring the Variability in Suspended Sediment Yield using BASINS-HSPF and Probabilistic Modeling: Implications for Land Use Planning

The purpose of this study is to examine the use of Monte Carlo simulation method together with BASINS-HSPF, a deterministic water quality simulation model to investigate the variability of sediment yield from various land cover types in the East Fork Little Miami River watershed, Ohio, UISA. The study has two main objectives: first, to obtain interval estimates of suspended sediment yield from urban, agricultural and forest land; and second, to generate probability density and cumulative distribution functions for those estimates. As a result, we will know not only the range of possible values of sediment yield in the watershed but also the probability with which those values are likely to occur. BASINS (Better Assessment Science Integrating Point and Non-Point Sources), a modeling system which provides a Window-based interface for the Hydrologic Simulation Program – Fortran (HSPF), is used in the analysis to simulate streamflow and suspended sediment yield. The daily values of suspended sediment yield from various land cover types generated by BASINS-HSPF are used as input to the Monte Carlo simulation technique that generates probability density and cumulative distribution functions. The distributions are used to draw conclusions about the uncertainty in the hydrologic model predictions in the form of confidence intervals for the predicted sediment yield. The study found that the width of the confidence interval has a critical importance for the evaluation of the model results.

The Soil and Water Assessment Tool: Historical Development, Applications, and Future Research Directions

The Soil and Water Assessment Tool (SWAT) model is a continuation of nearly 30 years of modeling efforts conducted by the USDA Agricultural Research Service (ARS). SWAT has gained international acceptance as a robust interdisciplinary watershed modeling tool as evidenced by international SWAT conferences, hundreds of SWAT-related papers presented at numerous other scientific meetings, and dozens of articles published in peer-reviewed journals. The model has also been adopted as part of the U.S. Environmental Protection Agency (USEPA) Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) software package and is being used by many U.S. federal and state agencies, including the USDA within the Conservation Effects Assessment Project (CEAP). At present, over 250 peer-reviewed published articles have been identified that report SWAT applications, reviews of SWAT components, or other research that includes SWAT. Many of these peer-reviewed articles are summarized here according to relevant application categories such as streamflow calibration and related hydrologic analyses, climate change impacts on hydrology, pollutant load assessments, comparisons with other models, and sensitivity analyses and calibration techniques. Strengths and weaknesses of the model are presented, and recommended research needs for SWAT are also provided.

Study of Total Maximum Daily Load and Nonpoint Source Pollution Control Strategies for Reservoir Watershed

In Taiwan, nonpoint source (NPS) pollution is one of the major causes of the impairment of surface waters. Thus, control of NPS has been considered as one of the major issues in developing watershed management strategies. The reduction in NPS must be implemented in the total watershed in order to achieve a sustainable management of the reservoir. This study employed the BASINS (Better Assessment Science Integrating point and nonpoint Sources) model to evaluate the impacts of NPS in the entire Fei-Tsui Reservoir watershed on the reservoir water quality. Additionally, the Vollenweider model was used to calculate the total phosphorus (TP) reduction. Several NPS reduction schemes had been proposed for the watershed and were tested using this model to develop allocation strategies. The purpose of this study is to estimate the TP yield loading from the entire watershed to Fei-Tsui Reservoir such that an appropriate NPS pollution control strategy can be developed for managing the Reservoir. Results of this study...

Calibration of BASINS HSP-F in Support of a Watershed Approach to CSO Long Term Control Planning

BASINS (Better Assessment Science Integrating point and Nonpoint Sources) HSP-F was used as part of the watershed approach in developing the City of Buffalo Lo…

Impacts of climate change on streamflow in the Upper Mississippi River Basin: A regional climate model perspective

Impact of climate change on streamflow in the Upper Mississippi River Basin is evaluated by use of a regional climate model (RCM) coupled with a hydrologic model, Soil and Water Assessment Tool (SWAT). The RCM we used resolves, at least partially, some fine‐scale dynamical processes that are important contributors to precipitation in this region and that are not well simulated by global models. The SWAT model was calibrated and validated against measured streamflow data using observed weather data and inputs from the U.S. Environmental Protection Agency Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) geographic information systems/database system. Combined performance of SWAT and RCM was examined using observed weather data as lateral boundary conditions in the RCM. The SWAT and RCM performed well, especially on an annual basis. Potential impacts of climate change on water yield and other hydrologic budget components were then quantified by driving SWAT with current and future scenario climates. Twenty‐one percent increase in future precipitation simulated by the RCM produced 18% increase in snowfall, 51% increase in surface runoff, and 43% increase in groundwater recharge, resulting in 50% net increase in total water yield in the Upper Mississippi River Basin on an annual basis. Uncertainty analysis showed that the simulated change in streamflow substantially exceeded model biases of the combined modeling system (with largest bias of 18%). While this does not necessarily give us high confidence in the actual climate change that will occur, it does demonstrate that the climate change “signal” stands out from the climate modeling (global plus regional) and impact assessment modeling (SWAT) “noise.”