Water Quality Assessment of Large‐scale Bioenergy Cropping Scenarios for the Upper Mississippi and Ohio‐Tennessee River Basins

The Upper Mississippi River Basin and Ohio‐Tennessee River Basin comprise the majority of the United States Corn Belt region, resulting in degraded Mississippi River and Gulf of Mexico water quality. To address the water quality implications of increased biofuel production, biofuel scenarios were tested with a Soil and Water Assessment Tool (SWAT) model revision featuring improved biofuel crop representation. Scenarios included corn stover removal and the inclusion of two perennial bioenergy crops, switchgrass and Miscanthus, grown on marginal lands (slopes >2% and erosion rates >2 t/ha) and nonmarginal lands. The SWAT model estimates show water quality is not very sensitive to stover removal. The perennial bioenergy crops reduce simulated sediment, nitrogen (N), and phosphorus (P) yields by up to 60%. Simulated sediment and P reductions in marginal lands were generally twice that occurring in the nonmarginal lands. The highest unit area reductions of N occurred in the less sloping tile‐drained lands. Productivity showed corn grain yield was independent from stover removal, while yields of the two perennial bioenergy crops were similar in the marginal and nonmarginal lands. The results suggest planning for biofuel production in the Corn Belt could include the removal of stover in productive corn areas, and the planting of perennial bioenergy crops in marginal land and in low‐sloped tile‐drained areas characterized by high N pollution. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Influence of Bioenergy Crop Production and Climate Change on Ecosystem Services

Land use change can significantly affect the provision of ecosystem services and the effects could be exacerbated by projected climate change. We quantify ecosystem services of bioenergy‐based land use change and estimate the potential changes of ecosystem services due to climate change projections. We considered 17 bioenergy‐based scenarios with Miscanthus, switchgrass, and corn stover as candidate bioenergy feedstock. Soil and Water Assessment Tool simulations of biomass/grain yield, hydrology, and water quality were used to quantify ecosystem services freshwater provision (FWPI), food (FPI) and fuel provision, erosion regulation (ERI), and flood regulation (FRI). Nine climate projections from Coupled Model Intercomparison Project phase‐3 were used to quantify the potential climate change variability. Overall, ecosystem services of heavily row cropped Wildcat Creek watershed were lower than St. Joseph River watershed which had more forested and perennial pasture lands. The provision of ecosystem services for both study watersheds were improved with bioenergy production scenarios. Miscanthus in marginal lands of Wildcat Creek (9% of total area) increased FWPI by 27% and ERI by 14% and decreased FPI by 12% from the baseline. For St. Joseph watershed, Miscanthus in marginal lands (18% of total area) improved FWPI by 87% and ERI by 23% while decreasing FPI by 46%. The relative impacts of land use change were considerably larger than climate change impacts in this paper. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Application of SWAT with and without Variable Source Area Hydrology to a Large Watershed

In this study, two different versions of the Soil and Water Assessment Tool (SWAT) model were used to simulate the hydrology and biogeochemical response of the Cannonsville Reservoir watershed, in New York. The first version distributes overland flow in ways that are consistent with variable source area (VSA) hydrology driven by saturation excess runoff, whereas the second version is the standard version of SWAT. These two models were each calibrated for streamflow (Flow), particulate phosphorus (PP), total dissolved phosphorus (TDP), and sediment (Sed) against measured data from the 1,200 km² Cannonsville watershed. The standard version of the model yielded an r² between the measured and simulated data of 0.85, 0.73, 0.70, and 0.72 for Flow, Sed, TDP, and PP, respectively. The VSA version yielded an r² of 0.84, 0.69, 0.72, and 0.53 for Flow, Sed, TDP, and PP, respectively. The two models were then used to determine the maximum upper bound on the reduction in phosphorus loading by removing all of the corn in the watershed. The average reductions between the two models were 65 and 37% for PP and TDP, respectively. The VSA version was also used to estimate the effect of moving corn land in the watershed from the wettest, most runoff prone areas to the driest, least runoff prone areas, which cannot be done directly with the standard SWAT model.     

Evaluation of Existing and Modified Wetland Equations in the SWAT Model

The ability to accurately simulate flow and nutrient removal in treatment wetlands within an agricultural, watershed‐scale model is needed to develop effective plans for meeting nutrient reduction goals associated with protection of drinking water supplies and reduction of the Gulf of Mexico hypoxic zone. The objectives of this study were to incorporate new equations for wetland hydrology and nutrient removal in Soil and Water Assessment Tool (SWAT), compare model performance using original and improved equations, and evaluate the ramifications of errors in watershed and tile drain simulation on prediction of NO₃‐N dynamics in wetlands. The modified equations produced Nash‐Sutcliffe Efficiency values of 0.88 to 0.99 for daily NO₃‐N load predictions, and percent bias values generally less than 6%. However, statistical improvement over the original equations was marginal and both old and new equations provided accurate simulations. The new equations reduce the model's dependence on detailed monitoring data and hydrologic calibration. Additionally, the modified equations increase SWAT's versatility by incorporating a weir equation and an irreducible nutrient concentration and temperature coefficient. Model improvements enhance the utility of SWAT for simulating flow and nutrients in wetlands and other impoundments, although performance is limited by the accuracy of inflow and NO₃‐N predictions from the contributing watershed. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Simulation of Daily Flow Pathways,Tile‐Drain Nitrate Concentrations,and Soil‐Nitrogen Dynamics Using SWAT

Tile drainage significantly alters flow and nutrient pathways and reliable simulation at this scale is needed for effective planning of nutrient reduction strategies. The Soil and Water Assessment Tool (SWAT) has been widely utilized for prediction of flow and nutrient loads, but few applications have evaluated the model's ability to simulate pathway‐specific flow components or nitrate‐nitrogen (NO₃‐N) concentrations in tile‐drained watersheds at the daily time step. The objectives of this study were to develop and calibrate SWAT models for small, tile‐drained watersheds, evaluate model performance for simulation of flow components and NO₃‐N concentration at daily intervals, and evaluate simulated soil‐nitrogen dynamics. Model evaluation revealed that it is possible to meet accepted performance criteria for simulation of monthly total flow, subsurface flow (SSF), and NO₃‐N loads while obtaining daily surface runoff (SURQ), SSF, and NO₃‐N concentrations that are not satisfactory. This limits model utility for simulating best management practices (BMPs) and compliance with water quality standards. Although SWAT simulates the soil N‐cycle and most predicted fluxes were within ranges reported in agronomic studies, improvements to algorithms for soil‐N processes are needed. Variability in N fluxes is extreme and better parameterization and constraint, through use of more detailed agronomic data, would also improve NO₃‐N simulation in SWAT. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Use of SWAT to Estimate Spatial Scaling of Phosphorus Export Coefficients and Load Reductions Due to Agricultural BMPS

Phosphorus export coefficients (kg/ha/yr) from selected land covers, also called phosphorus yields, tend to get smaller as contributing areas get larger because some of the phosphorus mobilized on local fields gets trapped during transport to regional watershed outlets. Phosphorus traps include floodplains, wetlands, and lakes, which can then become impaired by eutrophication. The Sunrise River watershed in east central Minnesota, United States, has numerous lakes impaired by excess phosphorus. The Sunrise is tributary to the St. Croix River, whose much larger watershed is terminated by Lake St. Croix, also impaired by excess phosphorus. To support management of these impairments at both local and regional scales, a Soil and Water Assessment Tool (SWAT) model of the Sunrise watershed was constructed to estimate load reductions due to selected best management practices (BMPs) and to determine how phosphorus export coefficients scaled with contributing area. In this study, agricultural BMPs, including vegetated filter strips, grassed waterways, and reduction of soil‐phosphorus concentrations reduced phosphorus loads by 4‐20%, with similar percentage reductions at field and watershed spatial scales. Phosphorus export coefficients from cropland in rotation with corn, soybeans, and alfalfa decreased as a negative power function of contributing area, from an average of 2.12 kg/ha/yr at the upland field scale (~0.6 km²) to 0.63 kg/ha/yr at the major river basin scale (20,000 km²). Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Augmenting Watershed Model Calibration with Incorporation of Ancillary Data Sources and Qualitative Soft Data Sources

Watershed simulation models such as the Soil & Water Assessment Tool (SWAT) can be calibrated using “hard data” such as temporal streamflow observations; however, users may find upon examination of model outputs, that the calibrated models may not reflect actual watershed behavior. Thus, it is often advantageous to use “soft data” (i.e., qualitative knowledge such as expected denitrification rates that observed time series do not typically exist) to ensure that the calibrated model is representative of the real world. The primary objective of this study is to evaluate the efficacy of coupling SWAT‐Check (a post‐evaluation framework for SWAT outputs) and IPEAT‐SD (Integrated Parameter Estimation and Uncertainty Analysis Tool‐Soft & hard Data evaluation) to constrain the bounds of soft data during SWAT auto‐calibration. IPEAT‐SD integrates 59 soft data variables to ensure SWAT does not violate physical processes known to occur in watersheds. IPEAT‐SD was evaluated for two case studies where soft data such as denitrification rate, nitrate attributed from subsurface flow to total discharge ratio, and total sediment loading were used to conduct model calibration. Results indicated that SWAT model outputs may not satisfy reasonable soft data responses without providing pre‐defined bounds. IPEAT‐SD provides an efficient and rigorous framework for users to conduct future studies while considering both soft data and traditional hard information measures in watershed modeling.     

Implications of Conceptual Channel Representation on SWAT Streamflow and Sediment Modeling

Hydrologic modeling outputs are influenced by how a watershed system is represented. Channel routing is a typical example of the mathematical conceptualization of watershed landscape and processes in hydrologic modeling. We investigated the sensitivity of accuracy, equifinality, and uncertainty of Soil and Water Assessment Tool (SWAT) modeling to channel dimensions to demonstrate how a conceptual representation of a watershed system affects streamflow and sediment modeling. Results showed the amount of uncertainty and equifinality strongly responded to channel dimensions. On the other hand, the model performance did not significantly vary with the changes in the channel representation due to the degree of freedom allowed by the conceptual nature of hydrologic modeling in the parameter calibration. Such findings demonstrated good modeling performance statistics do not necessarily mean small output uncertainty, and partial improvements in the watershed representation may neither increase modeling accuracy nor reduce uncertainty. We also showed the equifinality and uncertainty of hydrologic modeling are case‐dependent rather than specific to models or regions, suggesting great caution should be used when attempting to transfer uncertainty analysis results to other modeling studies, especially for ungauged watersheds. Editor's note: This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Environmental and economic analysis of switchgrass production for water quality improvement in northeast Kansas

The primary objectives of this research were to determine SWAT model predicted reductions in four water quality indicators (sediment yield, surface runoff, nitrate nitrogen (NO(3)-N) in surface runoff, and edge-of-field erosion) associated with producing switchgrass (Panicum virgatum) on cropland in the Delaware basin in northeast Kansas, and evaluate switchgrass break-even prices. The magnitude of potential switchgrass water quality payments based on using switchgrass as an alternative energy source was also estimated. SWAT model simulations showed that between 527,000 and 1.27 million metric tons (Mg) of switchgrass could be produced annually across the basin depending upon nitrogen (N) fertilizer application levels (0-224 kg N ha(-1)). The predicted reductions in sediment yield, surface runoff, NO(3)-N in surface runoff, and edge-of-field erosion as a result of switchgrass plantings were 99, 55, 34, and 98%, respectively. The average annual cost per hectare for switchgrass ranged from about 190 US dollars with no N applied to around 345 US dollars at 224 kg N ha(-1) applied. Edge-of-field break-even price per Mg ranged from around 41 US dollars with no N applied to slightly less than 25 US dollars at 224 kg N ha(-1) applied. A majority of the switchgrass produced had an edge-of-field break-even price of 30 Mg(-1) US dollars or less. Savings of at least 50% in each of the four water quality indicators could be attained for an edge-of-field break-even price of 22-27.49 US dollars Mg(-1).     

Testing of the Modified Streambank Erosion and Instream Phosphorus Routines for the SWAT Model

In some watersheds, streambanks are a source of two major pollutants, phosphorus (P) and sediment. P originating from both uplands and streambanks can be transported and stored indefinitely on floodplains, streambanks, and in closed depressions near the stream. The objectives of this study were to (1) test the modified streambank erosion and instream P routines for the Soil and Water Assessment Tool (SWAT) model in the Barren Fork Creek watershed in northeast Oklahoma, (2) predict P in the watershed with and without streambank‐derived P, and (3) determine the significance of streambank erosion P relative to overland P sources. Measured streambank and channel parameters were incorporated into a flow‐calibrated SWAT model and used to estimate streambank erosion and P for the Barren Fork Creek using modified streambank erosion and instream P routines. The predicted reach‐weighted streambank erosion was 40 kg/m vs. the measured 42 kg/m. Streambank erosion contributed 47% of the total P to the Barren Fork Creek and improved P predictions compared to observed data, especially during the high‐flow events. Of the total P entering the stream system, approximately 65% was removed via the watershed outlet and 35% was stored in the floodplain and stream system. This study successfully applied the SWAT model's modified streambank erosion and instream P routines and demonstrated that streambank‐derived P can improve P modeling at the watershed scale. Editor's note: This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Monitored and Modeled Correlations of Sediment and Nutrients with Chesapeake Bay Water Clarity

This article analyzes the correlations of the observed and modeled light attenuation coefficient, Kd, with in situ total suspended solids (TSS) and chlorophyll‐a concentrations in Chesapeake Bay (CB) tidal waters, and with sediment and nutrient loads from the Chesapeake watershed. Light attenuation is closely related to in situ TSS and chlorophyll‐a concentrations, however, the strength of the correlation differs among the CB segments. There are distinct differences between saline and tidal fresh segments in the main Bay, but less distinction among saline and tidal fresh segments in the tidal tributaries. The correlation between Kd with sediment and nutrient loads is complicated by the lag times of TSS and the chlorophyll‐a responses to reductions in nutrient and sediment loads from the watershed, and also due to the diverse load sources. Three sets of model sensitivity scenarios were performed with: (1) differential sediment and nutrient loads; (2) selective sediment source types; and (3) geographically isolated inputs. The model results yield similar findings as those based on observed data and provide information regarding the effect of sediment on specific water bodies. Based on the model results a method was developed to determine sediment and nutrient load reductions needed to achieve the water clarity standards of the CB segments.     

SWATmodel: A Multi‐Operating System,Multi‐Platform SWAT Model Package in R

The Soil and Water Assessment Tool (SWAT) model (Arnold et al., 1998) is a popular watershed management tool. Currently, the SWAT model, actively supported by the U.S. Department of Agriculture and Texas A&M, operates only on Microsoft^® Windows, which hinders modelers that use other operating systems (OS). This technical note introduces the Comprehensive R Archive Network (CRAN) distributed “SWATmodel” package which allows SWAT 2005 and 2012 to be widely distributed and run as a linear model‐like function on multiple OS and processor platforms. This allows researchers anywhere in the world using virtually any OS to run SWAT. In addition to simplifying the use of SWAT across computational platforms, the SWATmodel package allows SWAT modelers to utilize the analytical capabilities, statistical libraries, modeling tools, and programming flexibility inherent to R. The software allows watershed modelers to develop a simple hydrological watershed model conceptualization of the SWAT model and to obtain a first approximation of the minimum expected results a more complicated model should deliver. As a proof of concept, we test the SWAT model by initializing and calibrating 314 U.S. Geological Survey stream gages in the Chesapeake Bay watershed and present the results.     

Assessing Parameter Uncertainty of a Semi‐Distributed Hydrology Model for a Shallow Aquifer Dominated Environmental System

This paper examines the performance of a semi‐distributed hydrology model (i.e., Soil and Water Assessment Tool [SWAT]) using Sequential Uncertainty FItting (SUFI‐2), generalized likelihood uncertainty estimation (GLUE), parameter solution (ParaSol), and particle swarm optimization (PSO). We applied SWAT to the Waccamaw watershed, a shallow aquifer dominated Coastal Plain watershed in the Southeastern United States (U.S.). The model was calibrated (2003‐2005) and validated (2006‐2007) at two U.S. Geological Survey gaging stations, using significant parameters related to surface hydrology, hydrogeology, hydraulics, and physical properties. SWAT performed best during intervals with wet and normal antecedent conditions with varying sensitivity to effluent channel shape and characteristics. In addition, the calibration of all algorithms depended mostly on Manning's n‐value for the tributary channels as the surface friction resistance factor to generate runoff. SUFI‐2 and PSO simulated the same relative probability distribution tails to those observed at an upstream outlet, while all methods (except ParaSol) exhibited longer tails at a downstream outlet. The ParaSol model exhibited large skewness suggesting a global search algorithm was less capable of characterizing parameter uncertainty. Our findings provide insights regarding parameter sensitivity and uncertainty as well as modeling diagnostic analysis that can improve hydrologic theory and prediction in complex watersheds. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Assessing Sediment Yield for Selected Watersheds in the Laurentian Great Lakes Basin Under Future Agricultural Scenarios

In the Laurentian Great Lakes Basin (GLB), corn acreage has been expanding since 2005 in response to high demand for corn as an ethanol feedstock. This study integrated remote sensing-derived products and the Soil and Water Assessment Tool (SWAT) within a geographic information system (GIS) modeling environment to assess the impacts of cropland change on sediment yield within four selected watersheds in the GLB. The SWAT models were calibrated during a 6 year period (2000–2005), and predicted stream flows were validated. The R ² values were 0.76, 0.80, 0.72, and 0.81 for the St. Joseph River, the St. Mary River, the Peshtigo River, and the Cattaraugus Creek watersheds, respectively. The corresponding E (Nash and Sutcliffe model efficiency coefficient) values ranged from 0.24 to 0.79. The average annual sediment yields (tons/ha/year) ranged from 0.12 to 4.44 for the baseline (2000 to 2008) condition. Sediment yields were predicted to increase for possible future cropland change scenarios. The first scenario was to convert all “other” agricultural row crop types (i.e., sorghum) to corn fields and switch the current/baseline crop rotation into continuous corn. The average annual sediment yields increased 7–42 % for different watersheds. The second scenario was to further expand the corn planting to hay/pasture fields. The average annual sediment yields increased 33–127 % compared with baseline conditions.     

Modeling Changes to Streamflow,Sediment, and Nutrient Loading from Land Use Changes Due to Potential Natural Gas Development

Natural gas development using hydraulic fracturing has many potential environmental impacts, but among the most certain is the land disturbance required to build the well pads and other infrastructure required to drill and extract the gas. We used the Soil and Water Assessment Tool (SWAT) model to investigate how natural gas development could impact streamflow and sediment, total nitrogen (TN), and total phosphorous (TP) loadings in the upper Delaware River Basin (DRB), a relatively undeveloped watershed of 7,950 km² that lies above the Marcellus Shale formation. If gas development was permitted, our projections show the DRB could experience development of over 600 well pads to extract natural gas at build out, which, with supporting infrastructure (roads, gathering pipelines), could convert over 5,000 ha from existing land uses in the study area. In subbasins with development activity we found sediment, TN, and TP yields could increase by an average of 15, 0.08, and 0.03 kg/ha/yr, respectively (an increase of 2, 3, and 15%, respectively) for each one percent of subbasin land area converted into natural gas infrastructure. At the study area outlet on the Delaware River at Port Jervis, New York, we found increases in the annual average streamflow and sediment, nitrogen, and phosphorus loads of up to 0.01, 0.2, 0.2, and 1%, respectively, for a rapid development year, and 0.08, 1.3, 2.0, and 11%, respectively, for the full development scenario. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Effects of Land Use and Climate Change on Stream Temperature I: Daily Flow and Stream Temperature Projections

Freshwater mussels (order Unionida) are a highly imperiled group of organisms that are at risk from rising stream temperatures (T). There is a need to understand the potential effects of land use (LU) and climate change (CC) on stream T and have a measure of uncertainty. We used available downscaled climate projections and LU change simulations to simulate the potential effects on average daily stream T from 2020 to 2060. Monte Carlo simulations were run, and a novel technique to analyze results was used to assess changes in hydrologic and stream T response. Simulations of daily mean T were used as input to our stochastic hourly T model. CC effects were on average two orders of magnitude greater than LU impacts on mean daily stream T. LU change affected stream T primarily in headwater streams, on average up to 2.1°C over short durations, and projected CC affected stream T, on average 2.1‐3.3°C by 2060. Daily mean flow and T ratios from Monte Carlo simulations indicated greater variance in the response of streamflow (up to 55%) to LU change than in the response of stream T (up to 9%), and greater variance in headwater stream segments compared to higher order stream segments for both streamflow and T response. Simulations indicated that combined effects of climate and LU change were not additive, suggesting a complex interaction and that forecasting long‐term stream T response requires simulating CC and LU change simultaneously.     

Hydrological Variability and Uncertainty of Lower Missouri River Basin Under Changing Climate

The lower Missouri River Basin has experienced increasing streamflow and flooding events, with higher risk of extreme hydrologic impacts under changing climate. The newly available North American Regional Climate Change Assessment Program (NARCCAP) climate projections were used as atmospheric forcing for Soil and Water Assessment Tool (SWAT) model which runs with varying potential evapotranspiration (PET) methods to assess the hydrological change and uncertainty of 2040‐2069 over 1968‐1997. The NARCCAP temperature and precipitation predictions were refined using a bias correction method. The results show that, following the seasonal variability of precipitation, various water fluxes would increase in most seasons except the summer. Expected precipitation tends to increase in intensity with little change in frequency, triggering faster surface water concentration to form floods. The greatest streamflow increase would occur from November to February, increasing by around 10% on average. An increase of 3% occurs in the other months except for July and August in which river discharge decreases by around 2%. The climate predictions contribute more uncertainty annually, but PET algorithms gain more influence in winter or when other weather factors such as wind play a relatively more important role on evapotranspiration flux. This study predicts an even wetter environment compared to the historically very wet period, with the possibility of more flooding.     

HYDROLOGICAL MODELING OF THE IROQUOIS RIVER WATERSHED USING HSPF AND SWAT1

ABSTRACT: The performance of two popular watershed scale simulation models — HSPF and SWAT — were evaluated for simulating the hydrology of the 5,568 km² Iroquois River watershed in Illinois and Indiana. This large, tile drained agricultural watershed provides distinctly different conditions for model comparison in contrast to previous studies. Both models were calibrated for a nine‐year period (1987 through 1995) and verified using an independent 15‐year period (1972 through 1986) by comparing simulated and observed daily, monthly, and annual streamflow. The characteristics of simulated flows from both models are mostly similar to each other and to observed flows, particularly for the calibration results. SWAT predicts flows slightly better than HSPF for the verification period, with the primary advantage being better simulation of low flows. A noticeable difference in the models' hydrologic simulation relates to the estimation of potential evapotranspiration (PET). Comparatively low PET values provided as input to HSPF from the BASINS 3.0 database may be a factor in HSPF's overestimation of low flows. Another factor affecting baseflow simulation is the presence of tile drains in the watershed. HSPF parameters can be adjusted to indirectly account for the faster subsurface flow associated with tile drains, but there is no specific tile drainage component in HSPF as there is in SWAT. Continued comparative studies such as this, under a variety of hydrologic conditions and watershed scales, provide needed guidance to potential users in model selection and application.     

Development of the Spatial Rainfall Generator (SRGEN) for the Agricultural Policy/Environmental Extender Model

Accurate spatial representation of climatic patterns is often a challenge in modeling biophysical processes at the watershed scale, especially where the representation of a spatial gradient in rainfall is not sufficiently captured by the number of weather stations. The spatial rainfall generator (SRGEN) is developed as an extension of the “weather generator” (WXGEN), a component of the Agricultural Policy/Environmental eXtender (APEX) model. SRGEN generates spatially distributed daily rainfall using monthly weather statistics available at multiple locations in a watershed. The spatial rainfall generator as incorporated in APEX is tested on the Cowhouse watershed (1,178 km²) in central Texas. The watershed presented a significant spatial rainfall gradient of 2.9 mm/km in the lateral (north‐south) directions based on four rainfall gages. A comparative analysis between SRGEN and WXGEN indicates that SRGEN performs well (PBIAS = 2.40%). Good results were obtained from APEX for streamflow (NSE = 0.99, PBIAS = 8.34%) and NO₃‐N and soluble P loads (PBIAS ≈ 6.00% for each, respectively). However, APEX underpredicted sediment yield and organic N and P loads (PBIAS: 24.75‐27.90%) with SRGEN, although its uncertainty in output was lower than WXGEN results (PBIAS: ?13.02 to ?46.13%). The overall improvement achieved in rainfall generation by SRGEN is demonstrated to be effective in the improving model performance on flow and water quality output.