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.     

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.     

Assessment of Bioenergy Cropping Scenarios for the Boone River Watershed in North Central Iowa,United States

Several biofuel cropping scenarios were evaluated with an improved version of Soil and Water Assessment Tool (SWAT) as part of the CenUSA Bioenergy consortium for the Boone River Watershed (BRW), which drains about 2,370 km² in north central Iowa. The adoption of corn stover removal, switchgrass, and/or Miscanthus biofuel cropping systems was simulated to assess the impact of cellulosic biofuel production on pollutant losses. The stover removal results indicate removal of 20 or 50% of corn stover in the BRW would have negligible effects on streamflow and relatively minor or negligible effects on sediment and nutrient losses, even on higher sloped cropland. Complete cropland conversion into switchgrass or Miscanthus, resulted in reductions of streamflow, sediment, nitrate, and other pollutants ranging between 23‐99%. The predicted nitrate reductions due to Miscanthus adoption were over two times greater compared to switchgrass, with the largest impacts occurring for tile‐drained cropland. Targeting of switchgrass or Miscanthus on cropland ≥2% slope or ≥7% slope revealed a disproportionate amount of sediment and sediment‐bound nutrient reductions could be obtained by protecting these relatively small areas of higher sloped cropland. Overall, the results indicate that all biofuel cropping systems could be effectively implemented in the BRW, with the most robust approach being corn stover removal adopted on tile‐drained cropland in combination with a perennial biofuel crop on higher sloped landscapes. 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.     

SENSITIVITY ANALYSIS,CALIBRATION, AND VALIDATIONS FOR A MULTISITE AND MULTIVARIABLE SWAT MODEL1

The ability of a watershed model to mimic specified watershed processes is assessed through the calibration and validation process. The Soil and Water Assessment Tool (SWAT) watershed model was implemented in the Beaver Reservoir Watershed of Northwest Arkansas. The objectives were to: (1) provide detailed information on calibrating and applying a multisite and multivariable SWAT model; (2) conduct sensitivity analysis; and (3) perform calibration and validation at three different sites for flow, sediment, total phosphorus (TP), and nitrate‐nitrogen (NO₃‐N) plus nitrite‐nitrogen (NO₂‐N). Relative sensitivity analysis was conducted to identify parameters that most influenced predicted flow, sediment, and nutrient model outputs. A multi objective function was defined that consisted of optimizing three statistics: percent relative error (RE), Nash‐Sutcliffe Coefficient (R_NS²), and coefficient of determination (R²). This function was used to successfully calibrate and validate a SWAT model of Beaver Reservoir Watershed at multi‐sites while considering multivariables. Calibration and validation of the model is a key factor in reducing uncertainty and increasing user confidence in its predictive abilities, which makes the application of the model effective. Information on calibration and validation of multisite, multivariable SWAT models has been provided to assist watershed modelers in developing their models to achieve watershed management goals.     

Two‐Stage Ditch Floodplains Enhance N‐Removal Capacity and Reduce Turbidity and Dissolved P in Agricultural Streams

Two‐stage ditches represent an emerging management strategy in artificially drained agricultural landscapes that mimics natural floodplains and has the potential to improve water quality. We assessed the potential for the two‐stage ditch to reduce sediment and nutrient export by measuring water column turbidity, nitrate (NO₃^?), ammonium (NH₄⁺), and soluble reactive phosphorus (SRP) concentrations, and denitrification rates. During 2009‐2010, we compared reaches with two‐stage floodplains to upstream reaches with conventional trapezoid design in six agricultural streams. At base flow, these short two‐stage reaches (<600 m) reduced SRP concentrations by 3‐53%, but did not significantly reduce NO₃^? concentrations due to very high NO₃^? loads. The two‐stage also decreased turbidity by 15‐82%, suggesting reduced suspended sediment export during floodplain inundation. Reach‐scale N‐removal increased 3‐24 fold during inundation due to increased bioreactive surface area with high floodplain denitrification rates. Inundation frequency varied with bench height, with lower benches being flooded more frequently, resulting in higher annual N‐removal. We also found both soil organic matter and denitrification rates were higher on older floodplains. Finally, influence of the two‐stage varied among streams and years due to variation in stream discharge, nutrient loads, and denitrification rates, which should be considered during implementation to optimize potential water quality benefits.     

GIS‐BASED WATER QUALITY MODELING IN THE SANDUSKY WATERSHED,OHIO, USA1

ABSTRACT: This study focused on the Sandusky Watershed (SW) in Ohio, located within the Great Lakes Basin, with emphasis on two of its subwatersheds, namely Honey Creek (HC) and Rock Creek (RC). The goal was to assess the capabilities of the Soil and Water Assessment Tool (SWAT) to simulate suspended sediment (SS), phosphorus (P) and nitrogen (N) yield in the SW that contribute major sediment and nutrient loads into Lake Erie. The model was calibrated using water flow and water quality parameters for water years 1998 to 1999 and validated model simulations covering the period of water years 2000 to 2001 for monthly conditions. The validation of SS showed correlation coefficients of 0.29 (SW), 0.75 (HC) and 0.69 (RC). Correlation coefficients for P were 0.68 (SW), 0.78 (HC) and 0.37 (RC); for N0₂‐N 0.84 (HC) and 0.38 (RC); for N0₃‐N 0.27 (HC) and 0.76 (RC); for NH₃‐N 0.57 (SW), 0.49 (HC), and 0.13 (RC). In addition, mean errors, root mean square errors, Nash‐Sutcliffe coefficients, and graphs were used to compare simulated to measured data. Simulation success was variable with poor and good simulations, but in most cases, simulated water quality values followed the trend of measured data except for extreme (or intense) rainfall/runoff events. Reviews of 17 applications indicated that the SWAT is suitable for long term continuous simulations but not for storm events. A spatially distributed modeling approach generated maps showing the spatial distribution of SS, P, and N for each simulation element across the Sandusky Watershed.     

WATERSHED SCALING EFFECT ON BASE FLOW NITRATE,VALLEY AND RIDGE PHYSIOGRAPHIC PROVINCE1

ABSTRACT: A study of stream base flow and NO₃‐N concentration was conducted simultaneously in 51 subwatersheds within the 116‐square‐kilometer watershed of East Mahantango Creek near Klingerstown, Pennsylvania. The study was designed to test whether measurable results of processes and observations within the smaller watersheds were similar to or transferable to a larger scale. Ancillary data on land use were available for the small and large watersheds. Although the source of land‐use data was different for the small and large watersheds, comparisons showed that the differences in the two land‐use data sources were minimal. A land use‐based water‐quality model developed for the small‐scale 7.3‐square‐kilometer watershed for a previous study accurately predicted NO₃‐N concentrations from sampling in the same watershed. The water‐quality model was modified and, using the imagery‐based land use, was found to accurately predict NO₃‐N concentrations in the subwatersheds of the large‐scale 116‐square‐kilometer watershed as well. Because the model accurately predicts NO₃‐N concentrations at small and large scales, it is likely that in second‐order streams and higher, discharge of water and NO₃‐N is dominated by flow from smaller first‐order streams, and the contribution of ground‐water discharge to higher order streams is minimal at the large scale.     

Groundwater Nitrate Concentration Reductions in a Riparian Buffer Enrolled in the NC Conservation Reserve Enhancement Program

Riparian buffers have been used for many years as a best management practice to decrease the effects of nonpoint pollution from watersheds. The NC Conservation Reserve Enhancement Program (NC CREP) has established buffers to treat groundwater nitrate‐nitrogen (NO₃^?‐N) from agricultural sources in multiple river basins. A maturing 46 m wide riparian buffer enrolled in NC CREP was studied to determine its effectiveness in reducing groundwater NO₃^?‐N concentrations from a cattle pasture fertilized with poultry litter. Three monitoring blocks that included groundwater quality wells, water table wells, and soil redox probes, were established in the buffer. NO₃^?‐N concentrations decreased significantly across the buffer in all of the monitoring blocks with mean reductions of 76‐92%. Many biological processes, including denitrification and plant uptake, may have been responsible for the observed NO₃^?‐N reductions but could not be differentiated in this study. However, mean reductions in Cl^? concentrations ranged from 48‐65% through the blocks, which indicated that dilution was an important factor in observed NO₃^?‐N reductions. These findings should be carefully considered for future buffer enrollments when assigning nitrogen removal credits.     

Estimation of Nonpoint Source Nitrate Concentrations in Indiana Rivers Based on Agricultural Drainage in the Watershed

Subsurface tile‐drained agricultural fields are known to be important contributors to nitrate in surface water in the Midwest, but the effect of these fields on nitrate at the watershed scale is difficult to quantify. Data for 25 watersheds monitored by the Indiana Department of Environmental Management and located near a U.S. Geological Survey stream gage were used to investigate the relationship between flow‐weighted mean concentration (FWMC) of nitrate‐N and the subsurface tile‐drained area (DA) of the watershed. The tile DA was estimated from soil drainage class, land use, and slope. Nitrate loads from point sources were estimated based on reported flows of major permitted facilities with mean nitrate‐N concentrations from published sources. Linear regression models exhibited a statistically significant relationship between annual/monthly nonpoint source (NPS) nitrate‐N and DA percentage. The annual model explained 71% of the variation in FWMC of nitrate‐N. The annual and monthly models were tested in 10 additional watersheds, most with absolute errors within 1 mg/l in the predicted FWMC. These models can be used to estimate NPS nitrate for unmonitored watersheds in similar areas, especially for drained agricultural areas where model performance was strongest, and to predict the nitrate reduction when various tile drainage management techniques are employed.     

Spatial and Temporal Evaluation of Hydrological Response to Climate and Land Use Change in Three South Dakota Watersheds

This study analyzed changes in hydrology between two recent decades (1980s and 2010s) with the Soil and Water Assessment Tool (SWAT) in three representative watersheds in South Dakota: Bad River, Skunk Creek, and Upper Big Sioux River watersheds. Two SWAT models were created over two discrete time periods (1981‐1990 and 2005‐2014) for each watershed. National Land Cover Datasets 1992 and 2011 were, respectively, ingested into 1981‐1990 and 2005‐2014 models, along with corresponding weather data, to enable comparison of annual and seasonal runoff, soil water content, evapotranspiration (ET), water yield, and percolation between these two decades. Simulation results based on the calibrated models showed that surface runoff, soil water content, water yield, and percolation increased in all three watersheds. Elevated ET was also apparent, except in Skunk Creek watershed. Differences in annual water balance components appeared to follow changes in land use more closely than variation in precipitation amounts, although seasonal variation in precipitation was reflected in seasonal surface runoff. Subbasin‐scale spatial analyses revealed noticeable increases in water balance components mostly in downstream parts of Bad River and Skunk Creek watersheds, and the western part of Upper Big Sioux River watershed. Results presented in this study provide some insight into recent changes in hydrological processes in South Dakota 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.     

Hydrologic Calibration and Validation of SWAT in a Snow‐Dominated Rocky Mountain Watershed,Montana, U.S.A.1

Abstract: The Soil and Water Assessment Tool (SWAT) has been applied successfully in temperate environments but little is known about its performance in the snow‐dominated, forested, mountainous watersheds that provide much of the water supply in western North America. To address this knowledge gap, we configured SWAT to simulate the streamflow of Tenderfoot Creek (TCSWAT). Located in central Montana, TCSWAT represents a high‐elevation watershed with ～85% coniferous forest cover where more than 70% of the annual precipitation falls as snow, and runoff comes primarily from spring snowmelt. Model calibration using four years of measured daily streamflow, temperature, and precipitation data resulted in a relative error (RE) of 2% for annual water yield estimates, and mean paired deviations (Dv) of 36 and 31% and Nash‐Sutcliffe (NS) efficiencies of 0.90 and 0.86 for monthly and daily streamflow, respectively. Model validation was conducted using an additional four years of data and the performance was similar to the calibration period, with RE of 4% for annual water yields, Dv of 43% and 32%, and NS efficiencies of 0.90 and 0.76 for monthly and daily streamflow, respectively. An objective, regression‐based model invalidation procedure also indicated that the model was validated for the overall simulation period. Seasonally, SWAT performed well during the spring and early summer snowmelt runoff period, but was a poor predictor of late summer and winter base flow. The calibrated model was most sensitive to snowmelt parameters, followed in decreasing order of influence by the surface runoff lag, ground water, soil, and SCS Curve Number parameter sets. Model sensitivity to the surface runoff lag parameter reflected the influence of frozen soils on runoff processes. Results indicated that SWAT can provide reasonable predictions of annual, monthly, and daily streamflow from forested montane watersheds, but further model refinements could improve representation of snowmelt runoff processes and performance during the base flow period in this environment.     

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.     

NITROGEN AND ORGANIC MATTER LOSSES IN NO‐TILL CORN CROPPING SYSTEMS1

ABSTRACT: Intensive cropping systems based on mechanical movement of soil have induced land degradation in most agricultural areas due to soil erosion and soil fertility losses. Thus, farmers have been increasing fertilization rates to maintain an economically competitive crop yield. This practice has resulted in water quality degradation and lake eutrophication in many agricultural watersheds. Research was conducted in the Patzcuaro watershed in central Mexico to develop appropriate technology that prevents nonpoint source pollution from fertilizers. Organic matter (OM) and nitrogen (N) losses in runoff and nitrate (NO₃‐N) percolation in Andisols with corn under conventional till (CT) and no‐till (NT) treatments using variable percentages of crop residue as soil cover were investigated for steep‐slope agriculture. USLE type runoff plots were used to collect water runoff, while suction tubes with porous caps at 30, 60, and 90 cm depth were used to sample soil water solutes for NO₃‐N analyses. Results indicated a significant reduction of N and OM losses in runoff as residue cover increased in the NT treatments. Inorganic N in runoff was 25 kg/ha for NT without residue cover (NT‐0) and 6 kg/ha for the NT with 100 percent residue cover (NT‐100). Organic matter losses in runoff were 157 and 24 kg/ha for the NT‐0 and NT‐100 treatments, respectively. Nitrate‐N percolation was evident in CT and NT with 100 percent residue cover (NT‐100). However, NT‐100 had higher NO₃‐N concentration at the root zone, suggesting the possibility of reducing fertilization rates with the use of NT treatments.     

Integrating Temporal Inequality into Conservation Planning to Improve Practice Design and Efficacy

In contrast to spatial inequality, there are currently no methods for leveraging information on temporal inequality to improve conservation efficacy. The objective of this study was to use Lorenz curves to quantify temporal inequality in surface runoff and tile drainage, identify controls on nutrient loading in these flowpaths, and develop design flows for structural conservation practices. Surface runoff (n = 94 site‐years) and tile drainage (n = 90 site‐years) were monitored on 40 fields in Ohio. Results showed, on average, 80% of nitrate‐nitrogen, soluble reactive phosphorus (P), and total P loads occurred between 7 and 12 days per year in surface runoff and between 32 and 58 days per year in tile drainage. Similar temporal inequality between discharge and load provided evidence that loading was transport‐limited and highlighted the critical role hydrologic connectivity plays in nutrient delivery from tile‐drained fields. Design flow criterion for sizing structural practices based on load reduction goals was developed by combining Lorenz curves and flow duration curves. Comparing temporal inequality between fields and the Maumee River, the largest tributary to the western Lake Erie Basin, revealed challenges associated with achieving watershed load reduction goals with field‐scale conservation. In‐field (i.e., improved nutrient and water management), edge‐of‐field (i.e., structural practices), and instream practices will all be required to meet nutrient reduction goals from tile‐drained watersheds.     

IMPACT OF A TURFGRASS SYSTEM ON NUTRIENT LOADINGS TO SURFACE WATER1

ABSTRACT: Turfgrass systems are one of the most intensively managed land uses in the United States. Establishment and maintenance of high quality turfgrass usually implies substantial inputs of water, nutrients, and pesticides. The focus of this work was to quantify the concentration and loading of a typically maintained municipal turfgrass environment on surface water. Water quantity and quality data were collected from a golf course in Austin, Texas, and analyzed for a 13‐month period from March 20, 1998, to April 30, 1999. Twenty‐two precipitation events totaling 722 mm, produced an estimated 98 mm of runoff. Nutrient analysis of surface runoff exiting the course exhibited a statistically significant (p < 0.05) increase in median nitrate plus nitrite nitrogen (NO₃+NO₂‐N) concentration compared to runoff entering the course, a statistically significant decrease in ammonia nitrogen (NH₄‐N), but no difference in orthophosphate (PO₄‐P). During the 13‐month period, storm runoff contributed an estimated 2.3 kg/ha of NO₃+NO₂‐N and 0.33 kg/ha of PO₄‐P to the stream. Storm flow accounted for the attenuation of 0.12 kg/ha of NH₄‐N. Baseflow nutrient analysis showed a statistically significant increase in median NO₃+NO₂‐N, a significant reduction in NH₄‐N, and no change in PO₄‐P. Estimated NO₃+NO₂‐N mass in the baseflow was calculated as 4.7 kg/ha. PO₄‐P losses were estimated at 0.06 kg/ha, while 0.8 kg/ha of NH₄‐N were attenuated in baseflow over the study period. Even though nutrient concentrations exiting the system rarely exceeded nutrient screening levels, this turfgrass environment did contribute increased NO₃+NO₂‐N and PO₄‐P loads to the stream. This emphasizes the need for parallel studies where management intensity, soil, and climate differ from this study and for golf course managers to utilize an integrated management program to protect water quality while maintaining healthy turfgrass systems.     

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.     

Modeling Water Quantity and Sulfate Concentrations in the Devils Lake Watershed Using Coupled SWAT and CE‐QUAL‐W2

Devils Lake is an endorheic lake in the Red River of the North basin in northeastern North Dakota. During the last two decades, the lake water level has risen by nearly 10 m, causing floods that have cost more than 1 billion USD in mitigation measures. Another increase of approximately 1.5 m in the lake water level would cause spillage into the Sheyenne River. To alleviate this potentially catastrophic spillage, two artificial outlets were constructed. However, the artificial drainage of water into the Sheyenne River raises water quality concerns because the Devils Lake water contains significantly higher concentrations of dissolved solids, particularly sulfate. In this study, the Soil and Water Assessment Tool (SWAT) was coupled with the CE‐QUAL‐W2 model to simulate both water balance and sulfate concentrations in the lake. The SWAT model performed well in simulating daily flow in tributaries with E_NS > 0.5 and |PBIAS| < 25%, and reproduced the lake water level with a root mean square error of 0.35 m for the study period from 1995 to 2014. The water temperature and sulfate concentrations simulated by CE‐QUAL‐W2 for the lake are in general agreement with the field observations. The model results show that the operation of the two outlets since August 2005 has lowered the lake level by 0.70 m. Furthermore, the models show pumping water from the two outlets raises sulfate concentrations in the Sheyenne River from ~100 to >500 mg/L. 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.     

SWAT‐LUT: A Desktop Graphical User Interface for Updating Land Use in SWAT

Long‐term simulations of agricultural watersheds have often been done assuming constant land use over time, but this is not a realistic assumption for many agricultural regions. This paper presents the soil and water assessment tool (SWAT)‐Landuse Update Tool (LUT), a standalone, user‐friendly desktop‐based tool for updating land use in the SWAT model that allows users to process multi‐year land use data. SWAT‐LUT is compatible with several SWAT model interfaces, provides users with several options to easily prepare and incorporate land use changes (LUCs) over a simulation period, and allows users to incorporate past or emerging land use categories. Incorporation of LUCs is expected to provide realistic model parameterization and scenario simulations. SWAT‐LUT is a public domain interface written in Python programming language. Two applications at the Fort Cobb Reservoir Experimental Watershed located in Oklahoma and pertinent results are provided to demonstrate its use. Incorporating LUCs related to implementation of recommended conservation practices over the years reduced discharge, evapotranspiration, sediment, total nitrogen, and total phosphorus loads by 59%, 9%, 68%, 53%, and 88%, respectively. The user’s manual is included in this article as Supporting Information. The SWAT‐LUT executable file and an example SWAT project with three land use rasters and the user’s manual are available at the United States Department of Agriculture‐Agricultural Research Service Grazinglands Research Laboratory website under Software. Editor’s note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.     

Calibration and Verification of SWMM for Low Impact Development

The Storm Water Management Model was used to simulate runoff and nutrient export from a low impact development (LID) watershed and a watershed using traditional runoff controls. Predictions were compared to observed values. Uncalibrated simulations underpredicted weekly runoff volume and average peak flow rates from the multiple subcatchment LID watershed by over 80%; the single subcatchment traditional watershed had better predictions. Saturated hydraulic conductivity, Manning's n for swales, and initial soil moisture deficit were sensitive parameters. After calibration, prediction of total weekly runoff volume for the LID and traditional watersheds improved to within 12 and 5% of observed values, respectively. For the validation period, predicted total weekly runoff volumes for the LID and traditional watersheds were within 6 and 2% of observed values, respectively. Water quality simulation was less successful, Nash–Sutcliffe coefficients >0.5 for both calibration and validation periods were only achieved for prediction of total nitrogen export from the LID watershed. Simulation of a 100‐year, 24‐h storm resulted in a runoff coefficient of 0.46 for the LID watershed and 0.59 for the traditional watershed. Results suggest either calibration is needed to improve predictions for LID watersheds or expanded look‐up tables for Green–Ampt infiltration parameter values that account for compaction of urban soil and antecedent conditions are needed.