Abstract:This paper describes the effect of DEM data resolution on predictions from the SWAT model. Measured hydrologic, meteorological, watershed characteristics and water quality data from Moores Creek watershed (near Lincoln, AR, USA) were used in the simulation. The effect of input data resolution was evaluated by running seven scenarios at increasing DEM grid sizes (30 ð 30 m, 100 ð 100 m, 150 ð 150 m, 200 ð 200 m, 300 ð 300 m, 500 ð 500 m, 1000 ð 1000 m). The model was calibrated on an annual basis for flow, NO 3 -N and total P using 30 ð 30 m DEM data. The predicted output at the calibrated scale was used to evaluate output accuracy for the remaining input resolutions. Results of this study showed that DEM resolution affects the watershed delineation, stream network and sub-basin classification in the SWAT model. A decrease in DEM resolution resulted in decreased stream flow and NO 3 -N load predictions. However, model predicted total P did not always decrease with DEM resolution. Results of this study indicate that the choice of input DEM resolution depends on the watershed response of interest. Minimum DEM data resolution ranged from 100 to 200 m to achieve less than 10% error in SWAT output for flow, NO 3 -N and TP predictions.

Resolution of the input GIS data used to parameterize distributed‐parameter hydrologic/water quality models may affect uncertainty in model outputs and impact the subsequent application of model results in watershed management. In this study we evaluated the impact of varying spatial resolutions of DEM, land use, and soil data (30 × 30 m, 100 × 100 m, 150 × 150 m, 200 × 200 m, 300 × 300 m, 500 × 500 m, and 1,000 × 1,000 m) on the uncertainty of SWAT predicted flow, sediment, NO3‐N, and TP transport. Inputs included measured hydrologic, meteorological, and watershed characteristics as well as water quality data from the Moores Creek watershed in Washington County, Arkansas. The SWAT model output was most affected by input DEM data resolution. A coarser DEM data resolution resulted in decreased representation of watershed area and slope and increased slope length. Distribution of pasture, forest, and urban areas within the watershed was significantly affected at coarser resolution of land use and resulted in significant uncertainty in predicted sediment, NO3‐N, and TP output. Soils data resolution had no significant effect on flow and NO3‐N predictions; however, sediment was overpredicted by 26 percent, and TP was underpredicted by 26 percent at 1,000 m resolution. This may be due to change in relative distribution of various hydrologic soils groups (HSGs) in the watershed. Minimum resolution for input GIS data to achieve less than 10 percent model output error depended upon the output variable of interest. For flow, sediment, NO3‐N, and TP predictions, minimum DEM data resolution should range from 30 to 300 m, whereas minimum land use and soils data resolution should range from 300 to 500 m.

Vegetative filter strips (VFS) can reduce runoff losses of pollutants such as nitrogen (N) and phosphorus (P) from land areas treated with fertilizers. While VFS effectiveness is considered to depend on lengths of pollutant source and VFS areas, there is little experimental evidence of this dependence, particularly when the pollutant source is manuretreated pasture. This study assessed the effects of pollutant source area (fescue pasture treated with poultry litter) length

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