An Assessment of the Effects of Cell Size on AGNPS Modeling of Watershed Runoff

Shuo-sheng Wu, Lynn E. Usery, Michael P. Finn, David D. Bosch
2008 Cartography and Geographic Information Science  
Introduction T he Agricultural NonPoint Source (AGNPS) pollution model was developed by the U.S. Department of Agriculture in response to the need to quantitatively examine the influence of non-point source pollution on surface water and groundwater quality in agricultural watersheds. The model is designed to estimate sediment and nutrient yields from agricultural activities, and it is used most appropriately to compare the impacts of alternative land management strategies on sur-ABSTRACT: This
more » ... sur-ABSTRACT: This study investigates the changes in simulated watershed runoff from the Agricultural NonPoint Source (AGNPS) pollution model as a function of model input cell size resolution for eight different cell sizes (30 m, 60 m, 120 m, 210 m, 240 m, 480 m, 960 m, and 1920 m) for the Little River Watershed (Georgia, USA). Overland cell runoff (area-weighted cell runoff), total runoff volume, clustering statistics, and hot spot patterns were examined for the different cell sizes and trends identified. Total runoff volumes decreased with increasing cell size. Using data sets of 210-m cell size or smaller in conjunction with a representative watershed boundary allows one to model the runoff volumes within 0.2 percent accuracy. The runoff clustering statistics decrease with increasing cell size; a cell size of 960 m or smaller is necessary to indicate significant high-runoff clustering. Runoff hot spot areas have a decreasing trend with increasing cell size; a cell size of 240 m or smaller is required to detect important hot spots. Conclusions regarding cell size effects on runoff estimation cannot be applied to local watershed areas due to the inconsistent changes of runoff volume with cell size; but, optimal cells sizes for clustering and hot spot analyses are applicable to local watershed areas due to the consistent trends.
doi:10.1559/152304008786140542 fatcat:44wly5jx6fc6rln53fjpeibpne