Impacts of input parameter spatial aggregation on an agricultural nonpoint source pollution model

Abstract

The accuracy of agricultural nonpoint source pollution models depends in part on how well model input parameters describe the relevant characteristics of the watershed. The spatial extent of input parameter aggregation has previously been shown to have a substantial impact on model output. This study investigates this problem using the Soil and Water Assessment Tool (SWAT), a distributed-parameter agricultural nonpoint source pollution model. The primary question addressed here is: how does the size or number of subwatersheds used to partition the watershed affect model output, and what are the processes responsible for model behavior? SWAT was run on the Pheasant Branch watershed in Dane County, WI, using eight watershed delineations, each with a different number of subwatersheds. Model runs were conducted for the period 1990–1996. Streamflow and outlet sediment predictions were not seriously affected by changes in subwatershed size. The lack of change in outlet sediment is due to the transport-limited nature of the Pheasant Branch watershed and the stable transport capacity of the lower part of the channel network. This research identifies the importance of channel parameters in determining the behavior of SWAT's outlet sediment predictions. Sediment generation estimates do change substantially, dropping by 44% between the coarsest and the finest watershed delineations. This change is primarily due to the sensitivity of the runoff term in the Modified Universal Soil Loss Equation to the area of hydrologic response units (HRUs). This sensitivity likely occurs because SWAT was implemented in this study with a very detailed set of HRUs. In order to provide some insight on the scaling behavior of the model two indexes were derived using the mathematics of the model. The indexes predicted SWAT scaling behavior from the data inputs without a need for running the model. Such indexes could be useful for model users by providing a direct way to evaluate alternative models directly within a geographic information systems framework.