Abstract

The results of distributed watershed models could be sensitive to spatial and temporal scales at which inputs and model parameters are aggregated. This paper reports findings of a detailed sensitivity analysis conducted on the U.S. Department of Agriculture’s distributed watershed simulation model, known as the Soil and Water Assessment Tool (SWAT). The Big Creek Watershed, located in southern Illinois, is used for the study. The model is calibrated to improve accuracy of its streamflow and sediment concentration predictions using observed data at two locations in the study watershed. Streamflow and sediment concentrations that are simulated by the calibrated model at various spatial scales of discritization are extracted and compared, and inputs and model parameters responsible for sensitivity of model responses are identified. Several indices that could be used as indicators of model behavior are also derived. In addition, feasibility analysis of SWAT is conducted to see if the watershed simulation model could be used as a component in future decision support models developed to assist in identifying integrative watershed management practices that control agricultural nonpoint source pollutions from watersheds. The major findings of the study are: (1) accuracy of the raw model output (streamflow and sediment yield) is very poor for all delineations indicating the need for careful model calibration; (2) streamflow is relatively insensitive to spatial scale; and (3) sediment generated and sediment that leaves the watershed decreases as spatial scale gets coarser. Unlike the findings of previous studies, sediment yield significantly varies, even when properties of the outlet channel remain practically the same. (4) SWAT’s estimate of sediment yield is sensitive to human activities conducted in subbasins of the watershed, thus indicating the capability of SWAT to evaluate consequences of alternative watershed management practices.

Disciplines

Civil and Environmental Engineering

 

URL: http://digitalcommons.calpoly.edu/cenv_fac/260