Optimizing Structural Best Management Practices Using SWAT and Genetic Algorithm to Improve Water Quality Goals

Abstract

A genetic algorithm (GA), an evolutionary optimization technique, is coupled with a semi-distributed hydrologic model, Soil and Water Assessment Tool (SWAT) to find an optimum combination of structural Best Management Practices (BMPs) that meets the treatment goals at a watershed scale. The structural BMPs considered in the study are detention ponds, parallel terraces, filter strips, grassed waterways, and grade stabilization structures which are all applicable in agricultural watersheds. The decision variables in the optimization model are the type, size, and location of BMPs which minimize the construction cost and simultaneously reduce sediment and nutrients to target levels at the watershed outlet. The model is demonstrated on the Silver Creek, a sub-watershed of the Lower Kaskaskia watershed in Illinois. The model is used to compare three different sediment and nutrient reduction cases (i.e. 20%, 40%, and, 60%) at the watershed outlet.