Examining the Possibilities: Generating Alternative Watershed-Scale BMP Designs with Evolutionary Algorithms

Recent studies in water resources planning and management show a gradual shift in the state of the art from numerous on-site structural stormwater Best Management Practice (BMP) designs to watershed-scale BMP design approaches that meet both target water quantity (peak flow) and quality (sediment reduction) criteria. Such regionally-strategic approaches are not only cost-effective but emphasize comprehensive, holistic watershed-scale management, an idea strongly promoted by the U.S. Environmental Protection Agency (US EPA) since the early 1990s. Implementing a watershed-scale design can prove difficult when decision-makers have differing and sometimes conflicting objectives. We present a methodology that integrates the semi-distributed watershed model Soil and Water Assessment Tool (SWAT) with an evolutionary algorithm, Species Conserving Genetic Algorithm (SCGA). In addition to identifying an optimal watershed-scale BMP design (e.g., type, size, location), SCGA simultaneously produces several near-optimal design alternatives using a user-specified distance metric. We demonstrate this decision-oriented framework on a watershed in southern Illinois. Results of this application yield several high-quality alternative designs appropriate for solving integrated watershed management problems.