A Diagnostic Decision Support System for Selecting Best Management Practices

Title of Document: A DIAGNOSTIC DECISION SUPPORT SYSTEM FOR SELECTING BEST MANAGEMENT PRACTICES IN URBAN/SUBURBAN WATERSHEDS Yan Wang, Doctor of Philosophy, 2015 Directed By: Dr. Hubert J Montas, Fischell Department of Bio-Engineering Dr. Kaye L. Brubaker, Department of Civil and Environmental Engineering Best Management Practices (BMPs) have become the most effective way to mitigate the non-point source pollution (NPS) problems. Much attention has been paid on NPS in rural areas, where agricultural activities increase the nutrients, toxics, and sediments in surface water. Urban and suburban areas are also major contributors of NPS, largely due to stormwater. For watersheds bearing various soil types and land uses, a single type of BMP cannot be the panacea to all stormwater and related water quality problems. There is a need for a series of spatially distributed small-scale BMPs aimed at reducing flow volume and improving urban stormwater quality. This research seeks to develop a Diagnostic Decision Support System (DDSS) for urban BMP selection. The process-based distributed hydrologic model, Soil and Water Assessment Tool (SWAT), was used to simulate the hydrologic processes, estimate water quality variables, and to model the urban BMPs. The DDSS consists of three parts: a Hotspot Identifier, which locates the water quality and quantity hotspots; a Diagnostic Expert System (DES), which identifies the most likely physical reasons for excessive pollutants; and a Prescriptive Expert System (PES), which selects a proper set of spatially distributed BMPs. SWAT was calibrated and validated first to simulate pre-BMP watershed responses. The DDSS was then applied for BMP recommendation. The prescribed BMPs were modeled back into SWAT to quantify their effectiveness. Total Cost for BMP implementation was calculated as a function of BMP coverage area, BMP numbers and types, and residents’ preferences. Protocols for urban BMP modeling were developed based on the BMPs’ mechanism and the hydrologic processes involved. The DDSS was tested in Watts Branch, a small urban watershed in metropolitan Washington D.C., and Wilde Lake, a suburban watershed in Columbia, MD. Comparisons were carried out in terms of hotspots distribution and BMP recommendation between the two study areas. The hotspots identified and BMPs prescribed by the DDSS were also examined under future climate scenarios. The prescribed BMPs and GIS maps will be useful in agency-level decision making and in developing appropriate educational material for residents and the general public. A DIAGNOSTIC DECISION SUPPORT SYSTEM FOR SELECTING BEST MANAGEMENT PRACTICES IN URBAN/SUBURBAN WATERSHEDS