Combining GIS, BMP Performance, and Strategic Planning to Support Water Quality Implementation Planning

Abstract

Numerous efforts to improve storm water quality on a watershed-wide basis have lacked a reproducible, transparent, methodical approach to optimize the selection and implementation of structural Best Management Practices (BMPs) to meet receiving water quality goals. For urban stormwater retrofit projects, structural BMPs are primarily selected in an opportunistic, site-specific fashion, focusing on one or a few pollutants, stakeholder inputs, or local funding availability. As geographic information systems (GIS) technologies improve, computing power increases, and pollutant loading and treatment efficiency datasets become more robust there is an opportunity to improve watershed-based implementation planning efforts. The authors have developed methods to prioritize water quality improvement needs and identify structural BMP opportunities on a watershed scale to maximize the return on investment for improved water quality. Opportunity evaluation considers property ownership and the potential for retrofitting to achieve multiple benefits, such as water quality, aesthetics, recreation, and habitat. It is recognized that different types of land parcels typically have different types of opportunities and constraints. BMP opportunities can be regional or distributed in nature depending on the land use, size, and location of the public parcel, among other things. By utilizing GIS-based parcel and land use information in the context of water quality need, potential opportunities, and constraints, as well as BMP unit processes and performance data, watershed-wide benefits of BMP implementation can be assessed. An analysis tool has been developed in the ArcGIS™ environment that automates many of these spatial prioritization and identification processes, while allowing for stakeholders and decisions-makers to provide meaningful input that supports BMP implementation decisions. Once candidate BMPs have been identified for a high priority area, the tool can estimate the potential pollutant load reductions and planning level costs associated with site-specific implementation. Example studies are provided to illustrate the concepts and GIS methods employed.