Effects of Spatial Distribution of Stormwater Management Infrastructure on Pollutant Removal Efficiencies at the Watershed Scale: A Geographic Information Systems Approach

Abstract

Although urban areas comprise only 7% of the Chesapeake Bay Watershed, stormwater runoff from these areas represents a serious impairment to local streams and downstream ecosystems. Urban stormwater best management practices (SWBMPs) may be designed to retain, detain, or infiltrate stormwater runoff, and are sometimes also designed to treat stormwater runoff by removing or reducing nutrients and sediment. Using SWBMPs to protect streams in the Chesapeake Bay Watershed is of both ecological and economic importance. Conventional management of urban stormwater aims to convey runoff away from a developed area as quickly as possible. More recently, SWBMPs have been used in a distributed or decentralized manner to treat stormwater close to its source. This is sometimes referred to as a low impact development approach to stormwater management. The objective of this research is to compare annual pollutant removal efficiencies of two watersheds in Clarksburg, MD with differing spatial patterns of SWBMP implementation (centralized and distributed), and determine if spatially distributed SWBMPs offer the best water quality benefit. Annual pollutant removal efficiency (APRE) is the measured reduction of pollutants, typically in percent, from the inflow to the outflow of a SWBMP. The Monte Carlo method is applied to the ranges of APRE for each SWBMP. By utilizing the GIS data generated for DAs to each SWBMP, the information given for APRE are integrated to calculate a water quality benefit for the two watersheds. Because each watershed is similar in land cover characteristics, this research emphasizes the effectiveness of the spatial configuration of the SWBMPs. This research shows that spatially distributed SWBMPs remove annually between 0.95-1.00 lbs. more nitrogen, 0.048-0.049 lbs. more phosphorus, and 0.87-0.89 lbs. more sediment on average per acre as compared to centralized SWBMPs. In conclusion, this research utilizes a geographic information system to aid local and state governments to achieve federally mandated water quality regulations. Combined with cost and land use/land cover data, these new APRE data could optimize infrastructure design protocol for new urban development.