The implementation of Total Maximum Daily Load (TMDL) to control urban runoff presents major structural and managerial challenges for cities. We developed a decision support system (DSS) for TMDL compliance at the city level to solve for a phased, least-cost strategy toward meeting four TMDLs using stormwater filtration. Based on a case-study city, we modeled wet weather flows and associated discharge of Total Suspended Sediment (TSS), cadmium, copper, and zinc to receiving waters by coupling U.S. EPA's Storm Water Management Model (SWMM v. 5.0) with the geographic dataset of the urban drainage network. We linked a mixed integer linear programming algorithm to the watershed model for deriving cost-effective selection and placement of curb inlet filters to meet mass- and concentration-based TMDL requirements. The least cost solution for meeting the city's TMDL waste load allocations for TSS (73.9% reduction), Cd (50.6% reduction), Cu (30.0% reduction), and Zn (55.7% reduction) would require 1071 filter inserts at a cost of $1.7 million. In contrast, random placement of 1071 filters or uniform placement of 1266 filters is effective only for TSS and would cost $4.0 million and $4.8 million, respectively. Our results demonstrate the increases in cost-effectiveness of using an optimization-based DSS for urban watershed management.
ASJC Scopus subject areas
- Environmental Chemistry