USE OF MATHEMATICAL OPTIMIZATION TO SELECT COST-EFFECTIVE BEST MANAGEMENT PRACTICES

This paper presents a mathematical optimization model of stormwater management strategies to meet a water quality requirement at the least cost. Increasingly, national, state and local governments are passing laws requiring that urban stormwater runoff be managed to meet certain water quality requirements. A wide range of “best management practices“ (BMPs) have been developed to try to mitigate the negative impacts of runoff and meet regulatory requirements. These practices have widely varying costs and effectiveness. Given the amount of money that is spent on stormwater quality management, it is important that the selected stormwater management practices be costeffective, while meeting regulatory requirements and water quality goals.The selection of cost-effective stormwater management practices was formulated as a mathematical optimization problem. Linear programming is used to minimize the total cost of implementing a stormwater management program. The primary constraint is that a user-defined percentage of the annual suspended sediment load must be removed from watershed runoff. The model selects an optimal management program from three available best management practices: wet detention ponds, street sweeping, and settling/vortex devices. Various cost functions are developed to describe the cost of each BMP.This optimization model would be useful as a planning tool for communities that must meet stormwater quality regulations. The optimization technique used, linear programming, is widely available in software that is accessible to the average user. This type of model can provide information on which stormwater management strategies are likely to be cost-effective in reducing nonpoint source pollution, and which are not. Sensitivity analyses provide information on which variables have the largest effect on the optimal solution, and should therefore be focused on during the data gathering process. The primary purpose of this paper is not to recommend certain BMP programs, but to present an example of how proposed BMPs can be evaluated and compared. Hopefully this paper will encourage municipalities, consultants and government agencies to pursue ways to systematically evaluate and select stormwater management programs, rather than using a trial-and-error approach.