ABSTRACT Urban development normally occurs at the urban–rural interface, often in a spider-like appearance known as ‘urban sprawl’. Mixed urban–rural watersheds are likely to experience hydrologic alterations such as increased peak flow and pollutant loads, further intensified by climate change. The implementation of low-impact development (LID) controls and best management practices (BMPs) offers a promising approach to improve watershed resilience. However, determining the optimal type, size, and placement of these measures remains challenging due to multiple objectives and constraints. We present a multi-objective simulation–optimization tool that integrates a coupled modeling framework with an evolutionary algorithm to optimize the performance of LID and BMP strategies. The simulation framework sequentially couples the Storm Water Management Model (SWMM) and the Soil and Water Assessment Tool Plus (SWAT+), and links to a cost estimation module to identify cost-effective stormwater control measures (SCMs) that balance peak flow reduction and runoff volume reduction. This tool was applied to the Stroubles Creek watershed in Montgomery County, Virginia, to optimize SCMs across a mixed urban–rural landscape. The tool generated a set of Pareto-optimal strategies that illustrate trade-offs among peak flow reduction, volume reduction, and implementation cost, helping stakeholders make informed decisions based on regulations, budgets, and practical constraints.
Ahmadi et al. (Mon,) studied this question.
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