Identifying Cost-Effective Low-Impact Development (LID) under Climate Change: A Multi-Objective Optimization Approach

Abstract

Low-impact development (LID) is increasingly used to reduce stormwater’s quality and quantity impacts associated with climate change and increased urbanization. However, due to the significant variations in their efficiencies and site-specific requirements, an optimal combination of different LIDs is required to benefit from their full potential. In this article, the multi-objective genetic algorithm (MOGA) was coupled with the stormwater management model (SWMM) to identify both hydrological and cost-effective LIDs combinations within a large urban watershed. MOGA iteratively optimizes the types, sizes, and locations of different LIDs using a combined cost- and runoff-related objective function under both past and future stormwater conditions. The infiltration trench (IT), rain barrel (RB), rain gardens (RG), bioretention (BR), and permeable pavement were used as potential LIDs since they are common in our study area—the city of Renton, WA, USA. The city is currently adapting different LIDs to mitigate the recent increase in stormwater system failures and flooding. The results from our study showed that the optimum combination of LIDs in the city could reduce the peak flow and total runoff volume by up to 62.25% and 80% for past storms and by13% and 29% for future storms, respectively. The findings and methodologies presented in this study are expected to contribute to the ongoing efforts to improve the performance of large-scale implementations of LIDs.