Integrating Social Equity into Multiobjective Optimization of Urban Stormwater Low-Impact Development

Abstract

Recent studies have demonstrated some advantages of using advanced heuristic algorithms to identify near-Pareto-optimal future locations, types, and sizes for stormwater low-impact development and green infrastructure (LID/GI) across a given urban landscape. However, previous optimization studies did not consider social equity as an objective, which poses problems because urban green infrastructure often is distributed inequitably. Increasing access to LID/GI in historically marginalized areas is a prominent environmental justice issue, and increasingly is becoming a primary consideration when prioritizing future locations, types, and sizes of urban LID/GI. This study integrated a novel spatial social equity objective [LID/GI–Social Vulnerability Index (SVI) correlation objective, ρ] into a multiobjective LID/GI optimization model. The LID/GI-SVI correlation is an objective that directs the optimization algorithm to search for LID/GI distributions that maximize the linear correlation between LID/GI implementation and subbasins with higher estimated percentages of historically marginalized people. Our analysis focused on understanding the impacts of the LID/GI-SVI correlation objective on a LID/GI optimization model. This modeling study demonstrates that (1) the LID/GI-SVI correlation objective can be used to direct optimization algorithms to search for LID/GI distributions that can achieve runoff management objectives, increase green LID/GI implementation in more marginalized areas, and explore the potential trade-offs or synergies between hydrologic and equity goals; (2) LID/GI optimization formulations that consider only hydrologic objectives likely will not result in equitable LID/GI distributions; (3) LID/GI distributions that perform well on the LID/GI-SVI correlation may be composed of different types of LID/GI than less-equitable but more hydrologically favorable LID/GI distributions; and (4) for our study area, including spatial equity as an objective resulted in modest reductions in the hydrologic performance of near-Pareto-optimal LID/GI distributions. Low-impact development or stormwater green infrastructure (LID/GI) has been implemented across the globe to address the environmental issues of increased impervious surfaces, aging infrastructure, elevated stormwater runoff due to climate change, and to meet non-point-source discharge permit requirements. Recent research has demonstrated the use of advanced algorithms to help identify optimal locations, sizes, and types of LID/GI that will maximize local runoff reduction benefits. Although runoff control is a primary objective of LID/GI, many cities in the US have been striving to prioritize local areas with high proportions of historically underserved or vulnerable populations for implementation. In tune with this trend, we developed a novel equity objective function that forces a proportional relationship between LID/GI implementation and indicators of social vulnerability. We tested the impact of this new objective within a multiobjective LID/GI optimization algorithm and found minimal trade-offs between runoff and equity objectives in our study area.