Multi-objective optimization of distributed green infrastructure for effective stormwater management in space-constrained highly urbanized areas

Abstract

Green infrastructure (GI) is essential for stormwater management, but its implementation in highly urbanized areas is challenging due to the limited space available for GI retrofitting. There is a lack of comprehensive evaluations that assess the spatial adaptability, functionality, and cost-benefit of various GI measures, and optimize their placement to achieve the maximum reduction rate of total runoff (RTR) and reduction rate of pollution load (RPL) while minimizing life cycle cost (LCC) in space-constrained highly urbanized areas (SCHUA). To address this issue, a novel concept of infiltration, retention, and storage integrated GI (IRS-GI) for SCHUA was proposed, and a framework coupling the Storm Water Management Model (SWMM) with multi-objective optimization algorithms was developed to determine the optimal IRS-GI layout, focusing on the objectives of RTR, RPL, and LCC. The impacts of different GI type, size, and location, rainfall return periods, and algorithms (NSGA-II and NSGA-III) were then examined. The results showed that IRS-GI could achieve satisfactory RTR and RPL results while single-type GI may struggle to meet requirements. Optimization outcomes were significantly influenced by rainfall return periods, with cost-benefit decreasing as return periods increasing. Besides, the optimization results of NSGA-II and NSGA-III showed differences, and the comprehensive Pareto frontier obtained by reapplying non-dominated sorting could achieve more comprehensive results for determining the optimal IRS-GI configuration. Under the urban drainage design standard, the optimal IRS-GI layout, covering 32.97 % of the green spaces, 38.57 % of the rooftop, and 60.98 % of the ordinary roads and squares, respectively, could achieve a RTR of 50.09 %, RPL of 57.00 %, and LCC of 0.79 × 108 CNY/yr. Additionally, the optimal configuration suggested that a higher proportion of GI downstream of drainage system may contribute to better cost-benefit, emphasizing the need for location-specific GI solutions. This research offers valuable insights for optimizing GI in SCHUA, advancing sustainable urban stormwater management.