[A-HW23] Hydrology & Water Environment

[AHW23-07] Multi-objective optimization for green infrastructure planning with cost-effectiveness analysis based on TOPSIS

*Kexin Liu¹, Tsuyoshi Kinouchi¹ (1.Tokyo institute of technology)

Keywords:Urban hydrology, green infrastructure, urban flood, water quality

The dramatic change in climate and urbanization increase the risk of urban flood and water pollution, resulting in massive disruptions in existing ecosystems, societies, and economies. Green infrastructure (GI) is a natural-based rainwater management method that can provide many benefits for future urban planning. However, there is a lack of unified criteria for the integration of multi-objective benefits of GI, which impedes the application of GI to reliable engineering designs. Moreover, current research mainly focuses on the effectiveness of GI in flood mitigation. Other intangible benefits, such as water quality improvements and cost-effectiveness analyses, received little attention in the literature. Therefore, this research aims at the multi-objective optimization of green infrastructure planning with a cost-effectiveness analysis. PCSWMM was used to simulate and validate flooding and pollutant loads from actual storm events, in our case study area, Phnom Penh city, with an average NSE of 0.8. Based on the calibrated model, we analyzed and selected the type, location, and scale of GI infrastructures using SUSTAIN, which is a decision support system that selects GI strategies based on cost and effectiveness at various watershed scales. In this study, we considered three dimensions: hydrological (reduction rate of flood volume and peak flood volume), environmental (reduction rate of COD, SS, and E. coli contamination), and economic (construction cost) impacts for multi-objective analysis. The optimal solution analysis of the GI's design options was performed using TOPSIS algorithm. It would potentially serve as more efficient guidance in the design of GI at an early stage.