GIS and SWMM‐Integrated Multi‐Indicator Fuzzy Assessment for Urban Flood Risk in Chengdu

ABSTRACT Effective assessment of urban flood risk is essential for decision‐making under mixed and uncertain information conditions. This study proposes a multi‐indicator hesitant fuzzy assessment framework integrating hazard, exposure, and vulnerability. The framework couples the storm water management model (SWMM) with geographic information system techniques to simulate rainfall runoff processes and characterize spatial variations in flood risk. Quantitative indicators are derived from hydrological simulation and GIS‐based spatial analysis, and an urban flood risk distribution map is generated for the main urban area of Chengdu. The results indicate that high and very high flood risk zones account for 10.18% and 9.43% of the study area, respectively, and are mainly concentrated in districts with high imperviousness, dense populations, and complex transportation networks. Weight analysis shows that vulnerability is the dominant contributor to flood risk, with a weight of 0.412, followed by hazard at 0.362 and exposure at 0.225, highlighting the importance of reducing urban vulnerability and enhancing drainage capacity. The proposed framework provides a practical and transferable approach for urban flood risk assessment and offers scientific support for emergency response planning and disaster prevention strategies in cities with similar characteristics.