Urban Flood Risk analysis using the SWAGU-coupled model and a cloud-enhanced fuzzy comprehensive evaluation method

Abstract

This study introduces the SWAGU model, which overcomes limitations of existing approaches by combining SWMM's robust pipe network modeling capabilities with ANUGA's advanced unstructured mesh-based surface flow simulation, enabling more accurate prediction of flood dynamics in complex urban environments. The model's outputs are integrated into an enhanced cloud model framework. This framework improves upon traditional fuzzy evaluation methods by introducing cloud model theory to better handle uncertainty in both expert judgments and membership functions, while also incorporating a novel approach for processing extreme values. A comparative analysis of multi-indicator and single-indicator approaches reveals that the multi-indicator method, offers a more comprehensive and objective evaluation of flood risk. The findings demonstrate a reduction of 50 %–60 % in low-risk areas compared to the single-indicator approach. This study underscores the superiority of integrating advanced hydrodynamic modeling with cloud-enhanced multi-criteria evaluation in providing more precise and robust flood risk management frameworks.