Allocating Flood Protection Funds Based on Multi-Dimensional Vulnerability and Equity to Enhance Flood Prevention in Southern Tibet

Establishing an equitable, evidence-based mechanism for allocating flood prevention funding is critical to mitigating the risk of flash floods. However, existing research seldom accounts for the multi-dimensional nature of vulnerability or achieves an appropriate balance between efficiency and equity. To address this gap, we propose the Multi-dimensional Vulnerability-based Flood Disaster Fund Allocation Optimization Model (MD-FAOM), which integrates the coupling effects of exposure, sensitivity, adaptive capacity, and equity into allocation strategies using the NSGA-II algorithm, TOPSIS method, and geographical detectors. The model prioritizes funding for ecologically targeted flood prevention. We apply this framework to southern Tibet to derive optimal fund allocations and quantitatively assess the resulting benefits. Our results show that areas characterized by negative vulnerability account for 25.22% of the study region, mainly concentrated in Lhasa and Shannan. Under equivalent conditions, MD-FAOM delivers benefits across an area of 85,915 km2, achieving an improvement rate of 30.11%. These findings demonstrate that integrating vulnerability science with distributive equity can optimize the allocation of limited resources, thereby enhancing both flood resilience and ecosystem conservation. This approach advances ecohydrological disaster management and supports the achievement of Sustainable Development Goals (SDGs) 13 (Climate Action) and 15 (Life on Land).