Research and application of combined empowerment method for urban flood risk: Take Huai’an City as an example

Abstract

[Objective] Urban flood disasters have caused significant damage to lives and property. An objective and accurate quantitative risk assessment of these disasters is crucial for enhancing urban resilience. [Methods] Huai'an City was selected as the study area. The urban flood risk indicator system was established using the “Hazard-Exposure-Vulnerability(H-E-V)” framework adopted by the IPCC. The relative importance of flood factors was calculated using the random forest algorithm to determine objective weights, while subjective weights were assigned using the Analytic Hierarchy Process(AHP). The Kendall coefficient was applied to test the consistency between the weights, and the optimal combined weight was calculated. The refined indicator weights were then used to conduct a detailed risk assessment of urban flood hazards in Huai'an City. [Results] The results showed that:(1) The Kendall test confirmed a coordination coefficient of W=0.145 6, indicating consistency between objective and subjective weights at the 0.05 significance level.(2) The influence of exposure and vulnerability was found to be significantly higher than that of hazard, particularly in areas near major water systems and in regions with high population density.(3) Medium to high-risk areas in Huai'an City were closely associated with the distribution of major rivers and water systems, while Qingjiangpu District, northwest Lianshui County, eastern Huai'an County, and southeastern Huai'an District were also identified as medium to high-risk zones due to the effects of population density and per capita GDP. [Conclusion] Validation using recent extreme disaster points indicated that 88% of these points were located in the medium to high-risk zones of the combined risk level map. These findings are expected to provide valuable insights for improving urban flood disaster management in the future.

Keywords

urban flooding / random forest method / hierarchical analysis / risk assessment / Huai'an City / resilient city / extreme weather conditions / rainfall