城市洪涝风险的组合赋重方法研究与应用：以淮安市为例
Research and application of combined empowerment method for urban flood risk: Take Huai’an City as an example
【目的】城市洪涝灾害对人民的生命和财产安全造成了巨大的损失，客观、准确的对该灾害进行定量风险评估，对提高城市韧性发挥至关重要的作用。【方法】以淮安市为研究对象，从IPCC采纳的城市洪涝风险评估框架“危险性(Hazard)-暴露性(Exposure)-脆弱性(Vulnerability)”即“H-E-V”的框架出发，建立城市洪涝灾害风险的指标体系，基于随机森林算法计算洪涝因子对洪涝灾害的相对重要性，并以此作为客观权重，融合层次分析法确定各洪涝因子的主观权重。最后利用Kendall系数进行一致性检验并计算最优组合权重。使用优化后的新型指标赋权对淮安市的洪涝灾害风险进行精细化评估。【结果】结果表明：(1)利用Kendall法进行验证，协调系数W=0.145 6,在0.05显著性水平下，客、主观权重存在一定的一致性。(2)暴露性和脆弱性的影响显著高于危险性，尤其在主要河流水系和高人口密度区域，两者贡献更加突出。(3)淮安市中高风险区与洪泽湖、高邮湖、淮河及三河等主要河流水系分布关系密切，受人口密度、地均GDP等因素的影响，清江浦区、涟水县西北、东部地区和淮安区的东南部也位于中高风险区。【结论】利用网络爬取近年的极端灾害点进行验证，88%的极端灾害点位于较高及高等级规划的组合风险等级图中。研究成果对未来城市应对洪涝灾害起到借鉴作用。
[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.
城市洪涝灾害 / 随机森林法 / 层次分析法 / 风险评估 / 淮安市 / 韧性城市 / 极端天气 / 降雨
urban flooding / random forest method / hierarchical analysis / risk assessment / Huai'an City / resilient city / extreme weather conditions / rainfall
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