摘要:利用河北省1984～2014年142个国家气象站的降水资料和历史灾情，以房屋为承灾体，基于优势分析法确定致灾因子的影响权重，构建暴雨综合致灾指数模型。以影响环境脆弱性的要素为指标，运用K-mean聚类分析法将河北省分成5个区域，采用指数函数拟合房屋损失与综合致灾指数的关系，反推出各个类型区不同灾情等级对应的综合致灾指数阈值，并通过2015～2019年的124个灾情案例进行验证。结果表明：河北省暴雨造成的房屋灾情事件发生次数总体呈现出北多南少的特征，北部山区普遍在10次以上。致灾因子中过程总雨量的影响权重最大，为68%，最大日降水量、持续日数、过程最大小时雨强所占权重分别为22%、6%和4%。模拟灾情的最佳等级分割点为损坏房屋1180、335、235间，此时模拟灾情等级与实际灾情等级一致的比例最高（67.4%）。阈值检验中，2015～2019年灾情案例的准确率为69.8%，轻度灾情等级的准确率最高。
关键词:暴雨/
房屋/
致灾阈值/
优势分析法
Abstract:The influence weights of the disaster factors were determined to construct a comprehensive hazard index model based on the dominance analysis method with the houses as the disaster-bearing bodies by using the precipitation data of 142 national meteorological stations in Hebei Province and the historical disaster data from 1984 to 2014. Taking the environment vulnerability elements as indicators, Hebei was divided into five regions based on the K-mean clustering analysis method. An exponential function was used to fit the change of house loss and comprehensive index. The thresholds of different grades in each district were then determined and verified by 124 cases from 2015 to 2019. Results showed that the number of housing disasters caused by heavy rain in the north was higher than that in the south, with more than 10 times in the mountainous area. The influence weight of the total rainfall process (68%) was the largest. The weights of the maximum daily rainfall, duration, and maximum hourly rainfall were 22%, 6%, and 4%. The best classification points of simulated disaster were 1180, 335, and 235 damaged houses, and the proportion of the simulated disaster level consistent with the actual disaster level was the highest (67.4%). In the threshold test, the accuracy rate of disaster cases from 2015 to 2019 was 69.8%, and the accuracy rate of the mild disaster level was the highest.
Key words:Rainstorm/
House/
Disaster threshold/
Dominance analysis approach
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