Based on the precipitation data and torrential rain disaster data in Zhangjiajie City of Hunan Province from 2016 to 2020,taking the claim cases of the property and cargo insurance(hereinafter referred to as"prop...Based on the precipitation data and torrential rain disaster data in Zhangjiajie City of Hunan Province from 2016 to 2020,taking the claim cases of the property and cargo insurance(hereinafter referred to as"property and cargo insurance")from Hunan Branch of the People’s Insurance Company of China as the research sample,the Dominance Analysis Method was used to determine the influence weights of disaster-causing factors to establish a comprehensive disaster-causing index(I)model of torrential rain.Second,an exponential function was used to fit the relationship between the number of town or street which filed claims of property and cargo insurance and I,then to determine the threshold of I corresponding to different accident levels.The claim cases caused by torrential rain disaster in Zhangjiajie in the flood season of 2021 were selected to verify the I and its threshold.The results showed that the number of property and cargo insurance accidents caused by torrential rain in Zhangjiajie was generally low in east and west but high in middle areas.Among the disaster-causing factors,the weight of the 96-h accumulated precipitation on the scope of accident was the largest,reaching 28.6%.The simulated grades of the scope of accident,the amount of claim and the number of accidents of property and cargo insurance had a high correlation with the grades of actual disasters,and all passed the test at the 0.01 significance level.The threshold test results showed that the consistency rate or accuracy between the predicted level and the actual level of torrential rain disaster-causing cases was 71.4%,in which the predicted values of accuracy for the mild,moderate and severe disaster levels were 70%,70%and 100%,respectively.Therefore,the threshold of I established in this study can be used for the industrial meteorological services related to the property and cargo insurance in Zhangjiajie.展开更多
基金Supported by Key Project of Hunan Meteorological Bureau in 2021(XQKJ21A006)。
文摘Based on the precipitation data and torrential rain disaster data in Zhangjiajie City of Hunan Province from 2016 to 2020,taking the claim cases of the property and cargo insurance(hereinafter referred to as"property and cargo insurance")from Hunan Branch of the People’s Insurance Company of China as the research sample,the Dominance Analysis Method was used to determine the influence weights of disaster-causing factors to establish a comprehensive disaster-causing index(I)model of torrential rain.Second,an exponential function was used to fit the relationship between the number of town or street which filed claims of property and cargo insurance and I,then to determine the threshold of I corresponding to different accident levels.The claim cases caused by torrential rain disaster in Zhangjiajie in the flood season of 2021 were selected to verify the I and its threshold.The results showed that the number of property and cargo insurance accidents caused by torrential rain in Zhangjiajie was generally low in east and west but high in middle areas.Among the disaster-causing factors,the weight of the 96-h accumulated precipitation on the scope of accident was the largest,reaching 28.6%.The simulated grades of the scope of accident,the amount of claim and the number of accidents of property and cargo insurance had a high correlation with the grades of actual disasters,and all passed the test at the 0.01 significance level.The threshold test results showed that the consistency rate or accuracy between the predicted level and the actual level of torrential rain disaster-causing cases was 71.4%,in which the predicted values of accuracy for the mild,moderate and severe disaster levels were 70%,70%and 100%,respectively.Therefore,the threshold of I established in this study can be used for the industrial meteorological services related to the property and cargo insurance in Zhangjiajie.