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为解决保险费率厘定中所依据的历史洪涝灾害情况、灾害经济损失值的基础数据资料不全及实地调研所需费用高等问题,本文通过仿真模拟的方法,建立城市管网水力模型以实现洪涝灾害的淹没场景再现,得到淹没水深、淹没面积、淹没历时等洪涝淹没情况。选用灾损曲线理论计算不同重现期下不同土地利用类型的经济损失值,用伽玛分布进行拟合得到期望损失值用以计算保险净费率,利用资本资产定价CAPM模型得到风险附加费率并结合附加费率来厘定总保险费率。选择典型洪涝灾害易发区云南省昭通市昭阳区实例来验证该方法的实用性。研究结果表明:保险费率较高的有商业、服务活动、交通运输以及居住用地,保险费率为3.76%、3.21%、3.21%、2.1%。每万元保额建议收取的保费为376元、321元、321元、210元。该方法旨在为我国城市洪涝保险制度的建立提供依据。
Abstract：In order to solve the problems that there are incomplete basic data of historical flood disaster situations and disaster economic loss values used for ratemaking the premium rate and that the cost of field research is high, this paper uses the analogue simulation method to build a hydraulic model of urban pipe network to restore flooding scenes of flood disasters and to obtain such flooding situations as flooding water depth, flooding areas and flooding duration. The disaster damage curve theory is used to calculate economic losses of different land-use types during different recurrence intervals. Gamma distribution is used in this paper for fitting and obtaining the expected loss value. This paper then uses that value to calculate the net insurance rate and uses the capital assets pricing CAPM model to count the Risk Additional Rate. The total premium rate will be determined on the basis of the Risk Additional Rate. Zhaoyang District of Zhaotong City, Yunnan Province is selected as a typical flood-prone area to verify the practicability of this method. Research results show that commercial activities, service activities, transportation and residential lands have higher insurance rates. Their premium rates are 3.76%, 3.21%, 3.21% and 2.1% respectively and their premiums for every ten thousand yuan insured amount are suggested to be 376 yuan, 321 yuan, 321 yuan and 210 yuan. This method aims to provide reference for the establishment of urban flood insurance systems in China.
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基本信息:
DOI：10.13928/j.cnki.wrahe.2021.09.013
中图分类号:F842.64;F224
引用信息:
[1]赵梦阳,刘斌云,李智,等.基于水力模型的城市洪涝保险费率厘定[J],2021,52(09):126-134.DOI:10.13928/j.cnki.wrahe.2021.09.013.
基金信息:
国家自然科学基金(51809297)