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涝灾的发生往往是多种水文致灾因子共同作用的结果,而传统的排涝标准以超过某一量级暴雨的重现期作为排涝标准,实质上只考虑了涝灾的一个致灾因子——暴雨。这种考虑单一致灾因子的重现期标准没有反映出多种致灾因子对涝灾的共同影响,不能正确衡量涝灾发生的概率。本文以平原河网地区的排涝问题为例,采用Gumbel-Hougard Copula函数建立了暴雨和外江水位的联合概率分布模型,研究了在暴雨和外江水位共同作用下的涝灾概率、以及不同量级的暴雨和外江水位组合下的联合分布概率和条件概率。研究结果表明,考虑多种致灾因子共同作用下的涝灾概率更能真实地反映涝灾实际发生的概率,基于Copula函数构建的多变量联合概率模型,可以很方便地计算多种致灾因子的各种量级组合下灾害发生的概率。
Waterlogging is often the result of a combination of hydrological hazard factors. However, the traditional drainage standard takes the discharge period exceeding the reappearance period of a certain magnitude heavy rainfall as the drainage standard, and actually only considers one flood disaster causing factor - heavy rain . This standard of single recurrence considering single hazard does not reflect the common impact of multiple hazards on floods and can not correctly measure the probability of floods. Taking the drainage problems in the plain river network as an example, the joint probability distribution model of rainstorm and outer water level is established by using the Gumbel-Hougard Copula function. The probability of flood disaster under the combined effect of heavy rain and outer water level is studied. The joint distribution probability and conditional probability under the combination of heavy rain and outer river water level. The results show that considering the probability of floods combined with multiple hazard factors can truly reflect the actual probability of floods. Based on the multivariate joint probability model constructed by Copula function, it is easy to calculate the The probability of a disaster occurring at a species-level combination.