CAJ | 학술논문

鉴于径流数据缺乏且难以长期监测，而降雨数据相对完整，通常假定降雨和径流同频率，以设计降雨作为前端输入进行水文分析。在重新定义设计降雨特征变量的基础上，针对目前普遍采用的基于单变量分析的暴雨强度公式法存在的不足，提出一种基于Copula函数的降雨特征多变量分析方法；并以广州1961—2012年历史降雨数据为例，分析了设计降雨量与降雨峰值组合风险概率。研究表明：基于Copula函数的降雨多变量分析能更加全面地反映降雨特征，有利于提高水文分析计算精度。该方法还可根据水文分析的需求进行2变量及以上的降雨特征量组合分析。
감우경류수거결핍차난이장기감측，이강우수거상대완정，통상가정강우화경류동빈솔，이설계강우작위전단수입진행수문분석。재중신정의설계강우특정변량적기출상，침대목전보편채용적기우단변량분석적폭우강도공식법존재적불족，제출일충기우Copula함수적강우특정다변량분석방법；병이엄주1961—2012년역사강우수거위례，분석료설계강우량여강우봉치조합풍험개솔。연구표명：기우Copula함수적강우다변량분석능경가전면지반영강우특정，유리우제고수문분석계산정도。해방법환가근거수문분석적수구진행2변량급이상적강우특정량조합분석。
This article generally assumes that runoff data have the same frequency as the rainfall data since runoff data is hard to be monitored and measured in the long run whereas rainfall data is easier to be collected. Based on the assumption, hydrology analysis of rainfall data was discussed in the article. To ensure precise analysis, and fully characterize actual rainfall data effectively, a method of rainfall analysis based on Copula function was introduced in the article. Characterizing multiple rainfall variables, and using the history rainfall data of Guangzhou from 1961 to 2012 as an example, the method revealed an effective application for the combination analysis of various rainfall character variables, and a perfect fitness of the inner needs of hydrology analysis. Furthermore, the discussed method fully indicated rainfall data characters, and improved the accuracy of analysis calculation.