年最大值抽样估算的暴雨频率设计值的低估问题探讨

Underestimation of precipitation quantile estimates based on AMS data

由年最大值抽样(AMS)和年超大值抽样(AES)的基本理论及重现期(RP)的定义可知,AMS并不符合以"事件"为基础的重现期的定义.以美国西南半干旱区1 438个雨量站和太湖流域96个雨量站的降雨资料为例,通过经验频率与超过概率的比较,发现AMS估算的暴雨频率设计值偏小,尤其是对常遇频率降雨设计值的影响更加显著.美国的降雨量资料站点多、系列长,实际资料验证与理论分析一致.通过对太湖流域AMS资料的分布形态进行分析的结果表明:太湖流域的站点不多,资料长度不够,且大部分站点在雨量大值区数据稀少,使得频率直方图不连续,是造成我国太湖流域的资料验证效果不理想的可能原因.

This paper briefed the concept of annual maximum series（ AMS） and annual exceedance series（ AES）,indicating that the use of AMS contradicts the definition of return period.Having taken the rainfall data of 1 438 stations in the Southwest Semiarid area of the U.S.A（ SSUS） and 96 stations in the Taihu Lake Basin（ TLB） of China as examples for frequency analysis,we find out that the quantiles estimated based on AMS under current conventional computation are underestimated,especially for frequent events,by comparison of the empirical frequency of data with the theoretical exceedance probability.However,the findings for the SSUS data are more justified than those for the data in the TLB.The study suggests the possible causes for the difference could be,via a skewness analysis of AMS data in the TLB,that the stations used for the study in the TLB are very limited and data series are short in comparison with the SSUS data.Furthermore,only few high values are available in the high value interval,resulting in discontinuous AMS histograms for most stations in the TLB.