近年來因全球氣候變遷之影響日益顯著，極端水文事件頻仍發生。在一般暴雨事件之頻率分析上，利用傳統線性動差法於水文頻率分析乃給予所有觀測紀錄資料之相等權重，無法反應近年頻仍出現之極端或高尾端（higher tail）事件之實際情況，而造成重現期推估結果偏高之問題。 因此，Wang（1997）首先提出高尾線性動差法（LH-moments）之概念，並以修正通用極端值分布（Generalized Extreme Value, GEV）之高尾端資料權重方法進行頻率分析；虞、鄭、王、張等人(2012)，則進行適用於各階之GEV 分佈LH-moments推衍，並進一步應用於台灣地區極端降雨之重現期推估與探討。 本研究之目的乃進一步嘗試尋求皮爾遜第三型分布(PT3)之LH-moments數值方法，研究中，首先係針對不同參數之繁衍資料，接著以權重修正係數(m)進行參數之推估進而達到合理之重現期，希冀本方法可提供未來氣候變遷影響下水文設計上之參考與應用。 In recent years, the influence of global climate change is more significant, such as the extreme rainfall events have occurred frequently. In general, the L-moments are adopted and all data are usually given the equal weighting in conventional approach of rainfall frequency analysis. However, the consequence problem is that the return periods are always estimated higher for those extreme rainfall (or higher tail) events of recently occurring. Wang (1997) first introduced the idea of LH-moments, increasing the weighting of high tail parts of Generalized Extreme Value (GEV) distribution were developed for frequency analysis of extreme rainfall event. Moreover, Yu et al. (2012) derived the general form for various weighting factor m of LH-moments of GEV and also real applied to estimating the return period of extreme rainfall in Taiwan. The purpose of this study is to explore an approach of LH-moments for Pearson Type III distribution (PT3). First of all, the synthetic data of various parameter sets are generated to evaluate the rationality of return period estimate of LH-moments for data at high tail part of PT3. Eventually, it is hopeful that this study can be further adopted to play a referential role on application of hydrologic design.
