設計暴雨雨型對水文模式分析與暴雨排水設計是不可或缺的基本要素。在水工設計上，針對年最大降雨序列演算的暴雨雨型，可將頻率分析所求得的降雨深度做時間上的分配，以便進行各種水文分析。建立暴雨設計雨型之模式有許多種，研究中採用具尺度不變性之高斯馬可夫雨型模式，該暴雨雨型模式視每一場降雨事件為一隨機歷程，考慮每個時刻之序列符合常態分佈，以一階高斯馬可夫歷程敘述臨前水文條件的遺傳效應，該雨型亦為具有最大概似度之設計暴雨雨型。本研究以序率觀點出發，探討中國文化大學華林實驗林場降雨事件之時間變異特性，並針對不同降雨延時資料，分別建立無因次高斯馬可夫雨型，以供未來水文模式設計之應用。
Design storm hyetograph is the essential element for hydrologic modeling analysis and storm water drainage design. A storm hyetograph constructed by annual maximum rainfall series can distribute the design rainfall depth for specific duration and return period. It is a useful technique for storm water management and delineating floodplains. Several forms of design storm hyetograph have been developed. A scale-invariant Gauss-Markov hyetograph is based on a non-stationary first-order Markov process. It is a dimensionless hyetograph and the most likely to occur is the average hyetograph. The stochastic process was applied to study the temporal variation of rainfall events in Hwa-Lin Experimental Forest, and two different durations of scale-invariant Gauss-Markov hyetograph were established.
