近年來全球氣候變遷的議題引起各界的關注，全球氣候變遷將對水資源有多方面的影響，如改變全球降雨在時空的分布不均趨勢更加顯著、改變水資源的供需情況等。由於乾旱受到一些氣候與非氣候因素所衝擊，本研究利用希爾伯特黃轉換(HHT)分析探討乾旱趨勢；HHT係將訊號資料經由經驗模態分解（EMD），隨時間振盪的資料將分解成多個本質模態函數（IMF），再以希爾伯特轉換(HT)分析獲得以時間-頻率-能量描述時序資料之物理意義；如此藉由HHT分析具有非線性與非穩態之降雨資料。 本研究以臺灣地區北中南東四個地區各選一代表雨量站(臺北、臺中、臺南、花蓮)進行分析乾季雨量、最大不降雨天數與SPI指數之趨勢。以EMD分解成許多IMF及合併成「合併IMF」以及HHT時能圖可發現資料之趨勢性與特性及顯示統計模式之變異點。結果顯示臺北、臺中、臺南三站之乾旱趨勢在近期有減少之趨勢，但是台中站與臺南站在乾季之乾旱趨勢有升高之可能性；花蓮站則無明顯之乾旱趨勢；於SPI分析中，結合合併IMF法可以發現中長時間尺度之趨勢。 In recent years, Climate change has become one of the most critical global issues. Global climate change impacts water resources in many ways: changing the temporal and spatial distribution of precipitation, changing the demand and supply of water resources. This study uses the Hilbert-Huang Transform (HHT) to investigate the drought trend. The HHT method, consisting of empirical mode decomposition (EMD) and Hilbert spectral analysis, for analyzing precipitation can reveal the nonlinear and non-stationary nature of this phenomenon. The EMD can decompose any time series into a collection of intrinsic mode functions (IMF) and Hilbert transform can obtain a physically meaningful time-frequency-energy description of a time series. In this study, HHT is used to analyze the trend of precipitation in dry seasons, maximum number of consecutive non-rainy days and standard precipitation index (SPI). There are four rain gauges (Taipei, Taichung, Tainan, Hualien) selected as representative gauges of four parts (north, central, south and east Taiwan) in Taiwan. The EMD provides a framework for both information fission and fusion. The fission approach extracts features from IMFs; and the fusion approach merges information from the IMFs. Through fission, fusion and HHT spectrum, the trend and variation points of data. The results show that the drought trends of Taipei, Taichung and Tainan are decreasing in recent years; while Hualien does not significantly have the drought trend.
