台灣地區的氣候受到緯度與複雜地形之影響，降雨在空間與時間上的分布較為不均勻，隨著近年來台灣水文環境因全球氣候變遷的影響，極端氣候發生的頻率與強度增加，因此了解台灣地區乾旱變化是水資源管理上不可或缺的一環。本文以標準化降雨指數(standardized precipitation index, SPI)定義乾旱，以時空分量迴歸(spatio-temporal quantile regression)檢測氣候變量分布特性的變化，並使用貝式分層模式(Bayesian hierarchical modeling)將有關信息整合。本文選取台灣地區北、中、南、東四個區域12個雨量站，1947至2014年共68年的月雨量資料，轉換為標準化降雨指數以分析乾旱趨勢，考慮常態以下乾旱部份的分量0.01、0.05、0.1、0.15、0.2、0.3、0.4、0.5等8個分量作為代表，並使用雨量站位置之經緯度資料作為空間資訊，探討不同分量間的變化趨勢，並展示資料的時空關聯性。結果顯示台灣東南部沿海之區域與恆春半島區域皆顯示出較嚴重之乾旱趨勢，而在各月份之趨勢，選取0.05、0.15、0.3等3個分量作為表示，主要負趨勢顯示於10月至隔年2月，大致與台灣乾季時間吻合，顯示台灣乾季時，東南沿海區域與恆春半島區域處於乾季時乾旱有增加之趨勢。

Influenced by latitude and complex topography, temporal and spatial distribution of rainfall is uneven in Taiwan. Impacts of global climate change on water resources increase substantially. Understanding drought trend is an essential component in water resources management. In this study, drought is defined by the standardized precipitation index (SPI). Spatio-temporal quantile regression is employed to detect distributional changes of hydro-climate variables. Bayesian hierarchical modeling is then used to combine related information. Three-month rainfall series from 12 rainfall gauge station are used in this study to analyze drought trend in Taiwan. Quantiles of 0.01, 0.05, 0.1, 0.2, 0.3, 0.4 and 0.5 for SPI as well as location (latitude and longitude) of rainfall gauge stations are used to evaluate spatial correlation of drought trends and discuss the trend on different quantiles. The results show that more severe drought trend is observed at the southeast coastal area and Hengchun peninsula. For the monthly rainfall trend analysis, only quantiles of 0.05, 0.15, and 0.3 are chosen for analysis. Significant negative trend is observed in the period of October to February, which is the dry season in Taiwan. The results indicate that the drought in the southeast coastal area and Hengchun peninsula becomes more severe.

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