全球氣候變遷改變台灣地區的降雨型態，近年接連發生極端降雨與極端乾旱事件。在地表水供應量不足的期間，地下水被大量開發以支應迫切的民生產業用水需求。本研究選擇位於台灣中部的濁水溪沖積扇作為研究區域，提出一套簡便、統一的地下水枯旱度標準，分析2001至2016年期間第一含水層觀測站的地下水位歷線，指出歷史中地下水位相對枯旱的期間與強度，目的是了解本區地下水枯旱狀態的時間分布特性，提供未來地下水管理保育工作的研究基礎。
首先，本研究應用標準化地下水位指數法，將研究選定測站的連續180日地下水位累積值與360日地下水位累積值轉換成標準化的SGI指標：SGI180與SGI360。接著分別使用SGI180歷線與SGI360歷線，評估半年尺度與一年尺度下的地下水位相對強度變化。本研究利用SGI指標的出現機率訂定枯旱的等級，根據研究期間內SGI指標的資料累積分布函數，選擇50%、30%與10%出現機率對應的SGI指標值分別作為界定枯旱強度的門檻值。其次，使用Mann-Kendall檢定法評估研究期間內各測站地下水位的變化趨勢，並說明將枯旱度評估結果用於建立地下水管理標準線的設計方法。最後，本研究發展一套地下水枯旱度預測模式，使用歷年地下水自然消退期間的水位資料擬合消退水位預測式，將現有水位投入預測式計算產生水位消退線後，可計算SGI指標以評估未來地下水位狀態的枯旱度。
本研究使用SGI180與SGI360評估濁水溪沖積扇第一含水層的地下水枯旱狀態，相對枯旱期間的時間分布調查結果顯示：在連續豐水年出現期間，SGI180在扇頂、扇央與扇尾區測站入冬後的枯水期都偵測到枯旱訊號出現，其中扇頂區出現的枯旱強度相對輕微；而SGI360僅在少數測站偵測到短暫的枯旱訊號。在連續枯水年出現期間，SGI180與SGI360在扇頂、扇央與扇尾區都偵測到橫跨一整個豐枯水期的枯旱訊號。
研究成果說明在濁水溪沖積扇的第一含水層，地下水枯旱的時間分布與區域的降雨時間分布型態明顯相關。另外，本研究以扇頂區的二水測站與上游名竹盆地的新民測站為例，建立地下水枯旱度預測模式後，投入歷年水位消退期間檢驗枯旱度預測效果。在二水測站預測的枯旱度變化結果與現實狀態一致，但新民測站受水文地質條件影響，特定水位範圍內的水位消退變化不同，需要修正預測模式以改善低水位消退期的枯旱度預測成果。

Groundwater resources have been well exploited in Zhuoshui River Alluvial Fan area for a long history, and is considered to be a vital source of water supply during dry seasons of each year. Variation in precipitation patterns has caused many extreme events in recent decades as well as impacts on groundwater recharge characteristics owing to global climate change. Further studies of historical groundwater records should be taken to meet the need of better groundwater management strategies for the future.
In the present study, Zhuoshui River Alluvial Fan is chosen as study area. Daily groundwater level monitoring records during 2001 and 2016 from 42 stations on this area are investigated in order to assess the overall groundwater level response to natural drought phenomena.
Firstly, groundwater level records from each of the stations are analyzed to detect groundwater drought events in short and long time scale using the Standardized Groundwater Index (SGI) method. Two SGI indictor, SGI180 and SGI360, time series are estimated form data composed with daily groundwater level accumulative sum for an accumulation period of 180 days and 360 days separately.
Secondly, trend of groundwater level during study period of 42 stations are evaluated with Mann-Kendall test, and an appropriate groundwater management strategy is introduced.
Finally, a prediction model is developed for the purpose of estimating future groundwater level condition beforehand. Ershui station and Xin-Min station are chosen to build model and the effectiveness of model are tested.

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