本研究旨在建立「季長期缺水機率預報」模式並嘗試整合季長期天氣展望資料、降雨-逕流模式與水源供需系統動力模式，進行中部地區各縣市未來三個月之缺水機率預報。
本研究所提出之「季長期缺水機率預報」其主要架構包括三部分：(1)季長期天氣展望、(2)連續型降雨-逕流模式與(3)水源供需系統動力模式。首先，利用中央氣象局所提供之季長期天氣展望資料配合歷史水文資料進行轉換為月雨量及月溫度，再透過分解模式將月雨量及月溫度降為日時間尺度資料，並經由蒙地卡羅法配合降雨-逕流模式，進行台灣中部地區11個集水區未來三個月1000組之入流量預報。接著進一步結合水源供需系統動力模式，以推估未來可能之供需情形，進而評估未來三個月台灣中部地區各縣市可能之缺水情形，提供區域性乾旱預警資訊與防救決策之參考。模式率定與驗證分析結果發現：降雨-逕流模式能合理模擬研究區域內集水區之日流量序列，並配合天氣展望資料與水源供需系統動力模式能適當反映未來可能發生之缺水情況。最後利用民國100年上半年枯水期之缺水案例分析，結果顯示：本模式能適當反映未來可能會發生之缺水的情況，並於梅雨季來臨後能反映未來不缺水之情況。最後，本研究發展視窗化預報模式，使模式更具親和力。

This study proposed a stochastic approach to forecast water-shortage probabilities for three months ahead in central Taiwan. This approach integrates the seasonal weather outlook, rainfall-runoff model and system dynamic model of water resources system for providing early warning information on water shortage for the coming three months.
This approach comprises three components: (1) seasonal weather outlook, (2) continuous rainfall-runoff model, and (3) system dynamic model of water resources system. Central Weather Bureau of Taiwan issues the seasonal weather outlook every month which comprises the probabilities of being above normal, normal, and below normal for monthly rainfall and monthly mean temperature for 1 to 3 months ahead. The Monte Carlo method is used to repeat random sampling from the seasonal weather outlook. For each Monte Carlo trial, the monthly rainfalls and monthly mean temperatures for 1 to 3 months ahead in the eleven upstream catchments of central Taiwan can be obtained. Further, the disaggregation model is used to convert the monthly values into the daily rainfall and temperature series for the coming three months. The continuous rainfall-runoff model, i.e., HBV-based hydrological model, uses 1000 sets of daily rainfall and temperature series to simulate 1000 sets daily inflow series for each upstream catchment. With the simulated daily inflows, the system dynamic model is adopted to simulate the water budge of water resources system. After all the Monte Carlo trails, the water-shortage probabilities for one to three months ahead can be calculated for regional drought warning and disaster prevention. The results reveal that the HBV-based hydrological model has good performances for daily inflow simulation at the eleven inflow sites and the proposed approach can reasonably forecast the water-shortage conditions for one to three months ahead by using the water-shortage event in 2011 for validation. Moreover, the window-based model with user-friendly interfaces for the proposed approach has been developed.

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