在人口快速成長及經濟繁榮的背景因素下，基於防災需求考量，淹水預報模式的發展已為各國致力發展的重點。臺灣人口密集具經濟繁榮的地區大都為緊鄰淺山丘陵且濱鄰海岸的沖積平原，因河流底床坡度陡、長度短、水流湍急等地理環境特性，以及沿海低地平原易受暴潮上溯之影響，沖積平原在颱風豪雨期間常受水患之苦。雖設置防洪排水工程等設施加以保護。但由於社會文明進步，人口增加，經濟發達，土地開發利用之需求增加及保護標準提升，且極端氣候、極端水文事件之發生頻率增加，故不僅需要強化防洪之排水工程功能，且需發展非工程性的防洪措施。
非工程防洪措施為基於工程措施有其保護限度，而豪雨及淹水規模可能超過保護標準，故需能及時預報採行有效的應變救援對策。本研究發展具有即時演算效能的地文性淹水預報模式(PHIP model)，於豪雨發生時，配合預報之雨量及潮位，預報淹水範圍，期能及時提供執行防救災應變對策之即時資訊，減免洪泛淹水損失。
地文性淹水預報模式整合QPESUMS預報雨量與地文性淹排水模式，發展前導時間3小時之地文性淹水即時預報模式，並以臺灣西南部之曾文溪與鹽水溪之間，面積約1,138平方公里之區域為研究範圍。以2009年莫拉克颱風之豪雨淹水現象模擬進行模式參數檢定，並以現地堤防損壞情形改變模式地文條件設定進行模擬。以2010年凡那比颱風之豪雨淹水現象模擬進行模式驗證，並應用於2010年凡那比颱風之淹水現象預報測試。以四核心個人電腦測試結果顯示預報前導時間3小時之計算機時間少於5分鐘，能計算研究範圍內各處之淹水深度歷線。因此應用本研究發展之地文性淹水預報模式可於氣象預報豪雨事件時，因應堤防破壞與抽水機調度等現地實際情況，提供即時淹水資訊，可及時執行有效的預警與救災行動。

Over the last decade, there has been a dramatic increase in the global population. Internationally, efforts to meet demands for disaster prevention and rescue have focused on the development of inundation prediction models. Taiwan has an unfortunate tendency to suffer disasters due to its mountainous geography and its location in a typhoon-prone area. To make matters worse, Taiwan's rivers tend to have steep bed slopes and short length, and thus overland runoff occurs rapidly and can cause dangerous flooding in this population dense country. In order to protect both its citizens and extremely valuable high density urban developments in regions downstream it is thus critical and urgent to develop a physiographic inundation prediction model for real-time computing efficacy.
In order to satisfy demands for prompt disaster prevention and rescue, an ensamble is developed that the physiographic inundation prediction model (the PHIP model) with a 3-hour lead time which integrate QPESUMS (the quantitative precipitation estimation and segregation using multiple sensor) which is the system used for establishing the spatial distribution of rainfall, with the physiographic drainage-inundation model (the PHD model). Here this model is applied to a study area ranging from the north bank of Taiwan’s Zengwun River to the south bank of the Yansheui River, an area of 1,138 square kilometers. Tests using our new model have been run for the periods during Typhoon Morakot in 2009 and Typhoon Fanapi in 2010, in order to assess its practicability. The results of these tests show that the computing time for a simulated 3-hour lead time inundation prediction by using a quad-core computer for the study area, including such data as an inundation depth hydrograph, is less than 5 minutes. Therefore, the physiographic inundation prediction model developed in this study can be applied to provide real-time inundation information for executing fast and effective pre-warning and rescue information during severe storms or typhoons.

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