Development of Real-Time Updating Runoff Model Using Rainfall Forecasting Dada (III)

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Project title

Code/計畫編號

NSC101-2625-M019-002

Translated Name/計畫中文名

建立高精度與高效能之洪氾預警整合系統-總計畫暨子計畫:結合降雨預報資料發展即時校正逕流演算模式(III)

Project Coordinator/計畫主持人

Kwan-Tun Lee

Funding Organization/主管機關

National Science and Technology Council

Department/Unit

Department of Harbor and River Engineering

Website

https://www.grb.gov.tw/search/planDetail?id=2595781

Year

2012

Start date/計畫起

01-08-2012

Expected Completion/計畫迄

01-07-2013

Bugetid/研究經費

1458千元

ResearchField/研究領域

大氣科學

"台灣地區雨量豐沛，年平均降雨量高達2500公釐，為世界平均值的2.5倍。且降雨集中在每年5月至10月，佔全年雨量的四分之三，且大部份為颱風所帶來的豪雨。由1897年至2008 年資料統計結果顯示，侵襲台灣之颱風總計420次，即平均每年3.75次。除此之外，尚有上千次暴雨掠奪，更加深本省水患的嚴重性。2009年8月8日至10日之莫拉克風災造成南台灣地區，人民生命及經濟上之重大損失。因此如何開發高精度與高效能之洪氾預警系統，提供正確洪水預報資訊，以供相關單位與民眾進行防洪減災措施，減少洪水所帶來的災害，實乃刻不容緩之要務。本研究計畫之目的在於結合降雨預報方法，以發展即時校正逕流演算模式，進而提供河道水理演算，藉以發展洪氾預警系統。研究中首先將利用數值高程模式劃分欲計算渠道上游集水區、渠道兩側次集水區與殘流域之地文因子，而後採用地形性水文模式進行逕流演算，並配合即時流量回傳資料，以發展即時逕流校正方式，提高集水區逕流預測之精度與效能。 U第一年計畫U已先收集研究集水區之水文與地文資料，進行地形性水文模式之參數檢定，並以颱洪事件進行模式驗證，而後配合流量紀錄，開發具有即時校正功能之集水區降雨逕流模式。U第二年計畫U配合降雨預報方法，分析即時校正的降雨逕流演算結果，並且聯結河道洪水演算模式，以檢視河道洪水演算模式之模擬結果，檢討逕流演算之即時校正功能。U第三年計畫U將檢討集水區逕流分區原則，以及建立逕流模擬之替代演算模式，並且進行逕流模式參數敏感度分析，而後整合模式聯結與架構修正。本計畫完成之後，可將逕流演算模擬結果，提供予子計畫二以進行二維淹水即時模擬工作，藉以發展高精度與高效能之洪氾預警整合系統，提供流域防洪預警之即時相關資訊。" "The annual rainfall in Taiwan reaches 2,500 mm, which is about 2.5 times the world average. Three-fourth rainstorms mainly occured between May and October and resulted from typhoons. Records from 1897 to 2008 show that total 420 typhoon events invaded Taiwan, that is 3.5 typhoons in avarage every year. Since the typhoons and concentrated rainstorms caused severe damages in the island, such as Typhoon Morakot caused severe damage to southern Taiwan during August 8–10, developing a high precision and efficiency of flooding warning system to provide accuracy flood forecasting information for flooding prevention and disaster reduction is considered important for authority and people. The objective of this study is to develop the real-time flow updating model combined with rainfall forecasting method. The hydrographs generated from the runoff model will be input to the channel-flow routing model for water level predicting. A digital elevation model (DEM) will be adopted to delineate lateral areas and boundaries of subwatersheds along the mainstream. Detail geomorphic factors for the lateral areas and subwatersheds will be as the input to a geomorphology-based runoff model to generate flow hydrographs. Consequently, the real-time runoff feedback data will be adopted to develop a real-time updating runoff model to improve the precision and efficiency of runoff forecasting. In the first year project, hydrological and geomorphologic data of the study watershed were collected. The parameters of geomorphology-based runoff model will be calibration, and then use the given rainstorm events on watersheds will be simulated to confirm thes accuracy of the proposed model. Consequently, the real-time runoff feedback data will be adopted to develop the watershed runoff forecasting model with real-time error based updating. In the second year project, the incoming rainfall forecasting was combined the proposed model to analyze the results of real-time forecasting runoff. Furthermore, the results will be as input for real-time channel routing models (Subproject II) to confirm the simulated results, and the efficiency of real-time updating method will be reviewed. In the third year project, the area-delineated principles will be reviewed and the alternative runoff model will be developed. Consequently, the detailed sensitivity analysis of model parameters will also be performed, and then the proposed model will be integrated and revised. It is promising to develop an integrated flood warning system with high precision and efficiency using the predicted watershed runoff (Subproject I) and linking with the two-dimensional inundation model (Subproject II) to provide real-time flooding information to authorities and people."

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Development of Real-Time Updating Runoff Model Using Rainfall Forecasting Dada (III)

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