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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/880


    Title: 結合高解析度降水於分佈型水文模式之降雨逕流模擬;Rainfall-Runoff Simulations Using Distributed Watershed Models with High-Resolution Precipitation
    Authors: 石棟鑫;Dong-Sin Shih
    Contributors: 土木工程研究所
    Keywords: 高解析度降水;雷達降水;分佈型水文模式;漫地流;地下水;radar-rainfall estimates;groundwater flow;surface flow;distributed-parameter model;High-resolution precipitation
    Date: 2006-01-11
    Issue Date: 2009-09-18 17:14:36 (UTC+8)
    Publisher: 國立中央大學圖書館
    Abstract: 台灣地區的水文災害通常是由極端降水所引起,極端降水會在短時間內產生高強度的降雨,有時更會持續性的降下豪雨,這都容易引起水災的發生,進而對人民的生命財產造成威脅。為了增進對極端水文事件的瞭解,本研究利用分佈型水文模式,結合高解析度的降水,進行降雨逕流的模擬研究。 一般而言,降雨資訊是由水文站量測而來,但是各量測點只能提供該點的降雨值,並不能表示其周遭位置的降雨量。而利用雷達推估降水則是已經證實可以提供較佳的空間降水資訊,但是對於降雨量的準確性仍有待努力。本研究以地面水文站的觀測值校正雷達降水資料,以台北市與石門水庫集水區為研究區域,2001年的納莉颱風(Typhoon Nari)為分析案例。研究結果發現,由五分山雷達站所提供的雷達回波資料,確實對降雨的描述與雨量站觀測值吻合,顯示五分山雷達站的確可以確實的掌握研究區域內的降水變化。另外,我們從雷達回波上,觀察到部分地區發生極端降雨,但是卻沒有適當的雨量站記錄。我們分析雷達降水跟雨量站觀測的結果發現,雷達降水的結果容易產生高估降雨量的情況,其中的差異性可以利用降雨空間分佈的研究進一步證實。 我們進一步將高解析度的降水資料應用於石門水庫集水區,進行集水區的降雨逕流模擬,降雨輸入是採用雷達與雨量站資料,集水區模式是二維的分佈型水文模式。經由模式的檢定與校正結果發現,利用二維的St. Venant 方程式應用在石門水庫集水區是可行的,模擬的水位值與實測值趨勢一致。此外,模擬結果發現,當網格大小取160公尺時,可以得到最佳的模擬結果,而其模擬時間還可以比120公尺的網格少百分之四十。案例研究中,我們發現以反距離權重法(inverse-distance weighting method)推估降雨量,可得到最佳的模擬結果,但以雨量站推估的降水皆差異不大,雷達推估降水的模擬部分以比值法(ratio method)最佳,而雷達降水的模擬誤差略高於雨量站估算的結果。 接著我們發展了一套以物理機制為基礎的分佈型水文模式,該模式結合地表水與地下水模組來探討水文循環過程。其中地表水是由漫地流與渠道流所組成,地下水模組則是包含了飽和含水層與非飽和含水層。該模式包含了降水、入滲、蒸發散、滲漏、地表漫地流與地下水流等水文過程,測試結果證實模式具有良好的應用性,並當模擬間距小於5秒時,建議採用空間解析度160公尺的網格模擬。本模式接著模擬不同的水文狀況,包括暴雨事件、暴雨的退水段、以及長時期的水文歷程,案例分析的結果顯示該模式具有良好的模擬結果。 Hydrological hazards often occur in conjunction with extreme precipitation events in Taiwan. The exceptional volume and intensity of the precipitation cause frequent torrential floods, sometimes with devastating effects on life and property. To improve our understanding of extreme events, the study modeled the rainfall-runoff processes using distributed watershed models with high-resolution precipitation input. Precipitation data is generally collected from rain gauge stations. However, each measurement represents only the amount of rainfall at that particular spot, not precipitation in the surrounding area. Radar approaches are considered to offer a good spatial description of precipitation, but hardly predict precipitation quantities with acceptable accuracy. High resolution radar-rainfall estimates are compared with ground observations for an extreme precipitation event. The Taipei City area and the Shihmen reservoir watershed were chosen as the study sites, and the passage of Typhoon Nari (2001) through these areas was taken as the case study event. It was concluded that radar reflectivity from the Wufenshan radar station can be helpful for identifying precipitation variations during the passage of a land falling tropical cyclone. Spots with extreme rainfall can be identified when radar approaches are performed, but not based on gauge approaches. However, compared to the gauge approaches to the radar-rainfall estimates over the investigated domain tended to be overestimated. The divergence between radar-rainfall and gauge-rainfall can be identified via sub watershed investigations. The watershed model with high resolution precipitation data was tested on a complex mountainous reservoir region, the Shihmen reservoir watershed. Radar-rainfall estimates were examined on this study. Numerical results generally revealed acceptable agreement between the observed and simulated reservoir stage hydrographs. The model calibration processes verified that the proposed model was effective for flood routing in the Shihmen reservoir watershed. Moreover, simulated results obtained using a grid size equal to 160m by 160m had the strongest agreement between simulated and measured data, and resulted in an execution time reduction of 40% than that of the case with 120m by 120m. Case study showed that inverse-distance weighting method carried the smallest error in estimation compared to all other spatial precipitation interpretations. The ratio approach produced the smallest residual error in simulation results among all other radar approaches. Precipitation is identified to be the main factor forcing model result. A physical based distributed-parameter model combining surface runoff and groundwater flow is developed for investigating hydrological processes. Surface runoff is composed of both overland flow and river flow components, and the groundwater module considers the unsaturated zone and saturated zone in an unconfined aquifer system. An investigation of hydrological processes, including precipitation, infiltration, evaporation, percolation, surface runoff and groundwater flow are all considered in the proposed simulation model. Comparative analysis shows that the gradient method is superior to the GIS approach for describing the flow above riverbed. This study suggests using the Thiessen polygon method for precipitation interpolation. The best calibrations are obtained at a spatial resolution of 160m by 160m, when the simulated time step is less than five seconds. The proposed model shows good potential for storm based simulations, recession period description and long-term modeling. Therefore, the proposed model is confirmed to be suitable for mountainous watershed, such as Shihmen reservoir watershed.
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