Title: 機率警戒水位推估模式之建立 -以基隆河流域為例
Development of probabilistic warning water level estimation model–A case study of Keelung River watershed
Authors: 楊皓雯
Yang, Hao-Wen
Yeh, Keh-Chia
Wu, Shiang-Jen
Keywords: 警戒水位;SOBEK;多變量蒙地卡羅模擬法;不確定性與風險分析;預警可靠度;Warning level;SOBEK;Multivariate Monte Carlo Simulation;Uncertainty and risk analysis;Early warning reliability
Issue Date: 2017
Abstract: 警戒水位值為台灣中央及地方防救災單位於颱洪豪雨期間,評估緊急應變措施之重要參考,一般依據歷史水位及堤防高配合應用水文水理模式推估洪水上漲速率以決定其警戒值。然而隨著環境變遷,極端降雨事件發生頻率增加,造成水文地文水理特性具有變異性,使得採用水文水理模式所訂定之警戒水位產生不確定性。因此本研究考量水文因子(降雨特性、河口潮位及降雨-逕流模式參數)及地文因子(河道糙度係數)之不確定性下,整合水文水理模式(SOBEK模式)及不確定性及風險分析方法(改良一階二矩法)與羅吉斯迴歸分析,以發展機率警戒水位推估模式。本研究以基隆河為例,採用2008年至2015年間10場颱風事件之水文資料(降雨量、流量、水位及河口潮位)進行模式建置及測試。由模式應用結果可知,所發展的機率警戒水位推估模式可適用於評估不同因子(降雨特性、河口潮位、曼寧n值及SAC-SMA參數)之不確定性條件下,各目標水位站警戒水位值之可靠度,並量化各因子變異性對警戒水位可靠度之影響程度。此外,由模式評估結果亦可知基隆河13個水位站現行一級及二級警戒水位公告值之可靠度達0.93(溢頂風險僅為0.03),顯示現有警戒水位公告值具有相當高之防洪預警可靠度。
In Taiwan, flood early warning can be issued by Water Resources Agency (WRA) in accordance with the observed water stage exceeding the thresholds (named warning water level) specific river-stage gauges. In general, warning water-levels can be determined by using the hydrological and hydraulic models with historical hydrologic data based on the control elevation of dikes or hydraulic structures. However, climate change and extreme rainstorm events with high occurrence frequency significantly have led to variations in the hydrological and physiographic data in the watersheds which should impact the reliability of hydrological and hydrological models. There exists, accordingly, the uncertainty in resulting thresholds of water levels for flooding and inundation. Therefore, this study aims to develop a probabilistic model for the estimation of warning water levels in the fluvial system by taking into account uncertainties in hydrological and physiographic factors,of which uncertainty factors of interest, hydrological factors include the rainfall characteristics (i.e. rainfall duration, depth and storm pattern) and tide depth and the roughness in the river bed is regarded as the physiographic factor in terms of Manning’s n coefficient. Since the variation of hydrological data should influence the reliability of calibrated parameters of rainfall-runoff models, the parameters of rainfall-runoff models are also treated as the uncertainty factor. In detail, the proposed probabilistic model for the warning water levels is developed by using uncertainty and risk analysis in conjunction with the rainfall-runoff model and river routing model. Noted the in this study, the SOBEK model and SAC-SMA (Sacramento soil moisture accounting) are used in the estimation of runoff and water levels respectively. Eventually, the advanced first-order and second moment (AFOSM) approach is applied in quantifying the reliability of warning water levels attributed to uncertainty factors of interest. The Keelung river watershed is selected as the study area and the hydrological data (i.e. rainfall, discharge and tide depth during typhoon events),which were recorded in associated rainfall and water-stage gauges are adopted in the model development and application. The results from model application indicate that the proposed probabilistic model can not only quantify the reliability of warning water levels at stage stations in the case of combination of variations in the uncertainty factors, but also evaluate the effect of uncertainty factors considered on the warning water levels. In addition, through the proposed probabilistic model, it reveals that issued water levels by WRA at stage gauges along Keelung River are in association with high reliability in early warning and they can enhance the performance of disaster prevention operation.
URI: http://etd.lib.nctu.edu.tw/cdrfb3/record/nctu/#GT070451240
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