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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/94582

    Title: FLO-2D數值模式應用於土石流危害度之分析
    Other Titles: Hazard analysis of debris flow based on FLO-2D model
    Authors: 金旻勳;Jin, Ming-Hsun
    Contributors: 淡江大學水資源及環境工程學系碩士班
    黃富國;Huang, Fu-Kuo
    Keywords: 土石流;FRO-2D;降雨;可靠度分析;類神經網路;Debris Flow;hazard analysis;FLO-2D Model;Rainfall;Artificial Neural Network.
    Date: 2013
    Issue Date: 2014-01-23 14:47:33 (UTC+8)
    Abstract: 台灣位在地震活躍區上,土質易鬆動,又常由於山坡地之不當開發利用,每當出現豪大雨或颱風時,便容易引發土石流,造成災害。因此,實有必要針對土石流之危害度,進行深入探討及研究。
    本文以民國98年莫拉克颱風在高雄市六龜鄉新開地區之23鄰集水區土石流致災場址為例,採用FLO-2D軟體來進行土石流之數值模擬分析。首先使用ArcGIS整理23鄰集水區場址之地形資料與等高線,接著利用各不同之降雨參數(如降雨強度、降雨延時及降雨雨型)來模擬集水區內可能之降雨情境。並針對以下參數:降雨強度(I)、降雨延時(T)、降雨雨型(RP)、賓漢降伏應力(a1、b1)、賓漢黏滯係數(a2、b2)、曼寧粗糙係數(n)、土砂之體積濃度(Cv)、層流阻力係數(K)等,進行土石流參數變異性分析,以了解各參數對土石流災害之影響程度。接著,利用結合類神經網路 (ANN) 及一階可靠度法 (FORM) 或蒙地卡羅模擬法 (MCS) 之危害度分析技術 (ANN-based FORM、ANN-based MCS),來探討土石流受降雨影響之危害度,此分析模式在系統反應之模擬、計算效率之提昇、以及危害度(或超越機率)分析精度之改善上,皆有很好的表現。透過本文之探討,本研究在降雨對土石流影響之分析上,具體提供了一個可資落實,及具風險觀念的危害度評估方法,其成果可作為擬定土石流防災策略的參考。
    On August 8, 2009, Typhoon Morakot struck central and southern Taiwan with high rainfall intensity and accumulated rainfall.Debris flows were one of the severe disasters in Laonong River Basin. Therefore, a case study of rainfall hazard for debris flows in this area is explored. In this research, a method to assess the rainfall hazard for debris flows is proposed. Parameter studies are first done to investigate the influence of factors on debris flows. These factors include rainfall intensity, duration, patterns, geomorphological data, and the rheological property of slurry. Then 100 different combinations of parameters are generated and associated numerical analyses of debris flows are performed by the software of FLO-2D assumed that each parameter is uniform distributed around its reason ranges. Following, the inundation area, accumulative height and maximum flow velocity of debris flows are interpreted by the artificial neural network (ANN) trained and verified according to the above-mentioned 100 analysis results. The rainfall hazard for the debris flows are then evaluated by first-order reliability method (FORM), or Monte-Carlo simulation (MCS) in terms of different level of allowable inundation area, accumulative height and maximum flow velocity based on varied rainfall intensity, duration, patterns, etc. The evaluation model of ANN-based FORM or ANN-based MCS proposed is very efficient for assessing the rainfall hazard of the debris flows. It can be an effective auxiliary tool to design the countermeasures of debris flows for disaster mitigations.
    Appears in Collections:[水資源及環境工程學系暨研究所] 學位論文

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