土石流是指豐富的鬆散土體與水混合的高濃度含砂流體，在重力的作用之下，沿著坡面或溪溝，由高處往低處流動的自然現象，因其發生突然、流動快速、衝擊力強及破壞性大，往往造成人民生命財產損害，故有必要對土石流事件的發生與否進行研究。然而影響土石流發生與否的因子很多，如何利用一些地文及水文因子(如降雨或地表逕流)來提高判別土石流發生潛勢，是當前土石流防災的重要課提。本研究採用證據權重法來進行土石流發生潛勢的分析，此方法建立在貝式定理及勝算比的基礎上，利用現有的土石流資訊為基礎(驗前機率)，結合土石流發生與影響因子之間的關聯性，計算出每個因子對土石流發生的影響權重值(驗後機率)，將權重值以線性疊加方式建立土石流的潛勢指標，用以反映溪流發生土石流的潛勢高低。本研究以高屏溪流域的119條土石流潛勢溪流為研究範圍，以溪流長度、集水區面積、平均高程、地貌指標、形狀係數、集水區平均坡度、溪流平均坡度、標準化植生差異指標、崩塌率、曲率、碎形維度及岩性等12個地文因子，以降雨驅動指標(RTI)作為降雨因子，分別建立不含降雨因子的土石流發生地文潛勢指標(TSI)，及建立含降雨因子的土石流發生降雨地文潛勢指標。最後以八個颱風豪雨事件為案例，分析土石流發生情形，結果顯示將降雨因子納入考量的潛勢指標(RTSI)，在土石流發生潛勢上有較好的評估效果。本研究的研究成果可提供未來土石流事件在防災和減災時的參考。

Debris flow is a sediment-laden flow composed of loose sediment and water, which is delivered in the stream channel via gravity. This burst-geomorphic erosion process can be characterized as fast movement, having serious destruction to constructions and buildings that could be threaten to people’s life and properties. Hence, investigation about the occurrence of debris flows controlled by topographic and hydrological factors (e.g., rainfall and runoff) is an important issue for disaster prevention and mitigation. In this study, the weight of evidence method based on the Bayesian probability model, was applied to evaluate debris flow susceptibility in the Gaoping River basin that suffered 40 debris flow events during the period from 2005 to 2012. Based on this method, we can use current information of debris flow triggering (priori probability) with the controlling factors to estimate the influential weighting for each controlling factor (posterior probability). Here we considered the 12 topographic factors that includes river length, watershed area, elevation, topographic index, form factor, terrain and river slopes, normalized differential vegetation index (NDVI), percentage of landslide area, curvature, fractal dimension and lithology and one hydrological factor that is rainfall triggering index (RTI) to establish two susceptibility indices, i.e., the summation of weighting of each factor, which contain a hydrological factor (denoted by RTSI) or not (denoted by TSI). Results show that RTSI has the higher area of success rate curves and hence is more suitable for debris flow susceptibility mapping.

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