山區面積佔台灣總面積約70 %，地質年代年輕且構造運動頻繁致使山區眾多區域地質破碎，且台灣年降雨量在世界排前10位，降雨多集中於夏季、颱風時期，強降雨致使山崩、土石流等地質災害頻傳，因此，降雨引致地質災害為為重要課題。目前常用邊坡災害預警方法多採經驗法則，依照歷史破壞案例進行統計分析並訂定相關警戒值，常用於土石流警戒之雨量警戒值即屬其中之一，此類方法具備簡易運用特性，因此廣泛使用於目前各相關單位，但經驗法屬區域、統計之概念，隨著氣候變遷，瞬時降雨強度明顯增強之情況下，經驗法仍有不足之處。本研究以土壤邊坡破壞機制區分淺層破壞與深層破壞，並發展符合其破壞機制之依時預警架構，基於考量水利與力學特性之水力力學耦合分析方法，依時分析降雨引致之土體水頭與有效應力耦合變化，建立無限土壤邊坡水力力學耦合分析架構，並以特定深度之體積含水量與地下水位作為淺層與深層破壞之依時監測指標，配合自主研發之物聯網感測模組，可提供監測場址即時與連續水力反應，作為警戒與行動依據。後續以甲仙攔河堰通達道路邊坡與台20線52公里處邊坡作為淺層與深層土壤邊坡潛在破壞場址，依現有鑽探與試驗結果，配合無限土壤邊坡水力力學耦合分析架構，客製化場址依時預警系統。研究成果適用於已知滑動面與場址相關水利與力學參數之重要邊坡保全對象，在考量嚴謹力學機制之無限土壤邊坡水力力學耦合分析架構下，依場址特性建立客製化依時預警，可增進預警系統之可靠性，並與傳統經驗法互補，提供不同需求之預警架構。

Under climate change, the landslide disaster induced by rainfall has become frequent than before. The empirical warning method based on the statistics results of history failure case, the short-duration intense rainfall cause inaccuracy in the empirical method. In this research, a time-dependent warning framework for the shallow and deep soil slope failure proposed. Based on the coupled hydromechanical analysis, the time-dependent infiltration analysis and slope stability analysis performed. Under the consideration of the failure mechanism of soil slope, the volumetric water content or the groundwater elevation is being as a time-dependent index for monitoring the failure behavior of a shallow or deep slope site. Moreover, the developed IoT sensing module can provide the real-time and continuous hydromechanical response in filed under the rainfall event. From above, a customized time-dependent warning system for rainfall-induced soil slope failure is constructed. The research results can provide judgment based on field evacuation for local administration.

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