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氣候變異引致降雨強度改變下未飽和邊坡信賴度之評估

Reliability Analysis of Unsaturated Slope Stability Due to Precipitation Variation

摘要


氣候變異的影響造成降雨量的改變,進一步的對土體邊坡會造成相當大的影響。當降雨強度的增加時,會影響到未飽和土壤邊坡不穩定發生的情形。當降雨入滲至邊坡內部時,土壤的基質吸力隨降雨入滲而改變,導致許多推估邊坡穩定性的參數不確定性增加。本研究利用信賴度分析,以機率分佈輸入土壤力學參數不同於傳統輸入定值,進而評估信賴指標(reliability index)。本研究主要考量氣候變異造成降雨強度改變,設計兩種不同的案例,一為土壤水力傳導係數大於降雨強度,另一為土壤水力傳導係數小於降雨強度,以信賴指數進行土體邊坡安全的評估,並利用各時間點的孔隙水壓變化,探討降雨入滲至邊坡的影響機制。本研究應用模擬降雨入滲至未飽和土壤邊坡內部,首先進行邊坡暫態滲流分析,將所評估之孔隙水壓空間分布代入邊坡穩定分析,計算出各時間點邊坡信賴指標,進而探討降雨強度與土壤水力傳導係數。本研究結果顯示,當土壤水力傳導係數大於降雨強度時,於降雨事件開始信賴指數就發生明顯下降,於降雨事件開始6小時後,下降幅度趨於平緩,下降為初始信賴指數的23%。另外,當土壤水力傳導係數小於降雨強度時,降雨入滲發生時,信賴指數有一段7小時的遲滯,其後發生一大幅度的下降,下降為初始信賴指數的65%。模擬結果指出當氣候變異造成一強降雨發生時,如果土壤水力傳導係數小於降雨強度時,邊坡發生不穩定的時間會相對降雨強度小較早發生。

並列摘要


The precipitation variation can potentially alter the stability of unsaturated slopes. The stability of the unsaturated slope decreased with the rainfall infiltration. There are numerous parameters that need to be analyzed to assess the unsaturated slope stability.In this study, we used a reliability analysis to assess the stability of unsaturated slopes. The numerical software Geo-Studio was used to simulate rainfall infiltration in the unsaturated soil. Two cases were simulated to determine the important parameters that affected the unsaturated slopes. The first case, we selected a fixed rainfall intensity, I=7.0×10^(-5) m/s, and two hydraulic conductivities, ks=2.15×10^(-4) m/s and ks=2.15×10^(-5) m/s. The second case, we selected a fixed hydraulic conductivity, ks=1.0×10^(-6) m/s, and two rainfall intensities, I =1.1×10^(-6) m/s and I=8.3×10^(-7) m/s. The finite element method and limit equilibrium method are used to simulate rainfall infiltration of different rainfall patterns and calculate the reliability index with time to assess the soil slope stability.For the first case, when the ks is greater than I, the reliability index decreased immediately by a quarter and remained stable after 6 hours. When the ks is less than I, the reliability index stayed the same till 7 hours later when the reliability index dropped by 65%. For the second case, when the ks is less than I the probability of landslide was greater than when the ks is greater than I.

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