Probabilistic parameter estimation and predictive uncertainty based on field measurements for unsaturated soil slope |
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| Institution: | 1. MOE Key Laboratory of Road and Traffic Engineering, College of Transportation Engineering, Tongji University, Shanghai 201804, China;2. Faculty of Engineering, China University of Geosciences (Wuhan), Wuhan, Hubei 430074, China;3. Glenn Department of Civil Engineering, Clemson University, Clemson, SC 29634, USA;4. Department of Civil Engineering, National Central University, Jhongli 32001, Taiwan;1. Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China;2. Glenn Department of Civil Engineering, Clemson University, Clemson, SC 29634, USA;3. Department of Civil Engineering, University of Akron, Akron, OH 44325-3905, USA;1. Faculty of Engineering, China University of Geosciences, Wuhan, Hubei 430074, China;2. Department of Civil and Environmental Engineering and Engineering Mechanics, The University of Dayton, Dayton, OH 45469-0243, USA;3. Department and Civil Engineering and Graduate Institute of Applied Geology, National Central University, Taoyuan City 32001, Taiwan |
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| Abstract: | A key issue in assessment of rainfall-induced slope failure is a reliable evaluation of pore water pressure distribution and its variations during rainstorm, which in turn requires accurate estimation of soil hydraulic parameters. In this study, the uncertainties of soil hydraulic parameters and their effects on slope stability prediction are evaluated, within the Bayesian framework, using the field measured temporal pore-water pressure data. The probabilistic back analysis and parameter uncertainty estimation is conducted using the Markov Chain Monte Carlo simulation. A case study of a natural terrain site is presented to illustrate the proposed method. The 95% total uncertainty bounds for the calibration period are relatively narrow, indicating an overall good performance of the infiltration model for the calibration period. The posterior uncertainty bounds of slope safety factors are much narrower than the prior ones, implying that the reduction of uncertainty in soil hydraulic parameters significantly reduces the uncertainty of slope stability. |
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