期刊
COMPUTERS AND GEOTECHNICS
卷 48, 期 -, 页码 72-81出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.compgeo.2012.09.011
关键词
Rainfall infiltration; Unsaturated soils; Slope failure; Bayesian theory; Markov Chain simulation
类别
资金
- Natural Science Foundation of China [41172252, 41002097]
- State Key Laboratory of Ocean Engineering Self-Development Grant [GKZD010053 (2011)]
- Science and Technology Committee of Shanghai [12QA1401800]
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. (C) 2012 Elsevier Ltd. All rights reserved.
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