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Water 2017, 9(10), 758; https://doi.org/10.3390/w9100758

Uncertainty of the Soil–Water Characteristic Curve and Its Effects on Slope Seepage and Stability Analysis under Conditions of Rainfall Using the Markov Chain Monte Carlo Method

1
School of Civil Engineering and Architecture, Nanchang University, Nanchang 330031, China
2
School of Civil Engineering and Architecture, Jiangxi Science and Technology Normal University, Nanchang 330013, China
3
School of Civil Engineering and Architecture, Nanchang Institute of Technology, Nanchang 330099, China
*
Author to whom correspondence should be addressed.
Received: 25 August 2017 / Revised: 20 September 2017 / Accepted: 29 September 2017 / Published: 9 October 2017
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Abstract

It is important to determine the soil–water characteristic curve (SWCC) for analyzing slope seepage and stability under the conditions of rainfall. However, SWCCs exhibit high uncertainty because of complex influencing factors, which has not been previously considered in slope seepage and stability analysis under conditions of rainfall. This study aimed to evaluate the uncertainty of the SWCC and its effects on the seepage and stability analysis of an unsaturated soil slope under conditions of rainfall. The SWCC model parameters were treated as random variables. An uncertainty evaluation of the parameters was conducted based on the Bayesian approach and the Markov chain Monte Carlo (MCMC) method. Observed data from granite residual soil were used to test the uncertainty of the SWCC. Then, different confidence intervals for the model parameters of the SWCC were constructed. The slope seepage and stability analysis under conditions of rainfall with the SWCC of different confidence intervals was investigated using finite element software (SEEP/W and SLOPE/W). The results demonstrated that SWCC uncertainty had significant effects on slope seepage and stability. In general, the larger the percentile value, the greater the reduction of negative pore-water pressure in the soil layer and the lower the safety factor of the slope. Uncertainties in the model parameters of the SWCC can lead to obvious errors in predicted pore-water pressure profiles and the estimated safety factor of the slope under conditions of rainfall. View Full-Text
Keywords: soil–water characteristic curve; unsaturated soil; Bayesian approach; Markov chain Monte Carlo method; confidence interval soil–water characteristic curve; unsaturated soil; Bayesian approach; Markov chain Monte Carlo method; confidence interval
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Liu, W.; Luo, X.; Huang, F.; Fu, M. Uncertainty of the Soil–Water Characteristic Curve and Its Effects on Slope Seepage and Stability Analysis under Conditions of Rainfall Using the Markov Chain Monte Carlo Method. Water 2017, 9, 758.

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