Abstract
Rainfall and water level change are two of the main factors causing failure of reservoir slopes. Thus, soil-fluid mechanics is applied with the fluctuation of groundwater table. However, many of the geotechnical parameters needed for the analysis are highly varied. Spatial random field-based Bayesian method is proposed, which can systematically assimilate prior knowledge, borehole testing data, and long-term monitoring data to obtain posterior distributions. There are three major components of the method. They include unsaturated soil-fluid coupling mechanics, spatial multivariate discretization, and subset Monte Carlo simulation of reliability analysis. The approach is applied to the Shiliushubao slope of the Three Gorges Reservoir area, which is located 9.0 km downstream of the Badong County in Hubei Province, China. Results prove that the updated key geotechnical parameters will quantitatively predict the geohazards of landslide, especially for unsaturated soil slope conditions that suffer an unprecedented heavy rainfall subject to low reservoir water level in the upcoming summer.
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Funding
The above work is sponsored by the Shanghai Pujiang Program (18PJ1403900) and Key Laboratory of Geotechnical and Underground Engineering of Ministry of Education, Tongji University (KLE-TJGE-B1706). Research is also supported by the Program for Professor of Special Appointment (Eastern Scholar) at the Shanghai Institutions of Higher Learning (TP2018042).
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Huang, M.L., Sun, D.A., Wang, C.H. et al. Reliability analysis of unsaturated soil slope stability using spatial random field-based Bayesian method. Landslides 18, 1177–1189 (2021). https://doi.org/10.1007/s10346-020-01525-0
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DOI: https://doi.org/10.1007/s10346-020-01525-0