Stochastic Analysis of Reservoir Bank Landslide by Considering the Spatial Random Field Characteristics of Hydraulic Parameter

Rainfall and water level change are two main factors causing failure of reservoir slopes. Thus, many geotechnical parameters needed for the analysis are highly varied. Spatial random fields-based Bayesian method is proposed, which can systematically assimilate prior knowledge, borehole test data, and long-term monitoring data to obtain posterior distributions. There are three major components of the method. The approach is applied to the Shiliushubao slope of the Three Gorges Reservoir area. Results prove that the updated key geotechnical parameters will quantitatively predict the geohazard of landslide, especially for unsaturated soil slope that suffers an unprecedented heavy rainfall when the reservoir water level is low in the summer. According to the conditions of heavy rainfall and rapid rise and fall of the Yangtze River water level in 2020, the reliability analysis of the old Shiliushubao landslide is carried out in the Three Gorges Reservoir area. The results for the two different conditions both indicate that the safety factor of the slope stability is low, but the reliability index meets the minimum requirement of 2.70 according to the specification. None of the additional reinforcement measures are required.