The uncertain mechanical parameters of clay layer under torrential rain are the key to the dynamic evolution process and stability assessment of landslide geological hazards. Due to the complex environment, engineering geology and physical chemistry process, the mechanical parameters of clay layer show significant spatial variability and correlation. In addition, due to technical and economic conditions constraints, the actual investigation and test data of soft cohesive soil are very limited, which seriously restricts the stability evaluation of clay slope and the prevention of instability disaster. To characterize anisotropic spatial variations of uncertain mechanical parameters for clay layer using incomplete probability data, the elastic modulus, Poisson ratio and shear strength under saturated conditions were measured, and statistical data and variation properties of uncertain mechanical parameters were analyzed. A modeling approach was proposed for characterizing incomplete probability data of clay layer. The accuracy of the proposed approach is verified by comparison of the statistical characteristic for measured data and simulated data. A novel linear fitting method was proposed for assessing scale of fluctuation and autocorrelation distances. The variability and correlation of uncertain mechanical properties for soft cohesive soil layer are discussed. The results show that the mechanical properties of the clay layer are uncertain in spatial position. Both the original observation data and the simulated data of three mechanical parameters have symmetrical correlation structure. The clay layer display the horizontal layered structure on the soil profile, and the vertical autocorrelation distances are shorter than the horizontal distances. This paper clearly illustrates the anisotropic spatial variations of uncertain mechanical parameters for clay layer using incomplete probability data and it can provide scientific data for the uncertainty analysis and risk assessment of clay slope under torrential rain conditions.

Quantitative assessment of landfill slope failure risk provides valuable information about slope design and risk reduction. This study presents a reliability-based analysis in which an accurate method is applied to assess slope failure risk using the stochastic finite difference method. This method incorporates the spatial variability of municipal solid waste properties due to anisotropic autocorrelation structures and evaluates the consequence associated with each failure separately. This method was evaluated using the data of the Saravan landfill (Rasht, Iran) and presenting a parametric analysis. Several Monte Carlo simulations were conducted to indicate the heterogeneity of the municipal solid waste, taking into account the shear strength and the unit weight of the municipal solid waste randomly. Finally, the safety factor, probability of failure, and risk were assessed using different analysis cases. Deterministic analysis was also performed for all modes using mean values for various municipal solid waste properties. The results show that spatial variability of municipal solid waste parameters and autocorrelation structures significantly affect the safety factor, probability of failure, and risk. Also, comparing the obtained results revealed that for the given slope, the safety factor values in deterministic analyses are overestimated compared to those of the probabilistic analyses. However, risk shows the opposite behavior.