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Landslides, which are a type of process-based geological hazard, exhibit stagewise characteristics that serve as important guidance for the prevention and mitigation of slope engineering disasters. The cross-correlation and randomness of soil parameters can influence the evolution of landslide characteristics. This paper, based on the spatial variability of slope soil parameters, combines copula theory and the material point method (MPM) to establish a Monte Carlo-random material point method considering the cross-correlation of soil parameters. This resulting method is called copula-RMPM. It investigates the probability distributions of slope instability and landslide large deformation characteristics, such as sliding distance, landslide thickness, collapse range, and volume of sliding mass. The results indicated that in the study of soil parameter characteristics, failure probability increases with increased correlation coefficient. Also, failure probability showed a positive correlation with the variability coefficient of cohesion and internal friction angle, with failure probability being more sensitive to the variability coefficient of the internal friction angle. The landslide large deformation characteristics generally follow the normal distribution; they exhibit significant fluctuations in sliding distance and sliding mass area despite the relatively small variability coefficient. Compared with the results of random field simulation of soil parameters, the probability of landslide large deformation characteristics obtained by deterministic soil parameters is often lower. Therefore, the probability distribution of landslide large deformation characteristics obtained by the Monte Carlo-random material point method considering the cross-correlation of soil parameters is more meaningful for engineering guidance.

来源平台：NATURAL HAZARDS REVIEW