Uncertainty quantification of three factors by geostatistical simulations applied to a stability analysis case study using a discrete element method

Uncertainties of sliding surfaces and structures of soil-rock mixture are two critical factors that affect slope stability. In this study, an uncertainty slope stability analysis method of a landslide with several potential sliding surfaces is proposed. Two geostatistical simulation methods, i.e., single normal equation simulation and sequential indicator simulation, are chosen to quantify the geological uncertainty of slopes by generating a large number of simulation maps with different positions of potential sliding surfaces and different structures of soil-rock mixtures. These maps are imported into the discrete element method program MatDEM, and uncertainty analysis is carried out through Monte Carlo simulations. A case study named Dahua landslide is carried out using the proposed method, where limited monitoring data is available. Based on the results of uncertainty analysis, it is found that displacements of most areas in the Dahua landslide are very small, and the frontal part of this slope is the most dangerous. Through field survey found that there are many large cracks in the frontal part of the Dahua landslide.