Quantitative assessment of landslide risk using Monte Carlo material point method

Abstract

PurposeThe purpose of this paper is to provide an effective way to assess landslide risk quantitatively. Quantitative assessment plays an important role in mitigating the landslide risk and developing a landslide risk-based warning system. However, efficient risk assessment on the large deformation failure process of slope with spatially variable soils is a challenging problem.Design/methodology/approachCombining the Monte Carlo simulation (MCS) and the higher-order material point method – the B-spline Material Point Method (BSMPM) – the concept of MC-BSMPM to assess the landslide risk quantitatively is proposed in this paper. The overall dynamic evolution of soil slope failure has been simulated by the BSMPM, and the probability density function of the sliding duration, the sliding kinematic energy, the sliding mass and the sliding distance of the landslide are obtained based on the MCS. Through the four risk assessment parameters of the sliding duration, the sliding kinematic energy, the sliding mass and the sliding distance, the landslide risk could be assessed quantitatively.FindingsIt is found that the post-failure behavior of the landslide conforms well to a normal distribution as the soil physical parameter is in a normal distribution. The variation of soil’s shear strength affects the dynamic motion of the landslide greatly.Originality/valueThe result shows that the landslide hazard cannot be estimated comprehensively by the deterministic BSMPM, while the landslide risk could be more clearly understood and quantitatively assessed with more details by the proposed method, which demonstrates that the MC-BSMPM method is an effective way to assess the landslide risk quantitatively.