Combining Statistical Design with Deterministic Modelling to Assess the Effect of Site-Specific Factors on the Extent of Landslides

Abstract

Landslides may be triggered by a variety of external factors and can lead to dramatic human and economic consequences. Systematically investigating all possible parameters that could potentially influence the extent of a landslide is costly and generally not practical. In this paper, a methodology to numerically assess the impact of potential landslides is proposed. In this approach the landslide simulations were carried out using finite element model estimates of potential failure volume as an input into a discrete element model which is used to assess run-out and consequences. A statistical design of experiments was implemented to determine the most important factors influencing the landslide extent thereby significantly reducing the number of simulations required. The method is illustrated on a case study of potential failure of an overburden dump at a coal mine. Over the parameter ranges considered, the particle–particle (rock block to rock block) friction coefficient and the volume of failing material were determined to be the most important factors influencing the extent of the landslide. A systematic analysis of varying the particle–particle friction coefficient was then undertaken to better understand the dynamics of the collapse and different types of collapses were identified between low and high inter-particle friction coefficients. The methodology proposed in this paper should be of interest to practitioners as a way to thoroughly yet efficiently identify and assess the main factors influencing a potential landslide on sites at risk.