A Probability-Based Framework for Evaluating Slope Failure Under Rainfall Using Coupled Finite Element Analysis

Rainfall is one of the major causes of geological hazards such as landslides and slope failures because it decreases shear strength along the failure surface and increases the driving force of the sliding mass due to the movement of the wetting front in the geological media. Deterministic limit equilibrium methods are typically used to evaluate the stability of slopes in terms of Factor of Safety (FoS), considering the worst-case scenario. However, a coupled flow deformation analysis procedure combined with a probabilistic method is required to consider the temporal and spatial variations in the soil properties due to water infiltration and to evaluate the probability of slope failure. The study aims to develop a probabilistic framework for evaluating the probability of failure of an earth slope using the response surface derived from sample data generated from a coupled flow–deformation finite element (FE) program considering uncertain rainfall characteristics. Finite slopes with 1.5H:1V and 2H:1V slope ratios composed of sandy soil were analyzed considering the possible variations in soil and rainfall parameters. Based on the FE results, a response surface was developed for the FoS as a function of soil and rainfall parameters. The response surface was utilized to generate random scenarios and calculate the failure probability using Monte Carlo Simulation (MCS). The results obtained from the MCS were compared using the First-Order Reliability Method (FORM). The results indicated that the total probability of failure predicted by MCS was closer to the probability of failure by FORM. The total probability of failure predicted from MSC and FORM were 0.0633 and 0.0640 for the 1.5:1 slope and 0.0249 and 0.0229 for the 2:1 slope, respectively. This level of probability of failure was deemed unsatisfactory to poor based on the criteria by the US Army Corps of Engineers. Therefore, the proposed framework provides a valuable tool from the probabilistic perspective for assessing the performance level of slopes subjected to uncertain rainfall conditions.