Reliability Analysis of Slope Stability Considering Uncertainty in Water Table Level

Abstract

Geotechnical analysis and design are usually based on traditional methods and empirical relationships. However, various challenges, such as the inability to model all parameters involved and the uncertainty of model input, make these methods ineffective. Therefore, probabilistic methods recently began to be used to estimate the probability of slope failure. In this study, slope stability is presented as an optimization problem and the simulated annealing (SA) method is used to identify the slip surface with the minimum safety factor. The SA algorithm is then integrated with the Monte Carlo sampling method to calculate the probability of slope failure. Next, the groundwater level is added to the problem formulation as a random variable to model the uncertainty for cases where the groundwater table is not accurately determined. The results of the analysis show that for slopes with low safety factors, the uncertainty of the groundwater table worsens the condition and increases the failure probability. Moreover, the parametric study shows that the insufficient understanding of groundwater-level distribution and the assumption of uniform distribution further increases the failure probability. The results of this study are presented in the form of a probability curve against the groundwater table. This presentation has practical applications in real projects.