Slope safety evaluation by integrating multi-source monitoring information

Abstract

A systematic method is presented for evaluating the slope safety utilizing multi-source monitoring information. First, a Bayesian network with continuously distributed variables for a slope involving the factor of safety, multiple monitoring indexes and their influencing parameters (e.g. friction angle and cohesion) is constructed. Then the prior probabilities for the Bayesian network are quantified considering model and parameter uncertainties. After that, multi-source monitoring information is used to update the probability distributions of the soil or rock model parameters and the factor of safety using Markov chain Monte Carlo simulation. An example of a slope with multiple monitoring parameters is presented to illustrate the proposed methodology. The method is able to integrate multi-source information based on slope stability mechanisms, and update the soil or rock parameters, the slope factor of safety, and the failure probability with the integrated monitoring information. Hence the evaluation becomes more reliable with the support of multiple sources of site-specific information.