Evaluating the likelihood of slope failure in ageing earthworks using Bayesian updating

Earthwork assets, including cut slopes and embankments, are essential components of the infrastructure supporting road and rail transportation networks. Asset owners must assess the stability of these slopes as they deteriorate, to prevent unwanted slope failures. Assessing the stability of individual earthworks within a portfolio using slope stability analyses can be expensive and time-consuming. Hence, a Bayesian logistic regression model was developed to evaluate the probability of slope failure, using training data from published case histories of slope failures. The Bayesian model was then used to assess the probability of failure for the more specific case of clay cut slopes within a railway earthwork asset portfolio owned by Network Rail (NR). The portfolio includes earthworks at various stages of degraded strength and with different drainage conditions. The results from models with material properties that were equivalent to those for the deteriorated strength of clays compared most closely with clay cut slope failures within the NR dataset. Steeper slopes (>35 degrees) had the highest probability of failure, regardless of the drainage condition. However, for shallower slopes, the poorly-drained slopes had a ≈20% higher probability of failure than the well-drained slopes.