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Abstract Background Rock slope instability is a complex geotechnical issue that is affected by site-specific rock properties, geological structures, groundwater, and earthquake load conditions. Numerous studies acknowledge these aleatory uncertainties in slope stability assessment; however, understanding the rock behaviour could still be improved. Therefore, this paper aims to summarise the probability methods applied in rock slope stability analysis in mining and civil engineering and develop new probabilistic design and assessment methodologies for four methods, namely empirical/rock mass classifications techniques, kinematic analysis, limit equilibrium (LE), and numerical methods and introduces how to integrate all methods to determine the total probability of failure. The case studies have been conducted based on slopes from Indonesia, a seismically active country, utilising the proposed design methods. Results Regarding the probabilistic empirical/rock mass classification (RMC) technique, this study has identified that seven of the ten most involved input parameters in RMC naturally exhibit aleatory uncertainty. Thus, the optimal way to present the output probability of RMC is as a confidence interval (CI) or total and conditional probability associated with each rock mass class. In probabilistic kinematic analysis, this study presents a systematic method to compute the probabilities of different types of failure alongside the total probability of occurrence (P tK ). The probability of failure (PoF) for jointed generalized Hoek-Brown (GHB) numerical modelling was lower than that obtained through the probabilistic LE approach for a similar slope. However, the PoF of jointed GHB is higher than the LE approach when loaded with 0.1 and 0.15 earthquake coefficients. Conclusions The variation of PoF across different failure criteria determines how epistemic uncertainty is apparent in the modelling process, while the aleatory uncertainty arises from input parameters. Furthermore, this study introduces the total probability of failure equation as a combination of kinematic and kinetic probabilities (limit equilibrium and numerical modelling). |
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