Probabilistic fragility assessment of slopes considering uncertainty associated with temporal patterns of rainfall intensity

The temporal patterns of rainfall intensity, characterized by the variability of rainfall intensity over time during a single rainfall event, play a crucial role in landslide triggering and evolution. However, the influence of temporal patterns of rainfall intensity on the fragility and reliability assessment of slope instability has received limited attention. This study presents a novel methodology for probabilistic slope fragility assessment accounting for uncertainty associated with the temporal patterns of rainfall intensity. Hourly-scale random time series for the rainfall event are generated, considering uncertainties in temporal patterns of rainfall intensity, using the statistical concepts of skewness and kurtosis within the Pearson system of distributions. A time-dependent seepagestability mechanical model coupling the finite element method and limit equilibrium method for the slope under hourly-scale rainfall time series is established. Slope fragility assessment under rainfall is conducted, accounting for uncertainties in temporal patterns of rainfall intensity based on Monte Carlo simulation. An illustrative example is provided, focusing on a hypothetical soil slope in the southeastern coastal area of China, susceptible to rainfall-induced landslides. The impact of skewness and kurtosis of rainfall time series on the slope failure probability and failure time are examined.