Effects of the spatial variability of permeability on rainfall-induced landslides

• Ks was modeling as a non-stationary lognormal random field.
• Generalized effective stress was adopted to analyze the slope stability.
• Probabilistic frame of rainfall-induced landslide was presented.
• Effects of the variability and trend component of Ks on the slope stability were investigated.

The saturated hydraulic conductivity (Ks) of soil is characterized by strong spatial variability and often decreases with depth. The main objective of this paper is to investigate how the trend function of the mean of saturated hydraulic conductivity (μKsμKs) and its spatial variability affect the distribution of critical failure surfaces and the probability of slope failure during a period of rainfall. A random field method is used to simulate the spatial variability structure in the numerical analysis of a slope, and a numerical procedure for a probabilistic slope stability analysis based on Monte Carlo simulations is presented, in which Ks is modeled as a non-stationary lognormal random field. For a hypothetical weathered soil slope subjected to rainfall, a deterministic analysis and a sequence of probabilistic analyses are conducted using an infinite unsaturated slope model. The results show that these shallow failures are attributed to the reduction of matric suction and the development of positive pore pressure. The probability of slope failure increases with an increase in the variation of the trend component (Δk  ), but the rate of increase levels off at the later stage of rainfall. Ignoring the trend component of μKsμKs would lead to less conservative estimates of the failure probability. The coefficient of variability has a more significant influence on the distribution of the critical failure surfaces and the probability of failure than does the correlation length of Ks.