Effects of soil spatial variability on rainfall-induced landslides
This paper presents a probabilistic framework to assess the stability of unsaturated slope under rainfall. The effects of soil spatial variability on the probability of rainfall-induced slope failure (landslides) are investigated. Soil spatial variability is considered by modeling the saturated hydraulic conductivity of the soil (ks) as a stationary lognormal random field. Subset simulation with a modified MetropolisHastings algorithm is used to estimate the probability of slope failure. It is demonstrated numerically that probabilistic analysis accounting for spatial variability of ks can reproduce a shallow failure mechanism widely observed in real rainfall-induced landslides. This shallow failure is attributed to positive pore-water pressures developed in layers near the ground surface. In contrast, analysis assuming a homogeneous profile cannot reproduce a shallow failure except for the extreme case of infiltration flux being almost equal to ks. Therefore, ignoring spatial variability leads to unconservative estimates of failure probability. The correlation length of ks affects the probability of slope failure significantly. The applicability of subset simulation with a modified MetropolisHastings algorithm to assess the reliability of problems involving spatial variability is highlighted.
spatial variability rainfall-induced landslide subset simulation metropolishastings algorithm probabilistic analysis unsaturated seepage