The spatial variability of soil properties is often assumed to be modeled as stationary or weakly stationary random fields in slope reliability analyses. However, abundant site-specific data have revealed that the mean and standard deviation of soil properties, such as the undrained shear strength of soil, change with depth. Thus, the non-stationary characteristics of soil properties need to be properly accounted for. The aim of this paper is to propose a non-stationary random field (RF) model for the characterization of the spatial variability and the depth-dependent nature of the undrained shear strength of soil. With the proposed model, the uncertainties of the trend and fluctuating components can be modeled individually. As an example, a clay slope under undrained conditions is investigated to illustrate the proposed model. A subset simulation is carried out to evaluate the slope reliability incorporating the non-stationary characteristics of soil properties. The advantages of the proposed model, relative to the existing non-stationary RF models and the commonly-used stationary RF model in the literature, are demonstrated through a series of sensitivity studies.
Jiang et al. (Thu,) studied this question.