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Accurate estimation of slope stability based on numerous candidate estimation methods is difficult as different results may be yielded. It becomes even more challenging when only limited data of geotechnical parameters (e.g., shear strength parameters) are available to evaluate slope reliability. Based on the Bayesian sequential updating technology, a hybrid framework for slope reliability was proposed in this study, through which prior knowledge, multiple estimation methods, and corresponding model uncertainties could be integrated to estimate slope reliability using a small amount of geotechnical data. Three slope examples with various stratigraphic configurations and soil properties were used to illustrate the accuracy and efficiency of the proposed framework, during which the Bishop's simplified method, the upper bound limit analysis method, and the finite element method were adopted. The results showed that with results of direct Monte Carlo simulation based on each method as the benchmark, a compromised mean of the factor of safety (μFS), and conservative standard deviation of the factor of safety (σFS) and failure probability (Pf) were yielded through the proposed framework. When the sample size of geotechnical parameters was greater than a threshold, the estimated μFS was stable, while the σFS and Pf synchronously varied within a small range with the increase in sample size. Demonstrations of the three examples indicated that the proposed hybrid framework can provide reliable and accurate estimations of slope reliability. The proposed framework may serve as a promising vehicle for slope/landslide engineering including failure and preventative mechanisms, movement prediction, and back analysis of geotechnical parameters in a probabilistic context, and big data analysis of geological and geotechnical problems as well. [ABSTRACT FROM AUTHOR]

Rainfall represents one of the most significant cause of landslide hazards. With runoff in the saturated zone of shallow soil considered, an improved Green–Ampt model was proposed to depict the rainfall infiltration process. Furthermore, a formula for calculating the depth of wetting front was derived, and the slope stability was evaluated accordingly. Finally, a formula for calculating the safety factor of multilayer slopes above different surfaces was obtained via the limit equilibrium method. An illustration is a multilayer colluvial slope in Guangdong Province of China, the results indicated that the downward speed of wetting front decreases gradually within the same layer with continuous rainfall but increases significantly when it extends to the interfaces between the soil layers. Safety factor of the slope decreases sharply at the initial stage of rainfall but then more slowly. Slope failure is more likely to occur along the first interface between the soil layers than along the surface of wetting front. The result from the proposed model is closer to the result of the physical model test than from the existed Green–Ampt model. The improved Green–Ampt model for multilayer slopes can accurately evaluate the infiltration process and related stability of multilayer slopes under rainfall. [ABSTRACT FROM AUTHOR]

The Green-Ampt (GA) model is one of the most widely used analytical methods of slope stability under rainfall. However, it may overestimate the soil water content above the wetting front. In this study, a novel approach to evaluate the time-dependent slope stability during intense rainfall based on a modified GA model is presented, and is known as the stratified Green-Ampt (SGA) model. By considering the stratified soil water content above the wetting front, the soil above the wetting front can be divided into saturated and transitional layers, and the SGA model is used to analyze the infiltration process of intense rainfall into slopes. Thereafter, safety factors (Fs) of infinite and finite slopes are derived using the SGA model. In the analysis of an infinite slope, the conventional limit equilibrium method is adopted to calculate the safety factor; as for a finite slope, the residual thrust method is introduced to obtain the safety factor with sliding mass divided into multiple soil slices. The performance of the SGA model is illustrated in two cases: an infinite slope and the Majiagou landslide as a finite slope. The results indicate that compared to the GA model, the calculated wetting front based upon the SGA model moves faster, and the wetting front depth shows a positive correlation with the slope surface angle and rainfall intensity. The evolution of the safety factor above the sliding surface can be divided into three phases, while the evolution of the safety factor above the wetting front can be divided into two phases. The critical time of the slope reaching a less stable state (safety factor is 1.05) or unstable state (safety factor is 1.00) decreases exponentially with an increase in rainfall intensity. In addition, the rainfall has a significant influence on the design of stabilizing piles for the Majiagou landslide. The presented SGA model appears to be accurate to investigate slope stability during intense rainfall events. [ABSTRACT FROM AUTHOR]

Multi-layer slopes are widely found in clay residue receiving fields. A generalized horizontal slice method (GHSM) for assessing the stability of multi-layer slopes that considers the energy dissipation between adjacent horizontal slices is presented. In view of the upper-bound limit analysis theory, the energy equation is derived and the ultimate failure mode is generated by comparing the sliding surface passing through the slope toe (mode A) with that below (mode B). In addition, the influence of the number of slices on the stability coefficients in the GHSM is studied and the stable value is obtained. Compared to the original method (Chen's method), the GHSM can acquire more precise results, which takes into account the energy dissipation in the inner sliding soil mass. Moreover, the GHSM, limit equilibrium method (LEM) and numerical simulation method (NSM) are applied to analyze the stability of a multi-layer slope with different slope angles and the results of the safety factor and failure mode are very close in each case. The ultimate failure modes are shown to be mode B when the slope angle is not more than 28°. It illustrates that the determination of the ultimate sliding surface requires comparison of multiple failure modes, not only mode A. [ABSTRACT FROM AUTHOR]