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This study investigated a dynamic stability analytical model for bedding rock slope with soil interlayer, considering various rain patterns. The critical rain intensities for anhydrous and water-filled fissure were derived, respectively. Rain coefficients (i.e., concentration and peak position coefficients) were subsequently introduced to investigate rain patterns. The evolving water head under different infiltration scenarios was derived based on Darcy's law and mass conversation law. Additionally, the time-varying water pressure along soil interlayer was obtained based on triangular distribution assumption. An analytical model incorporating time-varying water head was established to predict slope stability based on limit equilibrium method. Numerical simulations further validated the analytical solutions for time-varying water head and pressure. The evolving characteristic of slope stability was analyzed, and a failure threshold was proposed. Results demonstrated that rain patterns and rain coefficients significantly impact on the rainfall threshold corresponding to slope failure. For uniform rain-induced slope failure, rainfall threshold tends to increase as rain intensity decreases. For unimodal rain-induced slope failure, the rainfall threshold is the largest for post-peak rain corresponding to slope failure, followed by the medium-peak rain, and the smallest for forward-peak rain. These results and findings enhance our understanding of the dynamic stability of bedding rock slope with inclined soil interlayer and provide valuable insights into assessing the evolving slope stability under different rain patterns. Highlights: An analytical model of dynamic slope stability coupling time-varying water head was established. Impacts of rain pattern and rainfall intensity on slope stability were systematically investigated. Rainfall threshold for slope failure considering different rain patterns was proposed based on analytical model. 〹 [ABSTRACT FROM AUTHOR]

On 22 October 2018, at 17:20 (UTC+8), a bedding rockslide occurred on the right bank of the Jian-En expressway in Jianshi County, Hubei Province, Central China. Fortunately, a systematic displacement monitoring network provided an early warning. Thus, no casualties were caused by the rockslide, although two transport vehicles and three houses were damaged. To deduce the triggering factors and failure mechanism of the bedding rockslide, the geological characteristics, hydrogeological characteristics, slope excavation scheme, and rainfall data statistics were systematically investigated based upon field investigations, UAV photography, geological drilling, and laboratory tests. It was found that the bedding characteristics, presence of well-developed joints, and properties of the weak interlayers were the internal factors inducing the rockslide. The free face in front of the slope, the weak interlayer with low shear strength, and the through-going joint that formed the back boundary of slope constituted the boundary of the rockslide. The combined effects of improper slope excavation and concentrated rainfall were external factors that directly triggered the rockslide. The well-developed joints provided an effective infiltration channel for rainwater, and continuous rainfall deteriorated the shear strength of the weak interlayer ultimately causing the rockslide. [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]

The Huangtupo landslide is the volumetrically largest, most complex, and economically most significant landslide in the Three Gorges Reservoir Region. Detailed information about the character and dynamics of this tractive landslide is available because of access provided by a unique, 908-meter in situ research tunnel, augmented by long-term data provided by an extensive monitoring system for ground water levels, rainfall, and in situ deformation. Three major rupture surfaces plus 12 interlayer sliding zones (weak layers) were recognized during tunnel excavation, which also provided access and samples that establish a complex, multistage deformation history. Data from the in situ monitoring system shows that the toe of the landslide is creeping at a steady annual rate of about 25-30 mm, but at a slower rate of about 12 mm/year near the crown. However, the monthly creep rates are variable, being highest during May-August when rainfall is heavy and reservoir levels are low. Displacement-depth curves in the HZ6 borehole inclinometer establish that the creep of Slump Mass I# is most rapid above a depth of 37 m, where a major rupture zone occurs immediately above bedrock. Engineered defense structures along the toe of Huangtupo landslide can improve its stability to some extent. The effect of rapid changes of the reservoir level on landslide stability should be considered in reservoir management. [ABSTRACT FROM AUTHOR]

In recent years, a large number of bank destruction occur in the reservoir area under the effect of water fluctuation, which may be lead to reservoir accumulative landslide geological hazards finally. The paper conducted the bank destruction forecasting study for accumulative landslides in the Three Gorges Reservoir Region, China utilizing back-propagation (BP) neural network approach. A representative scenario of Jinle landslide is then taken for analysis purposes. On the basis of the existing data sets of bank destruction cases, the BP neural network forecasting model and the corresponding programs for bank destruction are both presented, whose forecasting result is validated by two independent approaches, namely empirical method and numerical modeling method. Furthermore, the BP neural network model had obvious advantages over the convention approaches in the aspects of the fast calculation speed and high convenience. According to the bank destruction forecasting scale presented above, the corresponding revetment measures can be proposed to prevent the occurring of the bank destruction, whose effectiveness has been further validated by the actual engineering practice. [ABSTRACT FROM AUTHOR]