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Estimation of the uncertainties of geotechnical parameters is a fundamental task in slope reliability analysis, and it becomes more challenging when only limited data on geotechnical parameters are available. In this study, a Bayesian bootstrap-Copula coupled method is proposed for slope reliability analysis based on limited geotechnical data. Specifically, the bivariate distribution of shear strength parameters ((cohesion (c) and friction angle (φ)) can be evaluated using the Bayesian bootstrap method and Copula theory, and then the slope reliability can be calculated using Monte Carlo simulation (MCS). Application to a homogeneous, undrained cohesive slope demonstrates the accuracy and effectiveness of the proposed approach. The results indicate that even when data are limited, the bivariate distribution of c and φ can be determined and the estimated statistics met the predefined ones well. Satisfying estimations of the mean ( μ FS ) and standard deviation ( σ FS ) of the factor of safety (FS) and failure probability (Pf) can be obtained. The representative sliding surface with the greatest likelihood is found to approximate the critical one based on the mean values of c and φ. Besides, when the available sample size of geotechnical data exceeds a threshold, stable estimations of the bivariate distribution of c and φ can be obtained, and the estimated μ FS is stable, while the values of σ FS and Pf synchronously vary within a small range. Applications of the proposed Bayesian bootstrap-Copula coupled method indicate that it can be used to estimate the bivariate distribution of correlated parameters and the reliability of various geotechnical problems based on limited data. [ABSTRACT FROM AUTHOR]

Analyzing and quantifying the deformation process of landslides is of paramount importance in facilitating landslide early warning. As such, this study is committed to proposing a universal phenomenological model for deformation stages division and early warning of landslides based on the kinematic features. First, five landslide deformation patterns were classified based on the creep theory, and suggestions for stage division of each deformation pattern are presented. Then, the statistical characteristics of landslide velocity were analyzed, and a probability-based deformation stage division method was proposed. Finally, the Comprehensive Standardized Deformation Index (CSDI) model, which includes the calculation of the CSDI M - M (Min-Max normalization) and CSDI M (Mean normalization) was proposed and verified in 24 landslides worldwide. The results show that, except for the oscillating pattern, the CSDI M - M is feasible in the stages division of all deformation patterns with a strong correspondence with the actual state of the landslides. The CSDI M is a reliable landslide warning criterion and threshold determination method, as it is effective in the early warning of imminent landslides with a low false alarm rate. The CSDI model provides new insight into the division of landslide deformation stages and landslide risk assessment. [ABSTRACT FROM AUTHOR]

A large-scale obliquely inclined bedding rockslide, activated by a heavy rainstorm, occurred on July 8, 2020, at 7:05 (UTC + 8) in Shiban Village, Songtao Miao Autonomous County, Guizhou Province, China. The loss of life in this event was greatly reduced owing to the local warning system for rainstorm-induced geohazards. To understand the failure characteristics, triggering factors, the genetic mechanism of the landslide, the geomorphological features, geological characteristics, hydrological conditions, and rainfall characteristics were systematically studied by a synthetic approach including field investigations, satellite imagery, unmanned aerial vehicle (UAV) photography, laboratory tests, and rainfall data statistics. The results indicated that the interface between the soft and hard rock, the well-developed joints, and the free face in front of the slope constituted the boundaries of this landslide. The concave topography at the back and southern edge of the landslide, the bare ground, and the cataclastic structure of the rock mass provided favorable conditions for the collection or infiltration of rainwater. The concentrated rainstorm was the direct trigger for the landslide, which led to a rapid inflow and retention of rainfall in the landslide through favorable landform and geological conditions. The groundwater recharge that cannot be drained in time caused the mechanical deterioration of rock mass and induced a rapid increase in pore water pressure in the landslide. Moreover, the water level of the Ganlong River at the toe of the slope also rose rapidly, and the uplift pressure in front of the slope increased accordingly. Under the combined action of these adverse factors, the overall anti-sliding force of the slope was less than the sliding force, finally resulting in the landslide. Remarkably, the local warning system for rainstorm-induced geohazards successfully forecasted the landslide, but the shortcoming is that the forecast time in advance is short. Nevertheless, the prediction has significantly reduced human casualties and provided valuable experience for the prediction of this type of landslide. [ABSTRACT FROM AUTHOR]

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]

Rock avalanches often cause many casualties and considerable property damage due to hypermobility. To better understand the propagation process of rock avalanches, the mechanical energy evolution was investigated based on numerical simulation method and field investigation. Taking the well-known Jiweishan landslide as an example, the kinetic, potential, and dissipation energy elements were extracted from the kinematics parameters, and effective collisions were determined by calculating the local peaks of velocity. The lower velocity regions were observed in the middle portion of the sliding mass. Blocks in these regions were the medium through which the energy was transferred from the back portion of sliding mass to the front portion, acting like the stationary spheres in Newton's Cradle. The entire sliding mass followed the law of conservation of energy, while the energy evolution of the individual blocks varied by their locations. Considering that more collisions occurred in the front portion of the sliding mass, blocks in this area received more energy during propagation, thus they traveled a longer distance. Furthermore, the energy transfer became more obvious with the increase in the volume of sliding mass, causing a larger travel distance for the rock avalanche. [ABSTRACT FROM AUTHOR]

An increasing number of landslides are occurring during the construction of highways in mountainous areas all over the world. A recent highway landslide located in the mountainous region of Southwest China is taken as a representative example to carry out the initiation mechanism and deformation characteristics analysis, and study the intelligent partitioning method in this paper. The geological conditions of the landslide are obtained through detailed geological surveys and investigation. A three-dimensional (3D) monitoring network with a total of 72 multi-points, including 53 surface displacement monitoring points and 19 deep displacement monitoring holes, is established to examine the spatial deformation characteristics of the landslide for nearly 25 months. The monitoring results of the surface displacement show that the dynamic deformation of the landslide can be divided into three stages, namely initial deformation stage, accelerated deformation stage, and stabilization stage. Based on the strata distribution obtained by the borehole investigation and the results of deep displacement monitoring, the depth of the slip surface can be reliably determined. The smart contract method in blockchain technology combined with the multi-point monitoring dataset is novelty applied to realize the intelligent automatic partition of the highway landslide without any human involvement. This method can provide the basis for further independent analysis of different landslide zones. According to the investigation and analysis, the initiation mechanism for the highway landslides is attributed to both internal poor geological conditions and external intense precipitation and engineering excavation. [ABSTRACT FROM AUTHOR]

The mechanical properties of stabilizing piles are directly affected by the spatial structure of the bedrock of landslides. To effectively reinforce landslides with a sandwich-type bedrock, the interaction mechanism between manually excavated stabilizing piles and the different types of bedrock must be investigated. The research presents experimental models of manually excavated stabilizing piles for two kinds of sandwich-type bedrock structures, namely hard rock–dominant interlayered bedrock (HDIB) and weak rock–dominant interlayered bedrock (WDIB). Six physical models with different bedrock structure types and dip angles θ were prepared to explore the influence of these two parameters on the pile-bedrock interaction mechanism. The mechanical properties of the pile were investigated based on the monitoring results of the earth pressure distributions against the piles and the bending moment distributions. The embedded section of the pile experiences a rotation subjected to lateral soil movement. The center point of the rotation in the HDIB is at a greater elevation than in the WDIB. The earth pressure in the HDIB appears to increase with dip angle θ but is similar to each other in the WDIB. The pile embedded in the HDIB exhibits flexible behavior, whereas the pile embedded in the WDIB exhibits rigid behavior. With the increase of dip angle θ in the WDIB material, the bending moment steadily rises followed by fluctuation. The maximum bending moment of the embedded section increases with θ. These results provide a basis for improving the design of manually excavated stabilizing piles in sandwich-type bedrock. [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]

Huangtupo landslide, volumetrically the largest, most complex landslide in the Three Gorges Reservoir region of China, is a dangerous mass on which the district of Badong has been inadvertently situated. Risk remediation efforts include the construction of a large observational tunnel and monitoring system that are unique in the world. This tunnel and its side branches permit detailed mapping of its 3D structure while providing samples for laboratory analysis. The new investigations validate that the Huangtupo landslide is a composite of several independent landslides and that movement occurs along the major rupture zones as well as on interlayer sliding zones in the underlying Badong Formation. Uranium-thorium disequilibrium dating establishes that the northern part of the landslide, called the Riverside Slump, underwent at least two periods of movement at about 100 and 40 ka (ka stands for a thousand years). These events were induced by the steep slope created by the downcutting of the Yangzte River. The results from in situ displacement monitoring over a 7-year period confirm that the central part of the landslide is creeping at a slow, relatively stable rate of about 15 mm/year rather than being in a stage of acceleration under the protection of anchored concrete beams and other defense structures at its toe. Available data suggest that engineering measures can control the independent landslides that together constitute the huge Huangtupo mass, which will avoid the need for costly relocation of thousands of people. [ABSTRACT FROM AUTHOR]