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The Chada rock avalanche is a prehistoric high-elevation giant rock landslide located in the Boshula Mountains, Lhorong County, Southeast Tibet. It is composed of conglomerates with a volume of 6.62 × 106 m3 and has a height difference of 1450 m and a transport distance of 3155 m. The accumulational landform shows characteristics indicating rock avalanches. With a unique red conglomerate as the marker of landslide movement, we combined the results of geological surveys, aerial surveys, and engineering geological drilling to determine the entrainment and geomorphic features of the rock avalanche. The rock avalanche was divided into the main scarp, entrainment zone (residual deposit, mixed deposit, and impact fragmentation areas), transport zone (compressed, local landslide, and longitudinal ridge areas), and deposit zone. The sequence of deposits in the valley indicates that the rock avalanche formed before the first-stage terrace and after the second-stage terrace. Combined with 3D numerical simulation, four movement stages were obtained: (1) the rock mass was broken and disintegrated due to progressive failure, initiating high-speed sliding; (2) the sliding mass scraped the thick previous slope material and formed oblique ridges by forward extrusion and lateral friction; (3) the 4.95 × 106 m3 sliding mass was compressed and decelerated to form bending ridges, and the 1.67 × 106 m3 sliding mass continued to move through the channel; and (4) the sliding mass extended to form longitudinal ridges in the channel and hummocks in the valley. The rock avalanche accelerated three times and decelerated three times during its motion. [ABSTRACT FROM AUTHOR]

Flow-like landslide is one of the most catastrophic types of natural hazards due to its high velocity and long travel distance. In 2019, a large catastrophic landslide was triggered by heavy rainfall and occurred in Shuicheng County, Guizhou, China. The Shuicheng landslide was characterized by a short slip time, high speed, and long sliding distance, causing significant damages to the downstream communities and properties. Depth-averaged models have been widely used to predict the velocity and runout distance of flow-like landslides. However, most of the existing depth-averaged models have various shortcomings for application in real-world simulations. In this study, a high-performance depth-averaged model taking into account the effects of topography-related vertical acceleration and centrifugal force was used to examine the influence of complex 3-D terrain on the landslide movement process. The simulation results were in satisfactory agreement with the field observations. This work reveals the landslide movement process at different stages, including acceleration, diversion, secondary acceleration, impact, and deposition. The maximum average velocity was predicted to be 35 m/s, with a local maximum velocity exceeding 50 m/s. The seismic records obtained from the adjacent seismic stations and the predicted kinetic energy and velocity of the landslide event revealed a dual acceleration and obstruction process. It was also found that the movement process and final deposit morphology were strongly influenced by the complex terrain and were sensitive to the surface friction coefficient. This may also be the reason for the survival of some houses in the middle of the slope during the event. This study provides a reference for investigating long-runout, high-speed, flow-like landslides. [ABSTRACT FROM AUTHOR]

A mountain disaster chain always brings about potential danger to the safety of people and the environment based on its characteristics of long time-scale, great destructive power, and broad scope. Mechanisms responsible for this hazard are represented by studying a landslide-caused disaster chain that occurred in the bank of Jinshajiang River, China on 10 October 2018. The evolution process of this disaster chain is simulated and analyzed using a coupled model that consists of several depth-averaged equations, and the results agree well with the measured data. Furthermore, several factors, including frictional coefficient, inflow flux, and critical dam slope coefficient, are tested by applying different values. Results indicate that the evolution of a mountain disaster chain can change at each stage with different initial conditions. [ABSTRACT FROM AUTHOR]

On July 23, 2019, a large catastrophic landslide was triggered by heavy rainfall at Jichang Town, Shuicheng County, Guizhou, China. This high-speed landslide was characterized by a short slip time, long slide distance, and great destructiveness. In less than 2 min, about 2 million m3 of cataclastic basalt soil failed with a runout of about 1.25 km over a total vertical distance of about 465 m. The landslide destroyed 21 houses and caused 42 fatalities with 9 people missing. To understand the possible mechanisms for the high-speed and long-runout behavior of the landslide, a detailed field survey was conducted. A preliminary analysis was performed on the movement characteristics and formation mechanism of the landslide based on combining data from multitemporal optical satellite remote sensing images, aerial photography from an unmanned aerial vehicle, and InSAR. The historical remote sensing images, InSAR results, and geological monitoring data indicated no obvious deformation signs before the landslide, which implies that it occurred suddenly. The landslide was probably primarily induced by heavy rainfall, while the direct impact of road excavation was small. The terrain controls motion characteristics of the landslide and air blast effect is still visible at the leading edge of the landslide. The results of this study may provide basic data for further research on the mechanisms for landslide initiation and movement. [ABSTRACT FROM AUTHOR]

Numerous interbedded rock (IR) slopes fail during the Wenchuan earthquake in the mountainous region of western China. Landslides are also triggered in IR slopes with a 60° layer inclination, which are generally stable in gravity-dominant environments. This study examines the effect of seismic motion on the response characteristics and failure patterns of IR slopes with steep layers to develop a landslide hazard assessment tool for earthquake-prone regions. First, we use a centrifuge shaking table test to model the failure process and acceleration responses of two IR slope models with stratigraphic dips of 60° and 80°, respectively, under different seismic intensities. Next, we adopt the Particle Flow Code to examine the crack propagation features and peak ground acceleration amplification effects for the IR slopes. We find that the seismic failure pattern of IR slopes depends largely on rock layer inclination: buckling failure is triggered when rock layers are parallel or nearly parallel to the slope surface, while toppling failure is triggered when the rock layer inclination is significantly higher than that of the slope surface. Following seismic excitation, the damage is mainly observed in the weak rock layers, creating lateral stress on adjacent strong rocks, which undergoes deformation and ultimate macroscopic failure. Further, displacement of the IR slope is negatively correlated to rock layer inclination. Rock layer thickness has a major influence on the damaged area inside the slope mass, while rock layer stiffness mainly affects the deformation distribution near the slope shoulder. • Interbedded slopes with steep layers under earthquake exhibit buckling or toppling. • Using centrifugal shaking table test to reproduce interbedded rock slope failures. • Non-uniform deformation is highly developed in interbedded slopes. • Rock layer inclination is a significant factor on failure type in interbedded slopes. [ABSTRACT FROM AUTHOR]

Earthquakes that occur in a mountainous region can trigger a mass of landslides (ETL), and these hazards can cause relatively heavy casualties. Compared with other evaluation models and methods, quantification theory I is a multivariate statistical approach that can simultaneously process qualitative and quantitative variables. On the basis of the ETL features and the influencing factors, in this paper, we select lithology, slope gradient, slope height, slope structure, distance to seismogenic fault, hanging wall/footwall of the seismogenic fault, and rock integrity, a total of seven impact factors, as the assessment index. By randomly selecting 128 single slopes in an intense seismic area as the samples, we develop an assessment model and apply it to investigate the regional stability of the Jushui River basin to prove its applicability. Moreover, this method calculates the factor weight; this can also prove the method through a comparison with the existing research results obtained using other methods. [ABSTRACT FROM AUTHOR]

The Guantan landslide, with a total displaced mass of about 468 × 10 m, was triggered by the 2008 Wenchuan earthquake and succeeding rainfall in Jushui Town, Sichuan Province, China. The landslide occurred on an anti-dip hard rock slope with a weak rock founding stratum of 200 m in thickness. To investigate the failure mechanism of the Guantan landslide, dynamic behaviors of hard and soft rock slopes were investigated by means of large scale shaking table tests. The laboratory models attempted to simulate the field geological conditions of the Guantan landslide. Sinusoidal waves and actual seismic waves measured from the Wenchuan Earthquake were applied on the slope models under 37 loading configurations. The experimental results indicated that deformation mainly developed at a shallow depth in the upper part of the hard rock slope and in the upper (near the crest) and lower (near the toe) parts of the soft rock slope. An equation for predicting the depth of sliding plane was proposed based on the location of the maximum horizontal acceleration. Finally, it was concluded that the failure process of the Guantan landslide occurred in three stages: (1) toppling failure caused by compression of the underlying soft rock strata, (2) formation of crushed hard rock and sliding surface in soft rock as the result of seismic shocks, particularly in the horizontal direction, and (3) aftershock rainfall accelerates the process of mass movement along the sliding plane. [ABSTRACT FROM AUTHOR]

Landslides are one of the commonly natural disasters triggered by rainfalls, earthquakes, and human activities, which cause fatalities, damage to properties, and economic losses in the world. Early warning method may predict landslide occurrence and reduce the risk. In this paper, we propose a self-developed site-specific landslide early warning system (LEWS), which has been progressively designed and accomplished over the past decade in Southwest China. The warning model for the prediction of slope instability is focused on multiple thresholds, including deformation rate, rate increment and tangential angle related to surface displacement measurement. The debris-flow initiation is determined by critical rainfall thresholds integrated with the topographic and geological conditions at a catchment scale. The recent Xingyi rockslide, Baige debris slide and debris flows in Zoumaling catchment are selected to explain the specific process of landslide early warning in a real-time operating system. The performance of the presented warning system is evaluated by comparison with the inverse-velocity model (INV) and gradient model (SLO) in the prediction of slope failure time. The Receiver Operator Characteristic (ROC) analysis is used to prove its feasibility and reliability in the debris-flow initiation prediction. The presented warning model and system can be applied to other regions in landslide early warning and to be useful to mitigate landslide losses and damages. • Provide a successfully real-time landslide early warning system. • Warning model and warning system can be applied in an emergency response to mitigate landslide losses. • Comparing with the SLO, INV model and using ROC analysis to evaluate the performance of the warning system. [ABSTRACT FROM AUTHOR]

The upper Minjiang catchment is frequently affected by a significant number of large to giant landslides. In one such massive older landslide, approximately 2 million m3 of sediment was reactivated, threatening the safety of a pylon on the landslide and the safety of the only route that allows high-speed travel from Wenchuan to Maoxian. To trace the deformation evolution history and analyze the current deformation of the new landslide, we examined SAR data since 2007, carried out geological and UAV surveys, and designed and installed real-time monitoring equipment. This paper presents the main spatial and temporal characteristics of the landslide. We found that the landslide has experienced creep deformation in the past five years and its sensitivity to rainfall. The development process of the landslide from the formation of tensile crack at the trailing edge to the gradual pushing forward of the crack propagation was revealed. The innovation of this paper is to reveal the whole process of the spatial-temporal evolution from its beginning to large deformation of a real case of creep landslide, which can provide a very good reference for the analysis and monitoring of such creeping landslide evolution process. This representative case also shows how to combine remote sensing and in situ monitoring methods to carry out continuous monitoring and the establishment of a warning system for potential landslide sites, so as to trace the evolution history, derive activity maps and analyze development trend, which can significantly reduce landslide risk. Additional mitigation procedures can be put into place if continuous monitoring of the Minjiang River Canyon occurs, resulting in a reduction of direct losses. In particular, modeling of the slope deformation and failure, damming process, and prospective flooding can be done in advance. Therefore, it is expected that this report can strengthen the case for the deployment of systematic monitoring of potential landslide sites by integrating earth observation methods and in situ monitoring systems as an approach to reduce risk. • The whole process of the spatial-temporal evolution of a real case of creep landslide is revealed. • This representative case shows how to combine remote sensing and in situ monitoring methods to carry out continuous monitoring. • Ground-based real-time monitoring provides accurate landslide early warning. [ABSTRACT FROM AUTHOR]

Real-time monitoring and intelligent early warning system are crucial and significant to take mitigation measures and reduce casualties and property losses related to landslides. It is difficult to obtain entire monitoring data in the accelerated deformation phase in a landslide event, and hard to issue early warning information using a traditional monitoring approach with fixed and low sampling frequency. Displacement increments of loess landslides induced by agriculture irrigation on the Heifangtai terrace could be sudden and extremely rapid. Typical landslide types include loess flowslides and loess falls. It is of practical significance to develop a self-adaptive data acquisition monitoring technique and establish a real-time landslide early warning system (LEWS) to meet the needs for risk mitigation of rapid sliding slopes on the Heifangtai terrace. The monitoring technique can wirelessly transmit displacement data and the LEWS was devised using the new artificial intelligence. The LEWS could automatically release the warning information in advance of the event once the early warning parameters exceed default thresholds. In this study, the early warning procedures, real-time monitoring approach, intelligent LEWS, a multiple criteria warning model, warning release and emergency mitigation measures, and performance are introduced in detail. Six loess landslides at Heifangtai and eight landslides in other regions of China have been successfully warned since its implementation in 2012. This study proposed an effective and practical solution for the early warning of loess landslides at Heifangtai. Two typical loess landslides that had successful early warnings at Heifangtai were presented. The successful implementation could serve as a reference for global rapid slope failure cases, considering the complex nature of landslide behaviors and failure mechanisms. • A self-adaptive data acquisition technique was successfully developed to monitor sudden failure of loess landslides. • 3D WebGIS-based platform developed by SKLGP becomes more intelligent and accurate. • Multiple alert criteria model including deformation rate, the rate increment, and tangential angle, is established. • The LEWS with multiple alert criteria model has successfully forecasted six loess landslides since its implementation in 2017. [ABSTRACT FROM AUTHOR]