Search Results (9)

Bedding rock landslides, characterized by their distinct geological structure, are widely distributed and highly susceptible to sliding under external disturbances, resulting in catastrophic events. This study aims to unravel the geomechanical mechanisms governing rainfall-induced instability through an integrated investigation of a representative landslide in Xing’an Village, Chongqing. Employing multidisciplinary approaches, including field monitoring, geotechnical testing, and dynamic numerical modeling, we systematically revealed two critical failure zones: a front failure zone and a rear potential instability zone. Under rainstorm conditions, the safety factor for both zones was 1.02, indicating a marginally unstable state. The DAN-W simulations indicate that the potential instability zone at the rear of the landslide experienced complete failure within 12 s under heavy rainfall, with a maximum run-out distance of 20 m, a maximum velocity of 4.32 m/s, and a maximum deposition thickness of 8.3 m, which could potentially bury the buildings at the toe of the landslide. The low strength and permeability of the mudstone-dominated Badong Formation, characterized by interbedded mudstone, siltstone, and sandstone within the Middle Triassic geological system, provides a fundamental prerequisite for the landslide. Rainwater infiltration into the mudstone layers degraded its mechanical properties, and excavation at the slope base ultimately triggered the landslide initiation. These findings can provide theoretical support for preventing and managing similar bedding rock landslides with similar geological backgrounds. Full article

High-speed and long-runout landslides constitute one of the most devastating natural disasters. The scraping and erosion of the foundation by these landslides significantly alter the dynamic and catastrophic properties of the landslide mass. This study centered on the movement process of the landslide mass, utilizing numerical simulations to delve into the interactions and dynamic mechanisms between the landslide mass and the foundation. It examined how the erosion of the foundation by the landslide mass impacts its movement distance and accumulation pattern. By employing the distance-potential discrete-element method, which was proposed by the authors, this research simulated the movement process of the landslide mass from a mesoscopic viewpoint. Through precise characterization of the contact forces between blocks, the study sheds light on the interactions among blocks and the energy transfer process during the landslide movement. Furthermore, a comparative analysis was performed to assess the movement distance and accumulation pattern of the landslide mass under varying foundation conditions. The findings revealed that the distance-potential discrete-element method effectively captures the impact and scraping action of the landslide mass on the foundation. The block units within the scraping zone, stimulated by the landslide’s impact and scraping, transition from a stable to a dynamic state. Under the influence of unbalanced forces, these units exhibit rotational and forward-moving motions. The kinetic energy among the blocks is progressively transferred from the rear of the scraping zone to the front through contact interactions and is continuously dissipated through contact, friction, and other mechanical processes, ultimately resulting in a stable accumulation. Due to the scraping zone’s influence, the movement distance of the landslide mass decreases compared to rigid foundations, but the volume of the accumulation increases. Full article

Traditional Newmark models estimate earthquake-induced landslide hazards by calculating permanent displacements exceeding the critical acceleration, which is determined from static factors of safety and hillslope geometries. However, these studies typically predict the potential landslide mass only for the source area, rather than the entire landslide zone, which includes both the source and sliding/depositional areas. In this study, we present a modified Newmark Runout model that incorporates sliding and depositional areas to improve the estimation of landslide chain risks. This model defines the landslide runout as the direction from the source area to the nearest river channel within the same slope unit, simulating natural landslide behavior under gravitational effects, which enables the prediction of the entire landslide zone. We applied the model to a subset of the Minjiang Catchment affected by the 1933 M_W 7.3 Diexi Earthquake in China to assess long-term landslide chain risks. The results indicate that the predicted total landslide zone closely matches that of the Xinmo Landslide that occurred on 24 June 2017, despite some uncertainties in the sliding direction caused by the old landslide along the sliding path. Distance-weighted kernel density analysis was used to reduce the prediction uncertainties. The hazard levels of the buildings and roads were determined by the distance to the nearest entire landslide zone, thereby assessing the landslide risk. The landslide dam risks were estimated using the kernel density module for channels blocked by the predicted landslides, modeling intersections of the total landslide zone and the channels. High-risk landslide dam zones spatially correspond to the locations of the knickpoints primarily induced by landslide dams, validating the model’s accuracy. These analyses demonstrate the effectiveness of the presented model for Newmark-based landslide risk estimations, with implications for geohazard chain risk assessments, risk mitigation, and land use planning and management. Full article

The glacial and torrential basin of Taconnaz (Mont-Blanc massif, France) dominates the Chamonix valley. It is one of the major paths for snow avalanches in the Alps, often triggered by serac falls from the Taconnaz glacier. On 24 November 2018, the basin’s multi-risk nature was further accentuated by a new type of hazard with a rockfall triggered at c. 2700 m a.s.l. It travelled down over a distance of 1.85 km and stopped 165 m away from the construction site of a micro-hydroelectric power station. We studied the triggering conditions at the permafrost lower limit, the effects of the supra-glacial path on the flow patterns, and the fate of the scar and the deposit on torrential activity. By comparing a pre-event Structure from Motion model with a post-event LiDAR model, we estimated the volume of the scar to be 42,900 m³ (±5%). A numerical model was employed to simulate the rapid runout. It revealed the complexity of the flow, attributed to the sequestration of a part of the deposit in crevasses, the incorporation of a significant volume of ice resulting in a transition from a dry granular flow to a mud-like flow, and the presence of numerous deposit zones. Subsequent monitoring of the area after the event allowed for the documentation of the scar’s evolution, including a landslide, as well as the progressive degradation and evacuation of the deposit by the torrent without producing debris flow. The study of the triggering factors indicated glacial retreat as the probable main cause, assisted by the melting of ice lenses left by the permafrost disappearance. Finally, we present replicable methods for managing risks at the site following the event. This event improves the understanding of cascading processes that increasingly impact Alpine areas in the context of climate change. Full article

Because the failure potential of a landslide is difficult to assess, a motorway landslide that has obviously deformed was used as a case study in this research. Several multi-integrated geotechniques, including field investigation, drilling, electrical resistivity tomography (ERT), stability analysis, and numerical simulations, were used to achieve this goal. Field investigation with drilling was used to roughly determine the failure potential mass boundary and the material composition ERT technique was further used to distinguish the structure and composition of underground materials; the results agreed well with the field investigation, as well as the drilling data in the lithology judgement. The above investigations also showed the failure potential mass is in a slow sliding state and the slip surface roughly follows the contact zone between the upper soil and bedrock. Next, stability analysis based on the limit equilibrium method (LEM) was used to judge the current stability status of the slope, and its factor of safety (FOS) was 1.2 under the natural condition, 1.05 under the earthquake condition, and 1.15 under the rainfall condition. Based on the assessed potential slip surface and digital elevation data, a three-dimensional smoothed particle hydrodynamics (SPH) model was used to simulate the failure potential process. The dynamic information of the run-out behavior, including velocity, movement distance, and frictional energy, can be obtained, which is useful for hazard prediction. Full article

It is normally difficult to identify the ground deformation of potential landslides in highly vegetation-covered areas in terms of field investigation or remote sensing interpretation. In order to explore a methodology to effectively identify potential landslides in highly vegetation-covered areas, this paper established an integrated identification method, including sliding prone area identification based on regional geological environment analysis, target area identification of potential landslides in terms of comprehensive remote sensing methods, and landslide recognition through engineering geological survey. The Miaoyuan catchment in Quzhou City, Zhejiang Province, southeastern China, was taken as an example to validate the identification methods. Particularly, the Shangfang landslide was successfully studied in terms of comprehensive methods, such as geophysical survey, drilling, mineral and chemical composition analysis, and microstructure scanning of the sliding zone. In order to assess the landslide risk, the potential runout of the Shangfang landslide was evaluated in a quantitative simulation. This paper suggests a methodology to identify potential landslides from a large area to a specific slope covered by dense vegetation. Full article

At about 20:40 on 23 July 2019, a high-level and long-runout landslide occurred in Jichang Town, Shuicheng County, Guizhou Province (hereafter called the Shuicheng landslide). This slope failure was highly devastating, and most of the local residents were severely affected, including 52 dead or missing. Based on the information provided by field investigations, drilling boreholes, and Google Earth, we describe the landform and stratigraphy characteristics of the Shuicheng landslide in this study. Additionally, the dataset of 1158 ancient landslides near the Shuicheng landslide is obtained by Google Earth and ArcGIS, including their morphological scales and spatial distribution characteristics, to analyze the landslide development preference in this region. Furthermore, the causes of the Shuicheng landslide are discussed by analyzing the effects of active tectonic activities on the broken basalt and the steep terrain, as well as the trigger action of continuous heavy rainfall. Finally, a previous empirical prediction formula of sliding distance is verified by the Shuicheng landslide parameters and is applied into the width range calculation of the ancient landslide risk zones, which is a kind of risk source for future landslides. The result indicates the area up to ≈3500 m away from the landslide risk source should be concerned during engineering construction in the study area. This study provides significant scientific guidance for the risk management of potential landslide hazards in this area. Full article

Landslides can be triggered by natural and human activities, threatening the safety of buildings and infrastructures. Mapping potential landslide runout zones are critical for regional risk evaluation. Although remote sensing technology has been widely used to discover unstable areas, an entire landslide runout zone is difficult to identify using these techniques alone. Some simplified methods based on empirical models are used to simulate full-scale movements, but these methods do not consider the kinematic uncertainties caused by random particle collisions in practice. In this paper, we develop a semi-empirical landslide dynamics method considering kinematic uncertainties to solve this problem. The uncertainties caused by the microtopography and anisotropy of the material are expressed by the diffusion angle. Monte Carlo (MC) simulations are adopted to calculate the probability of each cell. Compared with the existing Flow-R model, this method can more accurately and effectively estimate runout zones of the Yigong landslide where random particle collisions are intense. Combining the D-InSAR technique, we evaluate the runout zones in the Jinsha River from June 2019 to December 2020. This result shows that the method is of great significance in early warning and risk mitigation, especially in remote areas. The source area of the landslide and DEM resolution together affect the number of MC simulations required. A landslide with a larger volume requires a larger diffusion angle and more MC simulations. Full article

This study presents the results of a landslide susceptibility analysis applied to the Vrancea-Buzău seismogenic region in the Carpathian Mountains, Romania. The target area is affected by a large diversity of landslide processes. Slopes are made-up of various types of rocks, climatic conditions can be classified as wet, and the area is a seismically active one. All this contributes to the observed high landslide hazard. The paper analyses the spatial component of the landslide hazard affecting the target area, the regional landslide susceptibility. First, an existing landslide inventory was completed to cover a wider area for the landslide susceptibility analysis. Second, two types of methods are applied, a purely statistical technique, based on correlations between landslide occurrence and local conditions, as well as the simplified spatial process-based Newmark Displacement analysis. Landslide susceptibility maps have been produced by applying both methods, the second one also allowing us to simulate different scenarios, based on various soil saturation rates and seismic inputs. Furthermore, landslide susceptibility was computed both for the landslide source and runout zones—the first providing information about areas where landslides are preferentially triggered and the second indicating where landslides preferentially move along the slope and accumulate. The analysis showed that any of the different methods applied produces reliable maps of landslide susceptibility. However, uncertainties were also outlined as validation is insufficient, especially in the northern area, where only a few landslides could be mapped due to the intense vegetation cover. Full article