In recent years, rock avalanche disasters have been occurring frequently in southwest China, which seriously affect the regional ecological environment and human activities. To understand the fragmentation characteristics of the avalanche masses during their movement, this study is based on the field investigation of the rock avalanche in Zongling Town, Nayong County. The dynamic fragmentation process of the rock avalanche during the failure and accumulation stages was simulated using the particle discrete element method. Additionally, the distribution characteristics of the maximum feret’s diameter of the fragments within the rock avalanche mass were statistically analyzed. The results show that: (1) Under the effect of gravity, the internal structural joints of the rock avalanche rapidly interconnected, dividing the avalanche mass into numerous fragmented blocks that eventually slid along the down-dip joint surfaces. (2) The collapse exhibited significant fragmentation phenomena in the entire movement process, with extensive disintegration during the initial failure and friction-induced tearing and cracking fragmentation during the accumulation stage. (3) The feret’s diameter distribution curves of the fragments at different time intervals were fitted using Weibull two-parameter distribution model and fractal geometry theory. The results showed that the fragmentation degree of the avalanche during the accumulation stage (t = 21.7 to 72.4 s) was weaker than that during the initial failure stage (t = 0 to 21.7 s). The fractal dimension of the fragments and the proportion of fine-grained fragments continuously increased throughout the entire movement process, once again confirming the fragmentation and disintegration phenomena during the entire process of failure and accumulation. The research findings provide a theoretical basis for revealing the dynamic fragmentation mechanism of the Zongling rock avalanche, and provide scientific guidance for the prevention and control of rock avalanche disasters in the mountainous areas of southwest China.

The hazardous rock zone on the Wansui Mountain slope in Ganzi Town, Ganzi County, has experienced frequent rockfalls over the years, posing a serious threat to the lives and property of residents below. Therefore, it is crucial to conduct stability analysis of the hazardous rock zone and rockfall trajectory prediction for the Wansui Mountain slope. Focusing on the dangerous rock zone of Wansui Mountain's slope, the geometric dimensions and 3D morphology of the zone were obtained using drone oblique photography combined with field surveys. The development characteristics of the dangerous rock zone and the distribution characteristics of the dangerous rock bodies were analyzed, and the stability of the dangerous rocks was assessed. Based on RAMMS-ROCKFALL, considering the geometric shapes of the dangerous rocks and the 3D terrain, potential rockfall trajectories after the collapse of the dangerous rocks were simulated.The results show that:The slope is generally intact, with the main instability modes being falling and toppling due to weathering. A total of seven dangerous rock zones have developed, which are in an unstable state under seismic conditions; the simulation provided the relationships between rolling and bouncing heights, speeds, kinetic energy, trajectories, and positions. By predicting the rockfall trajectories, the threat range and targets of the dangerous rock zone were determined. The prediction results indicate a significant threat to the houses and pedestrians on the streets below the slope of Wansui Mountain, and remedial measures should be taken as soon as possible.The research results indicate that the use of drone oblique photography is beneficial for the stability analysis of dangerous rock bodies on slopes, compensating for the blind spots of traditional surveys, and improving the efficiency and quality of the investigation. This provides a new approach for the investigation of dangerous rock bodies and rockfall trajectory analysis, which has positive significance for disaster mitigation technology research and the management of dangerous rock bodies.

Taking the down-slope with weak strata in the south of Fushun west open-pit mine as the reference prototype, numerical simulations of the down-slope with weak strata were conducted through FLAC^3D software, which included the simulation of actual ground motion and ground motion input, the boundary conditions of slope model, rock mass parameters, and grid model division. The response rule of down-slope with weak strata under an earthquake was investigated by analyzing the acceleration and velocity of the monitoring points. The results revealed that: (1) The thickness of the weak layer is a critical factor affecting the response characteristics of the slope with a single weak layer under an earthquake, and it has a greater impact on the stability of the slope under earthquake load than the dip angle of a single weak layer. (2) Based on the horizontal velocity of monitoring point 2# at the intersection of the weak layer and the slope surface, it was concluded that the thickness has a significant influence on the velocity in the X direction. (3) The failure response law at the intersection of weak layers and slope changes with an increase in slope height when analyzing the response law of the double weak layer characteristic slope under an earthquake. The acceleration amplitude and velocity change degree of monitoring point 3# with double weak layers are more noticeable than that of monitoring point 2#. The response law of the down-slope under an earthquake is related to the dip angle, thickness, number, and location of weak layers. Therefore, the coupling effect of earthquake and weak layer characteristics on slope stability should be thoroughly considered in the process of slope treatment and protection.

The Qingkou landslide in Wulong, Chongqing, has developed on an inclined thick abrupt cliff, with a large area of goaf formed due to hundreds of years of coal mining below. Based on the analysis of the geological conditions, current goaf situation, and deformation characteristics of the mountain, it is identified that the landslide exhibits both bending-tension and sideslip deformations, suggesting a bending-sideslip failure mode. The deformation history of the mountain is examined, and the deformation characteristics of the landslide are analyzed in two stages: bending deformation and sideslipping deformation. Change in the rock surface occurrence are studied accordingly. Considering the combination relationship between bedding and the free face, the mountain failure is divided into bending-tension failure, wedge failure and plane-sliding failure. Criteria for each failure stage are established, revealing the evolution rules and formation mechanism of the bending-sideslip landslide. This study provides a scientific basis for the disaster prevention and mitigation of such landslides.

In this paper, five dangerous rockfall collapses at K1515 of the Shanghai-Chengdu expressway are taken as the research object. Through investigation, statistics, and analysis, the engineering geological conditions and developmental deformation characteristics of the dangerous rockfall collapse area are clarified. The research results show that: (1) the failure modes of dangerous rock masses W1 and W2 are misbreaking and cracking, the destruction mode of W3-1 dangerous rock mass is dumping, the destruction mode of W3-2 dangerous rock mass is sliding, and the destruction mode of W4 and W5 is bulging; (2) the stability coefficient of W1 and W2 is 1.12 and 1.61 respectively, which are in basically stable ~ stable state; the stability coefficient of dumping failure of W3-1 is 0.41 and in unstable state; the stability coefficient of sliding failure of W3-2 in W 3-2 is greater than 1.35 and in stable state; under rainstorm condition; the stability coefficient of bulging deformation of W4 and W5 is 1.25 and 1.15 respectively, which are in basically stable state; (3) The authors summarize the governance strategy of “reduce risk, minimize disturbance, ensure safe stability and feasible technology”, and adopt comprehensive remidiation measures of “embedding concrete retaining wall at the toe of slope + local active SNS network protection + prestressed anchor protection”, and the treatment effect was good. It can provide reliable reference basis for the treatment measures of dangerous rock collapse.

Heixiluo gully, located in Suxiong Town, Ganluo County of Sichuan Province, experienced a catastrophic debris flow disaster at 8:00 a.m. on August 31, 2020, causing significant losses to local residents, as well as to the Chengdu–Kunming railway bridges and infrastructure. To Study the activity and dynamic characteristics of the debris flow in Heixiluo gully, a comprehensive analysis was conducted using field investigations, on-site observations, and high-precision DEM data from the study area. The formation conditions and activity characteristics of the “8•31” debris flow were studied, and the Massflow software was utilized to simulate and verify the debris flow, inversely simulating the dynamic evolution process of the debris flow in Heixiluo Gully, and quantitatively evaluating the dynamic characteristics of the“8•31”debris flow. The study indicates that the “8•31” debris flow mainly underwent a“snowballing” cycle of processes, including “rainfall runoff convergence-, incision and erosion on the sides, sedimentation and selection on the first-level platform, erosion on the rear side of the platform, further sedimentation and selection on the second-level platform, further incision and erosion on the rear side of the platform, bank slope collapse, blockage and collapse, river blockage, formation of barrier lakes, and dam breach discharge.” Based on the Massflow analysis of the dynamic process of the debris flow, the simulated peak discharge, flow velocity, flow depth, erosion, and sedimentation depths in each gully segment match the measured data, confirming the reliability of this method. Through this method, the dynamic characteristics of debris flow can be more intuitively analyzed, providing a theoretical basis for subsequent disaster prevention and mitigation works.

Influenced by the 2013“4•20” Lushan earthquake, geological disasters occurred frequently along the Baiyan River Basin in Hanyuan County. At present, there is a large amount of loose material sources in the Xiaochang gully, posing a significant risk of large-scale debris flows, which severely threaten the factories and mining enterprises in the Hanyuan Industrial Park plant. Therefore, understanding the mechanism of disaster occurrence and its hazard is of great significance for future debris flow prediction, early warning, and prevention engineering design. Combining field investigation, UAV aerial photography, remote sensing interpretation, and RAMMS, this study analyzes the development characteristics of debris flows in Xiaochang gully, simulates the process of debris flow movement and accumulation, and reveals the disaster mechanism of disaster occurrence. The results show that the current dynamic storage of the source in Xiaochang gully reaches 370,000 m3. A wide and gentle channel ( 900 m long, and average width of 60 m ) has naturally formed in the middle reaches of the basin, acting as a natural sedimentation pond, which intercepts small-scale debris flows. Numerical simulation results show that when the rainfall frequency is less than once every 20 years, the main deposition of debris flows occurs in the middle and upper reaches of the gully, and will not directly threaten the industrial park; when the rainfall frequency reaches once every 50 years, the outbreak of large-scale debris flow will impact the industrial park.

Understanding the primary and secondary relations of influencing factors is crucial for predicting deformation and controlling collapse in cutting slopes. Using a cutting slope along the Shuangcheng to Dalijia expressway in Gansu Province as the research object, this research utilized the FLAC^3D finite element software platform to establish dynamic correlations between saturation, gravity, and soil shear strength through FISH language. Based on this, safety factors of the cutting slope were calculated under different rainfall intensities, slope ratios, and rainfall duration. Grey relational theory was applied to determine the primary and secondary relationships of key factors affecting shallow collapse of cutting slopes under rainfall conditions. Indoor rainfall experiments and on-site ecological protection tests were conducted to summarize the shallow collapse mechanism and propose the environmental control measures. The study revealed that the failure mode of cutting slopes transitioned from deep overall sliding to shallow local sliding during rainfall. As the slope ratio decreased, the shallow collapse area gradually shifted from the slope shoulder to the foot of the cutting slope. Cumulative erosion rates of shallow soil in cutting slopes decreased initially and then increased over time during rainfall. Installing arch skeletons and reducing the slope ratio enhanced the cutting slope's resistance against shallow collapses. Among with the protective materials, polypropylene fiber-reinforced soil protective materials exhibited the best timeliness and ecological control effect for shallow collapses of cutting slopes compared to HP-FGM and EFM materials.

Slope stability control is crucial for safe and efficient coal mining in open-pit mines with soft rock. To address the challenge of stabilizing dip soft rock slope rock slopes, the treatment engineering of inner row tracking pressure side of dip soft rock slope in open-pit mine is proposed based on the analysis of the main controlling factors of slope stability. This study takes the south side of the first mining area of Hesigewula south open-pit coal mine as the engineering background and proposes a synergistic treatment scheme for the slope stability of the stope and inner dump, utilizing the combination of limit equilibrium method and numerical simulation to design the spatial form of the stope slope. This treatment scheme maximizes the safe recovery of the coal resources covered by the slope. The research results indicate that the length of exposed weak layer is the primary controlling factor of the stability in inclined soft rock slopes in open-pit mines. Controlling the tracking distance between the stope and the inner dump is an effective way to improve slope stability. With an increase in tracking distance, the slope damage mode transitions from the cut-layer-sublayer-shear-out sliding with an arc as the side interface and the weak layer as the bottom interface to cut-layer-sublayer sliding with an arc as the side interface and weak layer as the bottom interface, leading to a gradual decrease in slope stability. Moreover, the stability of the inner dump and its composite slope with the stope increases exponentially with an increase in the backfill rock range of the weak layer of the failure floor. The study sets the shallow slope of the south slope of the first mining area of Hesigewula coal mine to be 40 m transportation flat and 15 m security flat, and the deep slope angle of the bottom slope is 29°. When the tracking distance is controlled within 50 m, it can meet the safety requirements. When the weak layer of the inner dump base is destroyed, and the inclined length of the backfill rock is 60 m, it can also meet the safety requirements. The study provides new insights into slope stability control in soft rock open-pit coal mines.

Pile-slab rockfall retaining wall is a novel passive protective structure designed to intercept falling rocks. It is made up of cantilever piles, pile-intermediate slabs, and cushion layers. This structure features strong terrain adaptability , small footprint, and high interception height, making it applicable in high-risk rockfall areas. However, due to the lack of detailed reports on the ultimate bearing capacity of cantilever piles, guidance for engineering practice is unavailable. This paper first proposes a reasonable thickness for the cushion layer based on the characteristics of the propagation of falling rock impact forces. Then, according to the stress and deformation characteristics of the pile body, theoretical calculation methods of the internal forces and displacements of the pile body are derived using the elastic support cantilever beam model and the Winkler elastic foundation beam model, enabling the automatic determination of design parameters for cantilever pile under falling rock impact. The results indicate that for a rockfall with a diameter of 2 m, impact height of 7.0 m, impact velocity of 10 m/s, and a cushion layer thickness of 1.5 times the rockfall diameter, a double-row triple-limb steel-reinforced 1.5 m × 1.2 m cantilever pile can withstand an impact force of 2.51 × 10⁶ N and impact energy of 565 kJ. For cases with higher falling rock impact energy, it is recommended to prioritize enhancing the bending resistance of the retaining wall. This research provides a scientific basis for disaster prevention and reduction in rockfall-prone areas in the western mountainous regions of China.

According to studies by relevant scholars, the ground subsidence rate in Sanhe City, Hebei, increased gradually from 2003 to 2016, with the most severe subsidence observed in the Yanjiao area , which has become contiguous with the subsidence area in Tongzhou, Beijing. However, the development trend of ground subsidence disasters in Sanhe City after 2016 remains unclear. With the implementation of national policies such as the integration of Beijing-Tianjin-Hebei region and the construction of Beijing’s sub-center, it is crucial to identify the development and evolution characteristics of land subsidence disasters in Sanhe City and analyze their causes to ensure the urban safety and sustainable development of Sanhe City. In this context, the authors used SBAS-InSAR technology to interpret the evolution characteristics of ground subsidence in Sanhe City from 2018 to 2020, and analyzed several inducing factors that led to land subsidence in Sanhe City, summarizing the main causes. Through this study, the spatial distribution and evolutionary characteristics of land subsidence disasters in Sanhe City were grasped: the western part of the city exhibits severe subsidence, while the eastern part is less affected, with a focus on the overall characteristics of key subsidence areas. Two main subsidence areas were identified, namely, the Yanjiao Town subsidence area with three subsidence funnels and the DuanJialing town subsidence area with one subsidence funnel, with the former being the most severely affected. From 2018 to 2020, the overall trend of ground subsidence disasters in Sanhe City showed a slowdown. Through comparative analysis, it was determined that severe overexploitation of groundwater, soil properties, urbanization development, and population growth are the main factors contributing to the occurrence and development of ground subsidence disasters in Sanhe City. The research results of this paper will provide reference for the prevention and control of ground subsidence disasters in the region.

On December 18, 2023, an M_s 6.2earthquake occurred in Jishishan County, Linxia Prefecture, Gansu Province, causing a large number of geological disasters and threatening people's lives and the safety of infrastructure. After the earthquake, Gansu and Qinghai provincial governments quickly deployed hundreds of geology professionals to carried out the investigation and verification geological disasters in the earthquake area. Based on the results of the earthquake geohazard investigation and verification, this paper analyses the characteristics, control factors and development trend of the earthquake-induced geohazards, and puts forward suggestions on disaster prevention and risk mitigation measures. Till December 23, a total of 2044 geohazards have been checked, including 78 new geohazards, 88 existing geohazards with intensified deformation due to earthquake, and 1 878 existing geohazards without obvious different from before. Most of new and intensified deforming geohazards are collapse, accounting for 67.5%, followed by landslide, accounting for 31.9%. Most of new and intensified deforming geohazards are small in scale, accounting for 84.9%, followed by medium, accounting for 10.8%. Disaster mode of new and intensified deforming geohazards are mostly small collapse threatening houses and roads. The co-seismic geohazards are densely distributed along the seismic fault, and the spatial density increases with the enhancement of earthquake intensity. Data from 206 groups of accelerate-meters within 50 km from the epicenter of the National Geological Safety Monitoring Network showed that the peak acceleration of the earthquake area was 30.4～1969.7 mg. and decayed logarithm with the increase of the distance from the epicenter. In addition, the surface deformation monitoring equipment also recorded the co-seismic displacement curve of a typical landslide. Analysis shows, earthquake put a deteriorate effect to rock and soil, which decreased their integration and strength. There is a magnificent geohazard after-effect of earthquake; collapse, landslide and debris flow will be much often than before. So the authors suggest: (1) update earthquake geohazard database as soon as possible, (2) work out targeted prevention and control measures for the geohazards with large potential danger, (3) conduct comprehensive remote sensing monitoring and research of earthquake-induced geohazard mechanism, (4) improve the meteorological early warning model and threshold. By all this efforts the risk of geohazards after earthquake will be reduced and controlled.

Lancang County is located in the longitudinal tectonic zone of western Yunnan, where landslides are frequently developed by strong tectonic movement and increasing human activities, thus posing a significant threat to the safety and security of the local population. Therefore, it is of great significance to assess the landslide risk in this area. To construct a landslide risk evaluation index system, data on previous landslides in Lancang County was analyzed, and eight control factors were selected, including elevation, slope, slope direction, stratigraphic lithology, distance from fault, vegetation coverage, distance from road and rainfall. By using the entropy weight method and information coupling value model, the landslide risk in the study area was qualitatively and quantitatively evaluated, and ArcGIS geospatial analysis was used to partition the results. According to the assessment, high-risk areas accounted for 17.91% of the total area, relatively high-risk areas accounted for 37.91%, moderate-risk areas accounted for 25.94%, and low-risk areas accounted for 18.25%.The evaluation results were deemed reasonable, and the entropy weight method and information coupling value model were found to be appropriate for landslide hazard assessment in the region.

The Yili Valley, located on the border between China and Kazakhstan, serves as the juncture of North and South Xinjiang, and stands as a pivotal outpost on the Silk Road Economic Belt. This area possesses a fragile ecological environment and experiences frequent debris flow disasters. In this study, four machine learning models:Random Forest (RF), Logistic Regression (LR), Support Vector Machine (SVM), and Decision Tree (DT)-- were employed to evaluate the debris flow susceptibility and compute the weights of evaluation factors. The models were fed inputs comprising 398 identified debris flow channels and 14 feature parameters such as fault density, topographic relief, land use, NDVI, multi-year average rainfall, etc obtained through remote sensing and field surveys. Also, the accuracy of the four machine learning models was evaluated by ROC curves and calculating the Area Under the Curve (AUC). The research results show that: (1) High debris flow susceptibility areas are mainly located in the Tianshan Mountains in the deep river valley region and the loess-covered areas in the mountain front slopes; (2) Multi-year average rainfall, drought index, and topographic relief variability are the top three influential factors controlling the spatial development of debris flows; (3) The AUC values for the validation datasets of the four models were 0.938 (RF), 0.932 (SVM), 0.89 (LR), 0.79 (DT), with the Random Forest model exhibiting superior predictive capability in assessing susceptibility in the region; (4) The disruption of ecological vegetation in the loess-covered region of the study area is a significant cause of frequent debris flow occurrences. Ecological governance and protection efforts should be emplasized to reduce soil erosion and effectively mitigate debris flow disasters at their source.

China is a nation severely impacted by landslide disasters, which poses a great threat to the lives and properties of people in the disaster-affected areas. Landslide susceptibility assessment, as an important tool for landslide risk prediction, is of great significance for disaster mitigation and prevention. However, traditional landslide susceptibility assessment faces the issue of imbalanced data between landslide and non-landslide samples, leading to the inherent undersampling of non-landslide data in the training set. This results in the loss of important information features related to landslide events, thereby affecting the reliability of landslide susceptibility assessment. In this study, using the Zigui-Badong section of the Three Gorges Reservoir Area as an example, 14 evaluation factors, such as elevation and slope were chosen as landslide susceptibility assessment factors, and the original training set and the validation set were divided. In this study, the synthetic minority oversampling technique - Tomek Links (SMOTE-Tomek) method was employed to process the original training dataset, construct the input training set. A convolutional neural networks (CNN) was then trained using this input data, resulting in the SMOTE-Tomek-CNN coupling model. In addition, by intersecting the SMOTE-Tomek method with undersampling methods (random undersampling, RUS), they were separately coupled with the CNN model and support vector machine model (SVM) to form three coupled models: SMOTE-Tomek-SVM, RUS-CNN, and RUS-SVM. These were compared with the SMOTE-CNN coupled model. The results indicate that, among the four coupling models, the SMOTE-CNN coupled model has higher specific class accuracy and area under the ROC curve, with values of 73.60% and 0.965, respectively. This indicates that this method's predictive ability is superior to that of traditional methods, making it a reliable resource for landslide prediction in the studied area.

The rational selection of non-geological hazard samples is of great significance to improve the accuracy of geological hazard susceptibility prediction. This study uses Liulin County as a case study, where appropriate impact factors were selected, and the random forest (RF) model was employed for susceptibility assessment based on GIS technology. A total of twenty sets of models were created by varying the ratio of geological hazard to non-geological hazard points (1∶1, 1∶1.5, 1∶3, 1∶5 and 1∶10) and the distance from non-geological hazard points to known hazard points (100,500,800,1000 m). The results demonstrate that: (1) Through error index, confusion matrix, and ROC curve tests, the sample proportion and distance from the known hazard point significantly influenced the geological hazard susceptibility evaluation. As the sample proportion decreased and the distance from known hazard points increased, the overall MAE and RMSE of the models decreased, while the overall ACC increased. All models achieved AUC value greater than 0.8, indicating excellent predictive performance. When the sample proportion was less than 1∶3, the increasing distance from the known hazard points on model error and accuracy became less pronounced, stabilizing the results. The most suitable model for the study area was found to have a sample ratio of 1∶10 and a distance of 1000 m from known hazard points. (2) High and very high susceptibility areas were primarily located in the central and northern regions, adjacent to roads and rivers, making them key areas for hazard prevention and reduction in Liulin County. (3) Differences in sample selection led to varying susceptibility results mainly due to changes in the RF model's data feature collection and judgment during the modeling process, as well as the representativeness of the samples. These research findings hold significant implications for the implementation of hazard prevention and reduction measures.