Geological Disaster Prevention Research Articles

Analysis on the Spatial-Temporal Distribution Patterns of Major Mine Debris Flows in China

In order to provide more accurate data support for the prevention and control of geological disasters in mines, the article counts the major mine debris flow accidents in China from 1954 to 2019; studies the distribution of debris flow disasters in each province; reveals the intra-annual and inter-annual variation patterns of the number of mine debris flow disasters; analyzes the distribution of mine debris flows under different geoenvironmental backgrounds; and combines AHP hierarchical analysis with a comprehensive regional evaluation of the likelihood of mine debris flows. The results of the study show that from 1954 to 2019, the number of major mine debris flow disasters first increased and then decreased. The proportion of mine debris flow disasters to the total number of debris flow disasters also showed a trend of first increasing and then decreasing, with the southwestern region being the area of high occurrence of mine debris flow, and the geoenvironmental areas of middle and low hills and middle and high mountains being the topographic areas of high occurrence of mine debris flow. More than 90% of the major mine debris flow disasters occurred from May to September, with the largest number of disasters occurring in July. A comprehensive evaluation of the regional nature of mine debris flow distribution based on the regional evaluation score is derived.

Study on characteristic maps of multi-spectral remote sensing images of geological hazards

Geological disasters, as the main problems facing urban construction and development, directly threaten the life and property of social residents and living environment, with sudden, wide distribution, destruction and other characteristics. Nowadays, the traditional ground monitoring technology has been unable to meet the needs of geological disaster monitoring research in the new era. Therefore, on the basis of mastering the traditional monitoring experience, scholars from various countries put forward the use of multi-spectral remote sensing image data to obtain the data information of geological disasters in various regions, study the main causes and distribution rules of geological disasters, and put forward effective prediction models and solutions as soon as possible. On the basis of understanding the current situation of geological disaster monitoring and prevention work in China, this paper uses multi-source remote sensing image fusion technology to deeply study the multi-spectral remote sensing image feature map of geological disaster and clarify the relationship between different types of remote sensing image features, so as to provide effective basis for earthquake disaster monitoring and prevention work.

Implications for identification of principal stress directions from acoustic emission characteristics of granite under biaxial compression experiments

The rock fracture characteristics and principal stress directions are crucial for prevention of geological disasters. In this study, we carried out biaxial compression tests on cubic granite samples of 100 mm in side length with different intermediate principal stress gradients in combination with acoustic emission (AE) technique. Results show that the fracture characteristics of granite samples change from ‘sudden and aggregated’ to ‘continuous and dispersed’ with the increase of the intermediate principal stress. The effect of increasing intermediate principal stress on AE amplitude is not significant, but it increases the proportions of high-frequency AE signals and shear cracks, which in turn increases the possibility of unstable rock failure. The difference of stress in different directions causes the anisotropy of rock fracture and thus leads to the obvious anisotropic characteristics of wave velocity variations. The anisotropy of wave velocity variations with stress difference is probable to identify the principal stress directions. The AE characteristics and the anisotropy of wave velocity variations of granite under two-dimensional stress are not only beneficial complements for rock fracture characteristic and principal stress direction identification, but also can provide a new analysis method for stability monitoring in practical rock engineering.

Research on geological environment protection and geological disasters control countermeasures in China

Geological disasters in mines, ecological environment and geology and geomorphology are closely bound up with each other. To reduce or avoid economic loss and to decrease the threat degree of geological disasters to life safety, the protection of geological environment are formulated in this study. Specifically, this includes taking mines that are dominated by thin bedded carbonate as the research objects. The goals of this study include prevention and control of geological disasters and protection of geological environment. The data are based on characteristics of geological strata in mines collected by the exploration, and combined with the characteristics of geomorphic environment, relevant rules aiming at the prevention and control of geological disasters. Then, pursuant to the selection of indicators, an evaluation system is constructed to verify the effectiveness of measures and strategies proposed, in which the score value is converted into the corresponding level to test the implementation effect of the measures and strategies proposed. Through comparing the changes of the utility levels before and after the implementation of measures and strategies proposed, it can be seen that the geological disaster levels of the five mining areas in the study region are respectively improved from the non-ideal levels V, IV, V, V, IV to II, I, I, II, II, with the tailings pond leakage times less than 4 times and collapse volume less than 5m3. And, the levels of geological environment are upgraded from levels IV, IV, IV, V, V to ideal levels II, II, II, I, II, accomplished by the vegetation coverage rate of the mine reaching more than 35%, as well as the recovery rate of exploitation and utilization rate of tailings both exceeding 85%, which indicates that the protection strategy proposed in this paper has good practicality and feasibility.

Experimental research on a novel soil displacement monitoring system based on measurement unit cells (MUCs)

Advanced measurement technology is of great significance to the prevention of geological disasters and engineering construction and simultaneously promotes geotechnical engineering development. This paper reports a novel soil displacement monitoring system based on multiple measurement unit cells. A modularized structure and corresponding positioning algorithm were proposed to monitor the 3D displacement of soil. The monitoring software was developed to dynamically display deformation. Then, a calibration experiment was performed to verify the feasibility of the measurement unit cell. Furthermore, a model experiment adopting X-ray visualization was performed to validate the reliability of the soil displacement monitoring system. It is determined that the proposed soil displacement monitoring system has a mm-level accuracy and satisfies geotechnical engineering requirements.

Detection of former goaf and analysis of deformation characteristics of overburden in Dameidong coal mine

In order to analyze the deformation of the old goaf in Dameidong Coal Mine and its influence on the surrounding rock and soil layer, it provides guidance for the prevention and control of geological disasters in the region. In this paper, the transient electromagnetic method and numerical simulation method were used to study the deformation law of the overlying strata in the mining area. The results of transient electromagnetic detection showed that the subsidence area of the goaf in Dameidong Coal Mine was within the range of the elliptical water-rich area, and the average buried depth of the goaf was expected to be 90 m. The model was established by discrete element numerical simulation to study the variation law of mining overburden rock. The results showed that the stress change in coal mining was mainly reflected at both ends of the goaf, which was a stress concentration phenomenon. Overburden rock deformation changed with the mining process. The stress concentration area and the displacement change area were highly coincident, consisted with the displacement monitoring map, showing a “U”-type distribution. The results proved that the numerical simulation results do have theoretical guidance for mining subsidence control.

The influence of the selection of non-geological disasters sample spatial range on the evaluation of environmental geological disasters susceptibility: a case study of Liulin County.

The reasonable selection of non-geological disaster samples is of great significance to improve the accuracy of geological disaster assessment, reduce the cost of disaster management, and maintain the sustainable development of ecological environment. Liulin County was selected as the study area. This paper creatively divided non-geological disaster sampling areas by macro-geomorphology, and carried out susceptibility mapping based on random forest (RF) and frequency ratio-random forest (FR-RF) models. The accuracy of each model was evaluated by receiver operating characteristic curve (ROC) combined with the distribution characteristics of geological disasters and the actual urban construction in the study area. The results show that the FR-RF model constructed by selecting non-geological disaster samples in hilly area is most suitable for the susceptibility mapping of this study area. The different results in different sampling areas are mainly due to the great changes in the representativeness of non-geological disaster samples. The distance from the roads is the most important factor affecting the occurrence of disasters in the study area. The statistical results of disaster management cost estimation and gross domestic product (GDP) value show that the disaster management cost of HFR-RF model decreases by 13.45% on average compared with other models, and the ratio of GDP to disaster management cost is relatively high. These research results promote the progress of geological disaster prevention technology, maintain the stability of geological environment, and are of great significance to the stable and sustainable development of local economy.

Influence of cracks on loess collapse under heavy rainfall

Collapse is one of the frequent geological disasters on the Loess Plateau, which seriously threatens the safety of people's life and property. Taking the typical loess collapse in Wangdonggou, Changwu County, China as the research object, the loess collapse model is established through the field geological investigation and laboratory tests. Based on the principle of fluid–solid coupling, the failure mechanism of collapse body with the different crack depth and crack width are numerically simulated by the finite element method to study the influence of cracks on loess collapse under the action of heavy rainfall. The results show that with the infiltration of rainfall, on the one hand, the self-weight of the collapse body increases, which causes the increase of shear stress at the slope foot. On the other hand, when rainwater seeps out from the slope surface, it generates the seepage force, resulting the increase of the overturning moment of the collapse body. When the crack depth gradually increases from 0 to 6.0 m, the tensile stress at the crack tip gradually increases, the trend of collapse body toppling towards the free face is more and more obvious, the plastic zone gradually expands from the slope foot to the crack tip, and the safety factor of the collapse body decreases from 1.135 to 0.958. With the increase of crack width, the gravity center of collapse body gradually moves outward, the soil deformation at the slope foot and crack tip gradually increases, and the stability of the collapse body continuously decreases. The failure process of toppling loess collapse includes tensile crack initiation, crack expansion and collapse body bending and toppling. The results reveal the influence of crack depth and crack width on the stability of the collapse body under the action of rainfall, as well as the instability failure mechanism of the collapse body, which can provide theoretical support for the prevention and control of collapse geological disasters and soil gravity erosion in Loess Plateau.

Multi-Window Identification of Landslide Hazards Based on InSAR Technology and Factors Predisposing to Disasters

Identification of potential landslide hazards is of great significance for disaster prevention and control. CNN (Convolutional Neural Networks), RNN (Recurrent Neural Networks) and many other deep learning methods have been used to identify landslide hazards. However, most samples are made with a fixed window size, which affects recognition accuracy to some extent. This paper presents a multi-window hidden danger identification CNN method according to the scale of the landslide in the experimental area. Firstly, the hidden danger area is preliminarily screened by InSAR deformation processing technology. Secondly, based on topography, geology, hydrology and human activities, a total of 15 disaster-prone factors are used to create factor datasets for in-depth learning. According to the general scale of the landslide, models with four window sizes of 48 × 48, 32 × 32, 16 × 16 and 8 × 8 are trained, respectively, and several window models with better recognition effect and suitable for the scale of landslide in the experimental area are selected for the accurate identification of landslide hazards. The results show that, among the four windows, 16 × 16 and 8 × 8 windows have the best model recognition effect. Then, according to the scale of the landslide, these optimal windows are pertinently selected, and the precision, recall rate and F-measure of the multi-window deep learning model are improved (82.86%, 78.75%, 80.75%). The research results prove that the multi-window identification method of landslide hazards combining InSAR technology and factors predisposing to disasters is effective, which can play an important role in regional disaster identification and enhance the scientific and technological support ability of geological disaster prevention and mitigation.

Thinking on Effective Methods of Successful Prediction of Geological Hazards in Shaanxi, China

In the process of human survival and development, it is inevitable to transform the original state of the world, thus forming a contradiction between the earth and the earth. The violent form of this contradiction is geological disasters. Geological disasters pose a threat to human life and property, and cause damage caused by natural or human factors, often causing casualties. The destruction process of geological disasters is usually a gradual process, showing many pre-disaster symptoms, such as local landslides, surface cracks, building deformation, tree skew, and ground sound. Evacuation can be avoided in advance according to the disaster precursors, so as to avoid casualties and achieve successful prediction. By reviewing the general situation of geological disasters in Shaanxi Province and the casualties in 2020, the difficulties in the prevention and control of geological disasters are summarized. In view of these difficulties, an on-site investigation, visit and analysis of geological disaster points and successful forecast points in Shaanxi Province in 2020 were conducted. In addition, combined with actual cases and years of work experience, the successful prediction experience of geological disasters was discussed from 8 aspects. Finally, the “Regulations on the Reward for Successful Geological Disaster Forecasting in Shaanxi Province” was revised in order to improve the successful prediction ability of geological disasters in Shaanxi Province and even the whole country, provide reference for future prevention and control of geological disasters, and effectively protect the safety of people’s lives and property.

Comparison of the Causes of Erosion-Deposition between Yellow River, Yangtze River and Mekong River Subaqueous Deltas II: Comparative Analysis

The estuary delta is an area where human economic activities are active and natural ecological environment is fragile. With global change and the intensification of human activities, coastal and seabed erosion around the world is becoming more and more serious. In this paper, we used the Delft 3D numerical simulation to compare the hydrodynamic effects of sediment transport paths in the Yellow River delta (river-controlled type), Yangtze River delta (tidal type) and Mekong River delta (tidal wave type) in the East Asian monsoon area, and analyzed the causes of accumulation erosion landform distribution in three different types of subaqueous deltas. This study finds the Yellow River Delta has experienced varying degrees of erosion at the estuary, but its subaqueous delta is still dominated by deposition; the Yangtze River Delta has ensured the stability of its shoreline under the influence of artificial shoreline reinforcement, but the subaqueous delta (water depth: 0–15 m) is in a state of erosion all year round; and in the Mekong River Delta the erosion occurs in both its shoreline and subaqueous delta. Additionally, only by analyzing the erosion and deposition within the transport range of resuspended sediment, the changes in the properties of the entire subaqueous delta could be recognized. The research results can not only be helpful to analyze whether the change of river sediment will lead to the change of delta type under human influence, but also provide more powerful scientific support for the protection of delta ecological environment, geological environment safety and geological disaster prevention.

Investigation on permeability anisotropy in unconsolidated hydrate-bearing sediments based on pore-scale numerical simulation: Effect of mineral particle shape and pore-filling

Resulting from the preferential alignment of sediment particles, permeability anisotropy of unconsolidated strata is an essential parameter for natural gas hydrate (NGH) exploitation. Fundamentally, the effect of mineral particle shape and pore-filling NGH on the permeability anisotropy are considered in this study. A simulation with combining methods of particle flow code and computational fluid dynamics is conducted to construct a series of numerical samples and calculate the anisotropic permeabilities. Different particles shapes and hydrate saturations are preinstalled in these samples. It is firstly proved that the elongated particles have little effect on permeability anisotropy. Meanwhile, the preferential alignment of plate-shaped particles is the main reason for permeability anisotropy. In principle, the difference between intermediate orthogonal axes and short orthogonal axes of plate-shaped particles makes the tortuosity different in directions, thus inducing the permeability anisotropy. The anisotropy ratio decreases with the increase of hydrate saturation, which is caused by the nonlinear decline of main channel flow resulting from the thrombus-like hydrate particles. The results provide an insight into the formation mechanism of permeability anisotropy and display potential application value in NGH exploitation, groundwater environment protection and geological disaster prevention.

Evaluation of Geological Disaster Sensitivity in Shuicheng District Based on the WOE-RF Model

To improve the prevention and control of geological disasters in Shuicheng District, 10 environmental factors—slope, slope direction, curvature, NDVI, stratum lithology, distance from fault, distance from river system, annual average rainfall, distance from road and land use—were selected as evaluation indicators by integrating factors such as landform, basic geology, hydrometeorology and engineering activities. Based on the weight of evidence, random forest, support vector machine and BP neural network algorithms were introduced to build WOE-RF, WOE-SVM and WOE-BPNN models. The sensitivity of Shuicheng District to geological disasters was evaluated using the GIS platform, and the region was divided into areas of extremely high, high, medium, low and extremely low sensitivity to geological disasters. By comparing and analyzing the ROC curve and the distribution law of the sensitivity index, the AUC evaluation accuracy of the WOE-RF, WOE-SVM and WOE-BPNN models was 0.836, 0.807 and 0.753, respectively; the WOE-RF model was shown to be the most effective. In the WOE-RF model, the extremely high-, high-, medium-, low- and extremely low-sensitivity areas accounted for 15.9%, 16.9%, 19.3%, 21.0% and 26.9% of the study area, respectively. The extremely high- and high-sensitivity areas are mainly concentrated in areas with large slopes, broken rock masses, river systems and intensive human engineering activity. These research results are consistent with the actual situation and can provide a reference for the prevention and control of geological disasters in this and similar mountainous areas.

Editorial: Mine engineering geological disaster forecasting, monitoring, and prevention

Editorial: Mine engineering geological disaster forecasting, monitoring, and prevention

Characteristic analysis and potential hazard assessment of reclaimed mountainous areas in Lanzhou, China

The limited available land and unique geomorphological features of the Loess Plateau have restricted the urbanization process, causing the spread of land reclamation (LR). This study examined the city of Lanzhou using remote sensing, statistical methods and a numerical model to analyze the distribution law and the potential disaster impact within the LR areas to suggest prevention and control measures. The results showed that the numbers of 93 LR can be divided into remove-mountaintop (RM), cut-one-side-slope (COSS) and cut-both-side-slopes (CBSS), and their numbers increased from 2000 to 2010, thereafter decreasing; a good exponent relationship was also observed between land creation area and excavation volume. A large number of LR areas are distributed on both sides of the Yellow River, which can potentially generate more mudflows and cause huge economic losses and casualties, especially in the core urban areas. A positive exponential relationship was found between the mudflow volume and accumulation area in the simulation results and the statistical data, and the fitting results were generally similar. The mudflow impact scale, simulated using a modified LAHARZ model, was found to be reliable. The analysis of disaster risk demonstrates that the potential hazards of LR are both preventable and controllable and that a focus on long-term risk is required. This study aims to support geological disaster prevention, control and emergency management.

Influence of the Primary Key Stratum on Surface Subsidence during Longwall Mining

The surface subsidence caused by mining influences the mine environment and construction safety. In this paper, strata movement and surface subsidence were combined. Based on elasticity and Winkler theory, a prediction method of surface subsidence was established with the primary key stratum as the research object. Using the Tingnan Coal Mine as an example, the mining subsidence of the second panel was predicted. Comparing the predicted results with the measured results, the causes of errors were analyzed and the field of application of the model was clarified. Besides, the geological and mining factors affecting surface subsidence were also analyzed. The results show that the mining subsidence is the surface manifestation of the strata movement. Surface subsidence is affected by the mining area, load, and flexural rigidity of the primary key stratum, foundation modulus of the goaf, and the rock mass. The research results have significance for the planning of the coal resources and the prevention of geological disasters.

Assessment of Spatial Heterogeneity of Soil Moisture in the Critical Zone of Gully Consolidation and Highland Protection

The Gully Consolidation and Highland Protection (GCHP) project (such as for gully head landfills), a consideration of soil and water conservation measures, has been explored and developed continuously in recent decades in the Chinese Loess Plateau. Using high-precision images taken by drones to extract the topography of the basin, the changes in vegetation and land use were also analyzed. The observation of soil moisture in the critical gully head area of the GCHP was carried out. The results indicated that the critical zones of the GCHP project implementation include the gully head landfill, the gully, and the highland farming area. The soil moisture of the landfill area was 6.91% and 23.61% higher than that of the gully and farming area, respectively, with obvious spatial heterogeneity. The soil sand content in the gully head landfill area was higher than that in the gully area and the agricultural area of the plateau. The main reason for the high soil moisture in the gully head landfill area is that the terrain at the outlet is low, and it is at the lowest point of the whole basin. Analyzing the spatial distribution of soil moisture can point out the direction for the monitoring, prevention, and treatment of geological disasters, such as landslides and debris flow, induced by water erosion. This study will help to understand in detail the spatial heterogeneity and influencing factors of soil moisture under the implementation of the GCHP and improve the GCHP project management system.

Softening and deformation characteristics of Tianjin soft soil under principal stress rotation induced by traffic loading

The vibration caused by moving traffic loading can create additional shear stress in the soil element, thereby resulting in the rotation of the principal stress axis, which can, in turn, accelerate soil softening and increase the cumulative deformation of soft clay. Nevertheless, the designed parameters are often obtained by the cyclic triaxial test (i.e., the rotation of the principal stress axis cannot be considered), or the cumulative axial plastic strain prediction is inaccurate, and these are some of the main reasons for geotechnical engineering problems. In this study, cyclic triaxial and cyclic torsional shear tests were performed to understand the softening and deformation characteristics of soft clay. The influences of the cyclic stress ratio, shear stress ratio, and loading frequency on the softening index and cumulative axial plastic strain of soft clay were analyzed. When the rotation of the principal stress axis was considered, the softening index decreased by 19.57%–51.09%, or the cumulative axial strain increased by 35.49%–74.39%, and failure occurred under higher cyclic stress ratios and shear stress ratios. Additionally, increasing the cyclic stress ratio and shear stress ratio and reducing the loading frequency will cause a surge in the softening index and cumulative axial plastic strain of soft clay. A cumulative axial plastic strain prediction equation considering the influences of cyclic stress ratio, shear stress ratio, and loading frequency was established and verified on the basis of literature. The availability of the prediction equation was verified by comparison with monitoring data. The relevant results can provide a theoretical reference for the prevention of urban engineering geological disasters.

RISK ASSESSMENT OF GEOLOGICAL DISASTERS ALONG THE G213 MAOXIAN-WENCHUAN SECTION BASED ON GF-6 DATA

Abstract. China is a country prone to natural disasters, and roads are easily damaged in natural disasters. As the infrastructure of people's production and life and the lifeline of post-disaster rescue, roads play a very important role. There are many previous studies on geological disasters risk assessment, but few special researches on highway geological disasters risk assessment, especially quantitative risk assessment combined with remote sensing images. Therefore, the risk assessment of geological disasters along the road is of great significance for the prevention and control of geological disasters and the protection of life and property safety. Based on GF-6 data and other geographic data, this study used the comprehensive evaluation method to realize the geological disasters risk assessment of the Maoxian-Wenchuan section along the G213 line, and analysed and discussed the causes and spatial distribution of geological disasters along the G213 line. Our study presents several key findings, (1) The order of impact degree of each impact factor is road network density, soil erosion, slope, human activities, vegetation coverage, rainfall, and slope aspect, among them, the road network density factor plays a leading role, and the aspect factor is the least impact factor; (2) The geological disasters risk in the study area is divided into five categories: extremely low risk, low risk, medium risk, high risk, and extremely high risk. In general, the geological disasters risk of the research road section is relatively high, and the risk area division is consistent with the historical disaster point data. The research results can provide reference for the smooth development and implementation of road geological disasters risk assessment in the mountainous areas in southwestern China.

Dynamic assessment of slope stability based on multi‐source monitoring data and ensemble learning approaches: A case study of Jiuxianping landslide

Accurate assessment of slope stability is the most important task in geological disaster prevention and control. This study developed an ensemble learning approach based on stacking strategy and eight commonly used machine learning (ML) models, for exploring the feasibility of the factor of safety (FS) prediction using dynamic multi‐source monitoring data of slopes and landslides. Based on long‐term and dynamic field monitoring and numerical calculation, a dataset for constructing the FS prediction model for the Jiuxianping landslide was established. The dataset includes five types of monitoring data namely rainfall, reservoir water level, groundwater level, surface displacement and deep displacement for a total of nine features, and one label FS. Four regularized regression models, kernel ridge regression (KRR), lasso, elastic net and support vector regression (SVR), as well as four ensemble learning models, random forest (RF), gradient boosting decision tree (GBDT), extreme gradient boosting (XGBoost) and light gradient boosting machine (LightGBM), were adopted to obtain the nonlinear association between the nine features and the label FS, respectively. Based on five repeated 5‐fold cross‐validation (CV) and successive halving (SH) hyperparameter searching method, the hyperparameters of each model were determined, and the prediction effects of each optimal model were compared. The results show that the ensemble learning models outperform the common regression models. Furthermore, with the help of the stacking ensemble learning thinking, four excellent ensemble models were combined, and the final stacking ensemble learning model was used to predict the FS of the Jiuxianping landslide. The results indicate that the stacking model has better robustness and generalization performance. Besides, the feature relative importance of four ensemble learning models was analysed, for enhancing the interpretability of ML models and pointing out the research direction of feature engineering in the future.