The main purpose of this research is to apply the logistic regression (LR) model, the support vector machine (SVM) model based on radial basis function, the random forest (RF) model, and the coupled model of the whale optimization algorithm (WOA) and genetic algorithm (GA) with RF, to make landslide susceptibility mapping for the Ankang City of Shaanxi Province, China. To this end, a landslide inventory map consisting of 4278 identified landslides is randomly divided into training and test landslides in a ratio of 7 : 3. The 15 landslide influencing factors are selected as follows: slope aspect, slope degree, elevation, terrain curvature, plane curvature, profile curvature, surface roughness, distance to faults, distance to roads, landform, lithology, distance to rivers, rainfall, stream power index (SPI), and normalized difference vegetation index (NDVI), and the potential multicollinearity problem among these factors is detected by Pearson correlation coefficient (PCC), variance inflation factor (VIF), and tolerance (TOL). We evaluate the performance of the model separately by statistical training and test dataset metrics, including sensitivity, specificity, accuracy, kappa, mean absolute error (MSE), root mean square error (RMSE), and area under the receiver operating characteristic curve. The training success rates of LR, SVM, RF, WOA-RF, and GA-RF models are 0.7546, 0.8317, 0.8561, 0.8804, and 0.8957; the testing success rates are 0.7551, 0.8375, 0.8395, 0.8348, and 0.85007. The results show that the GA significantly improves the predictive power of the RF model. This study provides a scientific reference for disaster prevention and control in this area and its surrounding areas.

Water inrush disaster is one of the major disasters affecting the production safety of coal mines following roof caving, fire, gas outburst, and dust explosion disasters. It is urgent to reveal the water inrush mechanism and take effective measures to prevent the disasters. More than 80% of water inrush accidents occur around geological structural zones such as faults and karst collapse columns (KCCs). The water inrush events from KCCs caused huge economic losses and heavy casualties, and the water inrush process often shows certain hysteresis characteristics. Taking the water inrush disaster from a KCC during roadway excavation in PanEr Coal Mine of Huainan Mining Area as the case study, the delayed inrush mechanism of KCC was analyzed from the aspects of floor failure, KCC activation, seepage transition, and water inrush development characteristics. The results show that the rock mechanical properties and the excavation depth are the main factors affecting the floor failure characteristics. The seepage transformation from pore flow to fracture flow and pipeline flow, with the change in internal composition structure, is the internal mechanism of the delayed water inrush from KCC. The research is of great significance for the prediction and prevention of water inrush disasters from KCCs.

The coal-forming period is mainly Permian and Carboniferous in the North China coalfield, which is one of the main coal accumulating areas in China. It is characterized by high coal rank, abundant reserves, and varieties. However, water outburst accidents originating from karst aquifers under the coal seam floor have become a terrible disaster in accompany with the deep coal exploited progressively. Water inrush events of the deep limestone have often occurred during excavation in mines. To decrease the risk of high confined water from the coal seam floor and ensure the mining under the safe water pressure of limestone aquifers, the comprehensive exploration and regional treatment are all implemented, such as drainage depressurization, curtain grouting, and grouting transformation of aquifers. Through the comprehensive treatment of the ground and underground, the water channel will be effectively filled with slurry to prevent limestone water bursting into the roadway, and the value of water-inrush coefficient is decreased below the critical value. In the study, utilizing COMSOL Multiphysics based on the finite element method to verify and determine the real layout of grouting parameters, the result shows the design plans satisfy the engineering requirements. 13321 working face located in South No.1 mining area has analyzed the effect of water hazard prevention and control. On the basis of the analysis of geophysical prospecting and validation boreholes, it is concluded that the fracture is filled with grouting slurry to block water-conducting channel effectively. In turn, the rational design parameters of grouting are confirmed as well. Finally, the water-inrush coefficient of Taiyuan formation limestone and Ordovician limestone water is calculated, respectively. The result shows that water-inrush coefficient is less than the critical value after treatment, the safety of excavating coal seam can be further assured.

Landslides caused countless economic and casualty losses in China, especially in mountainous and hilly areas. Landslide susceptibility mapping is an important approach and tool for landslide disaster prevention and control. This study presents a landslide susceptibility assessment using frequency ratio (FR) and index of entropy (IOE) models within a geographical information system for She County in the mountainous region of South Anhui, China. First, the landslide locations were ascertained in the study area using historical landslide records, aerial photographs, and multiple field surveys. In all, 502 landslides were identified and randomly divided into two groups as training (70%) and validation (30%) datasets. Additionally, the landslide-influencing factors, including slope angle, slope aspect, curvature, landform, lithology, distance to faults, distance to roads, distance to rivers, rainfall, and normalized difference vegetation index, were selected and their relative importance and weights were determined by FR and IOE models. The results show that the very high and high susceptibility classes cover nearly 50% of the study area. Finally, the comprehensive performance of the two models was validated and compared using receiver operating characteristic curves. The results demonstrated that the IOE model with the area under the curve (AUC) of 0.802, which is slightly better in prediction than the FR model (AUC = 0.786). The interpretation of the susceptibility map indicated that landform, slope degree, and distance to rivers plays a major role in landslide occurrence and distribution. The research results can be used for preliminary land use planning and hazard mitigation purposes.

Fully mechanized top-coal caving mining with high mining height, hard roofs and strong mining pressure are popular in the Shendong mining area, China. The occurrence of dynamic disasters, such as rock burst, coal and gas outburst, mine earthquakes and goaf hurricanes during the coal exploitation process under hard roof conditions, pose a threat to the safe production of mines. In this study, the characteristics of overburden fracture in fully mechanized top-coal caving with a hard roof and high mining height are studied, and the technology of advanced weakening by hard roof staged fracturing was proposed. The results show that the hard roof strata collapse in the form of large “cantilever beams”, and it is easy to release huge impact kinetic energy, forming impact disasters. After the implementation of advanced hydraulic fracturing, the periodic weighting length decreases by 32.16%, and the length of overhang is reasonably and effectively controlled. Ellipsoidal fracture networks in the mining direction of the vertical working face, horizontal fracture networks perpendicular to the direction of the working face, and near-linear fracture planes dominated by vertical fractures were observed, with the accumulated energy greatly reduced. The effectiveness of innovation technology is validated, and stress transfer, dissipation and dynamic roof disasters were effectively controlled.