Bedding-controlled landslides are a common geological hazard for open-pit metal mines and occur on layered rock slopes. It can spread spatially over the final boundary of the dip slope and persist throughout the entire life cycle of the mine, substantially compromising the safety of mining operations. Identifying potential landslide areas and determining the landslide mechanism is crucial for the safety production and slope management of mines. This study proposes a combination of satellite radar interferometry measurement and numerical simulation to determine the landslide mechanism of the bedding-controlled slope in open-pit mines. First, the multidimensional small baseline subset (MSBAS) technique of interferometric synthetic aperture radar (InSAR) is used to capture deformation information in the vertical and east–west directions of the slope, locate large-scale and long-term movements, and preliminarily determine the trend of landslides. Then, a layered slope damage constitutive model is established, and a three-dimensional stability calculation of the layered slope is performed using COMSOL Multiphysics 5.3 software based on the strength reduction method to study the development and evolution process of landslides. The effectiveness of the method is validated by a large-scale bedding-controlled slope failure in the Nanfen open-pit mine in Liaoning, China, revealing the failure mechanism of the slope under excavation conditions. The study shows that the eastern slope bedding-controlled landslide in the Nanfen open-pit mine is a multizone composite-mode landslide caused by excavation, which belongs to the shear–slip–tension deformation failure mechanism as a whole. This study provides a new method for analyzing the mechanism of layered rock slope landslides under mining activities in open-pit mines, which can be used to assess and predict similar landslides.

The automatic P-wave onset time (P-onset) picking of microseismic (MS) waveforms generated during rock failure is the basis of and key to locating the source and exploring the failure mechanism of rock failure in underground engineering. However, it is hard to ensure the accuracy in picking P-onset of MS waveforms with a low signal-to-noise ratio (SNR) mixed with noises. Moreover, traditional P-onset picking methods mainly depend on manual intervention, which imposes onerous requirements on the SNR of MS waveforms. Hence, a new P-onset picking method is proposed based on the deep learning model: the principal components of MS waveforms are extracted based on the multi-channel singular spectrum analysis (MSSA) method to reduce the influence of noise; afterwards, a short-time Fourier transform (STFT) is applied to the processed MS waveforms to attain essential parameters of the waveforms; finally, a model for P-onset picking is established based on the long short-term memory (LSTM) network. Subsequently, a comparison is conducted between the proposed method and other methods based on actual field MS data collected from Xiadian Gold Mine and the seismic data from Stanford Earthquake Dataset. The results show that the proposed method can accurately extract data features of MS waveforms and further improve the P-onset picking performance.

Shallow coal mining in gully regions has resulted in significant subsidence hazards and increased the risk of surface water inflow into mining panels, compromising the sustainability of surface water management and underground resource exploitation. In this study, the chain disaster process caused by shallow coal seam mining and heavy rainfall is quantitatively analyzed. The findings reveal that shallow coal seam mining leads to the formation of caved and fractured zones in the vertical direction of the overlying rock. The fractured zone can be further classified into a compression subsidence zone and a shear subsidence zone in the horizontal direction. The shear subsidence zone is responsible for generating compression and shear deformations, intercepting rainfall runoff, and potentially triggering landslides, necessitating crack landfill treatments, which are critical for promoting sustainable mining practices. The HEC-RAS program was utilized to integrate annual maximum daily rainfall data across different frequencies, enabling the establishment of a dynamic risk assessment model for barrier lakes. Numerical simulations based on unsaturated seepage theory provide insights into the infiltration and seepage behavior of rainfall in the study area, indicating a significant increase in saturation within lower gully terrain. Precipitation infiltration was found to enhance the saturation of the shallow rock mass, reducing matric suction in unsaturated areas. Finally, the disaster chain is discussed, and recommendations for managing different stages of risk are proposed. This study offers a valuable reference for the prevention and control of surface water damage under coal mining conditions in gully regions.

To study the mechanism of surface collapse and crack evolution in a roadway chain failure process in the pillar recovery of Hongling lead zinc ore in Inner Mongolia Province, China, microseismic monitoring technology, moment tensor theory, and numerical simulation are used for the inversion of rock mass fracturing, the destruction type classification of crack, and the mechanism of surrounding rock. Research shows the following: (1) the rock mass fracturing is first produced within the +955 m level, before extending through the hanging wall to the ground surface. Then, many shear failures occur in the ground surface of the footwall, extending downwards in an arc-shaped path to the +905 m level. Finally, the surface gradually collapses with large-scale shear failures. (2) The mechanism of surface collapse is as follows: after the recovery of pillars in the +905 m level, tensile cracks generated in the top of orebody #2 extend upwards and obliquely. Analogously, shear cracks are generated in the top of orebody #1, extending upwards. After the recovery of pillars in the +855 m level, the marble interlayer is destroyed and sinks, and many tensile cracks and shear cracks exist and incise in the ground surface, which cause the ground surface to collapse. (3) The mechanism of crack evolution is as follows: after the recovery of 5107 pillars, the footwall haul road in the +905 m level was damaged and collapsed by the cut-through cracks. Those cracks then continue to extend upwards and converge with the slanting shear cracks in the +905 m level, which form a triangular failure in the footwall rock. Finally, the failure causes the tensile and shearing cracks in the haulage way of the +955 m level to extend and connect, which forms the haulage way chain failure.

To obtain a better economic benefit, Xiadian Gold Mine intended to increase the stope structure parameter from 2.5 m (height) to 8 m. A test stope using the new structure parameter was mined to verify the surrounding rock’s stability. Based on the mechanical indices relating to the ore and rock, the “static” stability of the test stope under the new stope structure was analyzed by the Mathews stability diagram method. Then, a microseismic (MS) monitoring system was installed around the test stope to determine the “dynamic” stability of the test stope during mining. The spatio-temporal evolution of MS events was analyzed to understand the failure behaviors of the surrounding rock. Based on the MS monitoring results, a damage model was established and used to quantify the damage degree and dimension within the surrounding rock during mining the test stope. The study results show that the damage degree increased from less than 0.05 to 0.6, the damage dimension increased from less than 1500 m² to more than 14,000 m², and the shear plastic zone appeared around the two sidewalls and the roof of the stope. The results show that the test stope is at risk of instability under the new stope structure.