The main frequency of microseismic signals has recently been identified as a dominant indicator for characterizing vibration events because it reflects the energy level of these events. Frequency information directly determines whether effective signals can be collected, which has a significant impact on the accuracy of predicting rock burst disasters. In this study, we adopted a characterizing method and developed a monitoring system for capturing rock failure events at various strata in an underground coal mine. Based on the rock break mechanism and energy release level, three types of rock failure events, namely, high roof breaking, low roof breaking, and coal fracture events, were evaluated separately using specific sensors and monitoring systems to optimize the monitoring accuracy and reduce the general cost. The captured vibration signals were processed and statistically analyzed to characterize the main frequency features for different rock failure events. It was found that the main frequency distribution ranges of low roof breaking, high roof breaking, and coal fracture events are 20–400 Hz, 1–180 Hz, and 1–800 Hz, respectively. Therefore, these frequency ranges are proposed to monitor different vibration events to improve detection accuracy and reduce the test and analysis times. The failure mechanism in a high roof is quite different from that of low roof failure and coal fracturing, with the main frequency and amplitude clustering in a limited zone close to the origin. Coal fracturing and lower roof failure show a synergistic effect both in the maximum amplitude and main frequency, which could be an indicator to distinguish failure locations in the vertical direction. This result can support the selection and optimization of the measurement range and main frequency parameters of microseismic monitoring systems. This study also discussed the distribution law of the maximum amplitude and main frequency of different events and the variation in test values with the measurement distance, which are of great significance in expanding the application of optimized microseismic monitoring systems for rock burst monitoring and prevention.

Extracting shallow coal seams beneath gullies risks catastrophic surface water inrush via mining-induced fractures. Conventional 3D geological models rely heavily on sparse borehole data, causing severe topographic over-smoothing in rugged terrains and undermining hazard evaluations. Investigating a longwall panel beneath a seasonal gully, this study proposes an integrated modeling approach combining high-precision Real-Time Kinematic (RTK) surface surveying with subsurface borehole logs. Using 3DMine software, dual models—borehole-only versus RTK-integrated—were constructed and coupled with surface runoff simulations and overburden thickness analyses. Comparative results demonstrate that the borehole-only model systematically distorts gully geometry and overestimates protective overburden thickness, masking true fracture penetration risks. Conversely, the integrated model captures realistic incision depths and slope gradients, successfully pinpointing localized runoff convergence zones and preferential infiltration paths. Fusing high-density terrain point clouds with stratigraphic boundaries establishes an evidence-based engineering framework for designing targeted mitigation measures, including upstream catchment diversion and dynamic mining sequence adjustments.