Rock mass instability early warning model: A case study of a high and steep annular slope mining areas using Sen’s slope trend analysis

Abstract

As mineral resources continue to be developed, the risk of rock mass instability from deep mining has gradually increased, particularly in high and steep annular slope mining areas, where hazards such as landslides and rock collapses are more prevalent. Consequently, establishing a reliable and early warning model is crucial. This study proposes a multi-index fusion early warning model for rock mass instability based on Sen’s slope trend analysis. First, the microseismic activity patterns and source parameters of a gold mine in northwest China were analyzed. Using a rock mass instability event as a case study, the cumulative Benioff strain, b-value, S-value, energy index, cumulative apparent volume, and Hurst exponent were selected to explore the change patterns of these indicators before the event. Next, the trends of these indicators were analyzed using a sliding time window and Sen’s slope method, and the correlation between the event occurrence (target variable) and indicator values (characteristic variables) was calculated, leading to the development of a rock mass instability warning method and multi-index fusion rock mass instability warning index, the Q-value. Finally, the model generated a visual cloud chart for real-time monitoring of Q-value changes across different areas. By observing the trend of early warning index changes over time or space, potential danger zones can be effectively predicted. Results show that the early warning model based on Sen’s slope trend analysis is highly effective in providing early warnings for rock mass instability in high and steep annular slope mining areas. The proposed warning model offers valuable technical support for mine managers, enabling stratified management strategies and ensuring safe mine operations.