Unravelling the Past for a Safer Future: How Historic Rock Mass Classification Data Compare With Slope Performance Monitoring Data

Abstract

This research investigates the correlation between empirically derived monitoring threshold values and actual slope monitoring data in open-pit mining, focusing on the Gamsberg Mine in South Africa. The study analyses two slope failure events within a schist layer. The goal was to quantitatively analyse available datasets to determine their relationship and evaluate whether empirical predictions can accurately forecast real-world rock mass behaviour in open pit slopes. Rock mass classification data (RMR and GSI) from borehole logs were compared with real-time deformation measurements from slope stability radar. The methodology involved extracting relevant geotechnical data, calculating rock mass modulus and strain values, and comparing these with actual recorded deformations. Statistical analysis utilizing Z-tests and visual representations was employed to assess the correlation. The study reveals a significant alignment between empirical predictions and actual measurements, with both events falling within one standard deviation of the empirical dataset's mean. This validates the utilization of empirical methods for initial deformation threshold estimations in slope stability monitoring. The research underscores the importance of continuous calibration with site- specific data while validating empirical methods. It contributes to improving risk management and operational efficiency in open-pit mining by bridging the gap between theoretical models and real-world slope behaviour. Future research should focus on expanding the sample size, investigating environmental factors, and integrating emerging technologies to enhance prediction accuracy. These steps will further refine the application of empirical methods in slope stability monitoring and improve overall mining safety and efficiency. This study provides valuable insights into the practical application of empirical deformation thresholds in open-pit mining, offering a foundation for more accurate and reliable slope stability assessments. The findings have implications for iv enhancing safety protocols, optimizing resource extraction and improving overall operational efficiency in the mining industry.