Open-pit slope risk zoning and main factor identification using multi-source information fusion

Open-pit slope instability is governed by coupled geological, hydrogeological, geometric, and operational factors, while available information is heterogeneous, incomplete, and uncertain. To support georisk assessment and management, this study proposes a multi-source information fusion framework for identifying controlling factors and grading slope risk in open-pit mines. The framework integrates r, s, t-spherical fuzzy numbers, expert-index correction, coefficient-of-variation-based agreement analysis, objective field-state calibration, entropy weighting, and TOPSIS within a unified zonal evaluation workflow. It is applied to the Kambove mining area in the Democratic Republic of the Congo using four criteria, 15 risk factors, and 10 slope zones. The results indicate that rock mass quality, the relationship between discontinuity orientation and slope aspect, unfavourable discontinuity conditions, rainfall, groundwater conditions, and adequacy of support measures are the principal contributors to slope risk, while Zones III, IV, and VIII are identified as high-risk areas. The patterns are consistent with field observations, including developed faults and joints, weak lithologies, intense rainy-season precipitation, and water-rich strata. Sensitivity analysis and comparisons with simplified fuzzy formulations and representative slope-evaluation methods support framework robustness and engineering interpretability. The proposed approach provides an interpretable basis for risk zoning, monitoring prioritisation, and targeted mitigation of open-pit slope geohazards.