Abstract

To improve the practicality of water-inrush hazard identification in underground metal mines under complex hydrogeological conditions, this study develops a multi-source information fusion evaluation framework. An index system is established that encompasses water-source conditions, water-conducting pathway characteristics, mining-induced disturbance, and goaf-related hazards. Subjective and objective information are integrated through combined weighting based on the intuitionistic fuzzy analytic hierarchy process (IFAHP) and the entropy weight method (EWM). To characterize uncertainty and support hazard classification, a normal cloud model is introduced. The proposed method is applied to three stopes, namely 150701, 200-6-1, and 400-27-3, in a copper–iron mine in Anhui Province. The evaluation results classify the three stopes as Level III, Level II, and Level IV, respectively, which are consistent with the observed water inflows of approximately 28 m3/h, 17 m3/h, and 35 m3/h. These results indicate that the proposed method shows applicability in stope-scale water-inrush hazard assessment in the case mine and can provide a quantitative reference for risk identification and prevention under complex hydrogeological conditions.

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