Assessment of water inrush risk based comprehensive cloud model: a case study in a lead zinc mine, China

This paper presents a water inrush comprehensive evaluation model based on cloud model. The qualitative and quantitative transformation of water inrush evaluation indices are realized by cloud generator, applied in the water inrush risk evaluation of lead zinc ore body mining in karst aquifer. 9 factors were selected to construct the water inrush evaluation index system. The risks of water inrush were classified to five levels: risk level I, risk level II, risk level III, risk level IV and risk level V, respectively. The improved analytic hierarchy process (IAHP) and the criteria importance though intercriteria correlation (CRITIC) were adopted to determine the subjective and objective weights of the evaluation indicators, respectively. The concept of Kullback information was applied to determine the combination weight of evaluation indices. Then, the comprehensive certainty of the water inrush risk level was determined, combining the index weight and the corresponding cloud eigenvalue. In addition, combined with the water inrush risk level of the samples, the water inrush risk zoning of the study area was realized with geographic information system (GIS). This model was applied to the Maoping lead zinc mine in southwestern China to evaluate the risk of water inrush from the mining of the ore body. The results show that the combined weight method (CWM) based on the concept of Kullback information is characteristic by both subjective and objective, without weight bias; the cloud model can better convert the qualitative and quantitative between evaluation indices; the prediction accuracy of the water inrush evaluation model constructed based on the CWM is higher than that of IAHP, CRITIC and water inrush coefficient (WIC), with a better fitting effect. This work provides an innovative idea for water inrush evaluation of ore body mining in karst aquifers.