Research on the simulation of groundwater flow fields disturbed by coal mining based on multi-scale coupled...

Under the influence of subsurface engineering activities such as coal mining, the investigation of groundwater flow field variations holds significant importance for water resource management and environmental protection in deep aquifers. This study proposes a multi-scale coupled decision-based simulation method integrating microscopic physical properties of aquifers, macroscopic lithological distribution characteristics, and zonal modeling of coupled decision parameters. The proposed methodology integrates multi-scale characteristics of geological structures with spatially varied parameter weighting schemes, achieving comprehensive simulation of groundwater flow field variations induced by coal mining activities through systematic coupling of numerical modeling and decision support systems. The results indicate that sandstone specimens from the Zhiluo Formation exhibit porosities ranging from 20.8 % to 22.3 %, while those in the Yan'an Formation display a broader porosity spectrum of 9.1 %-20.9 %. Hydrogeological analysis reveals the marked superiority of coarse-grained sandstones in enhancing aquifer water storage capacity and hydraulic conductivity, with their permeability-enhancing effects progressively diminishing as particle size reduces. The established variable weight set pair-connection cloud model significantly enhances analytical accuracy in multi-scale coupled zoning, enabling effective parameter partitioning for both Zhiluo and Yan'an Formations. The constructed simulation model successfully replicates aquifer flow field evolution during mining disturbances, achieving over 90 % consistency between simulated and measured water levels across monitoring points. This modeling framework demonstrates strong predictive capability for assessing coal mining impacts on groundwater systems, providing scientific support for environmental protection, resource management, disaster prevention, and decision-making processes.