An investigation into the disturbance effects of coal mining on groundwater and surface ecosystems

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Abstract
Coal mining disturbs surface ecosystems in coal mining subsidence areas. Based on the groundwater–surface composite ecosystem analysis, we constructed an ecological disturbance evaluation index system (18 indices) in a coal mining subsidence area using the analytic hierarchy process (AHP). Taking the Nalinhe mining area in Wushen Banner, China, in 2018–2020 as an example, the weight, ecological disturbance grade and correlation of different indicators were determined by implementing fuzzy mathematics, weighting method, and correlation analysis method. The major conclusions of this review were: (i) After two years of mining, ecological disturbance was the highest in the study area (Grade III) and the lowest in the non-mining area (Grade I). (ii) Coal mining not only directly interfered with the environment, but also strengthened the connection of different ecological indicators, forming multiple ecological disturbance chains such as “mining intensity–mining thickness–buried depth/Mining thickness”, “coal mining–surface subsidence–soil chemical factors”, and “natural environment–soil physical factors”. The disturbance chain that controls the ecological response factors in the region remains to be determined. However, the ecological response factors are the most important factor that hinders the restoration of the ecology in a coal mining subsidence area. (iii) The ecological disturbance in the coal mining subsidence area continued increasing over two years due to coal mining. The ecological disturbance by coal mining cannot be completely mitigated by relying on the self-repair capability of the environment. This study is of great significance for ecological restoration and governance of coal mining subsidence areas.
Funding Information
  • The National Key R&D Program of China (2022YFF1303304, 2022YFF1303304, 2022YFF1303304, 2022YFF1303304, 2022YFF1303304, 2022YFF1303304, 2022YFF1303304)
  • The National Natural Science Foundation of China (42177037, 42177037, 42177037, 42177037, 42177037, 42177037, 42177037)
  • the Talent Introduction Plan for Xinjiang in 2020

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