Mining activities interfere into the natural groundwater chemical environment, which may lead to hydrogeochemical changes of aquifers and mine water inrush disasters. The study of hydrogeochemical evolution processes of underground aquifers is helpful to the prevention and control of mine water inrush. The results show that the study area is mainly impacted by four hydrogeochemical processes: dissolution, cation exchange, desulfurization and reduction, and pyrite oxidation. The Cenozoic aquifers are dominated by carbonate dissolution and desulfurization. The Permian aquifers are impacted mainly by cation exchange and sulfate dissolution, followed by pyrite oxidation. The Carboniferous aquifers are mainly impacted by dissolving sulfate, followed by pyrite oxidation and cation exchange. The hydrogeochemical evolution of the aquifers was controlled by mining activities and tectonic changes, and a certain regularity in space. For the Cenozoic aquifers, sulfate dissolution and cation exchange increase from west to east, and desulfurization weakens. For the Permian aquifers, cation exchange and sulfate dissolution are stronger near synclines and faults, pyrite oxidation is enhanced, and desulfurization decreases from the middle to the east of the mining area. For the Carboniferous aquifers, there is a higher dissolution of rock salt, pyrite oxidation, and cation exchange from west to east, and the desulfurization effect weakens.
Coal mining at deep levels can cause mine water inrush and groundwater contamination, making it important to accurately and rapidly identify the water inrush source. In this study, 52 water samples were extracted from three types of aquifers in the Linhuan mining area, China. The water sample components Na+ + K+, Ca2+, Mg2+, HCO3−, Cl−, and SO42−, measured in the experiment, were used as evaluation variables, and the piecewise function equation was established by using the exponential whitening function. Finally, combined with water sample data and the CRITIC weighted grey situation decision-making method, the comprehensive membership degree was obtained, and the water inrush source was identified according to the principle of the maximum membership degree. The comprehensive accuracy of the model was 92.3%. The traditional grey situation decision-making method uses the linear whitening function to determine the membership value, ignoring that the value of the whitening function outside the adjacent level is 0, which improves the weight of the adjacent level, causes the loss of effective information, and reduces the discrimination rate. The exponential whitenization function in this paper will solve this problem and further improves the grey situation decision-making method to discriminate the water inrush source, which would also be beneficial regarding the prevention and control of mine water inrush and groundwater contamination.
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