Source identification of mine water inrush based on the exponential whitenization function and the grey situation decision model

Abstract

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.