Research and Application of Sandstone Water in Shengquan Coal Mine Based on Multidimensional Analysis
SHI Longqing
LI Xinyang
ZHANG Junwei
Abstract：Aiming at the problems of water environment destruction,domestic water pollution and gradual spreading of pro-duction sewage to deep aquifers caused by mining Shengquan coal mine,water samples of sandstone water in Shengquan well field of Xintai City were systematically collected,and 12 samples of sandstone water in Shengquan well field were used as the basis of the study.TDS,total hardness,pH,Ca2+,Mg2+,Fe3+,NH4+,Cl-,SO42-,HCO3-and K++Na+were selected as 11 water chemistry indicators for water quality evaluation.Paper trilinear diagram and ionic ratio analysis were used to reveal the water chemistry genesis and the formation mechanism of sandstone water.Secondly,the traditional Nemero index method,the improved Nemero index method,grey clustering method and the fuzzy comprehensive evaluation method based on the AHP-EWM calculation of the weights were applied to evaluate the water quality,and their evaluation results were compared respectively.The results show that the sandstone water samples in the Shengquan well field area are weakly acidic and alkaline,with the highest SO42-among the anions and the highest K++Na+among the cations,and the hydrochemical types are mainly of the HCO3·SO4-(K+Na)type and HCO3·SO4-(K+Na)·Mg·Ca type,and the sandstone ions in the water originated from the dissolution of salt rock and silicate weathering,the desulfurization is weak,the cation exchange adsorption is strong,and the water quality is obviously divided into two categories,category Ⅰ are all class Ⅰ water,applicable to domestic water.Compared with grey clustering method,fuzzy comprehensive evaluation method has better applicability.The results of the study can provide a useful reference for meeting the safety of domestic and industrial water use,and at the same time,provide a strong support for local water resources management and water environmental protection.
Keywords：water quality evaluationhydrochemical characteristicsNemero index methodgrey clustering methodfuzzy integrated evaluation method
Publication Date：2025-06-30
Online Publishing Date：2025-09-22(First online date of this platform, not the publication date of the document)
Pages：12( 98-109 )