Water (Jul 2024)

Hydrochemical Characteristics and Water Quality Evaluation of Groundwater in the Luohe Formation of Binchang Mining Area, China

  • Xu Wang,
  • Kui Sun,
  • Wanchao Ma,
  • Jie Peng,
  • Ruiping Liu,
  • Jianping Chen,
  • Kun Zhang,
  • Shuai Gao,
  • Cheng Li,
  • Penghua Zhang

DOI
https://doi.org/10.3390/w16131913
Journal volume & issue
Vol. 16, no. 13
p. 1913

Abstract

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The groundwater of the Luohe Formation in Binchang mining area is the main source of water for industrial and agricultural use and for drinking water for residents in the area. In order to study the hydrochemical characteristics and water-quality status of Luohe Formation groundwater in the mining area, statistical analysis, Piper three-line diagram, ion ratio relationship, and other methods were used to study the hydrochemical characteristics and formation factors of the groundwater. The Nemerow index evaluation method and the fuzzy comprehensive evaluation method based on principal component analysis were used to evaluate the groundwater quality in the mining area. The results show that the groundwater is weakly acidic as a whole, and the content of SO42− and Cl− have strong variability in terms of spatial distribution. The groundwater chemical type gradually evolves from SO4 • HCO3 • Cl–Na, SO4–Na and SO4 • Cl–Na-type water in the north of the mining area to SO4 • HCO3 • Cl–Na • Ca, HCO3 • SO4–Na • Mg, and SO4 • Cl–Na • Ca • Mg-type water in the south. The formation of the hydrochemical composition of groundwater in the study area may be related to multiple factors such as cation-alternating adsorption, carbonate and sulfate dissolution, and hydraulic exchange with the groundwater of the upper Huachi Formation. Comparing the evaluation results of the Nemerow index method and the principal component analysis method, the latter’s evaluation results can take into account the contribution of each indicator to the overall groundwater quality, and to a certain extent can weaken the control effect of a certain pollution indicator, exceeding the limit on the entire evaluation result. Therefore, the evaluation results based on the principal component analysis method are more credible.

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