Identifying Water Quality Drivers Using Hydrogeochemical Analysis and Self-Organizing Maps: A Case Study in Northwestern China

Groundwater plays a vital role in water supply for coal mining areas in arid and semi-arid regions. However, mining activities can alter aquifer properties, leading to changes in hydrochemical characteristics and degradation of water quality. This study uses the Dahaize coal mine as a case study to analyze the hydrochemical characteristics and formation mechanisms of groundwater using multivariate statistical methods and Self-Organizing Maps (SOM). The rationality of the weight assignment for water quality indicators was further validated using SOM and correlation analysis. The results indicate that groundwater in the Quaternary and Luohe Groups is classified as Ca-HCO₃ type, while groundwater samples from the Zhiluo Group are predominantly of the Na-Cl type, exhibiting stronger water–rock interactions and evaporation crystallization. The spatial distribution of ions indicates that the enrichment of Na⁺ and SO₄²⁻ is the main factor contributing to groundwater quality deterioration. SOM and correlation analysis jointly confirm that Na⁺, SO₄²⁻, and Cl⁻ are the dominant pollution-driving factors, validating the rationality of the weight assignments derived from the Objective Combined Weight Water Quality Index (OCWQI) calculation. Anthropogenic activities have a significant impact on groundwater hydrochemistry: coal mining leads to notable SO₄²⁻ enrichment in deep groundwater, while agricultural fertilization and domestic sewage primarily influence the distribution of NO₃⁻ and NH₄⁺ in shallow groundwater. This study not only provides a scientific basis for groundwater quality management in coal mining areas, but also offers a methodological reference for water quality evolution and pollution risk assessment in arid regions.