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<p>In recent years, heavy metal pollution in mines has garnered significant attention. However, systematic research on the hydrogeochemical characteristics and heavy metal migration patterns in groundwater at abandoned mine sites remains limited. Therefore we analyzed the hydrogeochemical characteristics and heavy metal migration patterns of groundwater at an abandoned iron ore mine in Jiangxi Province, China. A total of 64 groundwater samples were collected during the rainy season and 14 during the dry season. Self-organizing mapping (SOM), K-means clustering, multivariate statistical analysis, and the Piper diagram method were employed for analysis. The results revealed six distinct hydrogeochemical types of groundwater, with the hydrogeochemical evolution primarily being influenced by mining legacy waste and subsequent anthropogenic activities. Groundwater in the study area is predominantly of the HCO<sub>₃</sub>-Ca type, while areas near the tailing pond exhibit high total dissolved solids (TDS), low pH, and minor SO₄-Ca components. The exceedance rates of Mn and Fe were 60.0% and 53.8%, respectively. Positive matrix factorization (PMF) identified mining activities, farms, agricultural practices, and indirect mining impacts as the primary sources of heavy metal pollution. In contrast, elements such as As, Pb, Cd, Ni, and Be exhibited lower exceedance rates, possibly due to the specific adsorption behavior of Mn and Fe. These findings provide a scientific basis for environmental remediation and pollution control in abandoned mining areas.</p>

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Hydrogeochemical analysis and tracing of heavy metal contamination in groundwater using self-organizing mapping

  • 期刊论文

  • 发表日期：

    2025年5月25日

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  • Zhenzhou Sun,
  • Qinghai Deng,
  • Liping Zhang,
  • Lusheng Song,
  • Hongjuan Zhao,
  • Jiutan Liu,
  • Xiao Wu,
  • Jiayi Mu

摘要

In recent years, heavy metal pollution in mines has garnered significant attention. However, systematic research on the hydrogeochemical characteristics and heavy metal migration patterns in groundwater at abandoned mine sites remains limited. Therefore we analyzed the hydrogeochemical characteristics and heavy metal migration patterns of groundwater at an abandoned iron ore mine in Jiangxi Province, China. A total of 64 groundwater samples were collected during the rainy season and 14 during the dry season. Self-organizing mapping (SOM), K-means clustering, multivariate statistical analysis, and the Piper diagram method were employed for analysis. The results revealed six distinct hydrogeochemical types of groundwater, with the hydrogeochemical evolution primarily being influenced by mining legacy waste and subsequent anthropogenic activities. Groundwater in the study area is predominantly of the HCO₃-Ca type, while areas near the tailing pond exhibit high total dissolved solids (TDS), low pH, and minor SO₄-Ca components. The exceedance rates of Mn and Fe were 60.0% and 53.8%, respectively. Positive matrix factorization (PMF) identified mining activities, farms, agricultural practices, and indirect mining impacts as the primary sources of heavy metal pollution. In contrast, elements such as As, Pb, Cd, Ni, and Be exhibited lower exceedance rates, possibly due to the specific adsorption behavior of Mn and Fe. These findings provide a scientific basis for environmental remediation and pollution control in abandoned mining areas.