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January 30, 2026Journal of Contaminant Hydrology

Assessment of groundwater vulnerability to heavy metals in four aquifers using machine learning algorithms

Gholamheidari Hamideh Entezari Mojgan

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Key Points

Groundwater vulnerability to heavy metals is significant in four aquifers assessed.
Machine learning algorithms revealed vulnerability scores, highlighting key contamination areas.
Observational analysis across four aquifers led to the identification of heavy metal risks.
Support for using machine learning can enhance understanding of aquifer vulnerability and inform water management.

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Implication

Analysis shows groundwater vulnerability to heavy metals in four aquifers, indicating potential risk to water quality.

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Cite This Study

Hamideh et al. (2026) studied this question.

synapsesocial.com/papers/69a75f37c6e9836116a2a6f4 https://doi.org/10.1016/j.jconhyd.2026.104853

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