Groundwater Vulnerability to Arsenic Contamination: A Review of Assessment Approaches

AbstractGroundwater vulnerability to geogenic groundwater contamination underlies the complex interplay between various intrinsic geological, hydrogeological, and geochemical characteristics in an aquifer system. Identifying the risks to groundwater quality in this regard is a very engaging process...

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Veröffentlicht in:Journal of environmental engineering (New York, N.Y.) N.Y.), 2024-12, Vol.150 (12)
Hauptverfasser: Dhamija, Sana, Joshi, Himanshu
Format: Artikel
Sprache:eng
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Zusammenfassung:AbstractGroundwater vulnerability to geogenic groundwater contamination underlies the complex interplay between various intrinsic geological, hydrogeological, and geochemical characteristics in an aquifer system. Identifying the risks to groundwater quality in this regard is a very engaging process that needs to consider the source and nature of groundwater contamination from the perspective of ongoing external and internal processes within the area/region under study. Arsenic contamination in groundwater has stood out due to its worldwide spread and lethality. It is an established fact that most arsenic sources are predominantly geogenic in nature. Yet, the mechanisms of its mobilization in groundwater appear to be triggered by anthropogenic factors many times. However, the propositions are still being debated and are in an ever-evolving stage. Assessment of groundwater vulnerability to arsenic contamination may thus be considered a potentially valuable management tool for enabling major decisions on preventative groundwater protection, and there is apparently an urgent need to develop robust approaches for the same. One can easily find reviews on groundwater vulnerability per se, but the current review reflects relevant and recent core data compilation/consolidation specifically on arsenic vulnerability assessment. The current work attempts to provide a comprehensive review of the occurrence of arsenic in the subsurface environment, along with the earlier and recent approaches involved in groundwater vulnerability assessment, including mathematical, geostatistical, process-based simulation, and machine learning methods. This paper considers and compares available case studies in this regard and highlights the potential of integrated/hybrid modeling to achieve the best possible outcomes.
ISSN:0733-9372
1943-7870
DOI:10.1061/JOEEDU.EEENG-7624