Evaluating groundwater quality in an arsenic-contaminated aquifer in the Red River Delta using machine learning: a case study in Van Phuc, Hanoi, Vietnam
XGBoost-based machine learning applied to hydrogeochemical indicators shows that groundwater in Van Phuc's arsenic-contaminated aquifer is predominantly poor to marginal quality and is controlled by redox-driven hydrogeochemical zonation.
Institutions
- Vietnam National University, Hanoi (VN)
- Swiss Federal Institute of Aquatic Science and Technology (CH)
- VNU University of Science (VN)
- Vietnam Academy of Science and Technology (VN)
Publication Details
- Journal
- Environmental Science Advances
- Published
- 2025-12-09
- DOI
- https://doi.org/10.1039/d5va00368g
- Primary Topic
- Arsenic contamination and mitigation
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Đại học Quốc gia Hà Nội