Work

Evaluating groundwater quality in an arsenic-contaminated aquifer in the Red River Delta using machine learning: a case study in Van Phuc, Hanoi, Vietnam

Year: 2025

Type: article

Abstract: 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.

Source: Environmental Science Advances

DOI: 10.1039/d5va00368g

Authors: Thi Duyen Vu, Thanh Dam Nguyen, Thi Kim Trang Pham, Michael Berg, Hung Viet Pham

Institutions: Vietnam National University, Hanoi, Graduate University of Science and Technology, VNU University of Science, Vietnam Academy of Science and Technology, Swiss Federal Institute of Aquatic Science and Technology

Language: English

Topic: Water Quality and Pollution Assessment

Subfield: Water Science and Technology

Field: Environmental Science

Domain: Physical Sciences

SDG: Clean water and sanitation

Open Access status: diamond

Funder: Đại học Quốc gia Hà Nội

Award: G3690143722

OpenAlex ID: W7111016130

FWCI: 0.254

Cites: 51

Cited by: 1

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