Predicting the Distribution of Arsenic in Groundwater by a Geospatial Machine Learning Technique in the Two Most Affected Districts of Assam, India: The Public Health Implications

Arsenic (As) is a well‐known carcinogen and chemical contaminant in groundwater. The spatial heterogeneity in As distribution in groundwater makes it difficult to predict the location of safe areas for tube well installations, consumption, and agriculture. Geospatial machine learning techniques have...

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Detalles Bibliográficos
Autores principales: Nath, Bibhash, Chowdhury, Runti, Ni‐Meister, Wenge, Mahanta, Chandan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8934026/
https://www.ncbi.nlm.nih.gov/pubmed/35340282
http://dx.doi.org/10.1029/2021GH000585

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8934026/
https://www.ncbi.nlm.nih.gov/pubmed/35340282
http://dx.doi.org/10.1029/2021GH000585

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