Groundwater Arsenic Distribution in India by Machine Learning Geospatial Modeling.
Int J Environ Res Public Health
; 17(19)2020 09 28.
Article
en En
| MEDLINE
| ID: mdl-32998478
ABSTRACT
Groundwater is a critical resource in India for the supply of drinking water and for irrigation. Its usage is limited not only by its quantity but also by its quality. Among the most important contaminants of groundwater in India is arsenic, which naturally accumulates in some aquifers. In this study we create a random forest model with over 145,000 arsenic concentration measurements and over two dozen predictor variables of surface environmental parameters to produce hazard and exposure maps of the areas and populations potentially exposed to high arsenic concentrations (>10 µg/L) in groundwater. Statistical relationships found between the predictor variables and arsenic measurements are broadly consistent with major geochemical processes known to mobilize arsenic in aquifers. In addition to known high arsenic areas, such as along the Ganges and Brahmaputra rivers, we have identified several other areas around the country that have hitherto not been identified as potential arsenic hotspots. Based on recent reported rates of household groundwater use for rural and urban areas, we estimate that between about 18-30 million people in India are currently at risk of high exposure to arsenic through their drinking water supply. The hazard models here can be used to inform prioritization of groundwater quality testing and environmental public health tracking programs.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Arsénico
/
Contaminantes Químicos del Agua
/
Agua Subterránea
Tipo de estudio:
Prognostic_studies
Límite:
Humans
País/Región como asunto:
Asia
Idioma:
En
Revista:
Int J Environ Res Public Health
Año:
2020
Tipo del documento:
Article
País de afiliación:
Reino Unido