Groundwater Arsenic Distribution in India by Machine Learning Geospatial Modeling.

Area of Science:

• Environmental Science
• Hydrogeology
• Public Health

Background:

• Groundwater is vital for drinking and irrigation in India, but its quality is compromised by contaminants.
• Arsenic contamination in groundwater aquifers is a significant natural issue in India.

Purpose of the Study:

• To create hazard and exposure maps for arsenic contamination in Indian groundwater.
• To identify areas and populations at risk of high arsenic exposure (>10 µg/L).

Main Methods:

• Utilized a random forest model with over 145,000 arsenic concentration measurements.
• Incorporated over two dozen predictor variables of surface environmental parameters.
• Analyzed statistical relationships between environmental factors and arsenic mobilization in aquifers.

Main Results:

• Developed hazard and exposure maps, identifying known and novel arsenic hotspots across India.
• Estimated that 18-30 million people in India are at risk of high arsenic exposure via drinking water.
• Geochemical processes influencing arsenic mobilization were consistent with observed data.

Conclusions:

• The study highlights widespread arsenic risk in Indian groundwater, affecting millions.
• Identified new potential arsenic hotspots beyond traditional high-risk zones.
• The developed hazard models can guide groundwater quality testing and public health interventions.