Revealing the sources of arsenic in private well water using Random Forest Classification and Regression

Engineering & Materials Science

• Arsenic 100%
• Random forests 71%
• Potable water 68%
• Water wells 62%
• Water 36%
• Health risks 17%
• Land use 16%
• Drainage 14%
• Contamination 13%
• Abandoned mines 12%
• Soils 10%
• Orchards 10%
• Water quality 8%
• Learning algorithms 5%
• Health 4%
• Machine learning 4%
• Testing 3%

Earth & Environmental Sciences

• well water 77%
• arsenic 60%
• water well 48%
• drinking water 41%
• bedrock 17%
• health risk 12%
• human health 11%
• drainage 10%
• land use 9%
• well 8%
• contamination 8%
• abandoned mine 8%
• orchard 7%
• exposure 7%
• machine learning 6%
• soil type 6%
• mitigation 5%
• water quality 4%
• prediction 3%
• soil 2%
• water 2%

Chemical Compounds

• Drinking Water 55%
• Soil 11%
• Orchard 10%