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Groundwater Arsenic Distribution in India by Machine Learning Geospatial Modeling

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  • Joel Podgorski

    (Department of Earth and Environmental Sciences and Williamson Research Centre for Molecular Environmental Science, University of Manchester, Manchester M13 9PL, UK
    Now at Department Water Resources and Drinking Water, Eawag, Swiss Federal Institute of Aquatic Science and Technology, 8600 Dübendorf, Switzerland.)

  • Ruohan Wu

    (Department of Earth and Environmental Sciences and Williamson Research Centre for Molecular Environmental Science, University of Manchester, Manchester M13 9PL, UK)

  • Biswajit Chakravorty

    (Centre for Flood Management Studies, National Institute of Hydrology, Water and Land Management Institute Complex, Phulwarisharif, Patna, Bihar 801505, India)

  • David A. Polya

    (Department of Earth and Environmental Sciences and Williamson Research Centre for Molecular Environmental Science, University of Manchester, Manchester M13 9PL, UK)

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.

Suggested Citation

  • Joel Podgorski & Ruohan Wu & Biswajit Chakravorty & David A. Polya, 2020. "Groundwater Arsenic Distribution in India by Machine Learning Geospatial Modeling," IJERPH, MDPI, vol. 17(19), pages 1-17, September.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:19:p:7119-:d:421116
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    References listed on IDEAS

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    1. J. S. Famiglietti, 2014. "The global groundwater crisis," Nature Climate Change, Nature, vol. 4(11), pages 945-948, November.
    2. Matthew Rodell & Isabella Velicogna & James S. Famiglietti, 2009. "Satellite-based estimates of groundwater depletion in India," Nature, Nature, vol. 460(7258), pages 999-1002, August.
    3. Laura A. Richards & Arun Kumar & Prabhat Shankar & Aman Gaurav & Ashok Ghosh & David A. Polya, 2020. "Distribution and Geochemical Controls of Arsenic and Uranium in Groundwater-Derived Drinking Water in Bihar, India," IJERPH, MDPI, vol. 17(7), pages 1-26, April.
    4. S. Chidambaram & R. Thilagavathi & C. Thivya & U. Karmegam & M. V. Prasanna & AL. Ramanathan & K. Tirumalesh & P. Sasidhar, 2017. "A study on the arsenic concentration in groundwater of a coastal aquifer in south-east India: an integrated approach," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 19(3), pages 1015-1040, June.
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    Cited by:

    1. Joel Podgorski & Michael Berg, 2022. "Global analysis and prediction of fluoride in groundwater," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    2. Liang Xiao & Yong Zhou & He Huang & Yu-Jie Liu & Ke Li & Meng-Yao Li & Yang Tian & Fei Wu, 2020. "Application of Geostatistical Analysis and Random Forest for Source Analysis and Human Health Risk Assessment of Potentially Toxic Elements (PTEs) in Arable Land Soil," IJERPH, MDPI, vol. 17(24), pages 1-19, December.

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