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Groundwater vulnerability to pollution in Africa’s Sahel region

Author

Listed:
  • Joel Podgorski

    (Eawag, Swiss Federal Institute of Aquatic Science and Technology)

  • Oliver Kracht

    (International Atomic Energy Agency)

  • Luis Araguas-Araguas

    (International Atomic Energy Agency)

  • Stefan Terzer-Wassmuth

    (International Atomic Energy Agency)

  • Jodie Miller

    (International Atomic Energy Agency)

  • Ralf Straub

    (SFOE, Swiss Federal Office of Energy)

  • Rolf Kipfer

    (Eawag, Swiss Federal Institute of Aquatic Science and Technology)

  • Michael Berg

    (Eawag, Swiss Federal Institute of Aquatic Science and Technology)

Abstract

Protection of groundwater resources is essential to ensure quality and sustainable use. However, predicting vulnerability to anthropogenic pollution can be difficult where data are limited. This is particularly true in the Sahel region of Africa, which has a rapidly growing population and increasing water demands. Here we use groundwater measurements of tritium (3H) with machine learning to create an aquifer vulnerability map (of the western Sahel), which forms an important basis for sustainable groundwater management. Modelling shows that arid areas with greater precipitation seasonality, higher permeability and deeper wells or water table generally have older groundwater and less vulnerability to pollution. About half of the modelled area was classified as vulnerable. Groundwater vulnerability is based on recent recharge, implying a sensitivity also to a changing climate, for example, through altered precipitation or evapotranspiration. This study showcases the efficacy of using tritium to assess aquifer vulnerability and the value of tritium analyses in groundwater, particularly towards improving the spatial and temporal resolution.

Suggested Citation

  • Joel Podgorski & Oliver Kracht & Luis Araguas-Araguas & Stefan Terzer-Wassmuth & Jodie Miller & Ralf Straub & Rolf Kipfer & Michael Berg, 2024. "Groundwater vulnerability to pollution in Africa’s Sahel region," Nature Sustainability, Nature, vol. 7(5), pages 558-567, May.
    • Handle: RePEc:nat:natsus:v:7:y:2024:i:5:d:10.1038_s41893-024-01319-5
    DOI: 10.1038/s41893-024-01319-5
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    References listed on IDEAS

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    1. Wright, Marvin N. & Ziegler, Andreas, 2017. "ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 77(i01).
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    3. Mark O. Cuthbert & Richard G. Taylor & Guillaume Favreau & Martin C. Todd & Mohammad Shamsudduha & Karen G. Villholth & Alan M. MacDonald & Bridget R. Scanlon & D. O. Valerie Kotchoni & Jean-Michel Vo, 2019. "Observed controls on resilience of groundwater to climate variability in sub-Saharan Africa," Nature, Nature, vol. 572(7768), pages 230-234, August.
    4. Joel Podgorski & Michael Berg, 2022. "Global analysis and prediction of fluoride in groundwater," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
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    6. 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.
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