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Mapping global hotspots and trends of water quality (1992–2010): a data driven approach

Author

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  • Sebastien Desbureaux

    (CEE-M - Centre d'Economie de l'Environnement - Montpellier - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Institut Agro Montpellier - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement - UM - Université de Montpellier)

  • Frederic Mortier

    (UPR Forêts et Sociétés - Forêts et Sociétés - Cirad - Centre de Coopération Internationale en Recherche Agronomique pour le Développement, Cirad-ES - Département Environnements et Sociétés - Cirad - Centre de Coopération Internationale en Recherche Agronomique pour le Développement)

  • Esha Zaveri

    (World Bank Group)

  • Michelle T H van Vliet

    (Universiteit Utrecht / Utrecht University [Utrecht])

  • Jason Russ

    (World Bank Group)

  • Aude Sophie Rodella

    (World Bank Group)

  • Richard Damania

    (World Bank Group)

Abstract

Clean water is key for sustainable development. However, large gaps in monitoring data limit our understanding of global hotspots of poor water quality and their evolution over time. We demonstrate the value added of a data-driven approach (here, random forest) to provide accurate high-frequency estimates of surface water quality worldwide over the period 1992-2010. We assess water quality for six indicators (temperature, dissolved oxygen, pH, salinity, nitrate-nitrite, phosphorus) relevant for the sustainable development goals. The performance of our modeling approach compares well to, or exceeds, the performance of recently published process-based models. The model's outputs indicate that poor water quality is a global problem that impacts low-, middle-and high-income countries but with different pollutants. When countries become richer, water pollution does not disappear but evolves. Water quality exhibited a signif icant change between 1992 and 2010 with a higher percentage of grid cells where water quality shows a statistically significant deterioration (30%) compared to where water quality improved (22%).

Suggested Citation

  • Sebastien Desbureaux & Frederic Mortier & Esha Zaveri & Michelle T H van Vliet & Jason Russ & Aude Sophie Rodella & Richard Damania, 2022. "Mapping global hotspots and trends of water quality (1992–2010): a data driven approach," Post-Print hal-03855421, HAL.
    • Handle: RePEc:hal:journl:hal-03855421
    DOI: 10.1088/1748-9326/ac9cf6
    Note: View the original document on HAL open archive server: https://hal.inrae.fr/hal-03855421v1
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    Keywords

    water quality; sustainable development goals; random forest; data-driven modelling;
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