Barry A. A. auteur aut IRD Yameogo S. auteur aut IRD Touzani M. auteur aut IRD Nakolendoussé S. auteur aut IRD Jabrane M. auteur aut IRD Touiouine A. auteur aut IRD Mohsine I. auteur aut IRD Barbiéro Laurent auteur aut IRD Valles V. auteur aut IRD text journalArticle eng text/pdf born digital access In Sahelian Africa, the characteristics of boreholes are often lost and, when several aquifers are present on the same site, it is difficult to know which one is being tapped or is likely to be contaminated, which hinders good management of the resource. In this study conducted on 153 wells distributed in the four major aquifers of Burkina Faso, the variation in chemical composition within the aquifers is high compared to that between the aquifers. In spite of this, treatment by linear statistical analysis and/or machine learning allows the discrimination of the aquifers with a success rate of about 80%. The introduction of water isotopes as an additional parameter and a dimensional reduction by principal component analysis allowed a discrimination rate of 87.6% to be achieved. The pathway of water from sedimentary to basement aquifers explains some of the confusion. specialized aquifer discrimination groundwater management water chemistry discriminant analysis machine learning Burkina Faso BURKINA FASO 062 020 Early access [14 ] 2023 0262-6667 https://www.documentation.ird.fr/hor/fdi:010088828 10.1080/02626667.2023.2288209 0262-6667 [F B010088828] https://www.documentation.ird.fr/hor/fdi:010088828 https://www.documentation.ird.fr/intranet/publi/2024-02/010088828.pdf Accès réservé (Intranet de l'IRD) IRD - Base Horizon / Pleins textes 2024-02-07 2025-02-24 fdi:010088828 fre