The Multi-Parameter Mapping of Groundwater Quality in the Bourgogne-Franche-Comté Region (France) for Spatially Based Monitoring Management

Abderrahim Bousouis, Abdelhak Bouabdli, Meryem Ayach, Laurence Ravung, Vincent Valles and Laurent Barbiero ()
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Abderrahim Bousouis: Laboratoire de Géosciences, Faculté des Sciences, Université Ibn Tofaïl, BP 133, Kénitra 14000, Morocco
Abdelhak Bouabdli: Laboratoire de Géosciences, Faculté des Sciences, Université Ibn Tofaïl, BP 133, Kénitra 14000, Morocco
Meryem Ayach: Geosciences, Water and Environment Laboratory, Faculty of Sciences Rabat, Mohammed V University, Rabat 10000, Morocco
Laurence Ravung: Agence Régionale de Santé (ARS) Bourgogne-Franche Comté, 8 rue Heim, 90005 Belfort cedex, France
Vincent Valles: Mixed Research Unit EMMAH (Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes), Hydrogeology Laboratory, Avignon University, 84916 Avignon, France
Laurent Barbiero: Institut de Recherche pour le Développement, Géoscience Environnement Toulouse, CNRS, University of Toulouse, Observatoire Midi-Pyrénées, UMR 5563, 14 Avenue Edouard Belin, 31400 Toulouse, France

Sustainability, 2024, vol. 16, issue 19, 1-17

Abstract: Groundwater, a vital resource for providing drinking water to populations, must be managed sustainably to ensure its availability and quality. This study aims to assess the groundwater quality in the Bourgogne-Franche-Comté region (~50,000 km 2 ) of France and identify the processes responsible for its variability. Data were extracted from the Sise-Eaux database, resulting in an initial sparse matrix comprising 8723 samples and over 100 bacteriological and physicochemical parameters. From this, a refined full matrix of 3569 samples and 22 key parameters was selected. The data underwent logarithmic transformation before applying principal component analysis (PCA) to reduce the dimensionality of the dataset. The analysis of the spatial structure, using both raw and directional variograms, revealed a categorization of parameters, grouping major ions according to the regional lithology. Bacteriological criteria ( Escherichia coli and Enterococcus ) displayed strong spatial variability over short distances, whereas iron (Fe) and nitrates showed intermediate spatial characteristics between bacteriology and major ions. The PCA allowed the creation of synthetic maps, with the first seven capturing 80% of the information contained in the database, effectively replacing the individual parameter maps. These synthetic maps highlighted the different processes driving the spatial variations in each quality criterion. On a regional scale, the variations in fecal contamination were found to be multifactorial, with significant influences captured by the first four principal components. The 22 parameters can be grouped into six categories based on their spatial and temporal variations, allowing for the redefinition of a resource management and monitoring strategy that is adapted to the identified spatial patterns and processes at the regional scale, while also reducing analytical costs.

Keywords: bacteriological composition; Bourgogne-Franche-Comté region; chemical composition; cluster analysis; groundwater; principal component analysis (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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