Multi-parameter analysis of groundwater resources quality in the Auvergne-Rhône-Alpes region (France) using a large database
2023
Ayach, Meryem | Lazar, Hajar | Bousouis, Abderrahim | Touiouine, Abdessamad | Kacimi, Ilias | Valles, Vincent | Barbiero, Laurent | Université Mohammed V de Rabat [Agdal] (UM5) | Université Ibn Tofaïl (UIT) | Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes (EMMAH) ; Avignon Université (AU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) | Géosciences Environnement Toulouse (GET) ; Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3) ; Communauté d'universités et établissements de Toulouse (Comue de Toulouse)-Communauté d'universités et établissements de Toulouse (Comue de Toulouse)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)
International audience
Mostrar más [+] Menos [-]Inglés. The aim of this work is to gain a better understanding of the diversity of groundwater resource quality in the Auvergne-Rhône-Alpes region (France) using the national Sise-Eaux database. Three matrices were extracted, which included a hollow matrix (approximately 120,000 observations and 21 variables) and two complete matrices (8078 observations with 13 variables each and 150 observations with 20 variables each, respectively). The mapping of these parameters, the chemical profiles of the water, and the characteristics of the variograms make it possible to estimate the importance of the temporal variance compared with the spatial variance. This distinction led to a typology separating 4 groups of chemical parameters and 2 groups of bacteriological parameters, highlighting the information redundancies linking several parameters. A PCA was used to considerably reduce the size of the hyperspace of the data. The study of the factorial axes combined with their distribution over the study area made it possible to discriminate and identify certain mechanisms for acquiring the physico-chemical and bacteriological characteristics of groundwater, the importance of lithology, the components of faecal contamination, and the role of environmental conditions. A typology of the parameters by hierarchical clustering on the major part of the information makes it possible to reduce the information to that carried by a few representative parameters. This work is a new step in understanding the diversity of groundwater resources in general, with a view to more targeted monitoring based on this diversity.
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