Groundwater Bodies Subdivision in Corsica: A Critical Approach Based on Multivariate Water Quality Criteria Using Large Database

Abstract

The cross-referencing of two databases, namely the compartmentalization into groundwater bodies (GWB) and the quality monitoring (2830 observations including 15 physico-chemical and bacteriological parameters, on 662 collection points and over a period of 27 years) is applied to better understand the diversity of the waters of the island of Corsica (France) and to facilitate the surveillance and quality monitoring of the groundwater resource. Data conditioning (log-transformation), dimensional reduction (PCA), classification (AHC) and then quantification of the information lost during grouping (ANOVA), highlight the need to sub-divide the groundwater bodies in the crystalline part of the island in order to take better account of lithological diversity and other environmental factors (slope, altitude, soil thickness, etc.). The compartmentalization into 15 units, mainly based on structural geology, provides less information than the grouping into 12 units after subdivision of the crystalline region. The diversity of the waters in terms of chemical and bacteriological composition is discussed, and the results encourage a review of the compartmentalization of the island’s GWBs, with a view to more targeted monitoring based on this diversity.

Groundwaters in the Auvergne-Rhône-Alpes Region, France: Grouping Homogeneous Groundwater Bodies for Optimized Monitoring and Protection

“…The data used in this study were extracted from the Sise-Eaux database (https: //data.eaufrance.fr/concept/sise-eaux, accessed in 15 March 2021). For further details regarding this national database, previous works by our research group [8][9][10][11][12][13][14][15], as well as the basic references [25,26], can be consulted. The extraction conducted for a 30-year period from July 1990 to September 2020 for our study area resulted in a sparse matrix of 114,033 observations (water samples) distributed across 3146 sampling points (Figure 3a), with 21 measured parameters.…”

“…A study conducted in the vast Auvergne-Rhône-Alpes region established a typology of quality parameters based on structures or associations between these parameters, differing in terms of spatial extent, seasonality, or long-term behavior [14]. Finally, quantifying the information initially contained in the datasets and lost during the grouping into homogeneous water bodies validated the proposed analysis method [13,15] on scales ranging from small to large regions (8000 to 80,000 km 2 ). This method works across regions of variable size, ranging from moderately contrasting (Provence-Alpes-Côte d'Azur) to larger but moderately contrasting in lithological, altitudinal, environmental, or land use aspects.…”

“…Consistent with previous studies [10], the data underwent a logarithmic transformation (decimal logarithm) using the formula y = log10(x + DL), where x and DL, respectively, represent the measurement of the physico-chemical or bacteriological parameter X and its detection limit [15]. Only the pH, which already corresponds to the logarithmic transformation of the chemical activity of H 3 O + , was retained without conditioning.…”

“…The complement to 1 of R 2 , i.e., the fraction of unexplained variance, reflects temporal variance if we neglect a small portion of variance related to analytical imprecision. The same calculation conducted at the GWB and GWB group scales allows quantifying the amount of information contained at these different spatial scales and thus tracking the information loss during grouping [15].…”

Multi-Parameter Analysis of Groundwater Resources Quality in the Auvergne-Rhône-Alpes Region (France) Using a Large Database

“…Discriminating spatial and temporal variance has made it possible to highlight seasonal mechanisms or long-term trends [20][21][22]. Finally, quantification of the information initially contained in the datasets and lost when grouped into homogeneous bodies of water made it possible to validate the proposed analysis method [23,24] on the scale of small to large regions (8000 to 80,000 km 2 ). The grouping method works on regions of variable size, i.e., medium-sized and fairly contrasted (Provence-Alpes-Côte d'Azur) or larger but moderately contrasted (Occitanie) from a lithological, altitudinal, environmental, or land-use point of view.…”