Open AccessChloride-salinity as indicator of the chemical composition of groundwater: empirical predictive model based on aquifers in Southern Quebec, Canada
Author(s) -
Lamine Boumaiza,
Julien Walter,
Romain Chesnaux,
Randy L. Stotler,
Tao Wen,
Karen H. Johannesson,
K. Brindha,
Frédéric Huneau
Publication year - 2022
Publication title -
environmental science and pollution research international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.845
H-Index - 113
eISSN - 1614-7499
pISSN - 0944-1344
DOI - 10.1007/s11356-022-19854-z
Subject(s) - salinity , groundwater , aquifer , chloride , environmental science , hydrology (agriculture) , chemical composition , environmental chemistry , soil science , chemistry , geology , oceanography , geotechnical engineering , organic chemistry
The present study first describes the variations in concentrations of 12 chemical elements in groundwater relative to salinity levels in Southern Quebec (Canada) groundwater systems, and then uses this data to develop an empirical predictive model for evaluating groundwater chemical composition relative to salinity levels. Data is drawn from a large groundwater chemistry database containing 2608 samples. Eight salinity classes were established from lowest to highest chloride (Cl) concentrations. Graphical analyses were applied to describe variations in major, minor, and trace element concentrations relative to salinity levels. Results show that the major elements were found to be dominant in the lower salinity classes, whereas Cl becomes dominant at the highest salinity classes. For each of the major elements, a transitional state was identified between domination of the major elements and domination of Cl. This transition occurred at a different level of salinity for each of the major elements. Except for Si, the minor elements Ba, B, and Sr generally increase relative to the increase of Cl. The highest Mn concentrations were found to be associated with only the highest levels of Cl, whereas F was observed to be more abundant than Mn. Based on this analysis of the data, a correlation table was established between salinity level and concentrations of the chemical constituents. We thus propose a predictive empirical model, identifying a profile of the chemical composition of groundwater relative to salinity levels, to help homeowners and groundwater managers evaluate groundwater quality before resorting to laborious and costly laboratory analyses.