Application of multivariate statistical methods and inverse geochemical modeling for characterization of groundwater — A case study: Ain Azel plain (Algeria)

Multivariate statistical methods and inverse geochemical modeling were jointly used to define the variation and the genetic origin of chemical parameters of groundwater in the Ain Azel plain, Algeria. Interpretation of analytical data shows that the abundance of the major ions is as follows: Ca ≥ Mg...

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Bibliographic Details
Published in:Geoderma Vol. 159; no. 3; pp. 390 - 398
Main Authors: Belkhiri, Lazhar, Boudoukha, Abderrahmane, Mouni, Lotfi, Baouz, Toufik
Format: Journal Article
Language:English
Published: Amsterdam Elsevier B.V 15.11.2010
Elsevier
Subjects:
Agronomy. Soil science and plant productions
Ain Azel
Algeria
Biological and medical sciences
Earth sciences
Earth, ocean, space
Exact sciences and technology
Fundamental and applied biological sciences. Psychology
Geochemistry
Groundwater
Hierarchical cluster analysis
Hydrogeology
Hydrology. Hydrogeology
Inverse
Inverse geochemical modeling
Magnesium
Minerals
PHREEQC
Samples
Soils
Statistical analysis
Statistical methods
Surficial geology
Water chemistry
North Africa
Algeria
Africa
Ain Azel
Algeria
Inverse geochemical modeling
Hierarchical cluster analysis
PHREEQC
calcium
chemical properties
ground water
inverse modeling
magnesium
ground-water recharge
case studies
multivariate analysis
Modeling
aquifers
hydrochemistry
Partitioning
interpretation
geochemical models
plains
ions
cluster analysis
statistical analysis
soils
ISSN:0016-7061, 1872-6259
Online Access:Get full text
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Summary:Multivariate statistical methods and inverse geochemical modeling were jointly used to define the variation and the genetic origin of chemical parameters of groundwater in the Ain Azel plain, Algeria. Interpretation of analytical data shows that the abundance of the major ions is as follows: Ca ≥ Mg > Na > K and HCO 3 ≥ Cl > SO 4. Q-mode hierarchical cluster analysis (HCA) was employed for partitioning the water samples into hydrochemical facies, also known as water groups or water types. Three major water groups resulted from the HCA analysis. The samples from the area were classified as recharge area waters (Group 1: Ca–Mg–HCO 3 water), transition zone waters (Group 2: Ca–Mg–Cl–HCO 3 water), and discharge area waters (Group 3: Mg–Ca–HCO 3–Cl water). Inverse geochemical models of the statistical groups were developed using PHREEQC to elucidate the chemical reactions controlling water chemistry. The inverse geochemical modeling demonstrated that relatively few phases are required to derive water chemistry in the area. In a broad sense, the reactions responsible for the hydrochemical evolution in the area fall into three categories: (1) dissolution of evaporite minerals; (2) precipitation of carbonate minerals; and (3) weathering reactions of silicate minerals. ► Combination of statistical methods and geochemical modeling. ► Hierarchical cluster analysis (HCA). ► Element ratios. ► Inverse modelling to formulate hypotheses on the element sources and sinks involved in the evolution from the initial to the final chemical composition.
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ISSN:0016-7061
1872-6259
DOI:10.1016/j.geoderma.2010.08.016