Hydrochemical characterisation of groundwater using multifactorial approach in Foum el Gueiss basin, Northeastern Algeria

Journal of Water and Land Development

article

Somia Lakhdari¹  Slimane Kachi¹  Vincent Valles³  Laurent Barbiero⁴  Belgacem Houha²  Suzanne Yameogo⁵  Meryem Jabrane⁶  Naouel Dali² 

[1] University 8 May 1945, Faculty of Natural and Life Sciences and Earth Sciences and Universe, Department Ecology and Environment;Abbes Laghrour University, Department of Ecology and Environment;Avignon University, National Research Institute for Agriculture, Food and the Environment, Mediterranean Environment and Modeling of Agro-Hydrosystems;The National Center for Scientific Research, Toulouse University, Midi-Pyrénées Observatory, UMR 5563, Géoscience Environement Toulouse;Ouagadougou University Professor Joseph Ki-Zerbo;Mohammed V University, Faculty of Sciences, Geoscience, Water and Environment Laboratory

关键词: discriminant analysis;    Foum El Gueiss;    groundwater quality;    hydrochemistry;    irrigated agriculture;   

DOI  :  10.24425/jwld.2021.139944

学科分类：农业科学（综合）

来源: Instytut Technologiczno-Przyrodniczego / Institute of Technology and Life Sciences

【 摘 要 】

Knowledge of the quantity and quality of groundwater is a prerequisite to encourage investment in the development of a region and to consider the sedentarisation of populations. This work synthesises and analyses data concerning the chemical quality of the available water acquired in the Foum el Gueiss catchment area in the Aures massif. Two families of waters are observed, on the one hand, calcium and magnesian chlorated-sulphate waters and on the other hand, calcium and magnesium bicarbonate waters. Multivariate statistical treatments (Principal Component Analysis – PCA and Discriminant Analysis – DA) highlight a gradient of minerality of the waters from upstream to downstream, mainly attributed to the impact of climate, and pollution of agricultural origin rather localised in the lower zones. These differences in chemical composition make it possible to differentiate spring, well and borehole waters. The main confusion is between wells and boreholes, which is understandable because they are adjacent groundwater, rather in the lower part of the catchment area. The confusion matrix on the dataset shows a complete discrimination with a 100% success rate. There is a real difference between spring water and other samples, while the difference between wells and boreholes is smaller. The confusion matrix for the cross-validation (50%).

【 授权许可】

Unknown