Multivariate statistical analysis of groundwater quality in the Akbou region Bejaia
Keywords:
multivariate statistical techniquesAbstract
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The physico-chemical parameters are the most important analysis that characterizes the groundwater quality. Therefore, they determine the use of water (supply water, irrigation, industrie...)
The study aim determining the physico-chemical analysis and the hydrogeological characteristics of the aquifer of Akbou region Bejaia coming from the different wells.
To investigate the conformity of these wells, samples were taken in 2023, from 6 boreholes, which are principal resources of water supplying Akbou region, to have a dataset composed from 15 chemical variables over the entire study area, which then, exploited, and analyzed using multivariate statistical techniques.
The analysis is useful for the authorities to plan the supply of water to their populations, and rational use of groundwater resources.
References
Seikhy T.; Ramli M.R.; Aris A.Z.; Sulai¬man W.N.A.; Fakharian K..Spatiotemporal variation of groundwater quality using integrated multivariate statistical and geostatistical approaches in Amol-Babol Plain, Iran. Environ Monit Assess, 2014, 186, 5797–5815.
Anazawa K. Ohmori H. The hydrochemistry of surface waters in andesitic volcanic area, Nori¬kura volcano, central Japan. Chemosphere 2005, 59(5), 605–615.
Belkhiri L.; Bencer S.; Boudoukha A.; Mouni L. Multi¬variate statistical analysis of the groundwater of Ain Djacer area (Eastern of Algeria). Arab J Geosci 2016, 9, 248.
Tiri A.; Lahbari N.; Boudoukha A. Multivari¬ate statistical analysis and geochemical modeling to characterize the surface water of Oued Chemora Basin, Algeria. Nat Resour Res 2014, 23(4), 379–391.
Ferhati A.; Mitiche-Kettab R.; Belazreg N.; Djafer Khodja H.; Djerbouai S. and Hasbaia M. Hydrochemical analysis of groundwater quality in central Hodna Basin, Algeria: a case study. IJHST 2023, DOI:10.1504/IJHST.2021.10040507.
Metaiche E.; Djafer Khodja H.; Aichour A.; Gaci N. Multivariate Statistical Analysis of Groundwater Quality of Hassi R’mel, Algeria. JEE 2023, 24(5), 22–31. https://doi.org/10.12911/22998993/161140.
Khedidja A.; Boudoukha A. Risk assessment of agricultural pollution on groundwater quality in the high valley of Tadjenanet-Chelghoum Laid (Eastern Algeria). Des Water Treat 2014, 52(22–24), 4174–4182.
Blake S.; Henry T.;.Murray J.; Flood R.; Muller M.R.; Jones A.G.; Rath V. Compositional multivariate statistical analysis of thermal groundwater provenance: A hydrogeochemical case study from Ireland, Appl Geochem 2016, doi: 10.1016/j.apgeochem 2016, 05.008.
Barkat A.; Bouaicha F.; Bouteraa O.; Mester T.; Ata B.; Balla D.; Rahal Z.; Szabó G. Assessment of Complex Terminal Groundwater Aquifer for Different Use of Oued Souf Valley (Algeria) Using Multivariate Statistical Methods, Geostatistical Modeling, and Water Quality Index. Water 2021, 13, 1609. https://doi.org/10.3390/w13111609.
Djafer khodja H.; Aichour A.; Rezig A.; Baloul D..; Ferhati A. Application of Multivariate Statistical Methods to the Hydrochemical Study of Groundwater Quality in the Sahel Watershed, Algeria. JEE 2022, 23(8).
Boudoukha A.; Mouni L.; Baouz T. Statistical categorization geochemical modeling of groundwater in Ain Azel plain (Algeria), J Afr Earth Sci 2011, 59, 140–148.

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Copyright (c) 2024 Djafer Khodja Hakim, Aichour Amina, Metaiche Mehdi, Ferhati Ahmed, Ghessouli Moloud

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