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Multivariate statistical and hydrochemical approaches for evaluation of groundwater quality in north Bahri city-Sudan

Groundwater has recently been considered one of the primary sources of water supply in Sudan. However, groundwater quality is continuously degraded due to overexploitation and long-term agricultural operations. The fossilized Cretaceous Nubian sandstone is the principal aquifer in the study area. Th...

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Autores principales: Mohammed, Musaab A.A., Szabó, Norbert P., Szűcs, Péter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9638764/
https://www.ncbi.nlm.nih.gov/pubmed/36353162
http://dx.doi.org/10.1016/j.heliyon.2022.e11308
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author Mohammed, Musaab A.A.
Szabó, Norbert P.
Szűcs, Péter
author_facet Mohammed, Musaab A.A.
Szabó, Norbert P.
Szűcs, Péter
author_sort Mohammed, Musaab A.A.
collection PubMed
description Groundwater has recently been considered one of the primary sources of water supply in Sudan. However, groundwater quality is continuously degraded due to overexploitation and long-term agricultural operations. The fossilized Cretaceous Nubian sandstone is the principal aquifer in the study area. This research aims to determine the major factors influencing groundwater quality and detect the suitability of groundwater for drinking and irrigation purposes by integrating hydrochemical and multivariate statistical methods. Hydrochemical plots such as Piper, Chadha, and Durov diagrams were applied to detect the groundwater facies and hydrochemical processes controlling the groundwater quality. They indicated Ca–Mg–HCO(3) water type as a dominant groundwater facies followed by Na–HCO(3) and Na–Cl types. Gibbs plots suggested that the dissolution of the minerals is the main factor influencing the water quality. The results of the Gibbs plot were further interpreted using saturation indices (SI). The SI values indicated that aragonite, calcite, and dolomite precipitated respectively in 58.33%, 75%, and 75% of groundwater samples. Multivariate statistical analyses, including Pearson's correlation analysis, hierarchical cluster analysis (HCA), and principal component analyses (PCA), were jointly employed to identify the structure of water quality data and deduce the main factors controlling groundwater quality. The statistical analysis revealed the effect of the physical and human-induced activities as the main factors influencing groundwater chemistry. These factors are rock-water interaction, agricultural practice, and organic contamination from septic tanks. Further, the suitability of groundwater for irrigation is determined using sodium adsorption ratio (SAR) and sodium percent (Na(+)%) indices. They carefully indicated that 75% of the groundwater samples in the study area are excellent for irrigation except for some sample location where the salinity hazard is stimulated by ion exchange. This integrated approach was effective in calibrating water quality assessment methodologies. The current research concluded that the implication of a groundwater quality monitoring scheme is crucial to ensure water supply sustainability in north Bahri city.
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spelling pubmed-96387642022-11-08 Multivariate statistical and hydrochemical approaches for evaluation of groundwater quality in north Bahri city-Sudan Mohammed, Musaab A.A. Szabó, Norbert P. Szűcs, Péter Heliyon Research Article Groundwater has recently been considered one of the primary sources of water supply in Sudan. However, groundwater quality is continuously degraded due to overexploitation and long-term agricultural operations. The fossilized Cretaceous Nubian sandstone is the principal aquifer in the study area. This research aims to determine the major factors influencing groundwater quality and detect the suitability of groundwater for drinking and irrigation purposes by integrating hydrochemical and multivariate statistical methods. Hydrochemical plots such as Piper, Chadha, and Durov diagrams were applied to detect the groundwater facies and hydrochemical processes controlling the groundwater quality. They indicated Ca–Mg–HCO(3) water type as a dominant groundwater facies followed by Na–HCO(3) and Na–Cl types. Gibbs plots suggested that the dissolution of the minerals is the main factor influencing the water quality. The results of the Gibbs plot were further interpreted using saturation indices (SI). The SI values indicated that aragonite, calcite, and dolomite precipitated respectively in 58.33%, 75%, and 75% of groundwater samples. Multivariate statistical analyses, including Pearson's correlation analysis, hierarchical cluster analysis (HCA), and principal component analyses (PCA), were jointly employed to identify the structure of water quality data and deduce the main factors controlling groundwater quality. The statistical analysis revealed the effect of the physical and human-induced activities as the main factors influencing groundwater chemistry. These factors are rock-water interaction, agricultural practice, and organic contamination from septic tanks. Further, the suitability of groundwater for irrigation is determined using sodium adsorption ratio (SAR) and sodium percent (Na(+)%) indices. They carefully indicated that 75% of the groundwater samples in the study area are excellent for irrigation except for some sample location where the salinity hazard is stimulated by ion exchange. This integrated approach was effective in calibrating water quality assessment methodologies. The current research concluded that the implication of a groundwater quality monitoring scheme is crucial to ensure water supply sustainability in north Bahri city. Elsevier 2022-10-28 /pmc/articles/PMC9638764/ /pubmed/36353162 http://dx.doi.org/10.1016/j.heliyon.2022.e11308 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Mohammed, Musaab A.A.
Szabó, Norbert P.
Szűcs, Péter
Multivariate statistical and hydrochemical approaches for evaluation of groundwater quality in north Bahri city-Sudan
title Multivariate statistical and hydrochemical approaches for evaluation of groundwater quality in north Bahri city-Sudan
title_full Multivariate statistical and hydrochemical approaches for evaluation of groundwater quality in north Bahri city-Sudan
title_fullStr Multivariate statistical and hydrochemical approaches for evaluation of groundwater quality in north Bahri city-Sudan
title_full_unstemmed Multivariate statistical and hydrochemical approaches for evaluation of groundwater quality in north Bahri city-Sudan
title_short Multivariate statistical and hydrochemical approaches for evaluation of groundwater quality in north Bahri city-Sudan
title_sort multivariate statistical and hydrochemical approaches for evaluation of groundwater quality in north bahri city-sudan
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9638764/
https://www.ncbi.nlm.nih.gov/pubmed/36353162
http://dx.doi.org/10.1016/j.heliyon.2022.e11308
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