Cargando…
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...
Autores principales: | , , |
---|---|
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 |
_version_ | 1784825495839309824 |
---|---|
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. |
format | Online Article Text |
id | pubmed-9638764 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT mohammedmusaabaa multivariatestatisticalandhydrochemicalapproachesforevaluationofgroundwaterqualityinnorthbahricitysudan AT szabonorbertp multivariatestatisticalandhydrochemicalapproachesforevaluationofgroundwaterqualityinnorthbahricitysudan AT szucspeter multivariatestatisticalandhydrochemicalapproachesforevaluationofgroundwaterqualityinnorthbahricitysudan |