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Development of a groundwater quality index: GWQI, for the aquifers of the state of Bahia, Brazil using multivariable analyses

This work elaborated a groundwater quality index—GWQI, for the aquifers of the state of Bahia, Brazil, using multivariable analyses. Data from 600 wells located in the four hydrogeological domains: sedimentary, crystalline, karstic, and metasedimentary, were subjected to exploratory statistical anal...

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Autores principales: Barbosa Filho, José, de Oliveira, Iara Brandão
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8363630/
https://www.ncbi.nlm.nih.gov/pubmed/34389745
http://dx.doi.org/10.1038/s41598-021-95912-9
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author Barbosa Filho, José
de Oliveira, Iara Brandão
author_facet Barbosa Filho, José
de Oliveira, Iara Brandão
author_sort Barbosa Filho, José
collection PubMed
description This work elaborated a groundwater quality index—GWQI, for the aquifers of the state of Bahia, Brazil, using multivariable analyses. Data from 600 wells located in the four hydrogeological domains: sedimentary, crystalline, karstic, and metasedimentary, were subjected to exploratory statistical analysis, and 22 out of 26 parameters were subjected to multivariable analysis using Statistica (Version 7.0). From the PCA, 5 factors were sufficient to participate in the index, due to sufficient explanation of the cumulative variance. The matrix of factorial loads (for 1–5 factors) indicated 9 parameters related to water quality and 4 hydrological, with factor loads above ± 0.50, to be part of the hierarchical cluster analysis. The dendrogram allowed to choose the 5 parameters related to groundwater quality, to participate in the GWQI (hardness, total residue, sulphate, fluoride and iron). From the multivariable analyses, three parameters from a previous index—NGWQI, were not selected for the GWQI: chloride (belongs to the hardness hierarchical group); pH (insignificant factor load); and nitrate (significant factor load only for 6 factors), also, not a regionalized variable. From the set of communality values (5 factors), the degree of relevance of each parameter was extracted. Based on these values, were determined the relative weights (w(i)) for the parameters. Using similar WQI-NSF formulation, a product of quality grades raised to a power, which is the weight of importance of each variable, the GWQI values were calculated. Spatialization of 1369 GWQI values, with the respective colors, on the map of the state of Bahia, revealed good correlation between the groundwater quality and the index quality classification. According to the literature on water quality indexing, the GWQI developed here, using emerging technologies, is a mathematical tool developed as specific index, as it was derived using limits for drinking water. This new index was tailored to represent the quality of the groundwater of the four hydrogeological domains of the state of Bahia. Although it has a regionalized application, its development, using, factor analysis, principal component analysis, and hierarchical cluster analysis, participates of the new trend for WQI development, which uses rational, rather than subjective assessment. The GWQI is a successful index due to its ability to represent the groundwater quality of the state of Bahia, using a single mathematical formulation, the same five parameters, and unique weight for each parameter.
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spelling pubmed-83636302021-08-17 Development of a groundwater quality index: GWQI, for the aquifers of the state of Bahia, Brazil using multivariable analyses Barbosa Filho, José de Oliveira, Iara Brandão Sci Rep Article This work elaborated a groundwater quality index—GWQI, for the aquifers of the state of Bahia, Brazil, using multivariable analyses. Data from 600 wells located in the four hydrogeological domains: sedimentary, crystalline, karstic, and metasedimentary, were subjected to exploratory statistical analysis, and 22 out of 26 parameters were subjected to multivariable analysis using Statistica (Version 7.0). From the PCA, 5 factors were sufficient to participate in the index, due to sufficient explanation of the cumulative variance. The matrix of factorial loads (for 1–5 factors) indicated 9 parameters related to water quality and 4 hydrological, with factor loads above ± 0.50, to be part of the hierarchical cluster analysis. The dendrogram allowed to choose the 5 parameters related to groundwater quality, to participate in the GWQI (hardness, total residue, sulphate, fluoride and iron). From the multivariable analyses, three parameters from a previous index—NGWQI, were not selected for the GWQI: chloride (belongs to the hardness hierarchical group); pH (insignificant factor load); and nitrate (significant factor load only for 6 factors), also, not a regionalized variable. From the set of communality values (5 factors), the degree of relevance of each parameter was extracted. Based on these values, were determined the relative weights (w(i)) for the parameters. Using similar WQI-NSF formulation, a product of quality grades raised to a power, which is the weight of importance of each variable, the GWQI values were calculated. Spatialization of 1369 GWQI values, with the respective colors, on the map of the state of Bahia, revealed good correlation between the groundwater quality and the index quality classification. According to the literature on water quality indexing, the GWQI developed here, using emerging technologies, is a mathematical tool developed as specific index, as it was derived using limits for drinking water. This new index was tailored to represent the quality of the groundwater of the four hydrogeological domains of the state of Bahia. Although it has a regionalized application, its development, using, factor analysis, principal component analysis, and hierarchical cluster analysis, participates of the new trend for WQI development, which uses rational, rather than subjective assessment. The GWQI is a successful index due to its ability to represent the groundwater quality of the state of Bahia, using a single mathematical formulation, the same five parameters, and unique weight for each parameter. Nature Publishing Group UK 2021-08-13 /pmc/articles/PMC8363630/ /pubmed/34389745 http://dx.doi.org/10.1038/s41598-021-95912-9 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Barbosa Filho, José
de Oliveira, Iara Brandão
Development of a groundwater quality index: GWQI, for the aquifers of the state of Bahia, Brazil using multivariable analyses
title Development of a groundwater quality index: GWQI, for the aquifers of the state of Bahia, Brazil using multivariable analyses
title_full Development of a groundwater quality index: GWQI, for the aquifers of the state of Bahia, Brazil using multivariable analyses
title_fullStr Development of a groundwater quality index: GWQI, for the aquifers of the state of Bahia, Brazil using multivariable analyses
title_full_unstemmed Development of a groundwater quality index: GWQI, for the aquifers of the state of Bahia, Brazil using multivariable analyses
title_short Development of a groundwater quality index: GWQI, for the aquifers of the state of Bahia, Brazil using multivariable analyses
title_sort development of a groundwater quality index: gwqi, for the aquifers of the state of bahia, brazil using multivariable analyses
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8363630/
https://www.ncbi.nlm.nih.gov/pubmed/34389745
http://dx.doi.org/10.1038/s41598-021-95912-9
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