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

Abstract 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 statist...

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Autores principales:	José Barbosa Filho, Iara Brandão de Oliveira
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/e1c1d8cd62874504bb6baea2bcb1b999
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spelling	oai:doaj.org-article:e1c1d8cd62874504bb6baea2bcb1b9992021-12-02T19:06:44ZDevelopment of a groundwater quality index: GWQI, for the aquifers of the state of Bahia, Brazil using multivariable analyses10.1038/s41598-021-95912-92045-2322https://doaj.org/article/e1c1d8cd62874504bb6baea2bcb1b9992021-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-95912-9https://doaj.org/toc/2045-2322Abstract 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 (wi) 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.José Barbosa FilhoIara Brandão de OliveiraNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-22 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q José Barbosa Filho Iara Brandão de Oliveira Development of a groundwater quality index: GWQI, for the aquifers of the state of Bahia, Brazil using multivariable analyses
description	Abstract 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 (wi) 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.
format	article
author	José Barbosa Filho Iara Brandão de Oliveira
author_facet	José Barbosa Filho Iara Brandão de Oliveira
author_sort	José Barbosa Filho
title	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_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_sort	development of a groundwater quality index: gwqi, for the aquifers of the state of bahia, brazil using multivariable analyses
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/e1c1d8cd62874504bb6baea2bcb1b999
work_keys_str_mv	AT josebarbosafilho developmentofagroundwaterqualityindexgwqifortheaquifersofthestateofbahiabrazilusingmultivariableanalyses AT iarabrandaodeoliveira developmentofagroundwaterqualityindexgwqifortheaquifersofthestateofbahiabrazilusingmultivariableanalyses
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Development of a groundwater quality index: GWQI, for the aquifers of the state of Bahia, Brazil using multivariable analyses

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