Evaluation of the water quality of the Pardo River (MG) based on physical, chemical and microbiological parameters

Detalhes bibliográficos
Autor(a) principal: Collares, Maria Fernanda Antunes
Data de Publicação: 2021
Outros Autores: Silva, Leonardo França da, Barbosa, Rubens Barrichello Gomes, Dourado, Ana Carolina Chaves, Rezende, Bruna Nogueira, Nascimento, João Antônio Costa do
Tipo de documento: Artigo
Idioma: por
Título da fonte: Research, Society and Development
Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/15532
Resumo: This article presents an analysis of the monitoring of the water quality index and the use of multivariate statistical techniques in the mining portion of the Pardo River, in order to select the most significant parameters in the current aspects of water quality, grouping the stations according to the similarity of the studied parameters. The data used in the study were obtained from the Minas Gerais Water Management Institute - IGAM for the months of January to October of the year 2018. The water quality index was calculated for the 5 monitoring points and classified according to the IQA -NSF. Principal component analysis (PCA) and Cluster analysis (CA) were used to reduce the number of variables and to group stations with similar characteristics, respectively. The PD005 station presented the lowest average of the water quality index, this is due to the fact that the parameter of faecal coliforms stands out negatively in great quantity in the station. Using the PCA, two main components were selected as indicators of water quality explaining the cumulative variance of 78%. The CA grouped the stations into three groups, being able to identify the most polluted and the least polluted stations. The results obtained through multivariate statistics have proved to be important for understanding the current water quality situation in the basin and can be used to improve the management of water resources because the collection and analysis of all parameters at all monitoring stations requires greater availability of financial resources.
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spelling Evaluation of the water quality of the Pardo River (MG) based on physical, chemical and microbiological parametersEvaluación de la calidad del agua del río Pardo (MG) en base a parámetros físicos, químicos y microbiológicosAvaliação da qualidade de água do rio Pardo (MG) com base em parâmetros físicos, químicos e microbiológicosHydrographic basinMultivariate statisticsMonitoring networkCluster analysis.Red de monitoreoCuenca hidrográficaEstadística multivarianteAnálisis de conglomerados.Rede de monitoramentoBacia hidrográficaEstatística multivariadaAnálise de cluster.This article presents an analysis of the monitoring of the water quality index and the use of multivariate statistical techniques in the mining portion of the Pardo River, in order to select the most significant parameters in the current aspects of water quality, grouping the stations according to the similarity of the studied parameters. The data used in the study were obtained from the Minas Gerais Water Management Institute - IGAM for the months of January to October of the year 2018. The water quality index was calculated for the 5 monitoring points and classified according to the IQA -NSF. Principal component analysis (PCA) and Cluster analysis (CA) were used to reduce the number of variables and to group stations with similar characteristics, respectively. The PD005 station presented the lowest average of the water quality index, this is due to the fact that the parameter of faecal coliforms stands out negatively in great quantity in the station. Using the PCA, two main components were selected as indicators of water quality explaining the cumulative variance of 78%. The CA grouped the stations into three groups, being able to identify the most polluted and the least polluted stations. The results obtained through multivariate statistics have proved to be important for understanding the current water quality situation in the basin and can be used to improve the management of water resources because the collection and analysis of all parameters at all monitoring stations requires greater availability of financial resources.Este artículo presenta un análisis del seguimiento del índice de calidad del agua y el uso de técnicas estadísticas multivariadas en el tramo minero del río Pardo, con el fin de seleccionar los parámetros más significativos en los aspectos actuales de la calidad del agua, agrupando las estaciones según la similitud de los parámetros estudiados. Los datos utilizados en el estudio se obtuvieron del Instituto de Gestión del Agua de Minas Gerais - IGAM para los meses de enero a octubre del año 2018. El índice de calidad del agua se calculó para los 5 puntos de monitoreo y se clasificó según el IQA -NSF. El análisis de componentes principales (ACP) y el análisis de conglomerados (AC) se utilizaron para reducir el número de variables y agrupar estaciones con características similares, respectivamente. La estación PD005 presentó el promedio más bajo del índice de calidad del agua, esto se debe a que el parámetro de coliformes fecales se destaca negativamente en gran cantidad en la estación. Utilizando el ACP, se seleccionaron dos componentes principales como indicadores de la calidad del agua que explican la varianza acumulada del 78%. La CA agrupó las estaciones en tres grupos, pudiendo identificar las estaciones más contaminadas y las menos contaminadas. Los resultados obtenidos a través de estadísticas multivariadas han demostrado ser importantes para comprender la situación actual de la calidad del agua en la cuenca y pueden utilizarse para mejorar la gestión de los recursos hídricos porque la recopilación y análisis de todos los parámetros en todas las estaciones de monitoreo requiere una mayor disponibilidad de recursos financieros.Este artigo apresenta uma análise do monitoramento do índice de qualidade da água e o emprego de técnicas estatísticas multivariadas na porção mineira do rio Pardo, visando selecionar os parâmetros mais significativos nos aspectos atuais da qualidade da água, agrupando as estações de acordo com à semelhança dos parâmetros estudados. Os dados utilizados no estudo, foram obtidos no Instituto Mineiro de Gestão de Águas – IGAM referentes aos meses de janeiro a outubro do ano de 2018. O índice de qualidade da água foi calculado para os 5 pontos de monitoramento e classificados de acordo com o IQA-NSF. Análise de componentes principais (ACP) e a análise de Cluster (AC) foram usadas para reduzir o número de variáveis ​​e para agrupar estações com características semelhantes, respectivamente. A estação PD005 apresentou a menor média do índice de qualidade de água, isso se deve pelo fato do parâmetro de coliformes fecais se destacar negativamente em grande quantidade na estação. Usando o ACP, dois componentes principais foram selecionados como indicadores da qualidade da água explicando a variância cumulativa de 78%. A AC agrupou as estações em três grupos podendo identificar a estação mais poluída e a estação menos poluída. Os resultados obtidos através de estatística multivariada provaram ser importantes para a compreensão da situação atual da qualidade da água na bacia e pode ser usado para melhorar a gestão dos recursos hídricos porque a coleta e análise de todos os parâmetros em todas as estações de monitoramento exigem maior disponibilidade recursos financeiros.Research, Society and Development2021-05-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://rsdjournal.org/index.php/rsd/article/view/1553210.33448/rsd-v10i5.15532Research, Society and Development; Vol. 10 No. 5; e60010515532Research, Society and Development; Vol. 10 Núm. 5; e60010515532Research, Society and Development; v. 10 n. 5; e600105155322525-3409reponame:Research, Society and Developmentinstname:Universidade Federal de Itajubá (UNIFEI)instacron:UNIFEIporhttps://rsdjournal.org/index.php/rsd/article/view/15532/13397Copyright (c) 2021 Maria Fernanda Antunes Collares; Leonardo França da Silva; Rubens Barrichello Gomes Barbosa; Ana Carolina Chaves Dourado; Bruna Nogueira Rezende; João Antônio Costa do Nascimentohttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessCollares, Maria Fernanda AntunesSilva, Leonardo França daBarbosa, Rubens Barrichello Gomes Dourado, Ana Carolina ChavesRezende, Bruna NogueiraNascimento, João Antônio Costa do 2021-05-17T18:20:49Zoai:ojs.pkp.sfu.ca:article/15532Revistahttps://rsdjournal.org/index.php/rsd/indexPUBhttps://rsdjournal.org/index.php/rsd/oairsd.articles@gmail.com2525-34092525-3409opendoar:2024-01-17T09:36:20.243211Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)false
dc.title.none.fl_str_mv Evaluation of the water quality of the Pardo River (MG) based on physical, chemical and microbiological parameters
Evaluación de la calidad del agua del río Pardo (MG) en base a parámetros físicos, químicos y microbiológicos
Avaliação da qualidade de água do rio Pardo (MG) com base em parâmetros físicos, químicos e microbiológicos
title Evaluation of the water quality of the Pardo River (MG) based on physical, chemical and microbiological parameters
spellingShingle Evaluation of the water quality of the Pardo River (MG) based on physical, chemical and microbiological parameters
Collares, Maria Fernanda Antunes
Hydrographic basin
Multivariate statistics
Monitoring network
Cluster analysis.
Red de monitoreo
Cuenca hidrográfica
Estadística multivariante
Análisis de conglomerados.
Rede de monitoramento
Bacia hidrográfica
Estatística multivariada
Análise de cluster.
title_short Evaluation of the water quality of the Pardo River (MG) based on physical, chemical and microbiological parameters
title_full Evaluation of the water quality of the Pardo River (MG) based on physical, chemical and microbiological parameters
title_fullStr Evaluation of the water quality of the Pardo River (MG) based on physical, chemical and microbiological parameters
title_full_unstemmed Evaluation of the water quality of the Pardo River (MG) based on physical, chemical and microbiological parameters
title_sort Evaluation of the water quality of the Pardo River (MG) based on physical, chemical and microbiological parameters
author Collares, Maria Fernanda Antunes
author_facet Collares, Maria Fernanda Antunes
Silva, Leonardo França da
Barbosa, Rubens Barrichello Gomes
Dourado, Ana Carolina Chaves
Rezende, Bruna Nogueira
Nascimento, João Antônio Costa do
author_role author
author2 Silva, Leonardo França da
Barbosa, Rubens Barrichello Gomes
Dourado, Ana Carolina Chaves
Rezende, Bruna Nogueira
Nascimento, João Antônio Costa do
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Collares, Maria Fernanda Antunes
Silva, Leonardo França da
Barbosa, Rubens Barrichello Gomes
Dourado, Ana Carolina Chaves
Rezende, Bruna Nogueira
Nascimento, João Antônio Costa do
dc.subject.por.fl_str_mv Hydrographic basin
Multivariate statistics
Monitoring network
Cluster analysis.
Red de monitoreo
Cuenca hidrográfica
Estadística multivariante
Análisis de conglomerados.
Rede de monitoramento
Bacia hidrográfica
Estatística multivariada
Análise de cluster.
topic Hydrographic basin
Multivariate statistics
Monitoring network
Cluster analysis.
Red de monitoreo
Cuenca hidrográfica
Estadística multivariante
Análisis de conglomerados.
Rede de monitoramento
Bacia hidrográfica
Estatística multivariada
Análise de cluster.
description This article presents an analysis of the monitoring of the water quality index and the use of multivariate statistical techniques in the mining portion of the Pardo River, in order to select the most significant parameters in the current aspects of water quality, grouping the stations according to the similarity of the studied parameters. The data used in the study were obtained from the Minas Gerais Water Management Institute - IGAM for the months of January to October of the year 2018. The water quality index was calculated for the 5 monitoring points and classified according to the IQA -NSF. Principal component analysis (PCA) and Cluster analysis (CA) were used to reduce the number of variables and to group stations with similar characteristics, respectively. The PD005 station presented the lowest average of the water quality index, this is due to the fact that the parameter of faecal coliforms stands out negatively in great quantity in the station. Using the PCA, two main components were selected as indicators of water quality explaining the cumulative variance of 78%. The CA grouped the stations into three groups, being able to identify the most polluted and the least polluted stations. The results obtained through multivariate statistics have proved to be important for understanding the current water quality situation in the basin and can be used to improve the management of water resources because the collection and analysis of all parameters at all monitoring stations requires greater availability of financial resources.
publishDate 2021
dc.date.none.fl_str_mv 2021-05-07
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://rsdjournal.org/index.php/rsd/article/view/15532
10.33448/rsd-v10i5.15532
url https://rsdjournal.org/index.php/rsd/article/view/15532
identifier_str_mv 10.33448/rsd-v10i5.15532
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://rsdjournal.org/index.php/rsd/article/view/15532/13397
dc.rights.driver.fl_str_mv https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Research, Society and Development
publisher.none.fl_str_mv Research, Society and Development
dc.source.none.fl_str_mv Research, Society and Development; Vol. 10 No. 5; e60010515532
Research, Society and Development; Vol. 10 Núm. 5; e60010515532
Research, Society and Development; v. 10 n. 5; e60010515532
2525-3409
reponame:Research, Society and Development
instname:Universidade Federal de Itajubá (UNIFEI)
instacron:UNIFEI
instname_str Universidade Federal de Itajubá (UNIFEI)
instacron_str UNIFEI
institution UNIFEI
reponame_str Research, Society and Development
collection Research, Society and Development
repository.name.fl_str_mv Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)
repository.mail.fl_str_mv rsd.articles@gmail.com
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