Assessing the naturalization degree of water in the Doce River through Grade of Membership (GoM)

Detalhes bibliográficos
Autor(a) principal: Moura, Mirella Nazareth de
Data de Publicação: 2015
Outros Autores: Felippe, Miguel Fernandes
Tipo de documento: Artigo
Idioma: por
Título da fonte: Revista Espinhaço
Texto Completo: https://revistas.ufvjm.edu.br/revista-espinhaco/article/view/69
Resumo: Water quality is an extremely important topic to many scientific fields and also to the environmental management. Therefore, working with new paths to address the water quality is as challenging as relevant. The regular approach to the theme is the WQI, a worldwide-recognized model that integrates nine parameters. Although, the hardness of the WQI lead to gaps of interpretation. Assuming that the fuzzy logic can be an in-depth tool to reach the complexity of water quality, this work brings a methodological proposal to use the Grade of Membership method to measure the naturalization of water. This algorithm can indicate how closer any water sample is to a given pristine pattern. It was used 16 years of physical, chemical and biological parameters of water, sampled by trimester in 99 stations along the Doce River watershed. The results show that all samples are far from their pristine condition. Besides, almost all cases have some grade of membership to the three classes (good, medium and bad). The model was successfully applied, promoting a classification of the degree of naturalization of water. Furthermore, the fuzzy logic allows discussing the data beyond the classes, pointing the farther parameters to its pristine condition and guiding to a more efficient water and environmental management.
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spelling Assessing the naturalization degree of water in the Doce River through Grade of Membership (GoM)Aplicação do método Grade of Membership na classificação do grau de naturalização das águas na bacia do Rio Docequalidade da águanaturalizaçãoGoMclassificaçãowater qualitynaturalizationGoMclassificationWater quality is an extremely important topic to many scientific fields and also to the environmental management. Therefore, working with new paths to address the water quality is as challenging as relevant. The regular approach to the theme is the WQI, a worldwide-recognized model that integrates nine parameters. Although, the hardness of the WQI lead to gaps of interpretation. Assuming that the fuzzy logic can be an in-depth tool to reach the complexity of water quality, this work brings a methodological proposal to use the Grade of Membership method to measure the naturalization of water. This algorithm can indicate how closer any water sample is to a given pristine pattern. It was used 16 years of physical, chemical and biological parameters of water, sampled by trimester in 99 stations along the Doce River watershed. The results show that all samples are far from their pristine condition. Besides, almost all cases have some grade of membership to the three classes (good, medium and bad). The model was successfully applied, promoting a classification of the degree of naturalization of water. Furthermore, the fuzzy logic allows discussing the data beyond the classes, pointing the farther parameters to its pristine condition and guiding to a more efficient water and environmental management.A qualidade da água é um tema de grande importância para diversos campos da ciência e, também, para a gestão ambiental. Assim, trabalhar com novos caminhos para discutir a qualidade da água é tão desafiador quanto relevante. A abordagem comum para a temática é o IQA, um modelo reconhecido internacionalmente e amplamente replicado. Todavia, a rigidez do IQA leva a lacunas em sua interpretação. Métodos estatísticos baseados na lógica nebulosa oferecem ferramentas robustas capazes de captar a complexidade do tema. Diante disso, esse trabalho traz uma proposta metodológica de utilização do método Grade of Membership para avaliar a naturalização das águas. Esse algoritmo pode indicar o quão próximo uma amostra de água está de uma dada condição pristina. Foram utilizados dezesseis anos de dados físicos, químicos e biológicos de águas fluviais, amostradas trimestralmente em 99 estações ao longo da bacia do Rio Doce. Os resultados mostram que todas as amostras verificadas estão distantes de sua condição pristina. Além disso, praticamente todas possuem graus de inserção nas três classes criadas (bom, médio e ruim). Ademais, a lógica nebulosa viabiliza a discussão dos dados para além das classes definidas, apontando os parâmetros mais distantes de sua condição pristina, fornecendo subsídios para iniciativas de planejamento e gestão do meio ambiente e dos recursos hídricos.UFVJM2015-12-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArtigo avaliado pelos Paresapplication/pdfhttps://revistas.ufvjm.edu.br/revista-espinhaco/article/view/6910.5281/zenodo.3962610Revista Espinhaço ; Revista Espinhaço #72317-0611reponame:Revista Espinhaçoinstname:Universidade Federal dos Vales do Jequitinhonha e Mucuri (UFVJM)instacron:UFVJMporhttps://revistas.ufvjm.edu.br/revista-espinhaco/article/view/69/73Copyright (c) 2022 Revista Espinhaço https://creativecommons.org/licenses/by-nc-nd/4.0info:eu-repo/semantics/openAccessMoura, Mirella Nazareth deFelippe, Miguel Fernandes2022-07-22T18:44:49Zoai:ojs.pkp.sfu.ca:article/69Revistahttps://revistaespinhaco.com/index.php/revista/indexPUBhttps://revistas.ufvjm.edu.br/revista-espinhaco/oairevista.espinhaco@gmail.com || doug.sathler@gmail.com2317-06112317-0611opendoar:2022-07-22T18:44:49Revista Espinhaço - Universidade Federal dos Vales do Jequitinhonha e Mucuri (UFVJM)false
dc.title.none.fl_str_mv Assessing the naturalization degree of water in the Doce River through Grade of Membership (GoM)
Aplicação do método Grade of Membership na classificação do grau de naturalização das águas na bacia do Rio Doce
title Assessing the naturalization degree of water in the Doce River through Grade of Membership (GoM)
spellingShingle Assessing the naturalization degree of water in the Doce River through Grade of Membership (GoM)
Moura, Mirella Nazareth de
qualidade da água
naturalização
GoM
classificação
water quality
naturalization
GoM
classification
title_short Assessing the naturalization degree of water in the Doce River through Grade of Membership (GoM)
title_full Assessing the naturalization degree of water in the Doce River through Grade of Membership (GoM)
title_fullStr Assessing the naturalization degree of water in the Doce River through Grade of Membership (GoM)
title_full_unstemmed Assessing the naturalization degree of water in the Doce River through Grade of Membership (GoM)
title_sort Assessing the naturalization degree of water in the Doce River through Grade of Membership (GoM)
author Moura, Mirella Nazareth de
author_facet Moura, Mirella Nazareth de
Felippe, Miguel Fernandes
author_role author
author2 Felippe, Miguel Fernandes
author2_role author
dc.contributor.author.fl_str_mv Moura, Mirella Nazareth de
Felippe, Miguel Fernandes
dc.subject.por.fl_str_mv qualidade da água
naturalização
GoM
classificação
water quality
naturalization
GoM
classification
topic qualidade da água
naturalização
GoM
classificação
water quality
naturalization
GoM
classification
description Water quality is an extremely important topic to many scientific fields and also to the environmental management. Therefore, working with new paths to address the water quality is as challenging as relevant. The regular approach to the theme is the WQI, a worldwide-recognized model that integrates nine parameters. Although, the hardness of the WQI lead to gaps of interpretation. Assuming that the fuzzy logic can be an in-depth tool to reach the complexity of water quality, this work brings a methodological proposal to use the Grade of Membership method to measure the naturalization of water. This algorithm can indicate how closer any water sample is to a given pristine pattern. It was used 16 years of physical, chemical and biological parameters of water, sampled by trimester in 99 stations along the Doce River watershed. The results show that all samples are far from their pristine condition. Besides, almost all cases have some grade of membership to the three classes (good, medium and bad). The model was successfully applied, promoting a classification of the degree of naturalization of water. Furthermore, the fuzzy logic allows discussing the data beyond the classes, pointing the farther parameters to its pristine condition and guiding to a more efficient water and environmental management.
publishDate 2015
dc.date.none.fl_str_mv 2015-12-04
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Artigo avaliado pelos Pares
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://revistas.ufvjm.edu.br/revista-espinhaco/article/view/69
10.5281/zenodo.3962610
url https://revistas.ufvjm.edu.br/revista-espinhaco/article/view/69
identifier_str_mv 10.5281/zenodo.3962610
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://revistas.ufvjm.edu.br/revista-espinhaco/article/view/69/73
dc.rights.driver.fl_str_mv Copyright (c) 2022 Revista Espinhaço
https://creativecommons.org/licenses/by-nc-nd/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2022 Revista Espinhaço
https://creativecommons.org/licenses/by-nc-nd/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv UFVJM
publisher.none.fl_str_mv UFVJM
dc.source.none.fl_str_mv Revista Espinhaço ; Revista Espinhaço #7
2317-0611
reponame:Revista Espinhaço
instname:Universidade Federal dos Vales do Jequitinhonha e Mucuri (UFVJM)
instacron:UFVJM
instname_str Universidade Federal dos Vales do Jequitinhonha e Mucuri (UFVJM)
instacron_str UFVJM
institution UFVJM
reponame_str Revista Espinhaço
collection Revista Espinhaço
repository.name.fl_str_mv Revista Espinhaço - Universidade Federal dos Vales do Jequitinhonha e Mucuri (UFVJM)
repository.mail.fl_str_mv revista.espinhaco@gmail.com || doug.sathler@gmail.com
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