Prediction of the longitudinal dispersion coefficient for small watercourses

Detalhes bibliográficos
Autor(a) principal: Oliveira, Vanessa Vaz de
Data de Publicação: 2017
Outros Autores: Mateus, Marcos Vinícius, Gonçalves, Julio Cesar de Souza Inácio, Utsumi, Alex Garcez, Giorgetti, Marcius Fantozzi
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Acta scientiarum. Technology (Online)
Texto Completo: http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/29397
Resumo:  Longitudinal dispersion coefficient (DL) is considered an essential physical parameter to water quality modeling in rivers. Therefore, the estimation of this parameter with high accuracy guarantees the reliability of the results of a water quality model. In this study, the observed values of longitudinal dispersion coefficient are determined for natural streams (with discharge less than 2.84 m3s-1), based on sets of measured data from stimulus-response tests using sodium chloride as a tracer. Additionally, a semi-empirical equation for prediction of DL is derived using dimensional analysis and multiple linear regression technique. The performance of the produced equation was compared to five empirical prediction equations of DL selected from literature. It presented correlation coefficient r2 = 0.87, suggesting that this equation is suitable for the estimation of DL in streams. It also presented better results for predicting the DL than the five equations from literature, showing an accuracy of 71%. 
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spelling Prediction of the longitudinal dispersion coefficient for small watercourseslongitudinal dispersion coefficientsmall watercoursessodium chloride tracer.Engenharia Hidráulica Longitudinal dispersion coefficient (DL) is considered an essential physical parameter to water quality modeling in rivers. Therefore, the estimation of this parameter with high accuracy guarantees the reliability of the results of a water quality model. In this study, the observed values of longitudinal dispersion coefficient are determined for natural streams (with discharge less than 2.84 m3s-1), based on sets of measured data from stimulus-response tests using sodium chloride as a tracer. Additionally, a semi-empirical equation for prediction of DL is derived using dimensional analysis and multiple linear regression technique. The performance of the produced equation was compared to five empirical prediction equations of DL selected from literature. It presented correlation coefficient r2 = 0.87, suggesting that this equation is suitable for the estimation of DL in streams. It also presented better results for predicting the DL than the five equations from literature, showing an accuracy of 71%. Universidade Estadual De Maringá2017-07-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionmodelagem física e matemáticaapplication/pdfhttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/2939710.4025/actascitechnol.v39i3.29397Acta Scientiarum. Technology; Vol 39 No 3 (2017); 291-299Acta Scientiarum. Technology; v. 39 n. 3 (2017); 291-2991806-25631807-8664reponame:Acta scientiarum. Technology (Online)instname:Universidade Estadual de Maringá (UEM)instacron:UEMenghttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/29397/pdfCopyright (c) 2017 Acta Scientiarum. Technologyinfo:eu-repo/semantics/openAccessOliveira, Vanessa Vaz deMateus, Marcos ViníciusGonçalves, Julio Cesar de Souza InácioUtsumi, Alex GarcezGiorgetti, Marcius Fantozzi2017-07-14T10:09:05Zoai:periodicos.uem.br/ojs:article/29397Revistahttps://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/indexPUBhttps://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/oai||actatech@uem.br1807-86641806-2563opendoar:2017-07-14T10:09:05Acta scientiarum. Technology (Online) - Universidade Estadual de Maringá (UEM)false
dc.title.none.fl_str_mv Prediction of the longitudinal dispersion coefficient for small watercourses
title Prediction of the longitudinal dispersion coefficient for small watercourses
spellingShingle Prediction of the longitudinal dispersion coefficient for small watercourses
Oliveira, Vanessa Vaz de
longitudinal dispersion coefficient
small watercourses
sodium chloride tracer.
Engenharia Hidráulica
title_short Prediction of the longitudinal dispersion coefficient for small watercourses
title_full Prediction of the longitudinal dispersion coefficient for small watercourses
title_fullStr Prediction of the longitudinal dispersion coefficient for small watercourses
title_full_unstemmed Prediction of the longitudinal dispersion coefficient for small watercourses
title_sort Prediction of the longitudinal dispersion coefficient for small watercourses
author Oliveira, Vanessa Vaz de
author_facet Oliveira, Vanessa Vaz de
Mateus, Marcos Vinícius
Gonçalves, Julio Cesar de Souza Inácio
Utsumi, Alex Garcez
Giorgetti, Marcius Fantozzi
author_role author
author2 Mateus, Marcos Vinícius
Gonçalves, Julio Cesar de Souza Inácio
Utsumi, Alex Garcez
Giorgetti, Marcius Fantozzi
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Oliveira, Vanessa Vaz de
Mateus, Marcos Vinícius
Gonçalves, Julio Cesar de Souza Inácio
Utsumi, Alex Garcez
Giorgetti, Marcius Fantozzi
dc.subject.por.fl_str_mv longitudinal dispersion coefficient
small watercourses
sodium chloride tracer.
Engenharia Hidráulica
topic longitudinal dispersion coefficient
small watercourses
sodium chloride tracer.
Engenharia Hidráulica
description  Longitudinal dispersion coefficient (DL) is considered an essential physical parameter to water quality modeling in rivers. Therefore, the estimation of this parameter with high accuracy guarantees the reliability of the results of a water quality model. In this study, the observed values of longitudinal dispersion coefficient are determined for natural streams (with discharge less than 2.84 m3s-1), based on sets of measured data from stimulus-response tests using sodium chloride as a tracer. Additionally, a semi-empirical equation for prediction of DL is derived using dimensional analysis and multiple linear regression technique. The performance of the produced equation was compared to five empirical prediction equations of DL selected from literature. It presented correlation coefficient r2 = 0.87, suggesting that this equation is suitable for the estimation of DL in streams. It also presented better results for predicting the DL than the five equations from literature, showing an accuracy of 71%. 
publishDate 2017
dc.date.none.fl_str_mv 2017-07-06
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
modelagem física e matemática
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/29397
10.4025/actascitechnol.v39i3.29397
url http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/29397
identifier_str_mv 10.4025/actascitechnol.v39i3.29397
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/29397/pdf
dc.rights.driver.fl_str_mv Copyright (c) 2017 Acta Scientiarum. Technology
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2017 Acta Scientiarum. Technology
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Estadual De Maringá
publisher.none.fl_str_mv Universidade Estadual De Maringá
dc.source.none.fl_str_mv Acta Scientiarum. Technology; Vol 39 No 3 (2017); 291-299
Acta Scientiarum. Technology; v. 39 n. 3 (2017); 291-299
1806-2563
1807-8664
reponame:Acta scientiarum. Technology (Online)
instname:Universidade Estadual de Maringá (UEM)
instacron:UEM
instname_str Universidade Estadual de Maringá (UEM)
instacron_str UEM
institution UEM
reponame_str Acta scientiarum. Technology (Online)
collection Acta scientiarum. Technology (Online)
repository.name.fl_str_mv Acta scientiarum. Technology (Online) - Universidade Estadual de Maringá (UEM)
repository.mail.fl_str_mv ||actatech@uem.br
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