Principle of maximum entropy in the estimation of suspended sediment concentration

Detalhes bibliográficos
Autor(a) principal: Martins,Patrícia Diniz
Data de Publicação: 2017
Outros Autores: Poleto,Cristiano
Tipo de documento: Artigo
Idioma: eng
Título da fonte: RBRH (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2318-03312017000100221
Resumo: ABSTRACT The concern with water quality has been promoting development of better monitoring and control techniques every day. As sediments transport most of water contaminants, their study is fundamental. Given the large number of variables for estimating sediment concentration and high costs of monitoring campaigns, it becomes necessary to develop more accessible methods which bring satisfactory practical results. Therefore, this work deals with application of the principle of maximum entropy, a probabilistic method to determine concentration of sediments in river channels with various concentrations and particle sizes. For this purpose, it was proposed a relationship between the theory of entropy parameters in order to reduce the computational effort. The results were satisfactory at concentrations above 10 g/L with R2 greater than 0.88. The calculated squared errors in this study were lower than those found when using the theory of entropy by Tsallis and the equation of Rouse, classic models for determining the sediment concentration profile. The applicability of the proposed model and the ease of using the probabilistic method, since it reduces the amount of data needed to perform the estimate, makes it feasible on a global scale.
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spelling Principle of maximum entropy in the estimation of suspended sediment concentrationSedimentologyWater resourcesModelingABSTRACT The concern with water quality has been promoting development of better monitoring and control techniques every day. As sediments transport most of water contaminants, their study is fundamental. Given the large number of variables for estimating sediment concentration and high costs of monitoring campaigns, it becomes necessary to develop more accessible methods which bring satisfactory practical results. Therefore, this work deals with application of the principle of maximum entropy, a probabilistic method to determine concentration of sediments in river channels with various concentrations and particle sizes. For this purpose, it was proposed a relationship between the theory of entropy parameters in order to reduce the computational effort. The results were satisfactory at concentrations above 10 g/L with R2 greater than 0.88. The calculated squared errors in this study were lower than those found when using the theory of entropy by Tsallis and the equation of Rouse, classic models for determining the sediment concentration profile. The applicability of the proposed model and the ease of using the probabilistic method, since it reduces the amount of data needed to perform the estimate, makes it feasible on a global scale.Associação Brasileira de Recursos Hídricos2017-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S2318-03312017000100221RBRH v.22 2017reponame:RBRH (Online)instname:Associação Brasileira de Recursos Hídricos (ABRH)instacron:ABRH10.1590/2318-0331.011716058info:eu-repo/semantics/openAccessMartins,Patrícia DinizPoleto,Cristianoeng2017-03-23T00:00:00Zoai:scielo:S2318-03312017000100221Revistahttps://www.scielo.br/j/rbrh/https://old.scielo.br/oai/scielo-oai.php||rbrh@abrh.org.br2318-03311414-381Xopendoar:2017-03-23T00:00RBRH (Online) - Associação Brasileira de Recursos Hídricos (ABRH)false
dc.title.none.fl_str_mv Principle of maximum entropy in the estimation of suspended sediment concentration
title Principle of maximum entropy in the estimation of suspended sediment concentration
spellingShingle Principle of maximum entropy in the estimation of suspended sediment concentration
Martins,Patrícia Diniz
Sedimentology
Water resources
Modeling
title_short Principle of maximum entropy in the estimation of suspended sediment concentration
title_full Principle of maximum entropy in the estimation of suspended sediment concentration
title_fullStr Principle of maximum entropy in the estimation of suspended sediment concentration
title_full_unstemmed Principle of maximum entropy in the estimation of suspended sediment concentration
title_sort Principle of maximum entropy in the estimation of suspended sediment concentration
author Martins,Patrícia Diniz
author_facet Martins,Patrícia Diniz
Poleto,Cristiano
author_role author
author2 Poleto,Cristiano
author2_role author
dc.contributor.author.fl_str_mv Martins,Patrícia Diniz
Poleto,Cristiano
dc.subject.por.fl_str_mv Sedimentology
Water resources
Modeling
topic Sedimentology
Water resources
Modeling
description ABSTRACT The concern with water quality has been promoting development of better monitoring and control techniques every day. As sediments transport most of water contaminants, their study is fundamental. Given the large number of variables for estimating sediment concentration and high costs of monitoring campaigns, it becomes necessary to develop more accessible methods which bring satisfactory practical results. Therefore, this work deals with application of the principle of maximum entropy, a probabilistic method to determine concentration of sediments in river channels with various concentrations and particle sizes. For this purpose, it was proposed a relationship between the theory of entropy parameters in order to reduce the computational effort. The results were satisfactory at concentrations above 10 g/L with R2 greater than 0.88. The calculated squared errors in this study were lower than those found when using the theory of entropy by Tsallis and the equation of Rouse, classic models for determining the sediment concentration profile. The applicability of the proposed model and the ease of using the probabilistic method, since it reduces the amount of data needed to perform the estimate, makes it feasible on a global scale.
publishDate 2017
dc.date.none.fl_str_mv 2017-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2318-03312017000100221
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dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/2318-0331.011716058
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dc.publisher.none.fl_str_mv Associação Brasileira de Recursos Hídricos
publisher.none.fl_str_mv Associação Brasileira de Recursos Hídricos
dc.source.none.fl_str_mv RBRH v.22 2017
reponame:RBRH (Online)
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