Assessing the effects of rating curve uncertainty in flood frequency analysis

Detalhes bibliográficos
Autor(a) principal: Vieira,Luan Marcos da Silva
Data de Publicação: 2022
Outros Autores: Sampaio,Júlio César Lôbo, Costa,Veber Afonso Figueiredo, Eleutério,Julian Cardoso
Tipo de documento: Artigo
Idioma: eng
Título da fonte: RBRH (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2318-03312022000100210
Resumo: ABSTRACT Maximum flows are often estimated from flood frequency analysis, by means of the statistical fitting of a theoretical probability distribution to maximum annual flow data. However, because of the limitations imposed by the practice of at-site flow measurement, empirical models are applied as the rating curve for estimating streamflow. These curves are approximations of the actual flows and incorporate different sources of uncertainty, especially in the extrapolation portions. These uncertainties are propagated in the frequency analysis and influence the estimated quantiles. For better understanding and describing the influence of the stage-discharge uncertainty in this process, the results of Bayesian rating curve modeling, which considers the physical knowledge of the gauging station as prior information, were combined with Bayesian flood frequency analysis under asymptotic extreme value theory. The method was applied to the Acorizal stream gauging station, located in the interior of the state of Mato Grosso - BR. The main results suggested that, although the uncertainties of the rating curve can be relevant in the estimation of maximum flow quantiles, the uncertainties arising from finite-sample inference might exert greater impacts on the flow credibility intervals even for moderate sample sizes.
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spelling Assessing the effects of rating curve uncertainty in flood frequency analysisRating curveBayesian inferenceFlood frequency analysisBaRatinABSTRACT Maximum flows are often estimated from flood frequency analysis, by means of the statistical fitting of a theoretical probability distribution to maximum annual flow data. However, because of the limitations imposed by the practice of at-site flow measurement, empirical models are applied as the rating curve for estimating streamflow. These curves are approximations of the actual flows and incorporate different sources of uncertainty, especially in the extrapolation portions. These uncertainties are propagated in the frequency analysis and influence the estimated quantiles. For better understanding and describing the influence of the stage-discharge uncertainty in this process, the results of Bayesian rating curve modeling, which considers the physical knowledge of the gauging station as prior information, were combined with Bayesian flood frequency analysis under asymptotic extreme value theory. The method was applied to the Acorizal stream gauging station, located in the interior of the state of Mato Grosso - BR. The main results suggested that, although the uncertainties of the rating curve can be relevant in the estimation of maximum flow quantiles, the uncertainties arising from finite-sample inference might exert greater impacts on the flow credibility intervals even for moderate sample sizes.Associação Brasileira de Recursos Hídricos2022-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S2318-03312022000100210RBRH v.27 2022reponame:RBRH (Online)instname:Associação Brasileira de Recursos Hídricos (ABRH)instacron:ABRH10.1590/2318-0331.272220220012info:eu-repo/semantics/openAccessVieira,Luan Marcos da SilvaSampaio,Júlio César LôboCosta,Veber Afonso FigueiredoEleutério,Julian Cardosoeng2022-06-08T00:00:00Zoai:scielo:S2318-03312022000100210Revistahttps://www.scielo.br/j/rbrh/https://old.scielo.br/oai/scielo-oai.php||rbrh@abrh.org.br2318-03311414-381Xopendoar:2022-06-08T00:00RBRH (Online) - Associação Brasileira de Recursos Hídricos (ABRH)false
dc.title.none.fl_str_mv Assessing the effects of rating curve uncertainty in flood frequency analysis
title Assessing the effects of rating curve uncertainty in flood frequency analysis
spellingShingle Assessing the effects of rating curve uncertainty in flood frequency analysis
Vieira,Luan Marcos da Silva
Rating curve
Bayesian inference
Flood frequency analysis
BaRatin
title_short Assessing the effects of rating curve uncertainty in flood frequency analysis
title_full Assessing the effects of rating curve uncertainty in flood frequency analysis
title_fullStr Assessing the effects of rating curve uncertainty in flood frequency analysis
title_full_unstemmed Assessing the effects of rating curve uncertainty in flood frequency analysis
title_sort Assessing the effects of rating curve uncertainty in flood frequency analysis
author Vieira,Luan Marcos da Silva
author_facet Vieira,Luan Marcos da Silva
Sampaio,Júlio César Lôbo
Costa,Veber Afonso Figueiredo
Eleutério,Julian Cardoso
author_role author
author2 Sampaio,Júlio César Lôbo
Costa,Veber Afonso Figueiredo
Eleutério,Julian Cardoso
author2_role author
author
author
dc.contributor.author.fl_str_mv Vieira,Luan Marcos da Silva
Sampaio,Júlio César Lôbo
Costa,Veber Afonso Figueiredo
Eleutério,Julian Cardoso
dc.subject.por.fl_str_mv Rating curve
Bayesian inference
Flood frequency analysis
BaRatin
topic Rating curve
Bayesian inference
Flood frequency analysis
BaRatin
description ABSTRACT Maximum flows are often estimated from flood frequency analysis, by means of the statistical fitting of a theoretical probability distribution to maximum annual flow data. However, because of the limitations imposed by the practice of at-site flow measurement, empirical models are applied as the rating curve for estimating streamflow. These curves are approximations of the actual flows and incorporate different sources of uncertainty, especially in the extrapolation portions. These uncertainties are propagated in the frequency analysis and influence the estimated quantiles. For better understanding and describing the influence of the stage-discharge uncertainty in this process, the results of Bayesian rating curve modeling, which considers the physical knowledge of the gauging station as prior information, were combined with Bayesian flood frequency analysis under asymptotic extreme value theory. The method was applied to the Acorizal stream gauging station, located in the interior of the state of Mato Grosso - BR. The main results suggested that, although the uncertainties of the rating curve can be relevant in the estimation of maximum flow quantiles, the uncertainties arising from finite-sample inference might exert greater impacts on the flow credibility intervals even for moderate sample sizes.
publishDate 2022
dc.date.none.fl_str_mv 2022-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2318-03312022000100210
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dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/2318-0331.272220220012
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
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.27 2022
reponame:RBRH (Online)
instname:Associação Brasileira de Recursos Hídricos (ABRH)
instacron:ABRH
instname_str Associação Brasileira de Recursos Hídricos (ABRH)
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reponame_str RBRH (Online)
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repository.name.fl_str_mv RBRH (Online) - Associação Brasileira de Recursos Hídricos (ABRH)
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