Assessing the effects of rating curve uncertainty in flood frequency analysis
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , |
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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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 |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2318-03312022000100210 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2318-03312022000100210 |
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) |
instacron_str |
ABRH |
institution |
ABRH |
reponame_str |
RBRH (Online) |
collection |
RBRH (Online) |
repository.name.fl_str_mv |
RBRH (Online) - Associação Brasileira de Recursos Hídricos (ABRH) |
repository.mail.fl_str_mv |
||rbrh@abrh.org.br |
_version_ |
1754734702322778112 |