Hydrological regionalization of maximum stream flows using an approach based on L-moments
Autor(a) principal: | |
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Data de Publicação: | 2017 |
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=S2318-03312017000100219 |
Resumo: | ABSTRACT The proper design of hydraulic structures depends on estimates of maximum stream flows. The scarce stream flow monitoring in Brazil has led to the use of regionalization methods. The main objective of this study was to develop a tool via regional function to estimate maximum stream flows and their corresponding return periods (RP) with the aid of techniques based on the L-moments method, seeking for adequate hydrologic engineering applications and flood risk management. Annual maximum stream flow historical series were adjusted to traditional 2-parameter probability density functions (PDFs) (Normal, 2-parameter Log-Normal, Gumbel, Gamma) and multiparameter PDFs (GEV and Kappa), based on the L-moments method, which were used in the development of the regional function employing the dimensionless curve method. The regional function’s predictive capability was determined by cross-validation for different RPs. It can be concluded that the approach based on L-moments was successfully used to adjust the regional function. In addition, the regional function: i) was improved when using the aforementioned multiparameter PDFs and ii) was framed as optimum for RP of up to 100 years and considered useful for practical engineering projects and flood risk management. |
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Hydrological regionalization of maximum stream flows using an approach based on L-momentsFlood risk managementStatistical hydrologyGEVKappaMirim-São Gonçalo transboundary basinABSTRACT The proper design of hydraulic structures depends on estimates of maximum stream flows. The scarce stream flow monitoring in Brazil has led to the use of regionalization methods. The main objective of this study was to develop a tool via regional function to estimate maximum stream flows and their corresponding return periods (RP) with the aid of techniques based on the L-moments method, seeking for adequate hydrologic engineering applications and flood risk management. Annual maximum stream flow historical series were adjusted to traditional 2-parameter probability density functions (PDFs) (Normal, 2-parameter Log-Normal, Gumbel, Gamma) and multiparameter PDFs (GEV and Kappa), based on the L-moments method, which were used in the development of the regional function employing the dimensionless curve method. The regional function’s predictive capability was determined by cross-validation for different RPs. It can be concluded that the approach based on L-moments was successfully used to adjust the regional function. In addition, the regional function: i) was improved when using the aforementioned multiparameter PDFs and ii) was framed as optimum for RP of up to 100 years and considered useful for practical engineering projects and flood risk management.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=S2318-03312017000100219RBRH v.22 2017reponame:RBRH (Online)instname:Associação Brasileira de Recursos Hídricos (ABRH)instacron:ABRH10.1590/2318-0331.021720160064info:eu-repo/semantics/openAccessCassalho,FelícioBeskow,SamuelVargas,Marcelle MartinsMoura,Maíra Martim deÁvila,Leo FernandesMello,Carlos Rogério deeng2017-12-08T00:00:00Zoai:scielo:S2318-03312017000100219Revistahttps://www.scielo.br/j/rbrh/https://old.scielo.br/oai/scielo-oai.php||rbrh@abrh.org.br2318-03311414-381Xopendoar:2017-12-08T00:00RBRH (Online) - Associação Brasileira de Recursos Hídricos (ABRH)false |
dc.title.none.fl_str_mv |
Hydrological regionalization of maximum stream flows using an approach based on L-moments |
title |
Hydrological regionalization of maximum stream flows using an approach based on L-moments |
spellingShingle |
Hydrological regionalization of maximum stream flows using an approach based on L-moments Cassalho,Felício Flood risk management Statistical hydrology GEV Kappa Mirim-São Gonçalo transboundary basin |
title_short |
Hydrological regionalization of maximum stream flows using an approach based on L-moments |
title_full |
Hydrological regionalization of maximum stream flows using an approach based on L-moments |
title_fullStr |
Hydrological regionalization of maximum stream flows using an approach based on L-moments |
title_full_unstemmed |
Hydrological regionalization of maximum stream flows using an approach based on L-moments |
title_sort |
Hydrological regionalization of maximum stream flows using an approach based on L-moments |
author |
Cassalho,Felício |
author_facet |
Cassalho,Felício Beskow,Samuel Vargas,Marcelle Martins Moura,Maíra Martim de Ávila,Leo Fernandes Mello,Carlos Rogério de |
author_role |
author |
author2 |
Beskow,Samuel Vargas,Marcelle Martins Moura,Maíra Martim de Ávila,Leo Fernandes Mello,Carlos Rogério de |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Cassalho,Felício Beskow,Samuel Vargas,Marcelle Martins Moura,Maíra Martim de Ávila,Leo Fernandes Mello,Carlos Rogério de |
dc.subject.por.fl_str_mv |
Flood risk management Statistical hydrology GEV Kappa Mirim-São Gonçalo transboundary basin |
topic |
Flood risk management Statistical hydrology GEV Kappa Mirim-São Gonçalo transboundary basin |
description |
ABSTRACT The proper design of hydraulic structures depends on estimates of maximum stream flows. The scarce stream flow monitoring in Brazil has led to the use of regionalization methods. The main objective of this study was to develop a tool via regional function to estimate maximum stream flows and their corresponding return periods (RP) with the aid of techniques based on the L-moments method, seeking for adequate hydrologic engineering applications and flood risk management. Annual maximum stream flow historical series were adjusted to traditional 2-parameter probability density functions (PDFs) (Normal, 2-parameter Log-Normal, Gumbel, Gamma) and multiparameter PDFs (GEV and Kappa), based on the L-moments method, which were used in the development of the regional function employing the dimensionless curve method. The regional function’s predictive capability was determined by cross-validation for different RPs. It can be concluded that the approach based on L-moments was successfully used to adjust the regional function. In addition, the regional function: i) was improved when using the aforementioned multiparameter PDFs and ii) was framed as optimum for RP of up to 100 years and considered useful for practical engineering projects and flood risk management. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-01-01 |
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=S2318-03312017000100219 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2318-03312017000100219 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/2318-0331.021720160064 |
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.22 2017 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_ |
1754734701434634240 |