Combination of the SCS-CN and the GRADEX models to maximum flow estimation

Detalhes bibliográficos
Autor(a) principal: Mota,Tainá
Data de Publicação: 2018
Outros Autores: Naghettini,Mauro, Fernandes,Wilson, Silva,Francisco
Tipo de documento: Artigo
Idioma: eng
Título da fonte: RBRH (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2318-03312018000100225
Resumo: ABSTRACT The absence of hydrometric monitoring of adequate extension, periodicity, temporal resolution and quality is the Brazilian reality in many drainage basins. It’s common the use of rainfall-runoff models of simple application to determine rainfall excess volumes, such as the SCS-CN method. Although the SCS method is broadly accepted, many authors have questioned the results derived from its application to catchments with distinct characteristics than those studied during its original formulation. An alternate method for maximum flow estimation in catchments with scarce monitoring is the GRADEX method, which proposes extrapolation of the flood volumes’ frequency curve from precipitation series. Despite being a consolidated method, it is rarely used in Brazil because of the difficulties found in fulfilling its initial hypotheses. This paper suggests, therefore, the combination of both methods, aiming for a methodology that better describes the uncertainties involved in the determination of the direct flood volumes’ probability distribution. The case study is conducted on the Serra Azul river catchment, Juatuba – MG, which offers 12 years of continuous records. The referred combination occurs on the definition of the lower and upper boundaries of the probability distribution of global water retention in the soil and in the catchment, as embedded in the GRADEX method, from the CNASYMPTOTIC concept. The modelled scenarios bear evidence of the many possibilities that may exist in the extrapolation of the frequency curve of surface runoff volumes suggests a range of results that better underpins the definition of the saturation condition and, consequently, the maximum rainfall excess calculation, as compared to the originally proposed methods.
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spelling Combination of the SCS-CN and the GRADEX models to maximum flow estimationSCS-CN methodGRADEX methodProbability distributionMaximum flow-rateABSTRACT The absence of hydrometric monitoring of adequate extension, periodicity, temporal resolution and quality is the Brazilian reality in many drainage basins. It’s common the use of rainfall-runoff models of simple application to determine rainfall excess volumes, such as the SCS-CN method. Although the SCS method is broadly accepted, many authors have questioned the results derived from its application to catchments with distinct characteristics than those studied during its original formulation. An alternate method for maximum flow estimation in catchments with scarce monitoring is the GRADEX method, which proposes extrapolation of the flood volumes’ frequency curve from precipitation series. Despite being a consolidated method, it is rarely used in Brazil because of the difficulties found in fulfilling its initial hypotheses. This paper suggests, therefore, the combination of both methods, aiming for a methodology that better describes the uncertainties involved in the determination of the direct flood volumes’ probability distribution. The case study is conducted on the Serra Azul river catchment, Juatuba – MG, which offers 12 years of continuous records. The referred combination occurs on the definition of the lower and upper boundaries of the probability distribution of global water retention in the soil and in the catchment, as embedded in the GRADEX method, from the CNASYMPTOTIC concept. The modelled scenarios bear evidence of the many possibilities that may exist in the extrapolation of the frequency curve of surface runoff volumes suggests a range of results that better underpins the definition of the saturation condition and, consequently, the maximum rainfall excess calculation, as compared to the originally proposed methods.Associação Brasileira de Recursos Hídricos2018-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S2318-03312018000100225RBRH v.23 2018reponame:RBRH (Online)instname:Associação Brasileira de Recursos Hídricos (ABRH)instacron:ABRH10.1590/2318-0331.231820170123info:eu-repo/semantics/openAccessMota,TaináNaghettini,MauroFernandes,WilsonSilva,Franciscoeng2018-07-17T00:00:00Zoai:scielo:S2318-03312018000100225Revistahttps://www.scielo.br/j/rbrh/https://old.scielo.br/oai/scielo-oai.php||rbrh@abrh.org.br2318-03311414-381Xopendoar:2018-07-17T00:00RBRH (Online) - Associação Brasileira de Recursos Hídricos (ABRH)false
dc.title.none.fl_str_mv Combination of the SCS-CN and the GRADEX models to maximum flow estimation
title Combination of the SCS-CN and the GRADEX models to maximum flow estimation
spellingShingle Combination of the SCS-CN and the GRADEX models to maximum flow estimation
Mota,Tainá
SCS-CN method
GRADEX method
Probability distribution
Maximum flow-rate
title_short Combination of the SCS-CN and the GRADEX models to maximum flow estimation
title_full Combination of the SCS-CN and the GRADEX models to maximum flow estimation
title_fullStr Combination of the SCS-CN and the GRADEX models to maximum flow estimation
title_full_unstemmed Combination of the SCS-CN and the GRADEX models to maximum flow estimation
title_sort Combination of the SCS-CN and the GRADEX models to maximum flow estimation
author Mota,Tainá
author_facet Mota,Tainá
Naghettini,Mauro
Fernandes,Wilson
Silva,Francisco
author_role author
author2 Naghettini,Mauro
Fernandes,Wilson
Silva,Francisco
author2_role author
author
author
dc.contributor.author.fl_str_mv Mota,Tainá
Naghettini,Mauro
Fernandes,Wilson
Silva,Francisco
dc.subject.por.fl_str_mv SCS-CN method
GRADEX method
Probability distribution
Maximum flow-rate
topic SCS-CN method
GRADEX method
Probability distribution
Maximum flow-rate
description ABSTRACT The absence of hydrometric monitoring of adequate extension, periodicity, temporal resolution and quality is the Brazilian reality in many drainage basins. It’s common the use of rainfall-runoff models of simple application to determine rainfall excess volumes, such as the SCS-CN method. Although the SCS method is broadly accepted, many authors have questioned the results derived from its application to catchments with distinct characteristics than those studied during its original formulation. An alternate method for maximum flow estimation in catchments with scarce monitoring is the GRADEX method, which proposes extrapolation of the flood volumes’ frequency curve from precipitation series. Despite being a consolidated method, it is rarely used in Brazil because of the difficulties found in fulfilling its initial hypotheses. This paper suggests, therefore, the combination of both methods, aiming for a methodology that better describes the uncertainties involved in the determination of the direct flood volumes’ probability distribution. The case study is conducted on the Serra Azul river catchment, Juatuba – MG, which offers 12 years of continuous records. The referred combination occurs on the definition of the lower and upper boundaries of the probability distribution of global water retention in the soil and in the catchment, as embedded in the GRADEX method, from the CNASYMPTOTIC concept. The modelled scenarios bear evidence of the many possibilities that may exist in the extrapolation of the frequency curve of surface runoff volumes suggests a range of results that better underpins the definition of the saturation condition and, consequently, the maximum rainfall excess calculation, as compared to the originally proposed methods.
publishDate 2018
dc.date.none.fl_str_mv 2018-01-01
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=S2318-03312018000100225
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2318-03312018000100225
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/2318-0331.231820170123
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.23 2018
reponame:RBRH (Online)
instname:Associação Brasileira de Recursos Hídricos (ABRH)
instacron:ABRH
instname_str Associação Brasileira de Recursos Hídricos (ABRH)
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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
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