Combination of the SCS-CN and the GRADEX models to maximum flow estimation
Autor(a) principal: | |
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Data de Publicação: | 2018 |
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=S2318-03312018000100225 |
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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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) |
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_ |
1754734701541588992 |