STATIONARITY OF ANNUAL MAXIMUM DAILY STREAMFLOW TIME SERIES IN SOUTH-EAST BRAZILIAN RIVERS

Detalhes bibliográficos
Autor(a) principal: Damázio, Jorge Machado
Data de Publicação: 2015
Outros Autores: Costa, Fernanda da Serra
Tipo de documento: Artigo
Idioma: por
Título da fonte: Cadernos do IME. Série Estatística (Online)
Texto Completo: https://www.e-publicacoes.uerj.br/cadest/article/view/18302
Resumo: DOI: 10.12957/cadest.2014.18302The paper presents a statistical analysis of annual maxima daily streamflow between 1931 and 2013 in South-East Brazil focused in detecting and modelling non-stationarity aspects. Flood protection for the large valleys in South-East Brazil is provided by multiple purpose reservoir systems built during 20th century, which design and operation plans has been done assuming stationarity of historical flood time series. Land cover changes and rapidly-increasing level of atmosphere greenhouse gases of the last century may be affecting flood regimes in these valleys so that it can be that nonstationary modelling should be applied to re-asses dam safety and flood control operation rules at the existent reservoir system. Six annual maximum daily streamflow time series are analysed. The time series were plotted together with fitted smooth loess functions and non-parametric statistical tests are performed to check the significance of apparent trends shown by the plots. Non-stationarity is modelled by fitting univariate extreme value distribution functions which location varies linearly with time. Stationarity and non-stationarity modelling are compared with the likelihood ratio statistic. In four of the six analyzed time series non-stationarity modelling outperformed stationarity modelling.Keywords: Stationarity; Extreme Value Distributions; Flood Frequency Analysis; Maximum Likelihood Method.
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spelling STATIONARITY OF ANNUAL MAXIMUM DAILY STREAMFLOW TIME SERIES IN SOUTH-EAST BRAZILIAN RIVERSDOI: 10.12957/cadest.2014.18302The paper presents a statistical analysis of annual maxima daily streamflow between 1931 and 2013 in South-East Brazil focused in detecting and modelling non-stationarity aspects. Flood protection for the large valleys in South-East Brazil is provided by multiple purpose reservoir systems built during 20th century, which design and operation plans has been done assuming stationarity of historical flood time series. Land cover changes and rapidly-increasing level of atmosphere greenhouse gases of the last century may be affecting flood regimes in these valleys so that it can be that nonstationary modelling should be applied to re-asses dam safety and flood control operation rules at the existent reservoir system. Six annual maximum daily streamflow time series are analysed. The time series were plotted together with fitted smooth loess functions and non-parametric statistical tests are performed to check the significance of apparent trends shown by the plots. Non-stationarity is modelled by fitting univariate extreme value distribution functions which location varies linearly with time. Stationarity and non-stationarity modelling are compared with the likelihood ratio statistic. In four of the six analyzed time series non-stationarity modelling outperformed stationarity modelling.Keywords: Stationarity; Extreme Value Distributions; Flood Frequency Analysis; Maximum Likelihood Method.Universidade do Estado do Rio de Janeiro2015-08-24info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionAvaliado pelos Paresapplication/pdfhttps://www.e-publicacoes.uerj.br/cadest/article/view/1830210.12957/cadest.2014.18302Cadernos do IME - Série Estatística; v. 37 (2014): Volume 37, Dezembro de 2014; 292317-45361413-9022reponame:Cadernos do IME. Série Estatística (Online)instname:Universidade do Estado do Rio de Janeiro (UERJ)instacron:UERJporhttps://www.e-publicacoes.uerj.br/cadest/article/view/18302/13411Damázio, Jorge MachadoCosta, Fernanda da Serrainfo:eu-repo/semantics/openAccess2020-12-04T00:22:55Zoai:ojs.www.e-publicacoes.uerj.br:article/18302Revistahttps://www.e-publicacoes.uerj.br/index.php/cadestPUBhttps://www.e-publicacoes.uerj.br/index.php/cadest/oaifabiano@ime.uerj.br||fabiano@ime.uerj.br2317-45361413-9022opendoar:2024-05-17T13:37:34.867718Cadernos do IME. Série Estatística (Online) - Universidade do Estado do Rio de Janeiro (UERJ)false
dc.title.none.fl_str_mv STATIONARITY OF ANNUAL MAXIMUM DAILY STREAMFLOW TIME SERIES IN SOUTH-EAST BRAZILIAN RIVERS
title STATIONARITY OF ANNUAL MAXIMUM DAILY STREAMFLOW TIME SERIES IN SOUTH-EAST BRAZILIAN RIVERS
spellingShingle STATIONARITY OF ANNUAL MAXIMUM DAILY STREAMFLOW TIME SERIES IN SOUTH-EAST BRAZILIAN RIVERS
Damázio, Jorge Machado
title_short STATIONARITY OF ANNUAL MAXIMUM DAILY STREAMFLOW TIME SERIES IN SOUTH-EAST BRAZILIAN RIVERS
title_full STATIONARITY OF ANNUAL MAXIMUM DAILY STREAMFLOW TIME SERIES IN SOUTH-EAST BRAZILIAN RIVERS
title_fullStr STATIONARITY OF ANNUAL MAXIMUM DAILY STREAMFLOW TIME SERIES IN SOUTH-EAST BRAZILIAN RIVERS
title_full_unstemmed STATIONARITY OF ANNUAL MAXIMUM DAILY STREAMFLOW TIME SERIES IN SOUTH-EAST BRAZILIAN RIVERS
title_sort STATIONARITY OF ANNUAL MAXIMUM DAILY STREAMFLOW TIME SERIES IN SOUTH-EAST BRAZILIAN RIVERS
author Damázio, Jorge Machado
author_facet Damázio, Jorge Machado
Costa, Fernanda da Serra
author_role author
author2 Costa, Fernanda da Serra
author2_role author
dc.contributor.author.fl_str_mv Damázio, Jorge Machado
Costa, Fernanda da Serra
description DOI: 10.12957/cadest.2014.18302The paper presents a statistical analysis of annual maxima daily streamflow between 1931 and 2013 in South-East Brazil focused in detecting and modelling non-stationarity aspects. Flood protection for the large valleys in South-East Brazil is provided by multiple purpose reservoir systems built during 20th century, which design and operation plans has been done assuming stationarity of historical flood time series. Land cover changes and rapidly-increasing level of atmosphere greenhouse gases of the last century may be affecting flood regimes in these valleys so that it can be that nonstationary modelling should be applied to re-asses dam safety and flood control operation rules at the existent reservoir system. Six annual maximum daily streamflow time series are analysed. The time series were plotted together with fitted smooth loess functions and non-parametric statistical tests are performed to check the significance of apparent trends shown by the plots. Non-stationarity is modelled by fitting univariate extreme value distribution functions which location varies linearly with time. Stationarity and non-stationarity modelling are compared with the likelihood ratio statistic. In four of the six analyzed time series non-stationarity modelling outperformed stationarity modelling.Keywords: Stationarity; Extreme Value Distributions; Flood Frequency Analysis; Maximum Likelihood Method.
publishDate 2015
dc.date.none.fl_str_mv 2015-08-24
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Avaliado pelos Pares
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://www.e-publicacoes.uerj.br/cadest/article/view/18302
10.12957/cadest.2014.18302
url https://www.e-publicacoes.uerj.br/cadest/article/view/18302
identifier_str_mv 10.12957/cadest.2014.18302
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://www.e-publicacoes.uerj.br/cadest/article/view/18302/13411
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade do Estado do Rio de Janeiro
publisher.none.fl_str_mv Universidade do Estado do Rio de Janeiro
dc.source.none.fl_str_mv Cadernos do IME - Série Estatística; v. 37 (2014): Volume 37, Dezembro de 2014; 29
2317-4536
1413-9022
reponame:Cadernos do IME. Série Estatística (Online)
instname:Universidade do Estado do Rio de Janeiro (UERJ)
instacron:UERJ
instname_str Universidade do Estado do Rio de Janeiro (UERJ)
instacron_str UERJ
institution UERJ
reponame_str Cadernos do IME. Série Estatística (Online)
collection Cadernos do IME. Série Estatística (Online)
repository.name.fl_str_mv Cadernos do IME. Série Estatística (Online) - Universidade do Estado do Rio de Janeiro (UERJ)
repository.mail.fl_str_mv fabiano@ime.uerj.br||fabiano@ime.uerj.br
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