Probabilistic structure of an annual extreme rainfall series of a coastal area of the State of São Paulo, Brazil

Detalhes bibliográficos
Autor(a) principal: Blain,Gabriel C.
Data de Publicação: 2012
Outros Autores: Camargo,Marcelo B. P. de
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Engenharia Agrícola
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162012000300014
Resumo: This study aimed to describe the probabilistic structure of the annual series of extreme daily rainfall (Preabs), available from the weather station of Ubatuba, State of São Paulo, Brazil (1935-2009), by using the general distribution of extreme value (GEV). The autocorrelation function, the Mann-Kendall test, and the wavelet analysis were used in order to evaluate the presence of serial correlations, trends, and periodical components. Considering the results obtained using these three statistical methods, it was possible to assume the hypothesis that this temporal series is free from persistence, trends, and periodicals components. Based on quantitative and qualitative adhesion tests, it was found that the GEV may be used in order to quantify the probabilities of the Preabs data. The best results of GEV were obtained when the parameters of this function were estimated using the method of maximum likelihood. The method of L-moments has also shown satisfactory results.
id SBEA-1_25db11f51533b157695fb727c13946f7
oai_identifier_str oai:scielo:S0100-69162012000300014
network_acronym_str SBEA-1
network_name_str Engenharia Agrícola
repository_id_str
spelling Probabilistic structure of an annual extreme rainfall series of a coastal area of the State of São Paulo, Brazilextreme valuesadhesion teststime seriesThis study aimed to describe the probabilistic structure of the annual series of extreme daily rainfall (Preabs), available from the weather station of Ubatuba, State of São Paulo, Brazil (1935-2009), by using the general distribution of extreme value (GEV). The autocorrelation function, the Mann-Kendall test, and the wavelet analysis were used in order to evaluate the presence of serial correlations, trends, and periodical components. Considering the results obtained using these three statistical methods, it was possible to assume the hypothesis that this temporal series is free from persistence, trends, and periodicals components. Based on quantitative and qualitative adhesion tests, it was found that the GEV may be used in order to quantify the probabilities of the Preabs data. The best results of GEV were obtained when the parameters of this function were estimated using the method of maximum likelihood. The method of L-moments has also shown satisfactory results.Associação Brasileira de Engenharia Agrícola2012-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162012000300014Engenharia Agrícola v.32 n.3 2012reponame:Engenharia Agrícolainstname:Associação Brasileira de Engenharia Agrícola (SBEA)instacron:SBEA10.1590/S0100-69162012000300014info:eu-repo/semantics/openAccessBlain,Gabriel C.Camargo,Marcelo B. P. deeng2012-07-16T00:00:00Zoai:scielo:S0100-69162012000300014Revistahttp://www.engenhariaagricola.org.br/ORGhttps://old.scielo.br/oai/scielo-oai.phprevistasbea@sbea.org.br||sbea@sbea.org.br1809-44300100-6916opendoar:2012-07-16T00:00Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA)false
dc.title.none.fl_str_mv Probabilistic structure of an annual extreme rainfall series of a coastal area of the State of São Paulo, Brazil
title Probabilistic structure of an annual extreme rainfall series of a coastal area of the State of São Paulo, Brazil
spellingShingle Probabilistic structure of an annual extreme rainfall series of a coastal area of the State of São Paulo, Brazil
Blain,Gabriel C.
extreme values
adhesion tests
time series
title_short Probabilistic structure of an annual extreme rainfall series of a coastal area of the State of São Paulo, Brazil
title_full Probabilistic structure of an annual extreme rainfall series of a coastal area of the State of São Paulo, Brazil
title_fullStr Probabilistic structure of an annual extreme rainfall series of a coastal area of the State of São Paulo, Brazil
title_full_unstemmed Probabilistic structure of an annual extreme rainfall series of a coastal area of the State of São Paulo, Brazil
title_sort Probabilistic structure of an annual extreme rainfall series of a coastal area of the State of São Paulo, Brazil
author Blain,Gabriel C.
author_facet Blain,Gabriel C.
Camargo,Marcelo B. P. de
author_role author
author2 Camargo,Marcelo B. P. de
author2_role author
dc.contributor.author.fl_str_mv Blain,Gabriel C.
Camargo,Marcelo B. P. de
dc.subject.por.fl_str_mv extreme values
adhesion tests
time series
topic extreme values
adhesion tests
time series
description This study aimed to describe the probabilistic structure of the annual series of extreme daily rainfall (Preabs), available from the weather station of Ubatuba, State of São Paulo, Brazil (1935-2009), by using the general distribution of extreme value (GEV). The autocorrelation function, the Mann-Kendall test, and the wavelet analysis were used in order to evaluate the presence of serial correlations, trends, and periodical components. Considering the results obtained using these three statistical methods, it was possible to assume the hypothesis that this temporal series is free from persistence, trends, and periodicals components. Based on quantitative and qualitative adhesion tests, it was found that the GEV may be used in order to quantify the probabilities of the Preabs data. The best results of GEV were obtained when the parameters of this function were estimated using the method of maximum likelihood. The method of L-moments has also shown satisfactory results.
publishDate 2012
dc.date.none.fl_str_mv 2012-06-01
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=S0100-69162012000300014
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162012000300014
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S0100-69162012000300014
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 Engenharia Agrícola
publisher.none.fl_str_mv Associação Brasileira de Engenharia Agrícola
dc.source.none.fl_str_mv Engenharia Agrícola v.32 n.3 2012
reponame:Engenharia Agrícola
instname:Associação Brasileira de Engenharia Agrícola (SBEA)
instacron:SBEA
instname_str Associação Brasileira de Engenharia Agrícola (SBEA)
instacron_str SBEA
institution SBEA
reponame_str Engenharia Agrícola
collection Engenharia Agrícola
repository.name.fl_str_mv Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA)
repository.mail.fl_str_mv revistasbea@sbea.org.br||sbea@sbea.org.br
_version_ 1752126271008014336

Registros relacionados