STUDY OF THE MAXIMUM DAILY RAINS IN THE CITY OF BARREIRAS/BA THROUGH TIME SERIES METHODOLOGY

Detalhes bibliográficos
Autor(a) principal: Medeiros, Elias Silva de; Universidade Federal da Grande Dourados – UFGD Docente
Data de Publicação: 2020
Outros Autores: Silva, Alessandra Querino da; Universidade Federal da Grande Dourados – UFGD Docente, Oliveira, Luciano Antonio de; Universidade Federal da Grande Dourados – UFGD Docente, Bicalho, Carolina Cristina; Universidade Estadual de Mato Grosso do Sul Docente, Lima, Kelly Pereira de; Universidade Federal de Lavras – UFLA Pesquisadora
Tipo de documento: Artigo
Idioma: por
Título da fonte: Revista da Universidade Vale do Rio Verde (Online)
Texto Completo: http://periodicos.unincor.br/index.php/revistaunincor/article/view/5971
Resumo: Natural disasters are increasingly present in everyday society. In Brazil the most common natural disasters are landslides and floods which are phenomena directly related to hydrological variables such as rainfall. The study and statistical monitoring of the meteorological regime of a given region, in particular, daily maximum rainfall data can provide important information to guide public disaster prevention policies, as well as reduce the human vulnerability of the local population. The main objective of this paper was to analyze a historical series related to the maximum daily rainfall of the city of Barreiras/BA from january 1970 to may 2019 through time series analysis. Results of applied tests indicated the presence of seasonality and also that there is no trend in the series. Given this, the SARIMA model class was considered the most suitable for modeling and the adjusted models presented good predictions allowing the identification of patterns in the series.
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spelling STUDY OF THE MAXIMUM DAILY RAINS IN THE CITY OF BARREIRAS/BA THROUGH TIME SERIES METHODOLOGYFloods. Bahia. Natural disasters. SARIMANatural disasters are increasingly present in everyday society. In Brazil the most common natural disasters are landslides and floods which are phenomena directly related to hydrological variables such as rainfall. The study and statistical monitoring of the meteorological regime of a given region, in particular, daily maximum rainfall data can provide important information to guide public disaster prevention policies, as well as reduce the human vulnerability of the local population. The main objective of this paper was to analyze a historical series related to the maximum daily rainfall of the city of Barreiras/BA from january 1970 to may 2019 through time series analysis. Results of applied tests indicated the presence of seasonality and also that there is no trend in the series. Given this, the SARIMA model class was considered the most suitable for modeling and the adjusted models presented good predictions allowing the identification of patterns in the series.ABECKelly Pereira de Lima, CNPQMedeiros, Elias Silva de; Universidade Federal da Grande Dourados – UFGD DocenteSilva, Alessandra Querino da; Universidade Federal da Grande Dourados – UFGD DocenteOliveira, Luciano Antonio de; Universidade Federal da Grande Dourados – UFGD DocenteBicalho, Carolina Cristina; Universidade Estadual de Mato Grosso do Sul DocenteLima, Kelly Pereira de; Universidade Federal de Lavras – UFLA Pesquisadora2020-10-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://periodicos.unincor.br/index.php/revistaunincor/article/view/597110.5892/ruvrd.v1i18.5971Revista da Universidade Vale do Rio Verde; v. 18, n. 1 (2020): Revista da Universidade Vale do Rio Verde; 287-2952236-53621517-027610.5892/ruvrd.v1i18reponame:Revista da Universidade Vale do Rio Verde (Online)instname:Universidade Vale do Rio Verde (UNINCOR)instacron:UVRVporhttp://periodicos.unincor.br/index.php/revistaunincor/article/view/5971/pdf_995http://periodicos.unincor.br/index.php/revistaunincor/article/downloadSuppFile/5971/53610.5892/ruvrd.v18i1.5971.g1095200110.5892/ruvrd.v1i18.5971.s536Direitos autorais 2021 Revista da Universidade Vale do Rio Verdeinfo:eu-repo/semantics/openAccess2022-03-30T13:42:12Zoai:ojs.teste.unincor.br:article/5971Revistahttp://periodicos.unincor.br/index.php/revistaunincor/indexPRIhttp://periodicos.unincor.br/index.php/revistaunincor/oairevistaunincor@unincor.edu.br2236-53621517-0276opendoar:2022-05-31T14:30:27.106243Revista da Universidade Vale do Rio Verde (Online) - Universidade Vale do Rio Verde (UNINCOR)false
dc.title.none.fl_str_mv STUDY OF THE MAXIMUM DAILY RAINS IN THE CITY OF BARREIRAS/BA THROUGH TIME SERIES METHODOLOGY
title STUDY OF THE MAXIMUM DAILY RAINS IN THE CITY OF BARREIRAS/BA THROUGH TIME SERIES METHODOLOGY
spellingShingle STUDY OF THE MAXIMUM DAILY RAINS IN THE CITY OF BARREIRAS/BA THROUGH TIME SERIES METHODOLOGY
Medeiros, Elias Silva de; Universidade Federal da Grande Dourados – UFGD Docente
Floods. Bahia. Natural disasters. SARIMA
title_short STUDY OF THE MAXIMUM DAILY RAINS IN THE CITY OF BARREIRAS/BA THROUGH TIME SERIES METHODOLOGY
title_full STUDY OF THE MAXIMUM DAILY RAINS IN THE CITY OF BARREIRAS/BA THROUGH TIME SERIES METHODOLOGY
title_fullStr STUDY OF THE MAXIMUM DAILY RAINS IN THE CITY OF BARREIRAS/BA THROUGH TIME SERIES METHODOLOGY
title_full_unstemmed STUDY OF THE MAXIMUM DAILY RAINS IN THE CITY OF BARREIRAS/BA THROUGH TIME SERIES METHODOLOGY
title_sort STUDY OF THE MAXIMUM DAILY RAINS IN THE CITY OF BARREIRAS/BA THROUGH TIME SERIES METHODOLOGY
author Medeiros, Elias Silva de; Universidade Federal da Grande Dourados – UFGD Docente
author_facet Medeiros, Elias Silva de; Universidade Federal da Grande Dourados – UFGD Docente
Silva, Alessandra Querino da; Universidade Federal da Grande Dourados – UFGD Docente
Oliveira, Luciano Antonio de; Universidade Federal da Grande Dourados – UFGD Docente
Bicalho, Carolina Cristina; Universidade Estadual de Mato Grosso do Sul Docente
Lima, Kelly Pereira de; Universidade Federal de Lavras – UFLA Pesquisadora
author_role author
author2 Silva, Alessandra Querino da; Universidade Federal da Grande Dourados – UFGD Docente
Oliveira, Luciano Antonio de; Universidade Federal da Grande Dourados – UFGD Docente
Bicalho, Carolina Cristina; Universidade Estadual de Mato Grosso do Sul Docente
Lima, Kelly Pereira de; Universidade Federal de Lavras – UFLA Pesquisadora
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Kelly Pereira de Lima, CNPQ
dc.contributor.author.fl_str_mv Medeiros, Elias Silva de; Universidade Federal da Grande Dourados – UFGD Docente
Silva, Alessandra Querino da; Universidade Federal da Grande Dourados – UFGD Docente
Oliveira, Luciano Antonio de; Universidade Federal da Grande Dourados – UFGD Docente
Bicalho, Carolina Cristina; Universidade Estadual de Mato Grosso do Sul Docente
Lima, Kelly Pereira de; Universidade Federal de Lavras – UFLA Pesquisadora
dc.subject.por.fl_str_mv Floods. Bahia. Natural disasters. SARIMA
topic Floods. Bahia. Natural disasters. SARIMA
description Natural disasters are increasingly present in everyday society. In Brazil the most common natural disasters are landslides and floods which are phenomena directly related to hydrological variables such as rainfall. The study and statistical monitoring of the meteorological regime of a given region, in particular, daily maximum rainfall data can provide important information to guide public disaster prevention policies, as well as reduce the human vulnerability of the local population. The main objective of this paper was to analyze a historical series related to the maximum daily rainfall of the city of Barreiras/BA from january 1970 to may 2019 through time series analysis. Results of applied tests indicated the presence of seasonality and also that there is no trend in the series. Given this, the SARIMA model class was considered the most suitable for modeling and the adjusted models presented good predictions allowing the identification of patterns in the series.
publishDate 2020
dc.date.none.fl_str_mv 2020-10-06
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dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.uri.fl_str_mv http://periodicos.unincor.br/index.php/revistaunincor/article/view/5971
10.5892/ruvrd.v1i18.5971
url http://periodicos.unincor.br/index.php/revistaunincor/article/view/5971
identifier_str_mv 10.5892/ruvrd.v1i18.5971
dc.language.iso.fl_str_mv por
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dc.relation.none.fl_str_mv http://periodicos.unincor.br/index.php/revistaunincor/article/view/5971/pdf_995
http://periodicos.unincor.br/index.php/revistaunincor/article/downloadSuppFile/5971/536
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dc.rights.driver.fl_str_mv Direitos autorais 2021 Revista da Universidade Vale do Rio Verde
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Direitos autorais 2021 Revista da Universidade Vale do Rio Verde
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv ABEC
publisher.none.fl_str_mv ABEC
dc.source.none.fl_str_mv Revista da Universidade Vale do Rio Verde; v. 18, n. 1 (2020): Revista da Universidade Vale do Rio Verde; 287-295
2236-5362
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10.5892/ruvrd.v1i18
reponame:Revista da Universidade Vale do Rio Verde (Online)
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reponame_str Revista da Universidade Vale do Rio Verde (Online)
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repository.name.fl_str_mv Revista da Universidade Vale do Rio Verde (Online) - Universidade Vale do Rio Verde (UNINCOR)
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