Homogeneous regions and probability density functions of pluvial precipitation in Táchira State, Venezuela
Autor(a) principal: | |
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Data de Publicação: | 2006 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Pesquisa Agropecuária Brasileira (Online) |
Texto Completo: | https://seer.sct.embrapa.br/index.php/pab/article/view/7122 |
Resumo: | The objective of this work was to determine regions of monthly pluvial precipitation based on the seasonal and the probability distribution that best fit to precipitation of those areas in the State of Táchira, Venezuela. Long-term series of 24 throughout 62 years of monthly precipitation data of 25 climatological stations were used. The Ward's clustering methods of analyses was used to group the months with similar monthly pluvial precipitation and also the climatological locations with similar precipitation (homogeneous regions). The adjust of the probability density functions exponential, Gamma, Gumbel, normal, log-normal were evaluated with three parameters as well as Weibull distributions in order to observe monthly precipitation data. The precipitation seasonal variation at the State of Táchira presents three periods statistically defined as: dry, transition, and wet. For the dry and wet periods, four homogeneous regions of locations with similar monthly precipitation could be identified and, in the transition period, three regions. In the dry period, the recommended probability distribution is the exponential, except for the homogeneous regions with the largest rainfall values during that period, when Gamma distribution is better. In the wet period, in all regions, normal distribution prevails, except for August, when Gamma prevails. As far as transition periods are concerned, Gamma distributions are better in April and normal distribution, in November. |
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Homogeneous regions and probability density functions of pluvial precipitation in Táchira State, VenezuelaRegiões homogêneas e funções de distribuição de probabilidade da precipitação pluvial no Estado de Táchira, Venezuelarainfall; probability density functions; cluster analysis; Wardchuva; funções densidade de probabilidade; análise de agrupamento; WardThe objective of this work was to determine regions of monthly pluvial precipitation based on the seasonal and the probability distribution that best fit to precipitation of those areas in the State of Táchira, Venezuela. Long-term series of 24 throughout 62 years of monthly precipitation data of 25 climatological stations were used. The Ward's clustering methods of analyses was used to group the months with similar monthly pluvial precipitation and also the climatological locations with similar precipitation (homogeneous regions). The adjust of the probability density functions exponential, Gamma, Gumbel, normal, log-normal were evaluated with three parameters as well as Weibull distributions in order to observe monthly precipitation data. The precipitation seasonal variation at the State of Táchira presents three periods statistically defined as: dry, transition, and wet. For the dry and wet periods, four homogeneous regions of locations with similar monthly precipitation could be identified and, in the transition period, three regions. In the dry period, the recommended probability distribution is the exponential, except for the homogeneous regions with the largest rainfall values during that period, when Gamma distribution is better. In the wet period, in all regions, normal distribution prevails, except for August, when Gamma prevails. As far as transition periods are concerned, Gamma distributions are better in April and normal distribution, in November.O objetivo deste trabalho foi determinar regiões homogêneas baseadas na sazonalidade da precipitação pluvial mensal e a distribuição de probabilidade que melhor se ajusta à precipitação dessas regiões no Estado de Táchira, Venezuela. Utilizaram-se valores da precipitação mensal de 25 estações climatológicas, que apresentam séries entre 24 e 62 anos. Aplicou-se o método de Ward no agrupamento dos meses com precipitação pluvial mensal similar e também no das localidades com precipitação similar (regiões homogêneas). Avaliaram-se os ajustes das funções de densidade exponencial, gama, Gumbel, normal, log-normal a três parâmetros, e Weibull aos dados observados de precipitação mensal. A variação sazonal da precipitação no Estado de Táchira apresenta três períodos estatisticamente definidos como: seco, transição e úmido. Os períodos seco e úmido apresentam quatro regiões homogêneas de precipitação mensal similar e o de transição três. No período seco, a distribuição de probabilidade recomendada para as estimativas mensais é a exponencial, com exceção da região homogênea com os maiores valores de precipitação pluvial do período, onde a gama se sobressai. No período chuvoso, em todas as regiões homogêneas, a distribuição normal predomina, com exceção de agosto, em que a gama prevalece. Já nos meses de transição, destacam-se as distribuições gama, em abril, e normal, em novembro.Pesquisa Agropecuaria BrasileiraPesquisa Agropecuária BrasileiraLyra, Gustavo BastosGarcia, Beatriz Ibet LozadaPiedade, Sônia Maria De StefanoSediyama, Gilberto ChohakuSentelhas, Paulo César2006-02-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://seer.sct.embrapa.br/index.php/pab/article/view/7122Pesquisa Agropecuaria Brasileira; v.41, n.2, fev. 2006; 205-215Pesquisa Agropecuária Brasileira; v.41, n.2, fev. 2006; 205-2151678-39210100-104xreponame:Pesquisa Agropecuária Brasileira (Online)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPAporhttps://seer.sct.embrapa.br/index.php/pab/article/view/7122/4167info:eu-repo/semantics/openAccess2010-12-28T16:36:20Zoai:ojs.seer.sct.embrapa.br:article/7122Revistahttp://seer.sct.embrapa.br/index.php/pabPRIhttps://old.scielo.br/oai/scielo-oai.phppab@sct.embrapa.br || sct.pab@embrapa.br1678-39210100-204Xopendoar:2010-12-28T16:36:20Pesquisa Agropecuária Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false |
dc.title.none.fl_str_mv |
Homogeneous regions and probability density functions of pluvial precipitation in Táchira State, Venezuela Regiões homogêneas e funções de distribuição de probabilidade da precipitação pluvial no Estado de Táchira, Venezuela |
title |
Homogeneous regions and probability density functions of pluvial precipitation in Táchira State, Venezuela |
spellingShingle |
Homogeneous regions and probability density functions of pluvial precipitation in Táchira State, Venezuela Lyra, Gustavo Bastos rainfall; probability density functions; cluster analysis; Ward chuva; funções densidade de probabilidade; análise de agrupamento; Ward |
title_short |
Homogeneous regions and probability density functions of pluvial precipitation in Táchira State, Venezuela |
title_full |
Homogeneous regions and probability density functions of pluvial precipitation in Táchira State, Venezuela |
title_fullStr |
Homogeneous regions and probability density functions of pluvial precipitation in Táchira State, Venezuela |
title_full_unstemmed |
Homogeneous regions and probability density functions of pluvial precipitation in Táchira State, Venezuela |
title_sort |
Homogeneous regions and probability density functions of pluvial precipitation in Táchira State, Venezuela |
author |
Lyra, Gustavo Bastos |
author_facet |
Lyra, Gustavo Bastos Garcia, Beatriz Ibet Lozada Piedade, Sônia Maria De Stefano Sediyama, Gilberto Chohaku Sentelhas, Paulo César |
author_role |
author |
author2 |
Garcia, Beatriz Ibet Lozada Piedade, Sônia Maria De Stefano Sediyama, Gilberto Chohaku Sentelhas, Paulo César |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
|
dc.contributor.author.fl_str_mv |
Lyra, Gustavo Bastos Garcia, Beatriz Ibet Lozada Piedade, Sônia Maria De Stefano Sediyama, Gilberto Chohaku Sentelhas, Paulo César |
dc.subject.por.fl_str_mv |
rainfall; probability density functions; cluster analysis; Ward chuva; funções densidade de probabilidade; análise de agrupamento; Ward |
topic |
rainfall; probability density functions; cluster analysis; Ward chuva; funções densidade de probabilidade; análise de agrupamento; Ward |
description |
The objective of this work was to determine regions of monthly pluvial precipitation based on the seasonal and the probability distribution that best fit to precipitation of those areas in the State of Táchira, Venezuela. Long-term series of 24 throughout 62 years of monthly precipitation data of 25 climatological stations were used. The Ward's clustering methods of analyses was used to group the months with similar monthly pluvial precipitation and also the climatological locations with similar precipitation (homogeneous regions). The adjust of the probability density functions exponential, Gamma, Gumbel, normal, log-normal were evaluated with three parameters as well as Weibull distributions in order to observe monthly precipitation data. The precipitation seasonal variation at the State of Táchira presents three periods statistically defined as: dry, transition, and wet. For the dry and wet periods, four homogeneous regions of locations with similar monthly precipitation could be identified and, in the transition period, three regions. In the dry period, the recommended probability distribution is the exponential, except for the homogeneous regions with the largest rainfall values during that period, when Gamma distribution is better. In the wet period, in all regions, normal distribution prevails, except for August, when Gamma prevails. As far as transition periods are concerned, Gamma distributions are better in April and normal distribution, in November. |
publishDate |
2006 |
dc.date.none.fl_str_mv |
2006-02-01 |
dc.type.none.fl_str_mv |
|
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://seer.sct.embrapa.br/index.php/pab/article/view/7122 |
url |
https://seer.sct.embrapa.br/index.php/pab/article/view/7122 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://seer.sct.embrapa.br/index.php/pab/article/view/7122/4167 |
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 |
Pesquisa Agropecuaria Brasileira Pesquisa Agropecuária Brasileira |
publisher.none.fl_str_mv |
Pesquisa Agropecuaria Brasileira Pesquisa Agropecuária Brasileira |
dc.source.none.fl_str_mv |
Pesquisa Agropecuaria Brasileira; v.41, n.2, fev. 2006; 205-215 Pesquisa Agropecuária Brasileira; v.41, n.2, fev. 2006; 205-215 1678-3921 0100-104x reponame:Pesquisa Agropecuária Brasileira (Online) instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa) instacron:EMBRAPA |
instname_str |
Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
instacron_str |
EMBRAPA |
institution |
EMBRAPA |
reponame_str |
Pesquisa Agropecuária Brasileira (Online) |
collection |
Pesquisa Agropecuária Brasileira (Online) |
repository.name.fl_str_mv |
Pesquisa Agropecuária Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
repository.mail.fl_str_mv |
pab@sct.embrapa.br || sct.pab@embrapa.br |
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1793416661330558976 |