Modeling of the Rainfall and R-Factor for Tocantins State, Brazil
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista Brasileira de Ciência do Solo (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832019000100524 |
Resumo: | ABSTRACT The state of Tocantins is inserted in the new Brazilian agricultural frontier and has shown enormous potential for expansion of the agricultural lands. However, there is a lack of more elaborate scientific information for better planning and guide agricultural activities, especially regarding the soil and water conservation. Tocantins has a relevant rainfall spatial variability and, consequently, rainfall erosivity. Thus, this work aimed to develop models to estimate the mean monthly and annual rainfall and means rainfall erosivity factor (R-factor) of the Universal Soil Loss Equation (USLE) for the state of Tocantins. For that, 97 historical series of daily rainfall were studied, considering a standard period of 25 years (1985-2009). The fitting of the models adjustment datasets consists of 86 rain-gauges, out of which, 11 were randomly selected and used solely for model validation. Afterward, maps of these variables were generated based on the regression-kriging procedure. The fitted models presented precision statistical that allow characterizing them as “good quality”, with a coefficient of determination higher than 0.68 for rainfall models and 0.65 for the R-factor model, besides acceptable bias. Therefore, the application of the models can be successfully carried out, aiding the agricultural planning in the state of Tocantins. |
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Modeling of the Rainfall and R-Factor for Tocantins State, Brazilwater erosiongeostatisticsregression-krigingsoil and water conservationmappingABSTRACT The state of Tocantins is inserted in the new Brazilian agricultural frontier and has shown enormous potential for expansion of the agricultural lands. However, there is a lack of more elaborate scientific information for better planning and guide agricultural activities, especially regarding the soil and water conservation. Tocantins has a relevant rainfall spatial variability and, consequently, rainfall erosivity. Thus, this work aimed to develop models to estimate the mean monthly and annual rainfall and means rainfall erosivity factor (R-factor) of the Universal Soil Loss Equation (USLE) for the state of Tocantins. For that, 97 historical series of daily rainfall were studied, considering a standard period of 25 years (1985-2009). The fitting of the models adjustment datasets consists of 86 rain-gauges, out of which, 11 were randomly selected and used solely for model validation. Afterward, maps of these variables were generated based on the regression-kriging procedure. The fitted models presented precision statistical that allow characterizing them as “good quality”, with a coefficient of determination higher than 0.68 for rainfall models and 0.65 for the R-factor model, besides acceptable bias. Therefore, the application of the models can be successfully carried out, aiding the agricultural planning in the state of Tocantins.Sociedade Brasileira de Ciência do Solo2019-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832019000100524Revista Brasileira de Ciência do Solo v.43 2019reponame:Revista Brasileira de Ciência do Solo (Online)instname:Sociedade Brasileira de Ciência do Solo (SBCS)instacron:SBCS10.1590/18069657rbcs20190047info:eu-repo/semantics/openAccessAvanzi,Junior CesarViola,Marcelo RibeiroMello,Carlos Rogério deGiongo,Marcos ViniciusPontes,Lucas Machadoeng2019-09-26T00:00:00Zoai:scielo:S0100-06832019000100524Revistahttp://www.scielo.br/scielo.php?script=sci_serial&pid=0100-0683&lng=es&nrm=isohttps://old.scielo.br/oai/scielo-oai.php||sbcs@ufv.br1806-96570100-0683opendoar:2019-09-26T00:00Revista Brasileira de Ciência do Solo (Online) - Sociedade Brasileira de Ciência do Solo (SBCS)false |
dc.title.none.fl_str_mv |
Modeling of the Rainfall and R-Factor for Tocantins State, Brazil |
title |
Modeling of the Rainfall and R-Factor for Tocantins State, Brazil |
spellingShingle |
Modeling of the Rainfall and R-Factor for Tocantins State, Brazil Avanzi,Junior Cesar water erosion geostatistics regression-kriging soil and water conservation mapping |
title_short |
Modeling of the Rainfall and R-Factor for Tocantins State, Brazil |
title_full |
Modeling of the Rainfall and R-Factor for Tocantins State, Brazil |
title_fullStr |
Modeling of the Rainfall and R-Factor for Tocantins State, Brazil |
title_full_unstemmed |
Modeling of the Rainfall and R-Factor for Tocantins State, Brazil |
title_sort |
Modeling of the Rainfall and R-Factor for Tocantins State, Brazil |
author |
Avanzi,Junior Cesar |
author_facet |
Avanzi,Junior Cesar Viola,Marcelo Ribeiro Mello,Carlos Rogério de Giongo,Marcos Vinicius Pontes,Lucas Machado |
author_role |
author |
author2 |
Viola,Marcelo Ribeiro Mello,Carlos Rogério de Giongo,Marcos Vinicius Pontes,Lucas Machado |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Avanzi,Junior Cesar Viola,Marcelo Ribeiro Mello,Carlos Rogério de Giongo,Marcos Vinicius Pontes,Lucas Machado |
dc.subject.por.fl_str_mv |
water erosion geostatistics regression-kriging soil and water conservation mapping |
topic |
water erosion geostatistics regression-kriging soil and water conservation mapping |
description |
ABSTRACT The state of Tocantins is inserted in the new Brazilian agricultural frontier and has shown enormous potential for expansion of the agricultural lands. However, there is a lack of more elaborate scientific information for better planning and guide agricultural activities, especially regarding the soil and water conservation. Tocantins has a relevant rainfall spatial variability and, consequently, rainfall erosivity. Thus, this work aimed to develop models to estimate the mean monthly and annual rainfall and means rainfall erosivity factor (R-factor) of the Universal Soil Loss Equation (USLE) for the state of Tocantins. For that, 97 historical series of daily rainfall were studied, considering a standard period of 25 years (1985-2009). The fitting of the models adjustment datasets consists of 86 rain-gauges, out of which, 11 were randomly selected and used solely for model validation. Afterward, maps of these variables were generated based on the regression-kriging procedure. The fitted models presented precision statistical that allow characterizing them as “good quality”, with a coefficient of determination higher than 0.68 for rainfall models and 0.65 for the R-factor model, besides acceptable bias. Therefore, the application of the models can be successfully carried out, aiding the agricultural planning in the state of Tocantins. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-01-01 |
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=S0100-06832019000100524 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832019000100524 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/18069657rbcs20190047 |
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 |
Sociedade Brasileira de Ciência do Solo |
publisher.none.fl_str_mv |
Sociedade Brasileira de Ciência do Solo |
dc.source.none.fl_str_mv |
Revista Brasileira de Ciência do Solo v.43 2019 reponame:Revista Brasileira de Ciência do Solo (Online) instname:Sociedade Brasileira de Ciência do Solo (SBCS) instacron:SBCS |
instname_str |
Sociedade Brasileira de Ciência do Solo (SBCS) |
instacron_str |
SBCS |
institution |
SBCS |
reponame_str |
Revista Brasileira de Ciência do Solo (Online) |
collection |
Revista Brasileira de Ciência do Solo (Online) |
repository.name.fl_str_mv |
Revista Brasileira de Ciência do Solo (Online) - Sociedade Brasileira de Ciência do Solo (SBCS) |
repository.mail.fl_str_mv |
||sbcs@ufv.br |
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1752126522268844032 |