EMPIRICAL METHODS FOR ESTIMATING REFERENCE SURFACE NET RADIATION FROM SOLAR RADIATION
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Engenharia Agrícola |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162018000100032 |
Resumo: | ABSTRACT Net radiation (Rn) of reference surface is important information that has many applications, but its measurement is rare due to the high cost of the sensor and the complexity involved on the measurement. Therefore, estimate Rn from another variable is desirable, as from solar radiation (Rs); however, standard methods used are complex, making interesting the use of simplified methodologies. Considering these aspects, the present study aimed to set two empirical methods to estimate Rn from Rs for Dourados region, Mato Grosso do Sul, Brazil. One method was based on mathematical modeling (Gauss Method). The other one was a more simplified and practical approach (Practical Method) comprising the determination of fixed monthly conversion factors. It was used daily Rs data of a 12-years database. With these, there were estimated Rn values by the standard method recommended by FAO. Gauss Method was set using Table Curve 2D 5.01 software. Modeling consisted in defining the values of the equation parameters. On Practical Method, we developed monthly coefficients of the ratio Rn/Rs. In order to validate both methods it was measured Rs and Rn during two years using high precision sensors. Both estimating methods showed satisfactory results, with relative mean absolute error values lower than 5.8%. |
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Engenharia Agrícola |
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EMPIRICAL METHODS FOR ESTIMATING REFERENCE SURFACE NET RADIATION FROM SOLAR RADIATIONWeather stationGauss MethodPractical Methodreference evapotranspirationABSTRACT Net radiation (Rn) of reference surface is important information that has many applications, but its measurement is rare due to the high cost of the sensor and the complexity involved on the measurement. Therefore, estimate Rn from another variable is desirable, as from solar radiation (Rs); however, standard methods used are complex, making interesting the use of simplified methodologies. Considering these aspects, the present study aimed to set two empirical methods to estimate Rn from Rs for Dourados region, Mato Grosso do Sul, Brazil. One method was based on mathematical modeling (Gauss Method). The other one was a more simplified and practical approach (Practical Method) comprising the determination of fixed monthly conversion factors. It was used daily Rs data of a 12-years database. With these, there were estimated Rn values by the standard method recommended by FAO. Gauss Method was set using Table Curve 2D 5.01 software. Modeling consisted in defining the values of the equation parameters. On Practical Method, we developed monthly coefficients of the ratio Rn/Rs. In order to validate both methods it was measured Rs and Rn during two years using high precision sensors. Both estimating methods showed satisfactory results, with relative mean absolute error values lower than 5.8%.Associação Brasileira de Engenharia Agrícola2018-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162018000100032Engenharia Agrícola v.38 n.1 2018reponame:Engenharia Agrícolainstname:Associação Brasileira de Engenharia Agrícola (SBEA)instacron:SBEA10.1590/1809-4430-eng.agric.v38n1p32-37/2018info:eu-repo/semantics/openAccessFlumignan,Danilton L.Rezende,Maiara K. A.Comunello,EderFietz,Carlos R.eng2018-03-16T00:00:00Zoai:scielo:S0100-69162018000100032Revistahttp://www.engenhariaagricola.org.br/ORGhttps://old.scielo.br/oai/scielo-oai.phprevistasbea@sbea.org.br||sbea@sbea.org.br1809-44300100-6916opendoar:2018-03-16T00:00Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA)false |
dc.title.none.fl_str_mv |
EMPIRICAL METHODS FOR ESTIMATING REFERENCE SURFACE NET RADIATION FROM SOLAR RADIATION |
title |
EMPIRICAL METHODS FOR ESTIMATING REFERENCE SURFACE NET RADIATION FROM SOLAR RADIATION |
spellingShingle |
EMPIRICAL METHODS FOR ESTIMATING REFERENCE SURFACE NET RADIATION FROM SOLAR RADIATION Flumignan,Danilton L. Weather station Gauss Method Practical Method reference evapotranspiration |
title_short |
EMPIRICAL METHODS FOR ESTIMATING REFERENCE SURFACE NET RADIATION FROM SOLAR RADIATION |
title_full |
EMPIRICAL METHODS FOR ESTIMATING REFERENCE SURFACE NET RADIATION FROM SOLAR RADIATION |
title_fullStr |
EMPIRICAL METHODS FOR ESTIMATING REFERENCE SURFACE NET RADIATION FROM SOLAR RADIATION |
title_full_unstemmed |
EMPIRICAL METHODS FOR ESTIMATING REFERENCE SURFACE NET RADIATION FROM SOLAR RADIATION |
title_sort |
EMPIRICAL METHODS FOR ESTIMATING REFERENCE SURFACE NET RADIATION FROM SOLAR RADIATION |
author |
Flumignan,Danilton L. |
author_facet |
Flumignan,Danilton L. Rezende,Maiara K. A. Comunello,Eder Fietz,Carlos R. |
author_role |
author |
author2 |
Rezende,Maiara K. A. Comunello,Eder Fietz,Carlos R. |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Flumignan,Danilton L. Rezende,Maiara K. A. Comunello,Eder Fietz,Carlos R. |
dc.subject.por.fl_str_mv |
Weather station Gauss Method Practical Method reference evapotranspiration |
topic |
Weather station Gauss Method Practical Method reference evapotranspiration |
description |
ABSTRACT Net radiation (Rn) of reference surface is important information that has many applications, but its measurement is rare due to the high cost of the sensor and the complexity involved on the measurement. Therefore, estimate Rn from another variable is desirable, as from solar radiation (Rs); however, standard methods used are complex, making interesting the use of simplified methodologies. Considering these aspects, the present study aimed to set two empirical methods to estimate Rn from Rs for Dourados region, Mato Grosso do Sul, Brazil. One method was based on mathematical modeling (Gauss Method). The other one was a more simplified and practical approach (Practical Method) comprising the determination of fixed monthly conversion factors. It was used daily Rs data of a 12-years database. With these, there were estimated Rn values by the standard method recommended by FAO. Gauss Method was set using Table Curve 2D 5.01 software. Modeling consisted in defining the values of the equation parameters. On Practical Method, we developed monthly coefficients of the ratio Rn/Rs. In order to validate both methods it was measured Rs and Rn during two years using high precision sensors. Both estimating methods showed satisfactory results, with relative mean absolute error values lower than 5.8%. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-01-01 |
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=S0100-69162018000100032 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162018000100032 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1809-4430-eng.agric.v38n1p32-37/2018 |
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.38 n.1 2018 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_ |
1752126273622114304 |