EMPIRICAL METHODS FOR ESTIMATING REFERENCE SURFACE NET RADIATION FROM SOLAR RADIATION

Detalhes bibliográficos
Autor(a) principal: Flumignan,Danilton L.
Data de Publicação: 2018
Outros Autores: Rezende,Maiara K. A., Comunello,Eder, Fietz,Carlos R.
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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spelling 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
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dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162018000100032
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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)
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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
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