Spatial variability of coffee plant water consumption based on the SEBAL algorithm
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Scientia Agrícola (Online) |
Texto Completo: | https://www.revistas.usp.br/sa/article/view/154154 |
Resumo: | Awareness of evapotranspiration (ET) and crop coefficient (Kc ) is necessary for irrigation management in coffee crops. ET and Kc spatial variabilities are disregarded in traditional methods. Methods based on radiometric measurements have potential to obtain these spatialized variables. The Kc curve and spatial variability of actual evapotranspiration (ETa ) were determined using images from Landsat 8 satellite. We used images of young and adult coffee plantations from OLI (Operational Land Imager) and TIRS (Thermal Infrared Sensor) sensors over a two-year period. Evapotranspiration was estimated using the Surface Energy Balance Algorithm for Land (SEBAL). Moreover, the reference evapotranspiration (ETo ) was estimated through the Penman-Monteith method. We obtained the values for the evapotranspiration fraction (ETf ), analogous to Kc , according to ET and ETo values. The study was conducted in Buritis, Minas Gerais State, Brazil, in areas cropped with Coffea arabica irrigated by central pivots. A comparative analysis was made using different statistical indices. Average ETa was 2.17 mm d–1 for young coffee plantations, , and the Kc mean value was 0.6. For adult coffee plantations, average ETa was 3.95 mm d–1, , and the Kc mean value was 0.85. The ETc and Kc data obtained based on the SEBAL algorithm displayed similar values to studies that used traditional methods. This model has huge potential to estimate ET of different stages of coffee plantation for the region studied. |
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Scientia Agrícola (Online) |
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Spatial variability of coffee plant water consumption based on the SEBAL algorithmevapotranspirationcrop coefficientsatelliteAwareness of evapotranspiration (ET) and crop coefficient (Kc ) is necessary for irrigation management in coffee crops. ET and Kc spatial variabilities are disregarded in traditional methods. Methods based on radiometric measurements have potential to obtain these spatialized variables. The Kc curve and spatial variability of actual evapotranspiration (ETa ) were determined using images from Landsat 8 satellite. We used images of young and adult coffee plantations from OLI (Operational Land Imager) and TIRS (Thermal Infrared Sensor) sensors over a two-year period. Evapotranspiration was estimated using the Surface Energy Balance Algorithm for Land (SEBAL). Moreover, the reference evapotranspiration (ETo ) was estimated through the Penman-Monteith method. We obtained the values for the evapotranspiration fraction (ETf ), analogous to Kc , according to ET and ETo values. The study was conducted in Buritis, Minas Gerais State, Brazil, in areas cropped with Coffea arabica irrigated by central pivots. A comparative analysis was made using different statistical indices. Average ETa was 2.17 mm d–1 for young coffee plantations, , and the Kc mean value was 0.6. For adult coffee plantations, average ETa was 3.95 mm d–1, , and the Kc mean value was 0.85. The ETc and Kc data obtained based on the SEBAL algorithm displayed similar values to studies that used traditional methods. This model has huge potential to estimate ET of different stages of coffee plantation for the region studied.Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz2019-01-31info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://www.revistas.usp.br/sa/article/view/15415410.1590/1678-992x-2017-0158Scientia Agricola; v. 76 n. 2 (2019); 93-101Scientia Agricola; Vol. 76 Núm. 2 (2019); 93-101Scientia Agricola; Vol. 76 No. 2 (2019); 93-1011678-992X0103-9016reponame:Scientia Agrícola (Online)instname:Universidade de São Paulo (USP)instacron:USPenghttps://www.revistas.usp.br/sa/article/view/154154/150390Copyright (c) 2019 Scientia Agricolainfo:eu-repo/semantics/openAccessCosta, Jéfferson de OliveiraCoelho, Rubens DuarteWolff, WagnerJosé, Jefferson VieiraFolegatti, Marcos ViniciusFerraz, Silvio Frosini de Barros2019-02-04T14:46:08Zoai:revistas.usp.br:article/154154Revistahttp://revistas.usp.br/sa/indexPUBhttps://old.scielo.br/oai/scielo-oai.phpscientia@usp.br||alleoni@usp.br1678-992X0103-9016opendoar:2019-02-04T14:46:08Scientia Agrícola (Online) - Universidade de São Paulo (USP)false |
dc.title.none.fl_str_mv |
Spatial variability of coffee plant water consumption based on the SEBAL algorithm |
title |
Spatial variability of coffee plant water consumption based on the SEBAL algorithm |
spellingShingle |
Spatial variability of coffee plant water consumption based on the SEBAL algorithm Costa, Jéfferson de Oliveira evapotranspiration crop coefficient satellite |
title_short |
Spatial variability of coffee plant water consumption based on the SEBAL algorithm |
title_full |
Spatial variability of coffee plant water consumption based on the SEBAL algorithm |
title_fullStr |
Spatial variability of coffee plant water consumption based on the SEBAL algorithm |
title_full_unstemmed |
Spatial variability of coffee plant water consumption based on the SEBAL algorithm |
title_sort |
Spatial variability of coffee plant water consumption based on the SEBAL algorithm |
author |
Costa, Jéfferson de Oliveira |
author_facet |
Costa, Jéfferson de Oliveira Coelho, Rubens Duarte Wolff, Wagner José, Jefferson Vieira Folegatti, Marcos Vinicius Ferraz, Silvio Frosini de Barros |
author_role |
author |
author2 |
Coelho, Rubens Duarte Wolff, Wagner José, Jefferson Vieira Folegatti, Marcos Vinicius Ferraz, Silvio Frosini de Barros |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Costa, Jéfferson de Oliveira Coelho, Rubens Duarte Wolff, Wagner José, Jefferson Vieira Folegatti, Marcos Vinicius Ferraz, Silvio Frosini de Barros |
dc.subject.por.fl_str_mv |
evapotranspiration crop coefficient satellite |
topic |
evapotranspiration crop coefficient satellite |
description |
Awareness of evapotranspiration (ET) and crop coefficient (Kc ) is necessary for irrigation management in coffee crops. ET and Kc spatial variabilities are disregarded in traditional methods. Methods based on radiometric measurements have potential to obtain these spatialized variables. The Kc curve and spatial variability of actual evapotranspiration (ETa ) were determined using images from Landsat 8 satellite. We used images of young and adult coffee plantations from OLI (Operational Land Imager) and TIRS (Thermal Infrared Sensor) sensors over a two-year period. Evapotranspiration was estimated using the Surface Energy Balance Algorithm for Land (SEBAL). Moreover, the reference evapotranspiration (ETo ) was estimated through the Penman-Monteith method. We obtained the values for the evapotranspiration fraction (ETf ), analogous to Kc , according to ET and ETo values. The study was conducted in Buritis, Minas Gerais State, Brazil, in areas cropped with Coffea arabica irrigated by central pivots. A comparative analysis was made using different statistical indices. Average ETa was 2.17 mm d–1 for young coffee plantations, , and the Kc mean value was 0.6. For adult coffee plantations, average ETa was 3.95 mm d–1, , and the Kc mean value was 0.85. The ETc and Kc data obtained based on the SEBAL algorithm displayed similar values to studies that used traditional methods. This model has huge potential to estimate ET of different stages of coffee plantation for the region studied. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-01-31 |
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://www.revistas.usp.br/sa/article/view/154154 10.1590/1678-992x-2017-0158 |
url |
https://www.revistas.usp.br/sa/article/view/154154 |
identifier_str_mv |
10.1590/1678-992x-2017-0158 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://www.revistas.usp.br/sa/article/view/154154/150390 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2019 Scientia Agricola info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2019 Scientia Agricola |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz |
publisher.none.fl_str_mv |
Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz |
dc.source.none.fl_str_mv |
Scientia Agricola; v. 76 n. 2 (2019); 93-101 Scientia Agricola; Vol. 76 Núm. 2 (2019); 93-101 Scientia Agricola; Vol. 76 No. 2 (2019); 93-101 1678-992X 0103-9016 reponame:Scientia Agrícola (Online) instname:Universidade de São Paulo (USP) instacron:USP |
instname_str |
Universidade de São Paulo (USP) |
instacron_str |
USP |
institution |
USP |
reponame_str |
Scientia Agrícola (Online) |
collection |
Scientia Agrícola (Online) |
repository.name.fl_str_mv |
Scientia Agrícola (Online) - Universidade de São Paulo (USP) |
repository.mail.fl_str_mv |
scientia@usp.br||alleoni@usp.br |
_version_ |
1800222793914122240 |