Spatial variability of coffee plant water consumption based on the SEBAL algorithm

Detalhes bibliográficos
Autor(a) principal: Costa, Jéfferson de Oliveira
Data de Publicação: 2019
Outros Autores: Coelho, Rubens Duarte, Wolff, Wagner, José, Jefferson Vieira, Folegatti, Marcos Vinicius, Ferraz, Silvio Frosini de Barros
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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spelling 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
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