Accuracy of Potential Evapotranspiration Models in Different Time Scales

Detalhes bibliográficos
Autor(a) principal: Aparecido,Lucas Eduardo de Oliveira
Data de Publicação: 2020
Outros Autores: Meneses,Kamila Cunha de, Torsoni,Guilherme Botega, Moraes,José Reinaldo da Silva Cabral de, Mesquita,Daniel Zimmermann
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Revista Brasileira de Meteorologia (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862020000100063
Resumo: Abstract Know the precision of potential evapotranspiration models in different agronomic and climatic conditions is useful for irrigated agriculture. Therefore, we aimed to compare 18 methods of estimation of ETP with the Penman-Monteith (FAO-56) method, at different time scales for the State of Mato Grosso do Sul. Time series of climatic data were used on a daily scale between 1983 and 2018 from 22 locations in the state of Mato Grosso do Sul. ETP estimation models tested were: Benevidez-Lopez, Blaney-Criddle, Camargo, Hamon, Hargreaves, Hargreaves-Samani, Jensen-Haise, Jobson, Kharrufa, Linacre, Makkink, Penman, Priestley-Taylor, Radiation, Romanenko, Tanner-Pelton, Thornthwaite, and Turc. These models were compared with Penman-Monteith in daily, weekly, and monthly scales. The comparison between the ETP estimation models and the Penman-Monteith model was performed by the statistical indices: accuracy (MAPE) and precision (R2aj). Estimation methods showed differences in efficiency over time scales. The best performances of the models were on the daily scale. For daily scale, methods of Priestley-Taylor, Hargreaves, Hamon, and Makkink present the best values of accuracy and precision for the State of Mato Grosso do Sul. In the weekly scale, the most accurate methods are Hamon and Makkink, while for monthly scale the best methods are Makkink and Priestley-Taylor.
id SBMET-1_bf4b69ebeb3856888aaed130adb213f0
oai_identifier_str oai:scielo:S0102-77862020000100063
network_acronym_str SBMET-1
network_name_str Revista Brasileira de Meteorologia (Online)
repository_id_str
spelling Accuracy of Potential Evapotranspiration Models in Different Time Scalesestimation methodsaccuracyprecisionPenman-Monteithwater evaporationAbstract Know the precision of potential evapotranspiration models in different agronomic and climatic conditions is useful for irrigated agriculture. Therefore, we aimed to compare 18 methods of estimation of ETP with the Penman-Monteith (FAO-56) method, at different time scales for the State of Mato Grosso do Sul. Time series of climatic data were used on a daily scale between 1983 and 2018 from 22 locations in the state of Mato Grosso do Sul. ETP estimation models tested were: Benevidez-Lopez, Blaney-Criddle, Camargo, Hamon, Hargreaves, Hargreaves-Samani, Jensen-Haise, Jobson, Kharrufa, Linacre, Makkink, Penman, Priestley-Taylor, Radiation, Romanenko, Tanner-Pelton, Thornthwaite, and Turc. These models were compared with Penman-Monteith in daily, weekly, and monthly scales. The comparison between the ETP estimation models and the Penman-Monteith model was performed by the statistical indices: accuracy (MAPE) and precision (R2aj). Estimation methods showed differences in efficiency over time scales. The best performances of the models were on the daily scale. For daily scale, methods of Priestley-Taylor, Hargreaves, Hamon, and Makkink present the best values of accuracy and precision for the State of Mato Grosso do Sul. In the weekly scale, the most accurate methods are Hamon and Makkink, while for monthly scale the best methods are Makkink and Priestley-Taylor.Sociedade Brasileira de Meteorologia2020-03-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862020000100063Revista Brasileira de Meteorologia v.35 n.1 2020reponame:Revista Brasileira de Meteorologia (Online)instname:Sociedade Brasileira de Meteorologia (SBMET)instacron:SBMET10.1590/0102-7786351026info:eu-repo/semantics/openAccessAparecido,Lucas Eduardo de OliveiraMeneses,Kamila Cunha deTorsoni,Guilherme BotegaMoraes,José Reinaldo da Silva Cabral deMesquita,Daniel Zimmermanneng2020-07-09T00:00:00Zoai:scielo:S0102-77862020000100063Revistahttp://www.rbmet.org.br/port/index.phpONGhttps://old.scielo.br/oai/scielo-oai.php||rbmet@rbmet.org.br1982-43510102-7786opendoar:2020-07-09T00:00Revista Brasileira de Meteorologia (Online) - Sociedade Brasileira de Meteorologia (SBMET)false
dc.title.none.fl_str_mv Accuracy of Potential Evapotranspiration Models in Different Time Scales
title Accuracy of Potential Evapotranspiration Models in Different Time Scales
spellingShingle Accuracy of Potential Evapotranspiration Models in Different Time Scales
Aparecido,Lucas Eduardo de Oliveira
estimation methods
accuracy
precision
Penman-Monteith
water evaporation
title_short Accuracy of Potential Evapotranspiration Models in Different Time Scales
title_full Accuracy of Potential Evapotranspiration Models in Different Time Scales
title_fullStr Accuracy of Potential Evapotranspiration Models in Different Time Scales
title_full_unstemmed Accuracy of Potential Evapotranspiration Models in Different Time Scales
title_sort Accuracy of Potential Evapotranspiration Models in Different Time Scales
author Aparecido,Lucas Eduardo de Oliveira
author_facet Aparecido,Lucas Eduardo de Oliveira
Meneses,Kamila Cunha de
Torsoni,Guilherme Botega
Moraes,José Reinaldo da Silva Cabral de
Mesquita,Daniel Zimmermann
author_role author
author2 Meneses,Kamila Cunha de
Torsoni,Guilherme Botega
Moraes,José Reinaldo da Silva Cabral de
Mesquita,Daniel Zimmermann
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Aparecido,Lucas Eduardo de Oliveira
Meneses,Kamila Cunha de
Torsoni,Guilherme Botega
Moraes,José Reinaldo da Silva Cabral de
Mesquita,Daniel Zimmermann
dc.subject.por.fl_str_mv estimation methods
accuracy
precision
Penman-Monteith
water evaporation
topic estimation methods
accuracy
precision
Penman-Monteith
water evaporation
description Abstract Know the precision of potential evapotranspiration models in different agronomic and climatic conditions is useful for irrigated agriculture. Therefore, we aimed to compare 18 methods of estimation of ETP with the Penman-Monteith (FAO-56) method, at different time scales for the State of Mato Grosso do Sul. Time series of climatic data were used on a daily scale between 1983 and 2018 from 22 locations in the state of Mato Grosso do Sul. ETP estimation models tested were: Benevidez-Lopez, Blaney-Criddle, Camargo, Hamon, Hargreaves, Hargreaves-Samani, Jensen-Haise, Jobson, Kharrufa, Linacre, Makkink, Penman, Priestley-Taylor, Radiation, Romanenko, Tanner-Pelton, Thornthwaite, and Turc. These models were compared with Penman-Monteith in daily, weekly, and monthly scales. The comparison between the ETP estimation models and the Penman-Monteith model was performed by the statistical indices: accuracy (MAPE) and precision (R2aj). Estimation methods showed differences in efficiency over time scales. The best performances of the models were on the daily scale. For daily scale, methods of Priestley-Taylor, Hargreaves, Hamon, and Makkink present the best values of accuracy and precision for the State of Mato Grosso do Sul. In the weekly scale, the most accurate methods are Hamon and Makkink, while for monthly scale the best methods are Makkink and Priestley-Taylor.
publishDate 2020
dc.date.none.fl_str_mv 2020-03-01
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=S0102-77862020000100063
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862020000100063
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0102-7786351026
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 Meteorologia
publisher.none.fl_str_mv Sociedade Brasileira de Meteorologia
dc.source.none.fl_str_mv Revista Brasileira de Meteorologia v.35 n.1 2020
reponame:Revista Brasileira de Meteorologia (Online)
instname:Sociedade Brasileira de Meteorologia (SBMET)
instacron:SBMET
instname_str Sociedade Brasileira de Meteorologia (SBMET)
instacron_str SBMET
institution SBMET
reponame_str Revista Brasileira de Meteorologia (Online)
collection Revista Brasileira de Meteorologia (Online)
repository.name.fl_str_mv Revista Brasileira de Meteorologia (Online) - Sociedade Brasileira de Meteorologia (SBMET)
repository.mail.fl_str_mv ||rbmet@rbmet.org.br
_version_ 1752122086665486336