Accuracy of Potential Evapotranspiration Models in Different Time Scales
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , |
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. |
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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 |
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1752122086665486336 |