Application of different calibration methods for the Hargreaves-Samani model in Southeast Brazil

Detalhes bibliográficos
Autor(a) principal: Dohler, Rafael Esteves
Data de Publicação: 2020
Outros Autores: Zanetti, Sidney Sara, Cecílio, Roberto Avelino, Pezzopane, José Eduardo Macedo, Xavier, Alexandre Cândido
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Research, Society and Development
Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/4811
Resumo: The evapotranspiration is an important variable in the hydrological cycle and one of the main components of water balance in the soil. The use of simplified equations is a potential alternative to estimate reference evapotranspiration (ET0) when there is limited meteorological data. The objective of this study was to test different methods to estimate ET0 using the Hargreaves-Samani equation (HS) under different meteorological conditions. ET0 was calibrated with HS, adjusting the HS coefficient (HC), using different methods. Adjustment by linear regression was also performed. ET0 was also estimated using the original HS and Penman-Monteith FAO-56 methods with limited climatic data (PML). The performance of the methods (mean absolute error, mm day-1) to estimate evapotranspiration, based on Penman-Monteith, were: PML (1.46); HS (0.68); Vanderlinden et al. (2004) (0.81); Martí et al. (2015) (0.77); and linear regression (0.53). The PML method presented the worst performance. Adjustment by linear regression presented a better performance than the adjustments of HC, improving the ET0 estimates by up to 30%, and it is considered the most recommendable of the methods tested.
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spelling Application of different calibration methods for the Hargreaves-Samani model in Southeast BrazilAplicación de diferentes métodos de calibración para el modelo Hargreaves-Samani en el Sureste de BrasilAplicação de diferentes métodos de calibração do modelo de Hargreaves-Samani no Sudeste do BrasilBalanço hídricoEvapotranspiração potencialPenman-MonteithAgrometeorologiaBalance hídricoEvapotranspiración potencialPenman-MonteithAgrometeorologia.Water balancePotential evapotranspirationPenman-MonteithAgrometeorology.The evapotranspiration is an important variable in the hydrological cycle and one of the main components of water balance in the soil. The use of simplified equations is a potential alternative to estimate reference evapotranspiration (ET0) when there is limited meteorological data. The objective of this study was to test different methods to estimate ET0 using the Hargreaves-Samani equation (HS) under different meteorological conditions. ET0 was calibrated with HS, adjusting the HS coefficient (HC), using different methods. Adjustment by linear regression was also performed. ET0 was also estimated using the original HS and Penman-Monteith FAO-56 methods with limited climatic data (PML). The performance of the methods (mean absolute error, mm day-1) to estimate evapotranspiration, based on Penman-Monteith, were: PML (1.46); HS (0.68); Vanderlinden et al. (2004) (0.81); Martí et al. (2015) (0.77); and linear regression (0.53). The PML method presented the worst performance. Adjustment by linear regression presented a better performance than the adjustments of HC, improving the ET0 estimates by up to 30%, and it is considered the most recommendable of the methods tested.La evapotranspiración es una variable importante en el ciclo hidrológico y uno de los principales componentes del equilibrio hídrico en el suelo. El uso de ecuaciones simplificadas es una alternativa potencial para estimar la evapotranspiración de referencia (ET0) cuando hay datos meteorológicos limitados. El objetivo de este estudio fue probar diferentes métodos para estimar ET0 utilizando la ecuación Hargreaves-Samani (HS) en diferentes condiciones meteorológicas. ET0 se calibró con HS, ajustando el coeficiente HS (HC), utilizando diferentes métodos. El ajuste por regresión lineal también se realizó. ET0 también se estimó utilizando los métodos originales HS y Penman-Monteith FAO-56 con datos climáticos limitados (PML). El desempeño de los métodos (error absoluto medio, mm día-1) para estimar la evapotranspiración, basados en Penman-Monteith, fueron: PML (1.46); HS (0,68); Vanderlinden y col. (2004) (0,81); Martí y col. (2015) (0,77); y regresión lineal (0.53). El método PML presentó el peor desempeño. El ajuste por regresión lineal presentó un mejor desempeño que los ajustes de HC, mejorando las estimaciones de ET0 hasta en un 30%, y se considera el más recomendable de los métodos probados.A evapotranspiração é uma variável importante no ciclo hidrológico e um dos principais componentes do balanço hídrico no solo. O uso de equações simplificadas é uma alternativa potencial para estimar a evapotranspiração de referência (ET0) quando os dados meteorológicos são limitados. O objetivo deste estudo foi testar diferentes métodos para estimar a ET0 usando a equação de Hargreaves-Samani (HS) sob diferentes condições meteorológicas. A ET0 foi calibrada com HS, ajustando o coeficiente de HS (HC), utilizando diferentes métodos. O ajuste por regressão linear também foi realizado. A ET0 também foi estimada usando os métodos originais de HS e Penman-Monteith FAO-56 com dados climáticos limitados (PML). O desempenho dos métodos (erro absoluto médio, mm dia-1) para estimar a evapotranspiração, baseado em Penman-Monteith, foram: PML (1,46); HS (0,68); Vanderlinden et al. (2004) (0,81); Martí et al. (2015) (0,77); e regressão linear (0,53). O método PML apresentou o pior desempenho. O ajuste por regressão linear apresentou um desempenho melhor que os ajustes usando do HC, melhorando as estimativas de ET0 em até 30%, sendo considerado o mais recomendável dos métodos testados.Research, Society and Development2020-07-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://rsdjournal.org/index.php/rsd/article/view/481110.33448/rsd-v9i8.4811Research, Society and Development; Vol. 9 No. 8; e368984811Research, Society and Development; Vol. 9 Núm. 8; e368984811Research, Society and Development; v. 9 n. 8; e3689848112525-3409reponame:Research, Society and Developmentinstname:Universidade Federal de Itajubá (UNIFEI)instacron:UNIFEIenghttps://rsdjournal.org/index.php/rsd/article/view/4811/4910Copyright (c) 2020 Sidney Sara Zanettiinfo:eu-repo/semantics/openAccessDohler, Rafael EstevesZanetti, Sidney SaraCecílio, Roberto AvelinoPezzopane, José Eduardo MacedoXavier, Alexandre Cândido2020-08-20T18:00:17Zoai:ojs.pkp.sfu.ca:article/4811Revistahttps://rsdjournal.org/index.php/rsd/indexPUBhttps://rsdjournal.org/index.php/rsd/oairsd.articles@gmail.com2525-34092525-3409opendoar:2024-01-17T09:28:31.900685Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)false
dc.title.none.fl_str_mv Application of different calibration methods for the Hargreaves-Samani model in Southeast Brazil
Aplicación de diferentes métodos de calibración para el modelo Hargreaves-Samani en el Sureste de Brasil
Aplicação de diferentes métodos de calibração do modelo de Hargreaves-Samani no Sudeste do Brasil
title Application of different calibration methods for the Hargreaves-Samani model in Southeast Brazil
spellingShingle Application of different calibration methods for the Hargreaves-Samani model in Southeast Brazil
Dohler, Rafael Esteves
Balanço hídrico
Evapotranspiração potencial
Penman-Monteith
Agrometeorologia
Balance hídrico
Evapotranspiración potencial
Penman-Monteith
Agrometeorologia.
Water balance
Potential evapotranspiration
Penman-Monteith
Agrometeorology.
title_short Application of different calibration methods for the Hargreaves-Samani model in Southeast Brazil
title_full Application of different calibration methods for the Hargreaves-Samani model in Southeast Brazil
title_fullStr Application of different calibration methods for the Hargreaves-Samani model in Southeast Brazil
title_full_unstemmed Application of different calibration methods for the Hargreaves-Samani model in Southeast Brazil
title_sort Application of different calibration methods for the Hargreaves-Samani model in Southeast Brazil
author Dohler, Rafael Esteves
author_facet Dohler, Rafael Esteves
Zanetti, Sidney Sara
Cecílio, Roberto Avelino
Pezzopane, José Eduardo Macedo
Xavier, Alexandre Cândido
author_role author
author2 Zanetti, Sidney Sara
Cecílio, Roberto Avelino
Pezzopane, José Eduardo Macedo
Xavier, Alexandre Cândido
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Dohler, Rafael Esteves
Zanetti, Sidney Sara
Cecílio, Roberto Avelino
Pezzopane, José Eduardo Macedo
Xavier, Alexandre Cândido
dc.subject.por.fl_str_mv Balanço hídrico
Evapotranspiração potencial
Penman-Monteith
Agrometeorologia
Balance hídrico
Evapotranspiración potencial
Penman-Monteith
Agrometeorologia.
Water balance
Potential evapotranspiration
Penman-Monteith
Agrometeorology.
topic Balanço hídrico
Evapotranspiração potencial
Penman-Monteith
Agrometeorologia
Balance hídrico
Evapotranspiración potencial
Penman-Monteith
Agrometeorologia.
Water balance
Potential evapotranspiration
Penman-Monteith
Agrometeorology.
description The evapotranspiration is an important variable in the hydrological cycle and one of the main components of water balance in the soil. The use of simplified equations is a potential alternative to estimate reference evapotranspiration (ET0) when there is limited meteorological data. The objective of this study was to test different methods to estimate ET0 using the Hargreaves-Samani equation (HS) under different meteorological conditions. ET0 was calibrated with HS, adjusting the HS coefficient (HC), using different methods. Adjustment by linear regression was also performed. ET0 was also estimated using the original HS and Penman-Monteith FAO-56 methods with limited climatic data (PML). The performance of the methods (mean absolute error, mm day-1) to estimate evapotranspiration, based on Penman-Monteith, were: PML (1.46); HS (0.68); Vanderlinden et al. (2004) (0.81); Martí et al. (2015) (0.77); and linear regression (0.53). The PML method presented the worst performance. Adjustment by linear regression presented a better performance than the adjustments of HC, improving the ET0 estimates by up to 30%, and it is considered the most recommendable of the methods tested.
publishDate 2020
dc.date.none.fl_str_mv 2020-07-08
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://rsdjournal.org/index.php/rsd/article/view/4811
10.33448/rsd-v9i8.4811
url https://rsdjournal.org/index.php/rsd/article/view/4811
identifier_str_mv 10.33448/rsd-v9i8.4811
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://rsdjournal.org/index.php/rsd/article/view/4811/4910
dc.rights.driver.fl_str_mv Copyright (c) 2020 Sidney Sara Zanetti
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2020 Sidney Sara Zanetti
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Research, Society and Development
publisher.none.fl_str_mv Research, Society and Development
dc.source.none.fl_str_mv Research, Society and Development; Vol. 9 No. 8; e368984811
Research, Society and Development; Vol. 9 Núm. 8; e368984811
Research, Society and Development; v. 9 n. 8; e368984811
2525-3409
reponame:Research, Society and Development
instname:Universidade Federal de Itajubá (UNIFEI)
instacron:UNIFEI
instname_str Universidade Federal de Itajubá (UNIFEI)
instacron_str UNIFEI
institution UNIFEI
reponame_str Research, Society and Development
collection Research, Society and Development
repository.name.fl_str_mv Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)
repository.mail.fl_str_mv rsd.articles@gmail.com
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