Application of different calibration methods for the Hargreaves-Samani model in Southeast Brazil
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , |
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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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 |
_version_ |
1797052815780085760 |