HS Cal software for the calibration of the Hargreaves-Samani equation

Ferreira, Lucas Borges; Cunha, Fernando França da; Sediyama, Gilberto Chohaku; Campos, Flavio Bastos

doi:10.1590/S1678-3921.pab2019.v54.00226

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Agrometeorology • Pesq. agropec. bras. 54 • 2019 • https://doi.org/10.1590/S1678-3921.pab2019.v54.00226 copy

HS Cal software for the calibration of the Hargreaves-Samani equation

Programa HS Cal para calibração da equação de Hargreaves-Samani

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract:

The objective of this work was to develop a software (HS Cal) to calibrate the Hargreaves-Samani equation for specific periods of the year, in global, seasonal, and monthly time scales, as well as to compare the performance of calibrated and non-calibrated equations. The software was developed in order to use raw data provided by Banco de Dados Meteorológicos para Ensino e Pesquisa (BDMEP). All calibrations outperformed the original Hargreaves-Samani equation, especially with the use of seasonal and monthly calibrations. The HS Cal software can easily calibrate the Hargreaves-Samani equation, allowing the identification of the best form of this equation for a given site.

Index terms:
agrometeorology; irrigation; local calibration; minimum data; reference evapotranspiration; simplified models

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[1] *Corresponding author: contato.lucasbf@gmail.com

Statistical index⁽¹⁾	HS	HS global	HS season	HS month
	Barreiras, BA
RMSE (mm per day)	1.09	0.73	0.71	0.70
Classification	Medium	Good	Good	Good
	Belém, PA
RMSE (mm per day)	0.87	0.58	0.51	0.50
Classification	Not good	Medium	Good	Good
	Campina Grande, PB
RMSE (mm per day)	0.59	0.54	0.53	0.52
Classification	Very good	Very good	Great	Great
	Canarana, MT
RMSE (mm per day)	1.61	0.63	0.59	0.58
Classification	Terrible	Not good	Medium	Medium
	Curitiba, PR
RMSE (mm per day)	0.91	0.55	0.54	0.53
Classification	Very good	Great	Great	Great
	Januária, MG
RMSE (mm per day)	0.89	0.74	0.66	0.64
Classification	Good	Good	Very good	Very good
	Manaus, AM
RMSE (mm per day)	0.97	0.71	0.67	0.65
Classification	Not good	Medium	Good	Good
	Rio Branco, AC
RMSE (mm per day)	1.25	0.56	0.53	0.52
Classification	Not good	Good	Good	Good
	Santa Maria, RS
RMSE (mm per day)	0.97	0.67	0.68	0.69
Classification	Very good	Great	Great	Great
	Sorocaba, SP
RMSE (mm per day)	1.09	0.52	0.52	0.50
Classification	Very good	Great	Great	Great