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

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

doi:10.1590/s1678-3921.pab2019.v54.00226

Pesq. agropec. bras.

2019

DOI: 10.1590/s1678-3921.pab2019.v54.00226

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

Lucas Borges Ferreira

Fernando França da Cunha

Gilberto Chohaku Sediyama

et al.

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 ca… Show more

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2024

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Predicting the spatial distribution of water applied by subsurface drip in clay soil

Rocha,

Miranda,

Silva

et al. 2024

Rev. bras. eng. agríc. ambient.

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In subsurface drip irrigation systems, knowledge of the three-dimensional advancement of water in the soil is essential for selecting emitter spacing and installation depth. This research aimed to develop and test different mathematical models to estimate water distribution in the soil under subsurface drip irrigation. The experiment was set up in a completely randomized design with four replicates. The experimental arrangement was of split-plot in time, with different dripper installation depths in the plots (0, 5, 10, 15, 20, 25, and 30 cm) and in the subplots irrigation application times (0, 60, 120, 180, and 240 min). Three models (SLIDE 6.0, polynomial regression, and SPSS 2.0) were constructed to estimate the water distribution in the soil profile. All models showed statistical indexes within acceptable ranges. In comparison, the model generated in the numerical software SLIDE 6.0 was the one that presented the best performance, followed by SPSS 2.0 and polynomial regression. The generated models were efficient and simple, producing good results in predicting the water distribution in the soil profile under the studied conditions.

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Predicting the spatial distribution of water applied by subsurface drip in clay soil

Rocha,

Miranda,

Silva

et al. 2024

Rev. bras. eng. agríc. ambient.

View full text Add to dashboard Cite

show abstract

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

Cited by 1 publication

References 5 publications

Predicting the spatial distribution of water applied by subsurface drip in clay soil

Predicting the spatial distribution of water applied by subsurface drip in clay soil

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