2018
DOI: 10.4236/as.2018.910094
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Modifying Hargreaves-Samani Equation for Estimating Reference Evapotranspiration in Dryland Regions of Amudarya River Basin

Abstract: Reference evapotranspiration (ETo) is a key factor in determining the amount of water needed for crops, which is crucial to correct irrigation planning. FAO Penman-Monteith (EToPM) is among the most popular method to estimate ETo. Apparently sometimes it is difficult to compute ETo using Penman-Monteith due to challenges on data availability. FAO Penman-Monteith method requires many parameters (solar radiation, air temperature, wind speed and humidity), while Hargreaves-Samani method calculates ETo based on ai… Show more

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Cited by 6 publications
(2 citation statements)
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“…Regarding this issue, Ali Ghorbani et al ( 2018 ) stated that the main disadvantage of empirical models is the lack of consistency, as their accuracy is highly dependent on local calibrations and climatic conditions. Based on the studies of Cobaner et al ( 2017 ) and Gafurov et al ( 2018 ), the simple empirical models lack the universal approach required for ET forecasting. Citakoglu et al ( 2014 ) compared the performance of ANN and ANFIS in estimating the ET values in Turkey.…”
Section: Introductionmentioning
confidence: 99%
“…Regarding this issue, Ali Ghorbani et al ( 2018 ) stated that the main disadvantage of empirical models is the lack of consistency, as their accuracy is highly dependent on local calibrations and climatic conditions. Based on the studies of Cobaner et al ( 2017 ) and Gafurov et al ( 2018 ), the simple empirical models lack the universal approach required for ET forecasting. Citakoglu et al ( 2014 ) compared the performance of ANN and ANFIS in estimating the ET values in Turkey.…”
Section: Introductionmentioning
confidence: 99%
“…While the PM-FAO56 equation shows relatively stable results, the equations for empirical models based on temperature, solar radiation and mass transfer use fewer climatic parameters in the calculation of ETref. Therefore, the development and calibration of empirical model equations in different climates can be more effective for agricultural and hydrological projects where only a few climatic variables are available (Heydari and Heydari, 2014;Gafurov et al 2018).…”
Section: Introductionmentioning
confidence: 99%