Evaluation of Some Net Radiation Models for Improving Daily Reference Evapotranspiration Estimation in Iran
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Volume 142, Issue 11
Abstract
Net radiation () is one of the effective inputs for controlling soil heat flux, thermal convection, moisture flux exchange, and reference crop evapotranspiration () rate. In this research, the accuracy of some empirical and semiempirical models is examined for different climates of Iran versus the recommended net radiation model as proposed in the Penman–Monteith Food and Agricultural Organization of the United Nations 56 standard (FAO 56) model for the period 1980–2007. For estimating daily net radiation, various net radiation models [Wright, basic regression model (BRM), Linacre, Berliand, Irmak, and Monteith] were examined. Model evaluations were implemented for four climate types. On regional averages, the linear BRM had the superior performance in generating the most accurate daily . Results showed that for 70% of the study sites, the linear models can be reliable candidates instead of sophisticated nonlinear models, which are proposed in the reference FAO 56 model. For some sites, with low altitude and high relative humidity (e.g., coastal humid sites), the Irmak model suggested the minimum deviations from the reference FAO 56 model. Using the best-performing models is recommended for the agricultural sites where comprehensive weather data are not available.
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Acknowledgments
The authors wish to thank Bu-Ali Sina University for its support during the research. The first author would also like to express his gratitude to the IRIMO Data Center for providing the weather data. The authors also thank the meteorological observers for their efforts in measuring and reporting the weather data for the period of study.
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Journal of Irrigation and Drainage Engineering
Volume 142 • Issue 11 • November 2016
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© 2016 American Society of Civil Engineers.
History
Received: Oct 11, 2015
Accepted: Apr 6, 2016
Published online: Jun 27, 2016
Published in print: Nov 1, 2016
Discussion open until: Nov 27, 2016
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