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Evaluation of Some Existing Empirical and Semi-Empirical Net Radiation Models for Estimation of Daily ET0

A. A. Sabziparvar 1 and R. Mirgaloybayat 2
1. Faculty of Agriculture, Bu-Ali Sina University, Hamedan 65178, Iran
2. Bu-Ali Sina University, Hamedan 65178, Iran
Abstarct—Net radiation (Rn) is one of the effective parameters in predicting reference evapotranspiration (ET0) rate. In this research, the accuracy of some empirical and semi-empirical Rn models is compared against FAO 56 recommended net radiation model (hereafter referred as FAO 56) in different climates of Iran. Daily reference evapotranspiration was calculated by Penman-Monteith-FAO 56 standard model during a 28-year period (1980-2007). For estimating daily net radiation, various net radiation models (FAO 56, Wright, Basic Regression, Linacre, Berlind, Irmak and Monteith) were applied. The model evaluations were implemented for four climate types. For warm-arid and cold-arid climates, Basic Regression Model (BRM) performed the best estimates in comparison with the FAO 56. In cold semi-arid and warm semi-arid regions, Wright model presented the nearest results to the reference model (FAO 56), but for warm humid, using Irmak net radiation model was the best choice. In regional averages (all climates), linear BRM net radiation model performed the superior performance in estimating the daily ET0. Results showed that for 75 percent of the study sites, the linear Rn models can be reliable candidates instead of non-linear Rn models such as net radiation as used in FAO 56 model. For some sites with low altitude and high relative humidity (e.g. coastal sites) Irmak model showed the minimum deviations from the reference FAO 56 model. These results can be useful for the sites where all weather parameters are not available.

Index Terms—net radiation, Reference crop evapotranspiration, penman monteith FAO 56 model, different climates, Iran

Cite: A. A. Sabziparvar and R. Mirgaloybayat, "Evaluation of Some Existing Empirical and Semi-Empirical Net Radiation Models for Estimation of Daily ET0," Journal of Advanced Agricultural Technologies, Vol. 2, No. 1, pp. 46-49, June 2015. Doi: 10.12720/joaat.2.1.46-49
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