Assessment of 40 Empirical Models for Estimating Reference Evapotranspiration under the Three Major Climate Zones of Iraq

Accurate reference evapotranspiration (${\mathrm{ET}}_o$) estimation is crucial for water irrigation management and sustainable agriculture planning. The difficulty in obtaining several data requirements for employing the recommended Food and Agriculture Organization Penman-Monteith method (FAO-PM) for reliable estimation of ${\mathrm{ET}}_o$ has led to the development of many empirical models. This is particularly crucial for Iraq, located in West Asia (29°15′00″–38°15′00″ N; 38°45′00″–48°45′00″ E), where meteorological data are often limited or missing. The objectives of the present study were to assess the performance of 40 ${\mathrm{ET}}_o$ empirical models (13 radiation-based, 13 mass-transfer-based, and 14 temperature-based) against the FAO-PM model and identify alternative models with the minimal available data in three major climatic zones of Iraq: the Mediterranean climate (MCZ), semiarid (SCZ), and arid desert (ACZ). The recent ERA5 data set was adopted. The results indicate that (1) the Rohwer mass-transfer method is the best for estimating ${\mathrm{ET}}_o$ for two-thirds of Iraq with a mean correlation coefficient ($R^2$) of 0.97, mean Kling-Gupta efficiency (KGE) of 0.84, mean percent bias (PBIAS) of $-8.92\%$, mean Nash-Sutcliffe efficiency coefficient (NSE) of 0.92, and root mean square error (RMSE)-observations standard deviation ratio (RSR) of 0.27, followed by the Penman ($R^2=0.90$, $\mathrm{KGE}=0.75$, $\mathrm{NSE}=0.77$, $\mathrm{RSR}=0.46$, and $\mathrm{PBIAS}=6.36\%$) and Caprio ($R^2=0.90$, $\mathrm{KGE}=0.66$, $\mathrm{NSE}=0.54$, $\mathrm{RSR}=0.58$, and $\mathrm{PBIAS}=24.64\%$) models; (2) Caprio is the best radiation-based model for estimating ${\mathrm{ET}}_o$, mainly in the ACZ, whereas Kharrufa is the best temperature-based model for estimating ${\mathrm{ET}}_o$, primarily in the SCZ and ACZ. Overall, the mass-transfer-based models performed better than other-based models for ${\mathrm{ET}}_o$ estimation. The outcomes of this study provide a scientific reference for accurate ${\mathrm{ET}}_o$ estimation using empirical models under limited data sets, which is valuable for irrigation management in Iraq.

Accurately estimating ${\mathrm{ET}}_o$ is vital for effective water irrigation management and sustainable agriculture planning. However, the recommended method for estimating ${\mathrm{ET}}_o$, the FAO-PM method, requires various data inputs that may not always be readily available, especially in regions like Iraq. Therefore, this study assessed the performance of 40 empirical ${\mathrm{ET}}_o$ models, categorized into radiation-based, mass-transfer-based, and temperature-based models, against the FAO-PM model in three major climatic zones of Iraq: the Mediterranean climate, the semiarid region, and the arid desert. The study found that the Rohwer mass-transfer method showed the best performance in estimating ${\mathrm{ET}}_o$ for two-thirds of Iraq. The Penman and Caprio models also performed well in estimating ${\mathrm{ET}}_o$ in specific areas. The study revealed that the choice of the ${\mathrm{ET}}_o$ model varied depending on the climatic zone. The Caprio model performed best for radiation-based estimation in the arid desert, whereas the Kharrufa model was most effective for temperature-based estimation in the semiarid region and arid desert. Overall, the mass-transfer-based models outperformed other types of models in ${\mathrm{ET}}_o$ estimation.