Solar and Net Radiation-Based Equations to Estimate Reference Evapotranspiration in Humid Climates

Abstract

Two equations for estimating grass reference evapotranspiration $\left({\mathrm{ET}}_0\right)$ were derived using the Food and Agriculture Organization Penman–Monteith (FAO56-PM) method as an index. The first equation, solar radiation $\left(R_s\right)$ based, estimates ${\mathrm{ET}}_0$ from incoming $R_s$ and maximum and minimum air temperature, and the second equation, net radiation $\left(R_n\right)$ based, uses $R_n$ and maximum and minimum air temperature. The equations were derived using 15 years (1980–1994) of daily ${\mathrm{ET}}_0$ values estimated from the FAO56-PM method using the measured and carefully screened weather data from near Gainesville, Florida. The performance of the derived equations was evaluated for 6 validation years (1995–2000), including dry and wet years, for the same site and for other humid locations in the Southeast United States. Comparisons of the performance of the derived equations with the other commonly used methods indicated that they estimate ${\mathrm{ET}}_0$ as good or better than those other ${\mathrm{ET}}_0$ methods. The $R_s$- and $R_n$-based equations resulted in the lowest 6 year average standard error of estimate (SEE) of daily ${\mathrm{ET}}_0$ (0.44 and 0.41 mm day⁻¹, respectively). Both equations performed quite well for estimating peak month ${\mathrm{ET}}_0$ and had the lowest 6 year average daily SEE for the peak month ${\mathrm{ET}}_0$ (0.24 mm day⁻¹ for both equations). Estimates for annual total ${\mathrm{ET}}_0$ were very close to those obtained from the FAO56-PM method. The 6 year average ratio of ${\mathrm{ET}}_{0 \mathrm{method}}$ to ${\mathrm{ET}}_{0 \mathrm{FAO}56-\mathrm{PM}}$ were 1.05 and 1.03 for the $R_s$- and $R_n$-based equations, respectively. The derived equations were further evaluated in other humid locations in the Southeast United States, including two locations in coastal regions in Florida, one location in Georgia, and another location in Alabama. The comparisons showed that both equations are likely to provide good estimates of ${\mathrm{ET}}_0$ in humid locations of the Southeast United States. When the required input variables are considered, the Priestley–Taylor (PT) method was the closest method to the second derived equation $(R_n$ based). Therefore, it was necessary to evaluate how the PT method would perform compared to the $R_n$-based equation relative to the FAO56-PM method after it is calibrated locally. Although the performance of the PT method improved slightly after the calibration, its performances for estimating daily and peak month ${\mathrm{ET}}_0$ remained poorer than the $R_n$-based equation in all cases. Considering the limitations associated with the availability and reliability of the climatological data, especially in developing countries, the derived equations presented in this study are suggested as practical methods for estimating ${\mathrm{ET}}_0$ if the standard FAO56-PM equation cannot be used because of the above-mentioned limitations. These equations are recommended over the other commonly used simplified temperature and radiation-based methods evaluated in this study for humid climates in the Southeast United States.