Evaluation of FAO Penman–Monteith and alternative methods for estimating reference evapotranspiration with missing data in Southern Ontario, Canada

Grass reference evapotranspiration (ETo) is an important agrometeorological parameter for climatological and hydrological studies, as well as for irrigation planning and management. There are several methods to estimate ETo, but their performance in different environments is diverse, since all of them have some empirical background. The FAO Penman–Monteith (FAO PM) method has been considered as a universal standard to estimate ETo for more than a decade. This method considers many parameters related to the evapotranspiration process; net radiation (Rn), air temperature (T), vapor pressure deficit (Δe), and wind speed (U); and has presented very good results when compared to data from lysimeters populated with short grass or alfalfa. In some conditions, the use of the FAO PM method is restricted by the lack of input variables. In these cases, when data are missing, the option is to calculate ETo by the FAO PM method using estimated input variables, as recommended by FAO Irrigation and Drainage Paper 56. Based on that, the objective of this study was to evaluate the performance of the FAO PM method to estimate ETo when Rn, Δe, and U data are missing, in Southern Ontario, Canada. Other alternative methods were also tested for the region: Priestley–Taylor, Hargreaves, and Thornthwaite. Data from 12 locations across Southern Ontario, Canada, were used to compare ETo estimated by the FAO PM method with a complete data set and with missing data. The alternative ETo equations were also tested and calibrated for each location. When relative humidity (RH) and U data were missing, the FAO PM method was still a very good option for estimating ETo for Southern Ontario, with RMSE smaller than 0.53mmday−1. For these cases, U data were replaced by the normal values for the region and Δe was estimated from temperature data. The Priestley–Taylor method was also a good option for estimating ETo when U and Δe data were missing, mainly when calibrated locally (RMSE=0.40mmday−1). When Rn was missing, the FAO PM method was not good enough for estimating ETo, with RMSE increasing to 0.79mmday−1. When only T data were available, adjusted Hargreaves and modified Thornthwaite methods were better options to estimate ETo than the FAO PM method, since RMSEs from these methods, respectively 0.79 and 0.83mmday−1, were significantly smaller than that obtained by FAO PM (RMSE=1.12mmday−1).