Daily reference crop evapotranspiration in the humid environments of Azores islands using reduced data sets: accuracy of FAO-PM temperature and Hargreaves-Samani methods

• Published in: Theoretical and applied climatology 2018-10, Vol.134 (1-2), p.595-611
• Main Authors: Paredes, P., Fontes, J. C., Azevedo, E. B., Pereira, L. S.
• Format: Article
• Language: English
• Subjects: Accuracy; Aquatic Pollution; Atmospheric Protection/Air Quality Control/Air Pollution; Atmospheric Sciences; Climate science; Climatology; Crop evapotranspiration; Data; Data reduction; Earth and Environmental Science; Earth Sciences; Evapotranspiration; Islands; Linearity; Mathematical models; Methods; Original Paper; Procedures; Solar radiation; Temperature; Vapor pressure; Vapour pressure; Waste Water Technology; Water Management; Water Pollution Control; Weather; Weather stations; Wind speed
• ISSN: 0177-798X; 1434-4483
• DOI: 10.1007/s00704-017-2295-2

Reference crop evapotranspiration (ET o ) estimations using the FAO Penman-Monteith equation (PM-ET o ) require several weather variables that are often not available. Then, ET o may be computed with procedures proposed in FAO56, either using the PM-ET o equation with temperature estimates of actual vapor pressure ( e a ) and solar radiation ( R s ), and default wind speed values ( u 2 ), the PMT method, or using the Hargreaves-Samani equation (HS). The accuracy of estimates of daily e a , R s , and u 2 is provided in a companion paper (Paredes et al. 2017 ) applied to data of 20 locations distributed through eight islands of Azores, thus focusing on humid environments. Both estimation procedures using the PMT method (ET o PMT ) and the HS equation (ET o HS ) were assessed by statistically comparing their results with those obtained for the PM-ET o with data of the same 20 locations. Results show that both approaches provide for accurate ET o estimations, with RMSE for PMT ranging 0.48–0.73 mm day −1 and for HS varying 0.47–0.86 mm day −1 . It was observed that ET o PMT is linearly related with PM-ET o , while non-linearity was observed for ET o HS in weather stations located at high elevation. Impacts of wind were not important for HS but required proper adjustments in the case of PMT. Results show that the PMT approach is more accurate than HS. Moreover, PMT allows the use of observed variables together with estimators of the missing ones, which improves the accuracy of the PMT approach. The preference for the PMT method, fully based upon the PM-ET o equation, is therefore obvious.