Optimal Methods for Estimating Shortwave and Longwave Radiation to Accurately Calculate Reference Crop Evapotranspiration in the High-Altitude of Central Tibet

The FAO56 Penman–Monteith model (FAO56-PM) is widely used for estimating reference crop evapotranspiration (ET0). However, key variables such as shortwave radiation (Rs) and net longwave radiation (Rln) are often unavailable at most weather stations. While previous studies have focused on calibrating Rs, the influence of large Rln, particularly in high-altitude regions with thin air, remains unexplored. This study investigates this issue by using observed data from Bange in central Tibet to identify the optimal methods for estimating Rs and Rln to accurately calculate ET0. The findings reveal that the average daily Rln was 8.172 MJ m−2 d−1 at Bange, much larger than that at the same latitude. The original FAO56-PM model may produce seemingly accurate ET0 estimates due to compensating errors: underestimated Rln offsetting underestimated net shortwave radiation (Rsn). Merely calibrating Rs does not improve ET0 accuracy but may exacerbate errors. The Liu-S was the empirical model for Rs estimation calibrated by parameterization over the Tibetan Plateau and the Allen-LC was the empirical model for Rln estimation calibrated by local measurements in central Tibet. The combination of the Liu-S and Allen-LC methods showed much-improved performance in ET0 estimation, yielding a high Nash–Sutcliffe Efficiency (NSE) of 0.889 and a low relative error of −5.7%. This strategy is indicated as optimal for ET0 estimation in central Tibet. Trend analysis based on this optimal strategy indicates significant increases in ET0 in central Tibet from 2000 to 2020, with projections suggesting a continued rise through 2100 under climate change scenarios, though with increasing uncertainty over time. However, the rapidly increasing trends in precipitation will lead to decreasing trends in agricultural water use for highland parley production in central Tibet under climate change scenarios. The findings in this study provide critical information for irrigation planning to achieve sustainable agricultural production over the Tibetan Plateau.