The FAO56 Penman–Monteith model (FAO56-PM) is widely used for estimating reference crop evapotranspiration (ET₀). However, key variables such as shortwave radiation (R_s) and net longwave radiation (R_ln) are often unavailable at most weather stations. While previous studies have focused on calibrating R_s, the influence of large R_ln, 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 R_s and R_ln to accurately calculate ET₀. The findings reveal that the average daily R_ln 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 R_ln offsetting underestimated net shortwave radiation (R_sn). Merely calibrating R_s does not improve ET₀ accuracy but may exacerbate errors. The Liu-S was the empirical model for R_s estimation calibrated by parameterization over the Tibetan Plateau and the Allen-LC was the empirical model for R_ln 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.

While highland barley on the Tibetan Plateau is adversely affected by water stress during its growth period, precipitation enhancement could potentially mitigate this issue. Accurate assessment of the benefits obtained through precipitation enhancement is crucial for local governments to develop policies for sustainable agriculture. To quantify these benefits, the WOFOST model was employed to evaluate the effects under four different precipitation enhancement scenarios. The model demonstrated strong performance, with a Nash–Sutcliffe Efficiency (NSE) of 0.93 and a root mean square error (RMSE) of 3.66. Using the calibrated WOFOST model, yield increases were simulated under three meteorological drought conditions classified by the Standardized Precipitation Evapotranspiration Index (SPEI). The results showed that yield increases were minimal during years with less rainfall, primarily due to a lower leaf area index under extreme meteorological drought conditions. Additionally, the impact of precipitation enhancement on yield increases was nonlinear. An enhancement of 5% had negligible effects, while enhancements greater than 10% led to significant increases. Specifically, precipitation enhancement during the reproductive stage resulted in regional yield increases of 170.7, 325.5, 465.9, and 580.5 kg/ha for enhancements of 5%, 10%, 15%, and 20%, respectively, surpassing yield increases from enhancements during the vegetative stage. This greater yield increase is attributed to highland barley’s sensitivity to water stress at critical growth stages and the unique climate conditions of the Tibetan Plateau. For Longzi—the largest base for highland barley production, with a planting area of 3440 ha in 2024—a 10% enhancement at the reproductive stage could yield an economic benefit of CNY 9.8 million. Under climate change scenarios, the decreasing trends in highland barley yields could be effectively offset by precipitation enhancement, highlighting the applicability of precipitation enhancement as an effective tool for mitigating climate change in Tibet. Future studies should integrate crop models with weather numerical models to better address uncertainties.

Reference crop evapotranspiration (ET₀) is crucial for water management. Although the FAO56-PM method is widely used to estimate ET₀, its input variables of solar radiation (R_s) and net longwave radiation (R_nl) are not readily available. Currently, mere calibration of the formula for R_s is assumed to be effective in improving FAO56-PM’s performance. To test this hypothesis, all input variables for FAO56-PM were measured in Lhasa, Linzhi, and Bange over the Tibetan Plateau (TP) to assess how different calculation methods affect ET₀ estimates. Compared to the original FAO56-PM, calibration of both R_s and R_nl formulas yielded the best model performance. Mere calibration of the formula for R_nl notably improved ET₀ estimation accuracy, while mere calibration of the formula for R_s reduced its accuracy. The general calibration model was slightly less effective than calibration of both R_s and R_nl formulas but obviously outperformed the original FAO56-PM. This model showed that ET₀ increased from east to west, ranging from 569.4 mm/year to 1118.5 mm/year. Trend analysis indicated rapid increases in ET₀ in the eastern region and significant decreases in the western region of the TP over recent decades. The findings are useful for the regional application of FAO56-PM to achieve sustainable development in Tibet.