AbstractVariations in evapotranspiration and their sensitivity to controlling variables are pivotal for comprehending water balance dynamics and climate change, particularly in high‐altitude regions such as the Qilian mountains. Environmental shifts are bound to disrupt local water cycles and balance, with significant implications for these alpine areas. To enhance our understanding of evapotranspiration variability across different altitudes within the Qilian Mountains' high‐elevation region and to assess the model's adaptability and responsiveness to environmental factors, our study involved measuring actual evapotranspiration at three distinct elevations. This was achieved using meteorological stations and continuous data from a weighing‐type microlysimeter at the Shaliu River basin's gradients of 3797, 4250 and 4303 m, spanning the growing seasons from June 2020 to October 2022. We utilized 10 models to calculate the value of reference evapotranspiration, which were then matched against actual evapotranspiration data to identify the most appropriate model. Our research found that across the three elevation gradients, the daily average evapotranspiration were 3.663, 3.845 and 4.317 mm day−1, respectively. Across the three elevations, with consistent intra‐annual fluctuations. Notably, August experienced the highest monthly evapotranspiration at 4.750 mm day−1, and reach peak at 10:00 and 15:00 on the three elevation gradients. The results from the simulation of the 10 models indicate that the Dalton model is more suitable for our study area compared with the other models, showing the best R2, root mean square error and percentage error values. Partial least squares regression analysis, coupled with an enhanced regression tree model, identified precipitation as the most critical factor, with a variable importance in projection score of 2.079, contributing 52.6% to evapotranspiration. Collectively, precipitation were identified as key factors influencing evapotranspiration variability within our research area. Our study's insights are valuable for anticipating the impacts of future climate change. This conclusion is instrumental for refining water budget projections in Alpine regions under climate change scenarios.