Evapotranspiration (ET) is a vital process involving the transfer of water from the Earth's surface to the atmosphere through soil evaporation and plant transpiration. Accurate estimation of ET is important for a variety of applications, including irrigation management and water resource planning. The two-source energy balance (TSEB) model is a commonly used method for estimating ET using remotely sensed data. This study used the TSEB model and high-resolution unmanned aerial vehicle (UAV) imagery to estimate sorghum ET under four different irrigation regimes over two growing seasons in 2020 and 2021. The study also validated net radiation (Rn) flux through hand-held radiometer measurements and compared the estimated ET with a soil water balance model. The study outcomes revealed that that the TSEB model capably estimated Rn values, aligning well with ground-based Rn measurements for all irrigation treatments (RMSE = 32.9–39.8 W m⁻² and MAE = 28.1–35.2 W m⁻²). However, the TSEB model demonstrated robust performance in estimating ET for fully irrigated conditions (S1), while its performance diminished with increasing water stress (S2, S3, and S4). The R₂, RMSE, and MAE values range from 0.64 to 0.06, 10.94 to 17.04 mm, and 7.09 to 11.43 mm, respectively, across the four irrigation treatments over a 10-day span. These findings not only suggest the potential of UAVs for ET mapping at high-resolution over large areas under various water stress conditions, but also highlight the need for further research on ET estimation under water stress conditions.

蒸散（ET）是一个重要的过程，涉及通过土壤蒸发和植物蒸腾作用将水从地球表面转移到大气中。准确估算蒸散对于各种应用都很重要，包括灌溉管理和水资源规划。双源能量平衡（TSEB）模型是利用遥感数据估算蒸散的常用方法。本研究使用 TSEB 模型和高分辨率无人机 (UAV) 图像来估算 2020 年和 2021 年两个生长季四种不同灌溉方式下的高粱蒸散量。该研究还通过手持式辐射计验证了净辐射 (Rn) 通量测量并将估计的 ET 与土壤水平衡模型进行比较。研究结果表明，TSEB 模型能够估算 Rn 值，与所有灌溉处理的地面 Rn 测量结果吻合良好（RMSE = 32.9–39.8 W m ⁻²和 MAE = 28.1–35.2 W m ⁻²）。然而，TSEB 模型在完全灌溉条件下估算蒸散量 (S1) 方面表现出稳健的性能，而其性能随着水分胁迫的增加而下降（S2、S3 和 S4）。10 天跨度内四种灌溉处理的 R 2 、RMSE 和 MAE 值范围分别为 0.64 至 0.06、10.94 至 17.04 mm 和 7.09 至 11.43 mm _。这些发现不仅表明无人机在各种水分胁迫条件下大面积高分辨率蒸散测绘的潜力，而且还强调了在水分胁迫条件下进一步研究蒸散估计的必要性。