The observation of regional evaporative fraction (EF) over a heterogeneous area is crucial to surface energy balance modeling and satellite-based evapotranspiration (ET) validation over complex areas. However, regional EF observations are often lacking or not directly acquired because the sparse distribution and inadequate spatial representativeness of ground measurements cannot represent the region's heterogeneity in landscape and land-surface processes. The UAV-based eddy-covariance (EC) system can be used to observe the regional EF at large areas. UAV-based EC measurements were performed in December 2020 at around 90 m above the ground level over Yancheng coastal wetland, which included 7 flights for comparison with ground EC measurements and 4 flights for investigating the regional EF. The results of comparison showed that the sensible and latent heat fluxes from UAV were consistent with those measured from the ground, with the R² of 0.84, RMSE of 15.7 W/m², bias of 50.7 W/m² for sensible heat flux, and the R² of 0.77, RMSE of 13.1 W/m², bias of -3.67 W/m² for latent heat flux. Then, 53 flux observations were obtained from the 4 regional flights after applying a quality filter. A footprint model in conjunction with a high-resolution land cover map were used to determine the fluxes contribution source areas and to determine the accumulated footprint weight of the various land cover classes within the footprint areas. Thirdly, a multiple linear regression model was used to dis-aggregate the observed fluxes into component land-cover-class-specific fluxes, and to resolve the EF of each land cover class. The dis-aggregation results revealed that cropland had the highest EF (0.69 ± 0.11), followed by Spartina alterniflora (0.3 ± 0.11) and Phragmites australis (0.27 ± 0.09). Lastly, the EF of Phragmites australis was compared with ground measurement and had a relative error of 2.9%, demonstrating that the UAV-based EC system provided a reliable observation of regional EF.

对异质区域的区域蒸发率 (EF) 的观察对于复杂区域的表面能量平衡建模和基于卫星的蒸散 (ET) 验证至关重要。然而，由于地面测量的稀疏分布和空间代表性不足，无法代表该地区在景观和地表过程中的异质性，因此区域 EF 观测往往缺乏或无法直接获得。基于无人机的涡流协方差（EC）系统可用于大面积观测区域 EF。基于无人机的 EC 测量于 2020 年 12 月在盐城沿海湿地的地面以上约 90 m 处进行，其中包括 7 次与地面 EC 测量比较的飞行和 4 次调查区域 EF 的飞行。R ²为 0.84，RMSE为 15.7 W/m ²，显热通量偏差为 50.7 W/m ²，R ²为 0.77，RMSE为 13.1 W/m ²，偏差为 -3.67 W/m ²为潜热通量。然后，在应用质量过滤器后，从 4 个区域航班中获得了 53 个通量观测值。足迹模型结合高分辨率土地覆盖图用于确定通量贡献源区域并确定足迹区域内各种土地覆盖类别的累积足迹权重。第三，使用多元线性回归模型将观测到的通量分解为特定于土地覆盖类别的组分通量，并解析每个土地覆盖类别的 EF。分解结果显示农田的EF最高（0.69±0.11），其次是互花米草（0.3±0.11）和芦苇（0.27±0.09）。最后，芦苇的 EF 与地面测量进行比较，相对误差为 2.9%，表明基于无人机的 EC 系统提供了可靠的区域 EF 观测。