Understanding the impact of land use and land cover change on surface energy and water budgets is increasingly important in the context of climate change research. Eddy covariance (EC) methods are the gold standard for high temporal resolution measurements of water and energy fluxes, but cannot resolve spatial heterogeneity and are limited in scope to the tower footprint (few hundred meter range). Satellite remote sensing methods have excellent coverage, but lack spatial and temporal resolution. Long-range unmanned aerial systems (UAS) can complement these other methods with high spatial resolution over larger areas. Here we use UAS thermography and multispectral data as inputs to two variants of the Two Source Energy Balance Model to accurately map surface energy and water fluxes over a nutrient manipulation experiment in a managed semi-natural oak savanna from peak growing season to senescence. We use energy flux measurements from 6 EC stations to evaluate the performance of our method and achieve good accuracy (RMSD ≈ 60 W m⁻² for latent heat flux). We use the best performing latent heat estimates to produce very high-resolution evapotranspiration (ET) maps, and investigate the drivers of ET change over the transition to the senescence period. We find that nitrogen and nitrogen plus phosphorus treatments lead to significant increases in ET (P < 0.001) for both trees (4 and 6%, respectively) and grass (12 and 9%, respectively) compared to the control. These results highlight that the high sensitivity and spatial and temporal resolution of a UAS system allows the precise estimation of relative water and energy fluxes over heterogeneous vegetation cover.

在气候变化研究的背景下，了解土地利用和土地覆盖变化对地表能量和水收支的影响变得越来越重要。涡度协方差 (EC) 方法是水和能量通量的高时间分辨率测量的黄金标准，但无法解决空间异质性，并且范围仅限于塔占地面积（几百米范围）。卫星遥感方法具有很好的覆盖范围，但缺乏空间和时间分辨率。远程无人机系统 (UAS) 可以在更大区域内以高空间分辨率补充这些其他方法。在这里，我们使用 UAS 热成像和多光谱数据作为双源能量平衡模型的两个变体的输入，以准确映射在管理的半天然橡树稀树草原中从生长旺季到衰老的养分操纵实验中的表面能量和水通量。我们使用来自 6 个 EC 站的能量通量测量值来评估我们方法的性能并获得良好的精度（RMSD ≈ 60 W m^-2用于潜热通量）。我们使用表现最好的潜热估计来生成非常高分辨率的蒸散 (ET) 图，并研究在过渡到衰老期的过程中 ET 变化的驱动因素。我们发现，与对照相比，氮和氮加磷处理导致树木（分别为 4% 和 6%）和草（分别为 12% 和 9%）的 ET（P  < 0.001）显着增加。这些结果突出表明，UAS 系统的高灵敏度和空间和时间分辨率允许精确估计异质植被覆盖的相对水和能量通量。