Wetland evapotranspiration (ET), which involves the land–atmosphere exchange of energy and water, is dynamic and affects the spatiotemporal distribution of water resources. However, due to the variability and complexity of wetlands, accurate estimation of patch-scale ET and its spatial variability remain insufficiently characterized. To overcome this challenge, an advanced unmanned aerial vehicle (UAV) technology was developed by combining the three-temperature (3T) model, which is robust to estimate transpiration and its spatial variability with UAV-based thermal infrared remote sensing, and Penman equation, which is commonly used to estimate open water evaporation. The combined approach was verified using the Bowen ratio system over a subalpine wetland. The results show that the proposed method is simple and applicable for estimating wetland ET and its spatial variability, with a determination coefficient (R²) of 0.93, mean absolute percentage error (MAPE) of 7.90%, root mean squared error (RMSE) of 0.05 mm h⁻¹, and Nash-Sutcliffe efficiency (NSE) of 0.93. It depicts a large spatial variability in wetland ET with respect to surface vegetation characteristics, water regimes, meteorological factors, and larger transpiration rates than open water evaporation. With its limited inputs and no calibration requirements, the proposed method is concluded to be simple and to easily reveal the high temporal and spatial resolution characteristics of patch-scale ET and its components.

湿地蒸散 (ET) 涉及陆地-大气的能量和水交换，是动态的，影响水资源的时空分布。然而，由于湿地的可变性和复杂性，对斑块尺度 ET 及其空间变异性的准确估计仍未得到充分表征。为了克服这一挑战，通过结合三温度（3T）模型开发了一种先进的无人驾驶飞行器（UAV）技术，该模型对估计蒸腾及其空间变化具有鲁棒性与基于无人机的热红外遥感和Penman方程，通常用于估计开放水蒸发。使用 Bowen 比率系统对亚高山湿地进行了验证。² ) 为 0.93，平均绝对百分比误差 (MAPE) 为 7.90%，均方根误差 (RMSE) 为 0.05 mm h ^-1，Nash-Sutcliffe 效率 (NSE) 为 0.93。它描述了湿地 ET 在地表植被特征、水情、气象因素以及比开阔水域蒸发更大的蒸腾率方面的巨大空间变异性。由于其有限的输入和没有校准要求，所提出的方法被认为是简单的并且很容易揭示补丁尺度 ET 及其组件的高时间和空间分辨率特征。