## 1 Introduction  
In addition to the terrestrial carbon cycle, the hydrological cycle is also critical for the functionality and sustainability of terrestrial ecosystems [1]. As the principle component of terrestrial hydrology, evapotranspiration (ET), which is composed of evaporation and transpiration, is affected by both biophysical and environmental processes at the interface of soils, vegetation, and the atmosphere, thereby linking hydrological, energy, and carbon processes [2; 3; 4]. Globally, ET returns approximately 60% of land-based precipitation to the atmosphere [5; 6] and consumesmore than 50% of the solar radiation absorbed by the land's surface [7]. Within the atmospheric surface layer, ET affects environmental conditions through the turbulent exchange of momentum, heat, and moisture [8; 9; 10]. In return, environmental variation controls diverse physical and physiological processes within terrestrial ecosystems and, finally, alters the mass and energy exchange of land-atmosphere interactions, leading to direct climate impacts [3; 11; 12; 13]. Considering the importance of ET, the characterization of spatiotemporal variability is critical for better understanding interactions between the land and the atmosphere, the sustainable management of water resources, and the response of terrestrial ecosystems under climate change [14; 15; 16; 17; 18]. As one of the most important parts of the terrestrial ecosystem, global forests account for approximately 45% of total terrestrial ET [5]. Therefore, forest ET is considered to be an important indicator of water availability in natural ecosystems, as well as for human needs [19]. The routine monitoring of ET from forests in the headwaters of basins is particularly critical because these headwaters often provide water to ecosystems downstream. Knowledge of the dynamics of the headwaters is, therefore, often relevant for the sustainable development of an entire basin. The Heihe River Basin (HRB), located in the cold and arid environment of northwest China, is entirely dependent on headwaters. Water conflicts in this area are severe and information regarding forest processes is urgently needed. _In situ_ measurements using weighing lysimeters, Bowen ratios, sap flow meters, eddy covariance (EC), and scintillometers are considered reliable for quantifying ET at individual sites or for small footprints [4; 20; 21]. However, these types of measurements are unsuitable at large scales. An alternative approach is to use remote sensing information for characterizing spatiotemporal land surface information over large areas. With the incorporation of meteorological and other auxiliary data, remote sensing-based methods can be used to map various large-scale patterns of ET in a globally consistent and economically feasible manner by linking surface parameters and energy balance with ET [22; 23; 24; 25]. In general, land surface parameters retrieved using remote sensing data such as the Normalized Difference Vegetation Index (NDVI), the Leaf Area Index (LAI), Albedo, temperature, and emissivity have been used to drive ET models [16; 26]. The following four types of remote sensing-based ET models having been developed in recent decades: (1) surface energy balance models [23; 27; 28; 29]; (2) empirical statistical models [30]; (3) physical models [31; 32]; and (4) water balance models [33; 34]. Although they have been applied over a number of study areas, uncertainties related to the disadvantage of these models and their inputs, and parameterization and scaling schemes still exist [4; 35; 36; 37; 38]. As far as remote sensing techniques are concerned, the availability of measurements and estimations of land surface and atmospheric parameters have increased over time, and the improvement of model performance through the integration of various techniques and data sources has received renewed global interest.