## 1 Introduction
Meanwhile, remote-sensing-derived ET can also provide a relatively higher temporal resolution at daily or even shorter time intervals. At present, a good number of remote-sensing-derived ET products are available at global scales, such as the water balance (WB) ET product (0.5 \({}^{\circ}\)) developed by [PERSON] [22], the Global Land Evaporation Amsterdam Model (GLEAM) (0.25\({}^{\circ}\)) product [23; 24], the ET product developed by [PERSON] and [PERSON] (2017) which derived from remotely sensed land surface temperature (0.05\({}^{\circ}\) and 0.25\({}^{\circ}\)) [6], the Penman-Monteith-Leuning ET product(PML) (0.5\({}^{\circ}\)) [25], the Moderate-resolution Imaging Spectroradiometer global terrestrial evapotranspiration product (MOD16) (500 m) [11; 26], the ET product based on the Penman-Monteith-Leuning equation version 2 (PML-V2) (500 m) [7; 9], the ET product based on the Breathing Earth System Simulator (BESS) (1 km) [27], the ET product of the Global LAnd Surface Satellite (GLASS) (1 km) [28], etc. Among these remote sensing ET products, quite a few can provide a relatively high spatial and temporal resolution, such as MOD16, PML-V2, BESS, and GLASS. Although these remote-sensing-derived ET products were all globally validated by their developers, they are still subject to further assessment before their application in a given region owing to several reasons [29; 30]. Firstly, flux sites used in global validation are limited. For example, the number of flux sites used in the global validation of BESS, MOD16, PML-V2, and GLASS is 33, 46, 95, and 120, respectively. Secondly, it was not feasible to focus on a certain region during the global validation of these actual ET products. Studies have been conducted extensively to compare and assess different ET products at regional and local scales [31; 32; 33]. Nevertheless, there is a lack of consistency in the performance of ET products across different geographic regions [34; 35]. For example, [PERSON] et al. [36] compared the performances of MOD16, GLDAS ET and GLEAM in East and Southeast Asia, and found that the deviation of ET products is about 1.5-5.5 mm/8-day, and GLDAS shows lower uncertainties. [PERSON] et al. [37] assessed ET products from Australia's Commonwealth Scientific and Industrial Research Organization (CSIRO), GLDAS, TerraClimate and MOD16 over the Murray-Darling Basin in Australia, and found that the ET product from CSIRO performs best in this area. [PERSON] et al. [37] also found that MOD16 underestimates ET at 138.52 mm/year, especially in some arid areas with sparse vegetation. [PERSON] et al. [29] compared five ET products derived from different methods in the Amazon River Basin during 1982-2011, and found that a machine-learning-derived ET product records the best performance at both site level and basin scale. [PERSON] et al. [30] compared the accuracy of eight ET products (including MOD16, PML-V2 and BESS) in the Yellow River Basin and found that the Simplified Surface Energy Balance (SSEBop) model, after regional optimization, is most consistent with water balance evapotranspiration. MDO16 and SEB-based ET products were found to record a poor performance at the Murray-Darling Basin and in Northern China compared with global scales [37; 38]. Therefore, the inconsistent performances of global actual ET products necessitate a comprehensive assessment before being applied at local or regional scales. Eddy covariance observation has been recognized as an effective way to evaluate actual ET products [4; 29; 36; 39]. It can directly observe latent heat and sensible heat simultaneously, which other measurements such as a scintillometer and Bowen ratio system cannot offer. Although site flux observations can provide direct validation, they cannot entirely be relied upon owing to the uncertainties brought by complex data processing algorithms, and the mismatch between footprint and estimated pixel values [39; 40; 41].