## 5 Conclusions  
We evaluated the reliability of six satellite-based LE products in the vegetation dominated Haihe River basin of North China against ground-measured LE data collected from six eddy covariance flux tower sites at local scale and water balance method derived ET at basin scale. These six LE products consist of the GLASS LE product, FLUXCOM LE product, PML_V2 LE product, GLEAM LE product, BESS LE product, and MODIS LE product. Our results indicated that all six satellite-based LE products were able to simulate the seasonal cycle of LE. At site scale, GLASS LE product provided the highest R\({}^{2}\) (0.58, \(p\) < 0.01) and the lowest RMSE (28.2 W/m\({}^{2}\)), followed by FLUXCOM, PML, GLEAM, BESS, and MODIS LE products. At basin scale, the LE estimates from GLASS product showed comparable accuracy (R\({}^{2}\) = 0.79, RMSE = 18.8 mm) with other LE products. Among them, the BESS product had the highest R\({}^{2}\) value of 0.85 (\(p\) < 0.01) and the smallest RMSE value of 16.1 mm, and FLUXCOM presents the lowest R\({}^{2}\) value of 0.76 and the largest RMSE value of 20.1 mm against WBET. The Spatial distribution of annual averaged terrestrial LE (2013-2015) illustrated that LE showed large spatial variability over the whole are and presented strong seasonality according to the climate conditions. Moreover, there is similar spatiotemporal variability of estimated terrestrial LE from the six LE products. Errors in satellite-based LE products and uncertainties in reference data and evaluation methods were also discussed. Overall, this study further demonstrates that GLASS LE product with 0.05 degree is promising dataset to evaluate regional water budget. Conceptualization, Y.L. and X.S. ; methodology, Y.Y. ; validation, H.C., L.Z. and L.W. ; formal analysis, L.W. and K.S. ; investigation, L.W. and K.S. ; resources, L.W. ; data curation, L.W. ; writing--original draft preparation, J.N., J.Y., R.Y., L.L., X.G. and Z.X. ; writing--review and editing, Y.Y., H.C., L.Z., L.W. and K.S. ; visualization, L.W. ; supervision, Y.Y. ; project administration, Y.L. and Y.Y. ; funding acquisition, Y.L., X.S. and Y.Y. All authors have read and agreed to the published version of the manuscript. This research was funded by the National Natural Science Foundation of China (Grant No. 41671331) and the National Key Research and Development Program of China (Grant No. 2016 YFA0600103). This work was also supported by China Scholarship Council under Grant 201806040217 and Natural Resources Department of ITC, University of Twente, Netherlands. Not applicable. Data Availability Statement: Data available on request. The authors thank [PERSON], [PERSON], and [PERSON] from Beijing Normal University, China, and [PERSON], and [PERSON] from Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China for providing ground-measured data. Acknowledgement for the data support from \"National Earth System Science Data Center, National Science & Technology Infrastructure of China. ([[http://www.geodata.cn](http://www.geodata.cn)]([http://www.geodata.cn](http://www.geodata.cn)) accessed on 11 June 2021)\". Acknowledgement also for the data support from \"National Tibetan Plateau Data Center ([[http://data.tpdc.ac.cn/zh-hans/data](http://data.tpdc.ac.cn/zh-hans/data)]([http://data.tpdc.ac.cn/zh-hans/data](http://data.tpdc.ac.cn/zh-hans/data)) accessed on 11 June 2021)\". GLASS data can be obtained online ([[http://www.glass.umd.edu/](http://www.glass.umd.edu/)]([http://www.glass.umd.edu/](http://www.glass.umd.edu/)) accessed on 11 June 2021). The FLUXCOM datasets are available online ([[https://www.fluxcom.org/](https://www.fluxcom.org/)]([https://www.fluxcom.org/](https://www.fluxcom.org/)) accessed on 11 June 2021). The PML-V2 LE product was obtained from the National Tibetan Plateau Data Center (TPDC) ([[https://data.tpdc.ac.cn/zh-hans/accessed](https://data.tpdc.ac.cn/zh-hans/accessed)]([https://data.tpdc.ac.cn/zh-hans/accessed](https://data.tpdc.ac.cn/zh-hans/accessed)) on 11 June 2021).