Long time series of daily evapotranspiration in China based on the SEBAL model and multisource images and validation

Abstract. Satellite observations of evapotranspiration (ET) have been widely used for water resources management in China. An accurate ET product with a high spatiotemporal resolution is required research on drought stress and management. However, such currently lacking. Moreover, the performances different estimation algorithms China not clearly studied, especially under environmental conditions. Therefore, aims this study were as follows: (1) to use multisource images generate long-time-series (2001–2018) daily spatial 1 km × based Surface Energy Balance Algorithm Land (SEBAL); (2) comprehensively evaluate performance SEBAL using flux observational data hydrological data; (3) compare MOD16 at point scale basin conditions At scale, both models performed best forest cover, subtropical zones, hilly terrain, or summer, respectively, better most In general, accuracy (rRMSE = 44.91 %) was slightly higher than that 48.72 %). basin-scale validation, point-scale obtaining results superior 13.57 32.84 Additionally, showed negative bias, bias being ET. daily-scale root mean square error (RMSE) 0.92 mm d?1 an r value 0.79. can be qualitative analysis quantitative analyses regional The freely available https://doi.org/10.5281/zenodo.4243988 https://doi.org/10.5281/zenodo.4896147 (Cheng, 2020a, b). provide reference application remotely sensed products improvement satellite observation algorithms.