Abstract

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

Highlights

  • Evapotranspiration (ET) is the process of transferring surface water to the atmosphere, including soil evaporation and vegetation transpiration (Wang and Dickinson, 2012)

  • China can be divided into nine basin regions based on the distribution of water resources (Zhang et al, 2011): the Southwest Basin (SwB), Continental Basin (CB), Pearl River Basin (PRB), Yangtze River Basin (YRB), Southeast Basin (SeB), Haihe River Basin (HRB), Yellow River Basin (YeRB), Huaihe River Basin (HuRB), and Songhua and Liaohe River Basin (SLRB) (Fig. 1)

  • Compared to ETflux, ETSEBAL showed a good performance in China; the two data types showed high consistency, with an r value of 0.79 with 9896 samples

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Summary

Introduction

Evapotranspiration (ET) is the process of transferring surface water to the atmosphere, including soil evaporation and vegetation transpiration (Wang and Dickinson, 2012). This process is a key node linking surface water and energy balance. The methods for the estimation of ET based on point-scale or small-area-scale analysis, such as lysimeters and eddy covariance, cannot meet the requirement of global climate change research and regional water resource management (Li et al, 2018). Remote sensing technology with a high spatiotemporal continuity provides an effective means for regional ET estimation

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