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

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.

A daily and 500 m coupled evapotranspiration and gross primary production product across China during 2000–2020

“…10a). This result is overall consistent with previous studies (Yin et al, 2021;Cheng et al, 2021;Ma et al, 2019a), which also the country-wide averaged annual ET over China range from 359 ~ 482 mm yr -1 based on a variety of models including the machine learning, RS, and land surface models. Furthermore, previous studies by Ren et al (2015) and Wang et al (2012a) show that the long-term mean precipitation and runoff in China are about 720 mm yr -1 and 280 mm yr -1 , respectively.…”

“…In this paper, the water storage change (in Equation 7) from GRACE was included for purpose of reducing the uncertainties in estimating annual ETwb. Those studies not using TWSC in ET wb may not explain the decreasing groundwater such as in the Hai River Basin due to the human water extraction, which is not conducive to the credibility of the verification results (Cheng et al, 2021). In addition, the precision of its input data also affects the reliability of ET wb (Mao and Wang, 2017).…”

“…Besides, systematic bias in device, the loss from the contribution of low-frequency eddies to energy transmission and the ability to capture larger eddies and the secondary circulations, could cause the energy-imbalance problem (Liu et al, 2011). Hence, there are usually two schemes to deal with the energy non-closure issue for EC users, that is, to perform energy closure correction (Cheng et al, 2021), or to maintain the original four-component data including latent heat (LE), sensible heat (H), soil heat flux (G) and net radiation (R n ) Ma and Zhang, 2022). We chose the second method in this study, considering that (i) forcing energy closure will introduce new errors artificially, and (ii)…”

“…In fact, we artificially construct multiple site samples in the above PFTs sites, utilizing the characteristics of the long time series of these sites. Nevertheless, the terrestrial biome of the sole flux site maybe not typical in other climate zones for the same PFT (Cheng et al, 2021). Therefore, more flux sites for the same PFT are necessary to calibrate the model.…”

Evapotranspiration Estimation Using Remote Sensing Technology Based on a SEBAL Model in the Upper Reaches of the Huaihe River Basin

“…A number of studies have evaluated the performance of the SEBAL model in estimating the ET under different climate conditions, and results indicate that SEBAL models have shown reasonable accuracy for predicting ET in different parts of the world. For example, Cheng et al [70] used flux tower observational data to assess the performance of the SEBAL ET and found SEBAL underestimated ET in China, with an MBE of −0.15 mm/d.…”