**5. Conclusions**

In this study, the ET was calculated based on the water balance equation in nine exorheic catchments of China. The impacts of ignoring terrestrial water storage changes and di fferent terrestrial water storage changes from GRACE solutions on ET estimates were analyzed. The intercomparison between ETWB and ET estimates from GLEAM, and GLDAS land surface models was also conducted. The comparison was carried out on the monthly and annual scales.

We found that the impact of ignoring terrestrial water storage changes on the estimate of ET is noteworthy. The RMSEs of between monthly mean ETWB and ETPQ range from 6.4–27.2 mm/yr (17.5–45.2% in corresponding mean monthly ET). The annual RMSEs between ETWB and ETPQ in the estimate of ET range from 12.0–105.8 mm/yr (2.6–12.7% in corresponding annual ET) among these catchments. The STDs of annual ETWB for study periods are all less than those from ETPQ, which simply estimate the annual ET by subtracting runo ff from precipitation would overestimate the interannual variations of ET. Thus, TWSC should not be ignored in the estimate of ET.

The ET estimates from di fferent GRACE solutions show relatively small deviations. The RMSEs among di fferent GRACE solutions in most catchments are less than 10 mm/month on the monthly scale and 30 mm/yr on the annual scale. In all the catchments except the HRB and MRB, CSR-GSH.sf solutions exaggerate the monthly mean TWSC, and caution should be taken when applying this solution to derive TWSC.

Di fferent precipitation products are assessed to explain the inconsistency between di fferent ET products and regional ET from a water balance perspective. The di fference between ETWB and ET from GLDAS land surface model results can be partly explained from deviation from precipitation forcing data in several catchments, especially in the LRB. Furthermore, the ET estimates would also benefit from improved runo ff outputs during the simulation process. In the three semiarid catchments and the HuRB, the RMSEs between ETWB and ETGLEAM can be reduced, provided that the di fference of precipitation can be taken into consideration. However, the increased RMSEs with deviations of precipitation forcing data and modeled runo ff considering in the estimate of ET deserves further exploration.

The ET estimates show some arresting interannual fluctuations, which warrants further study. In the SRB and MRB, there may exist some positive trends, which are likely resulting from increased precipitation or other e ffects. The trends are also worthy of further research. In summary, our study emphasizes the capability of GRACE in estimating the ET on the basin scale. The ET estimate based on water balance can be a benchmark to other ET products, which would benefit the GLDAS LSMs and remote sensing ET estimates.

**Author Contributions:** Conceptualization, M.Z. and Y.Z.; Data curation, Y.Z.; Funding acquisition, Y.Z., M.Z. and B.J.; Investigation, Y.Z.; Methodology, Y.Z. and Y.M.; Supervision, M.Z. and B.J.; Writing—original draft, Y.Z.; Writing—review and editing, M.Z., Y.M. and B.J. All authors have read and agreed to the published version of the manuscript.

**Funding:** The research is funded by the National Natural Science Foundation of China (41874091, 41774094, and 41474061); Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan) (G1323519314); and Open Research Fund Program of State Key Laboratory of Geodesy and Earth's Dynamics (SKLGED2019-2-5-E, SKLGED2019-3-2-E).

**Acknowledgments:** The authors thank Fei Li, Wei Feng, and Haoming Yan for their insightful suggestion and discussions and thank Fan Xie for her help. We thank four anonymous reviewers for their comments, which help to improve this paper.

**Conflicts of Interest:** The authors declare no conflict of interest.
