**5. Conclusions**

This study developed a concise and practical algorithm for SM estimation using Sentinel-1/2 temporal data in a permafrost environment on the QTP in the thawing season. The R<sup>2</sup> of this SM retrieval algorithm reached 0.82 with an RMSE of 0.06 m3/m3.

Our retrieved SM results were compared with current SM products (ERA5-Land, GLDAS-Noah, and ESA CCI) in the Tuotuo River basin and showed that our results have more strength and advantage in characterizing the spatial heterogeneity of SM distribution. By analyzing the SM distribution of different vegetation types, the alpine swamp meadow had the largest SM of 0.26 m3/m3, followed by the alpine meadow (0.23), alpine steppe (0.2), and alpine desert (0.16). We also found a significantly negative correlation between the CV and SM in the permafrost area that the variability of SM is higher in drier environments and lower in wetter environments.

The study also explored the reasons for abnormal SM retrievals in some places. The developed algorithm is not applicable in some extremely bare and dry ground with very low SM. Overall, the proposed algorithm shows grea<sup>t</sup> potential to derive the detailed SM distribution in the permafrost environment on the entire QTP, which has grea<sup>t</sup> significance in studying the SM characteristics in spatial detail and helps facilitate the studies of the response of permafrost to climate change.

**Author Contributions:** Z.L., L.Z. and L.W. conceived and designed the experiments; Z.L., L.W., D.Z., E.D., Y.X., Z.X., S.L., H.Z. and Y.C. performed the experiments; and Z.L., L.Z., L.W., G.L., G.H., J.Z., C.W., Y.Q. and J.S. analyzed the data and wrote the paper. All of the authors contributed to the editing of the manuscript. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the Second Tibetan Plateau Scientific Expedition and Research Program (2019QZKK0201), the National Natural Science Foundation of China (41931180, 42001054, 42001051), and the Youth Fund for Basic Research Program of Jiangsu Province (BK20200828).

**Acknowledgments:** We are grateful to the anonymous reviewers and editors for appraising our manuscript and offering instructive comments. We are very grateful to Lei Fan and Xiaojing Bai for their guidance on the experiments of this paper. We also appreciate the free access to data sets from the Chinese Academy of Sciences. In addition, we would like to thank the Google Earth Engine platform for providing the data and processing methods needed in this study.

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