**5. Conclusions**

Snow is an important indicator to measure the global hydrological cycle and climate. The accurate long-term monitoring of snow depth is helpful for water resource management and climate disaster warning, and has important application prospects. Based on the current GNSS-IR snow depth retrieval method, the temporal resolution is affected by the number of sky satellite arcs, so multi-GNSS and multi-frequency GNSS-IR are introduced as a supplement. The snow depth retrieval is carried out by using the multi-GNSS and multi-frequency SNR data. The snow depth parameters are obtained by comparing the LSP results of snow-free and snow surfaces. At the same time, the results are compared and analyzed in terms of the PBO snow depth, and the correlation and error analysis of the multi-GNSS and multi-frequency GNSS-IR mean fusion results are carried out. The following conclusions are drawn through experimental analysis:


Compared with a single GNSS-IR signal, multi-GNSS and multi-frequency GNSS-IR improves the accuracy, continuity, and time resolution of snow depth retrieval. A mean fusion of multi-GNSS and multi-frequency GNSS-IR retrieval results can further enhance the accuracy. With the development of global navigation systems, more types of signals and perfect constellation structures will be provided. Multi-GNSS and multi-frequency GNSS-IR will play a more critical role in the field of snow depth detection.

**Author Contributions:** Conceptualization, H.W., R.Z. and L.Y.; methodology, J.T.; formal analysis, J.L. and X.L.; data curation, S.N., P.L., Y.W. and N.L.; writing—original draft preparation, J.T.; writing review and editing, H.W. and R.Z.; supervision, H.W. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the Jiangsu Agriculture Science and Technology Innovation Fund, grant number: CX (21) 3068 and the Anhui Educational Commission Key Project, grant number: KJ2020A00706.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The GNSS site data were provided under the PBO Observation Program of the United States, and the measured snow depth data were obtained from https: //data.unavco.org/archive/gnss/products (accessed on 21 October 2021).

**Acknowledgments:** We thank the PBO Observation Program of the United States for providing the GNSS data, and the University of Colorado for providing data for snow depth comparison analysis. We thank RTKLIB software for providing early SNR extraction. We also thank Roesler, C. and Larson, K.M for providing open access MATLAB code to generate reflector heights from GNSS SNR data (the paper that accompanies this code: Software tools for GNSS interferometric reflectometry (GNSS-IR)).

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

#### **References**

