Research on Shore-Based River Flow Velocity Inversion Model Using GNSS-R Raw Data
, Wanting Meng 2, Siqi Gu 2, Jin Qin 2, Yanling Han 1 and Zhonghua Hong 1Round 1
Reviewer 1 Report
This article has been revised well according to reviewer's suggestions.
So, I think it can go to publication.
Author Response
Thank you very much for your suggestions on this article.
Author Response File: 
Author Response.docx
Reviewer 2 Report
The authors addressed my concerns with appropriate changes. Only some minor corrections are required:
- Line 341, "reaches to" should be "reaches".
- Line 344, change "the precision (MAE and RMSE)" to "MAE and RSME" since the former is single which doesn't match "are".
- Line 352, "more far" should be "farther".
Author Response
Thank you very much for your suggestions on this article.
Author Response File: Author Response.docx
This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.
Round 1
Reviewer 1 Report
The present method for velocity measurement in rivers is unique and highly practical.
The aims and conclusions were well written and this study includes interesting contents contributing to progress in this research area. So, I recommend this article to be published in Remote Sensing after miner revision.
I hope authors to revise according to following my specific comments.
Specific remarks are listed below.
- line 101: What kind of flow meter did you use ? You need to describe it, because this data is used to examine the accuracy.
- I want to know the velocity range and hydraulic condition under which the present method can work.
If this system can cover the violent flow with over 3 m/s, it is very valuable for the flood monitoring.
In addition, is there any effects of surface water waves on the measurement error?
Author Response
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Author Response File: 
Author Response.pdf
Reviewer 2 Report
In this manuscript, the authors investigated the possibility of river flow velocity estimation from GNSS-R data. The effects of elevation angle, elevation angle change rate and SNR on the estimation accuracy are also evaluated using field data. The work fits the journal scope. I suggest the authors consider the following problems in revision:
- Line 41, sea ice sensing (e.g., DOI: 1109/JSTARS.2016.2582690, DOI: 10.1109/TGRS.2017.2699122) and inland water detection (e.g., https://doi.org/10.1029/2019GL085134, DOI: 10.1109/LGRS.2020.3020223) are also important application, you may include.
- Some abbreviations are not spelled out at their first locations, e.g., MAE, NCO…
- Line 90, broken sentence.
- Lines 98-99, please provide more details about the procedure for clarity.
- Line 166, broken sentence.
- Lines 179-180, the variable symbols are not consistent with those in Eq. (8).
- Line 189 and Line 267, article doesn’t use “chapter” but “Section”.
- Is it possible to use data longer than 2 hours, say one full day?
- Lines 269-270, you use PRN4 and PRN9, but you use other names in the table or text, please be consistent.
- Lines 315-319, the variable symbol is not consistent with those in Eq. (13).
- Explain how SNR is calculated from your data.
- Reference [11], the authors’ names have mistakes.
Author Response
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Author Response File: Author Response.pdf
Reviewer 3 Report
Review of manuscript remotesensing-1477328 "Research on shore-based river flow velocity inversion model using GNSS-R raw data" by Y. Zhang et al. November, 2021. GENERAL The authors propose an approach to recover the (surface) river flow velocity from intermediate frequency GPS (or BeiDou) of carrier phase Doppler analysis. An experiment on the shore of the Yantze river is presented to validate this method. Besides this application of GNSS-R to quatify the river flow speed is very interesting, the demonstration is not established. The study is largely inspired by the previous efforts of [25] but here for a ground-based double antenna system of acquisition. See my major comments below for improving the presentation in case this work will be considered for resubmitting: (1) I found exactely the same equations in reference [25] with the same symbols and structure (!), which is nearly pure plagirism of a previous work. In the future, I would suggest to cite this methodological work instead of trying to copy this former work that was made from airborne GNSS-R data. (2) As seen on Figure 12, the estimated variations of river flow are not very convicing, these important differences explain the bad or mean correlations. This is not in favour of the demonstration at all. This is maybe due to the fact that the specular points moves in given directions and rarely coincides with the in situ measurement point of the flow, giving only APPARENT river flow speed in the local vertical plane formed by the satellite and the receiver positions, and not absolute. (3) Figure 13: GPS-based estimates are not in agreement with the BeiDou ones (see possible a explanation that I give in my point #2). This is another important problem to solve or to explain. MINOR POINTS Figure 1: The term "Fresnel diagram" is much correct. What do "r_gps9" and L_gps9" mean in this Figure ? How are these parameters finally used afterwards? Why was the experiment near the Yangtze river limited to a couple of hours ? Why is it limited to a couple of satellites ? How do GPS and BeiDou data treatments differ ? There are typographic errors in the text. Please consider to check the text tightly to correct them. Please let spaces between numbers and their following units. --- End of document ---Author Response
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Round 2
Reviewer 2 Report
The authors addressed all my concerns. Only a few typos or grammar mistakes should be corrected before publication:
- "section" with a number should use "Section".
- Line 174, "affect" should be "affects".
- The sentence in Lines 186-188 should be rewritten.
- Line 236, remove "the" before f_flow.
- Line 300, "situ" should be "in situ".
- Line 358, "two the elevation angle change rate...", something wrong?
Author Response
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