Runoff for Russia (RFR v1.0): The Large-Sample Dataset of Simulated Runoff and Its Characteristics

Round 1

Reviewer 1 Report

The manuscript has 13 pages, 1 table, 7 figures, 41 reference. The main topic is about calculated climate projections using dataset of historical and River flow forecasting. Runoff for Russia (RFR v1.0, [13]) – the large-sample dataset of simulated runoff and its characteristics for river basins across Russia (Structure of hydrological data, meteo, GiS). Author gives in 3.3. subsection a brief view of RfR Runoff and Meteorological Characteristics Calculation in practice with different softwares tools.

 

Comments

Annotation. the abbreviations HBV and ISIMIP should be explained right here. I also suggest giving a brief characteristic (after line 14) of parameters (state of the soil reservoir that could characterize soil moisture dynamics, mm), snow water equivalent, mm), predicted amount of melted water, mm) and scales (regional, national). 

FIGURE 4 PRJ inclusions are not known for the readers. Please, enlarge the description. What is the difference between rср26, rср60, rср85? as I understand, these are scenarios. What are their main parameters? Are HadGEM2-ES, IPSL-CM5A-LR, MIR0C5 just projects names? Concerning which topic? 

[19] [27]- wrong repeating https://doi.org/https://doi.org/

[27]., 2019

[1][18][20] add "Available at..."

[23] [24] missed full reference. E.g. [23] Hydrology 2021, 8(1), 3

I still would be pleased, if the author provides some info about the source from data coming from (I mean mostly historical: is it a satellite datum, is it a paper derived datum, is it published in open source site for the world hydro-meteo weather). 

 

Author Response

We thank the reviewer for the detailed comments. Our response is in the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

This paper is fairly well written. However, the following flaws should be addressed prior to be accepted for publication:

1.  Several keywords duplicate the same as in the paper title. Other selections should be re-chosen.

2.  Have to be more specific with the word “tens” in Line 62.

3.  What is the real meaning of “in-home”?

4.  October month has only 30 days, not 31 days.

5.  More descriptive is needed for Figure 6.

6.  A brief descriptive of NSE (Nash-Sutcliffe efficiency coefficient) may be helpful. Why use this coefficient instead of others?

7.  A better heading for Section 4 is “Summary” or “Conclusion”.

8.  Figure 7 has not been referred to in the text. In fact, more details on the validity of the prediction may further enhance the quality of this paper and the practical contribution/implication of this dataset.

9.  Some English language check and improvement is also highly recommended.

Author Response

We thank the reviewer for the detailed comments. Our response is in the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report

The authors did some interesting work on the large-sample dataset of simulated runoff and its characteristics in Russia. The subject is important and relevant to the Data Journal. The quality of the manuscript however should be improved significantly, so I would like to suggest a complete revision before submitting it again. Please find below my comments.

 

1.    What I most concern about the manuscript is its novelty. Generally speaking, the topic of this study is to simulate runoff of river basins. Neither the topic nor the method is new. Therefore, I recommend the authors to fully stress what is new in the study (compared with previous works) and what new knowledge we can learn from their study

 

 

2.    Hydrological model setup must be expanded. At least, the reader must get some idea about the basic principles that are used to model the different processes mentioned in passing, to assess the validity of the model. More explanation of the model inputs should be included in this paper.

 

3.     I have a major concern about the boundary conditions. As it is well-known that boundary conditions dictate the results. The authors need to carry out sensitivity analysis. to understand the dependence of the parameters on the response of each model, a regional sensitivity analysis was carried out.

 

 

4.    I have a major concern on the modeling protocol the authors implemented, which lacks sensitivity analysis, model parameter uncertainty, and model uncertainty. The uncertainty of input data and setting parameters has certain randomness, and there is always an inevitable forecast deviation. Please discuss the uncertainties and I recommend performing the sensitivity analysis to assess the relative importance of the input variables. Thus, the scarce information provided in this section in combination is misleading to the reader.

 

5.    In results and discussion, the interpretation of the results is not getting deep and the outcomes are very general I would recommend adding more discussions about their results and findings to make clear the new contributions that the manuscript supports, including important implications of your work on the scientific community

 

6.    There is no conclusion made about results or learning from the presented study, thus, the authors should add the conclusions section. The authors could have made a better effort to explain what is better understood in the case they presented (Add the conclusion section).

 7.    Section 1 should be Introduction instead of Summary

 

 

 

 

 

 

 

 

Author Response

We thank the reviewer for the detailed comments. Our response is in the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

All my previous comments have been adequately addressed. This paper is readied for publication acceptance.

Reviewer 3 Report

There are major improvements in the manuscript. Most comments appear to have been dealt with, especially clarification of objectives, explanation behind the model setup and model boundary condition, in addition to the discussion section. I would recommend to accept this manuscript in this form.