Dear Editor

The editorial support team

Copernicus Publications

Hello

I am thankful to you for allowing me to review ESSD manuscript. The present MS targeted the calculation of R factor for China using high resolution data. The work was a good and tedious one and I liked it. However, I am against its acceptance for publication thanks to many deficits and ambiguities found in the context and made it unclear in many aspects. The big issue refers to the rationale of the work.

The formulation of the research setup needs more strong rationale particularly in the viewpoint of agreement with real conditions.

No proper reviewing of literatures with further focuses on the main goals of the study and recent none-Chinese ones has been made. 

It has no detailed and documented information on methodology. 

It has no comprehensive and integrated discussion.

According to the comments mentioned above and some comments, revisions or suggestions appended in the context, I therefore suggest  resubmitting a new and substantially improved MS. My all comments and suggestions have been annotated  in the reviewed file as an attachment. 

Dear editor,

Thanks for the review invitation. The USLE model is used in many regions over the world. It is a general method by several indicators. The R factor, i.e., rainfall erosivity, has significant effects on the modeling results. This study maps the rainfall erosivity over mainland China by using high density hourly rainfall records. The data sources are presented well and the results would be useful for related soil-erosion research. The manuscript should be improved in several aspects before it is considered for the publication.

1. The new development of USLE, especially the rainfall erosivity, should be presented and discussed in the introduction section. The meaning and rational of the study is not exhibited well.
2. How can the re-calculation of R factor help to reveal the mechanism of rainfall erosivity? I suggest the authors to add a flowchart for the study.
3. The validation of the results is conducted mainly by comparing with Yin’s results. If the authors provide more findings from field observation, the validation would be more meaningful.
4. The uncertainty of the results and methods should be added by more details in the discussion.

Overview and general recommendation:

The authors developed a new R-factor for Mainland China that requires a huge dataset and work. This study is really beneficial to future studies that requires a representative map of the R-factor for their purposes of application related to sediment transportation. However, there are some places that should be made up before published.

Many studies have developed a better R-factor map for now. So far just developing a R-factor map was meaningful as there was a few maps people can employ, but now it is different. The R-factor map at a large scale should be developed based on understanding of application domains (e.g. climate zones, hydrological regimes, and the other characteristics that can affect estimating the R-factor). In this point of view, I think authors can improve the current manuscript more.

General comments

1. Mainland China has a large area consisting of a variety of climate zones and hydrological units (e.g. basins, hydrological regimes, and so on). Providing a map of rainfall erosivity is good motivation to readers and users in the future, but if authors provide the data with meaningful analysis and findings it would be great. You could consider the previous study here (Kim et al., 2020).
2. Again, as the domain is considerable, there is a question mark to using one energy equation for entire Mainland China. Also, please describe more about using the conversion factor, 1.871, as a representative value for entire domain.
3. Using a conversion factor to correct the hourly data is good for estimating the 1-in10-year EI30 but it is concerned that whether the factor, 1.489, could be employed uniformly for entire Mainland China. I suggest authors provide some more details that can describe the uncertainty and its variability so readers can pre-understand its reliability before employing the newly developed map to their own applications.
4. In the verification part, suggest authors show the error on the map. This is to present the spatial distributed error and accuracy of the developed map. Also, it would be nice if authors describe errors varying in different density of gauge network.

Reference

Kim et al., 2020. Use of a high-resolution-satellite-based precipitation product in mapping continental-scale rainfall erosivity: A case study of the United States, Catena.

Specific comments

1. [Page 1 line 10] are indispensable for soil erosion assessment -> are necessary for sediment transportation estimation based on the ~
2. Recommend using a consistent word, for example, erosivity, rainfall erosivity, rainfall erosivity factor, erosivity factor, or R factor and erosivity map or R factor map. In addition, most studies use the ‘R-factor’ instead of ‘R factor’.
3. [Page 1 line 12-13] not a good place to provide data-source where the data is available. Please put the information somewhere in the introduction or data section.
4. Please mark the thousand commas into all of the values that over a thousand.
5. [Table 1] Please re-write the title.
6. [Introduction] please re-write the first paragraph and it is too long as one paragraph.
7. [Figure 6] Instead of saying ‘changes’, please find other words to express that. The developed map can be compared with the previous work, but the previous work having lower accuracy cannot be employed to analyze the changes.