Spatiotemporal Dynamics of Nitrogen Transport in the Qiandao Lake Basin, a Large Hilly Monsoon Basin of Southeastern China
, Steven G. Pueppke 3,4, Jiaping Pang 2 and Yaqin Diao 1,2Round 1
Reviewer 1 Report
The manuscript is original and the research well described and discussed. English language and style are correct and only minor revisions are needed for the publication.
Minor revisions:
L204: Figure 1S --> Figure 1; Figure 2S --> Figure 2
L206: QLB --> QLB.
L210: 1375 --> 1,375; 2373 --> 2,373; Figure 3S --> Figure 3
L214: Figure 3S --> Figure 3
L251: in the QLB --> in the QLB.
Figure and tables
Figure 6: In the legend is reported km^2 while in the text of the manuscript is referred as km2. Please use the same form.
Figure 10: please use , as thousands separator
Table 1: I suggest to use the same number of significative numbers in the table.
Author Response
Response to Comments of Reviewer 1
Point 1: L204: Figure 1S --> Figure 1; Figure 2S --> Figure 2
Response 1: The maps of land use and soil types are in the supplementary materials document, and this is indicated by inclusion of the letter “S” in reference to these figures. Thus, in line 204, the statements in parentheses are correct as written. The reviewer evidently overlooked this point.
Point 2: L206: QLB --> QLB.
Response 2: We are sorry for our carelessness and have corrected the ‘QLB’ to ‘QLB.’ in red in line 206.
Point 3: L210: 1375 --> 1,375; 2373 --> 2,373; Figure 3S --> Figure 3
Response 3: We have corrected the number formats ‘1375’ to ‘1,375’ and ‘2373’ to ‘2,373’ in line 210. We have made similar format corrections elsewhere, as shown in line 84, line 87 -88, line 153, line 238, line 246, line 262, line 272, line 389 and line 391. See the above explanation under Point 1 about the difference between Figure 3 and Figure 3S.
Point 4: L214: Figure 3S --> Figure 3
Response 4: See the above explanation under Point 1 about the difference between Figure 3 and Figure 3S.
Point 5: L251: in the QLB --> in the QLB.
Response 5: We have corrected the ‘QLB’ to ‘QLB.’ in red in line 251.
Point 6: Figure 6: In the legend is reported km^2 while in the text of the manuscript is referred as km2. Please use the same form.
Response 6: We have corrected all the superscripts in the text from ‘km2’ to ‘km2’, so that the designation in the text matches that in the legend in Figure 6.
Point 7: Figure 10: please use , as thousands separator
Response 7: We have corrected all the numbers with a thousands separator in Figure 10.
Point 8: Table 1: I suggest to use the same number of significative numbers in the table.
Response 8: We have corrected the numbers as suggested by the reviewer.
Author Response File: 
Author Response.docx
Reviewer 2 Report
This is a very interesting article. The studies were well planned and performed, the model was correctly used. In terms of editorial manuscript is prepared very well. I have no criticisms. I am impressed by the huge amount of data collected and used in modeling. The result of this work is also impressive.
Reviewer 3 Report
The manuscript was well written.
I was a little disappointed when the authors only looked at TN data and did not included ammonia, nitrate, nitrite and organic N (page 4, line 119-120). Even though, the data was available and this information would strengthen their manuscript.
I believe if the authors used the TN, ammonia, nitrate, nitrite and organic N data, they could run this data through a cluster analysis to explain site information. This data then could reinforce the authors simulations and significance.
Another troubling component that did not make sense was the importance of forest land to the TN data (page 11, line 317; page 12, line 375; page 15, line 486) ~ 10.9% of TN. I could not find an explanation for why forest land TN contributed to this high output.
Not sure if the authors are familiar with Hubbard Brook Experiment Forest in USA? They have looked at nutrients (N & P & C) input and output from a forest environment. Forests are generally thought to be nitrogen sinks rather than sources unless the forests are being disturbed (I included the some links below). So, why are the forests in your research area major TN sources?
https://hubbardbrook.org/online-book/nitrogen-cycling
https://www.ncbi.nlm.nih.gov/pubmed/17536402
https://harvardforest.fas.harvard.edu/sites/harvardforest.fas.harvard.edu/files/publications/pdfs/Driscoll_Environment_2003.pdf
Author Response
Response to Reviewer 2 Comments
Point 1: The manuscript was well written. I was a little disappointed when the authors only looked at TN data and did not included ammonia, nitrate, nitrite and organic N (page 4, line 119-120). Even though, the data was available and this information would strengthen their manuscript. I believe if the authors used the TN, ammonia, nitrate, nitrite and organic N data, they could run this data through a cluster analysis to explain site information. This data then could reinforce the authors simulations and significance.
Response 1: We are sorry that the text is unclear on this point and has led to confusion. The statement on page 4, line 119-120 , which we have now modified, was included to define our use of the term TN, i.e., the sum of all forms of nitrogen, including ammonia, nitrate, nitrite, organic N and so on. TN concentrations were measured by the Chun’an Environmental Protection Bureau, which provided the data to us. Unfortunately, detailed forms of nitrogen, including ammonia, nitrate, nitrite and organic N were not measured independently, and so it is not yet possible to make cluster analysis of different forms of nitrogen as recommended by the reviewer. We have been informed that different forms of N will likely be measured by the Chun’an authorities in the future, and when sufficient data are available, we intend to do a follow up study. We agree with the reviewer’s contention that this would provide important new information.
Point 2: Another troubling component that did not make sense was the importance of forest land to the TN data (page 11, line 317; page 12, line 375; page 15, line 486) ~ 10.9% of TN. I could not find an explanation for why forest land TN contributed to this high output. Not sure if the authors are familiar with Hubbard Brook Experiment Forest in USA? They have looked at nutrients (N & P & C) input and output from a forest environment. Forests are generally thought to be nitrogen sinks rather than sources unless the forests are being disturbed (I included the some links below). So, why are the forests in your research area major TN sources?
https://hubbardbrook.org/online-book/nitrogen-cycling
https://www.ncbi.nlm.nih.gov/pubmed/17536402
https://harvardforest.fas.harvard.edu/sites/harvardforest.fas.harvard.edu/files/publications/pdfs/Driscoll_Environment_2003.pdf
Response 2: We appreciate the reviewer’s comments about nutrient (N & P & C) input and output from forest environments. The corresponding author has carefully read the links provided by the reviewer. The information about the cycling and balance of nitrogen in the forest environment represents a different perspective from that adopted in our manuscript, which focuses on the proportion of N sources in the water body. Focus on balance seeks to understand nitrogen sources and sinks, while that on N loads seeks to understand N emission from different land use [1].
Nevertheless, and as the reviewer correctly points out, we need to better explain why forests in the QLB are relatively important sources of N emission. There are several reasons for this observation. Firstly, the area proportions of steep slope are major in the QLB. The mean slope of the study area is 24.88°, and the area proportion of slope < 10° is 22%, 10°-20° is 13%, 20°-25° is 9%, 25°-30° is 12%, >30° is 44%. This means that a large proportion of land in the study area is very steep and unsuited for clearing to facilitate other land uses.
Secondly, according to the RUSLE equation, the total erosion in study was close to 200 t/km2/yr. Especially from February to April, the vegetation coverage factor of forest land is below 0.7 based on calculations of NDVI from Landsat Modis products. This means that forest land in the QLB is primed for water and soil erosion. It is known that forests with steep slopes in the QLB are the critical sediment yield areas, and forest contributes more 80% of sediment [2]. Nitrogen in sediments accounts for 90% of TN in Xin’anjiang basin [3].
Thirdly, forest land use contributes approximately 16% of runoff N in upper basin of Anhui Province due to its large area [4]; we have found similar percentages in our other work. Soil erosion is also significant in the Xin'anjiang catchment, contributing to 66% of non-point source production [1], and N from atmospheric deposition is rising (our results but also see [2]). In short, a unique combination of topography, land use, and environment leads to relatively substantial N loads from the forests of the QLB.
The reviewer identifies lines 317, 375, and 486 as spots where we must improve discussion of these issues. We have done so in the revision, most extensively at line 375, so as to more adequately explain our results. This includes addition of a new citation and more precise referencing of relevant current citations. We are very pleased that the reviewer challenged us on these points and believe the explanation addresses the stated concerns.
- Wang, X.; Wang, Q.; Wu, C.; Liang, T.; Zheng, D.; Wei, X. A method coupled with remote sensing data to evaluate non-point source pollution in the Xin'anjiang catchment of China. Science of the Total Environment 2012, 430, 132-143, doi:10.1016/j.scitotenv.2012.04.052.
- Zhai, X.; Zhang, Y.; Wang, X.; Xia, J.; Liang, T. Non-point source pollution modelling using Soil and Water Assessment Tool and its parameter sensitivity analysis in Xin'anjiang catchment, China. Hydrological Processes 2014, 28, 1627-1640, doi:10.1002/hyp.9688.
- Jia, X.; Luo, W.; XueqianWu; HaobinWei; BaoliWang; Phyoe, W.; FushunWang. Historical record of nutrients inputs into the Xin'an Reservoir and its potential environmental implication. Environ Sci Pollut Res Int 2017, 24, 20330-20341, doi:10.1007/s11356-017-9537-9.
- Li, Z.; Liu, M.; Zhao, Y.; Liang, T.; Sha, J.; Wang, Y. Application of Regional Nutrient Management Model in Tunxi Catchment: In Support of the Trans-boundary Eco-compensation in Eastern China. CLEAN - Soil, Air, Water 2014, 42, 1729-1739, doi:10.1002/clen.201300380.
Author Response File: Author Response.docx
Round 2
Reviewer 3 Report
The revisions made the manuscript a lot clearer. I have no further comments.
