the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Long-term changes of nitrogen leaching and their contributions to lake eutrophication dynamics on the Yangtze Plain of China
Lian Feng
Stefan Olin
Guy Schurgers
Abstract. Over the past half century, drastically increased chemical fertilizer have entered agricultural ecosystems to promote the crop production on the Yangtze Plain, potentially enhancing agricultural nutrient sources for eutrophication in freshwater ecosystems. However, long-term trends of nitrogen dynamics in terrestrial ecosystems and their impacts on eutrophication changes in this region remain poorly studied. Using a process-based ecosystem model, we investigated the temporal and spatial patterns of nitrogen use efficiency (NUE) and nitrogen leaching on the Yangtze Plain from 1979 to 2018. The agricultural NUE for the Yangtze Plain significantly decreased from 50 % in 1979 to 25 % in 2018, with the largest decline of NUE in soybean, rice and rapeseed. Simultaneously, the leached nitrogen from cropland and natural land increased with annual rates of 4.5 kg N ha-1 yr-2 and 0.22 kg N ha-1 yr-2, respectively, leading to an overall increase of nitrogen inputs to the fifty large lakes. We further examined the correlations between terrestrial nutrient sources (i.e., the leached nitrogen, total phosphorus sources, and industrial wastewater discharge) and the satellite-observed probability of eutrophication occurrence (PEO) at an annual scale, and showed that PEO was positively correlated with the changes in terrestrial nutrient sources for most lakes. Agricultural nitrogen and phosphorus sources were found to explain the PEO trends in lakes in the western and central part of Yangtze Plain, and industrial wastewater discharge was associated with the PEO trends in eastern lakes. Our results revealed the importance of terrestrial nutrient sources for long-term changes in eutrophic status over the fifty lakes of the Yangtze Plain. This calls for sustainable nitrogen applications in agriculture systems to improve water quality of local lake ecosystems.
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Qi Guan et al.
Status: final response (author comments only)
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RC1: 'Comment on bg-2022-197', Anonymous Referee #1, 16 Dec 2022
Using a process-based LPJ-GUESS model, this paper investigated the linkage between the dynamics of terrestrial nitrogen in the Yangtze Plain and eutrophication changes in fifty large lakes for the past four decades. Overall, the paper is well organized and the results answer the questions mentioned by the authors, although some uncertainties exist. But some details regarding the innovation and the method need to add before publication. The specific issues are as follows:
1 Introduction
Suggest to strengthen the innovation of the study.
2 Materials and Methods
2.1 briefly introduce the agricultural cultivation types and management patterns in the study area.
2.2 How the fertilization process is represented in the model needs to be described
2.5.1 The remote sensing data of Guan, such as spatial and temporal resolution, should be briefly introduced.
4 Discussions and conclusions
(1) Lines 343-348 add a discussion of the reason for the decrease in NUE.
(2) add an outlook for future studies regarding the uncertainties of current results.
Citation: https://doi.org/10.5194/bg-2022-197-RC1 -
AC1: 'Reply on RC1', Qi Guan, 10 Mar 2023
The comment was uploaded in the form of a supplement: https://bg.copernicus.org/preprints/bg-2022-197/bg-2022-197-AC1-supplement.pdf
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AC1: 'Reply on RC1', Qi Guan, 10 Mar 2023
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RC2: 'Comment on bg-2022-197', Anonymous Referee #2, 20 Jan 2023
Comments on the study of Guan et al
This study examined the dynamics of major pollution sources contributing to eutrophication in the fifty large lakes of the Yangtze River Plain, a region with 340 million people. These dynamics were studied over a forty-year period (1979-2018) and correlated with satellite-tracked algal bloom events. Pollutant sources studied include leached nitrogen in agro-ecosystems, phosphorus sources, and industrial waste. Remarkable efforts have been made to characterize in space and time the leaching of nitrogen which is a very diffuse source of pollution. This characterization was made using a carbon-nitrogen coupled ecosystem model constrained with meteorological, soil and agronomic data. This study is exceptional by the size of the studied region, the diversity of ecosystems considered (crops, terrestrial and aquatic ecosystems) and used variables. Below I made some comments/criticisms with the aim of improving this manuscript that merit publication.
The title and conclusive sentences of the abstract only mention the impact of N leaching. However, your study also suggests an impact of P applications and industrial wastes. This must appear more clearly.
From my point of view, on the most important finding of your study is the suggestion that the origins of lake eutrophication change with space (and maybe with time). Indeed, this finding signifies that policies and technical changes that need to be implemented to decrease lake eutrophication must be adapted to local conditions.
In the discussion, you mention that the eutrophication induced by industrial wastes is now solved thanks to policies set by the government and changes made in industries. YOU CAN NOT CONCLUDE on that point because your data do not show that at all. You can only mention the fact that the government has become aware of the problem and set up incentives to decrease industrial pollutions.
The manuscript discussion starts by saying that it is now possible to deplete lake eutrophication because we know one of its main sources: low NEU and high N leaching. One might argues that we know since decades that N leaching causes eutrophication. The challenge rather lies in the setup of good agricultural practices leading to a decrease in nutrient loss. You should mention/list some examples of these practices (agriculture precision, cover cropping, residues managements etc) and how they are implemented or not in this region. More generally, I would suggest to start the discussion with your finding that the causes of eutrophication can be multiple and change in space requiring incentive policies adapted to local conditions.
L153 It seems that soil properties have been implemented in the model using the world database on soil types/soil pedology. How did you consider the impact of land use on these soil properties?
L199 This approach using the linear relationship is not clear? Why did you not directly use the model to estimate the N leaching?
L212-213 I do not understand why it is a problem since the model can provide those results.
L217 P sources are not simulated right? This should be specified.
L225 These choices are a bit strange. In general, N (especially mineral N) is more mobile than P. Thus, N leaching is likely to be more linked to N applications than P leaching to P applications. Despite this, you used a complex modelling to estimate N leaching whereas you simply used the P source for P leaching/pollution. You should better explain your choices, and maybe consider to also examine the correlation between N leaching and N applications to have something comparable for the different sources of pollutions.
L256 What do you mean with climatological NEU?
L270-273 There are considerable differences between crops, which is worth to discuss. The negative effect of double crops is surprising since maintaining a permanent plant cover generally promote N retention in agrosystems.
Figure 6 -> N leaching under natural ecosystems also increase during the period, which merits discussions.
L292-293 -> put the treatments close to the numbers to facilitate the reading.
L298 How did you define the drainage area? Watershed?
L303 What about the role of atmospheric N depositions? Did you consider this aspect or not? This should be specified.
L305 -> please recall us the acronyms of these variable to facilitate the reading.
LL377 Revise the sentence. The source of uncertainty is not “potential impacts of terrestrial nutrient losses” but the transport processes that mediate the quantity and quality of nutrients that will be transferred from sources to surface water (lakes?).
Citation: https://doi.org/10.5194/bg-2022-197-RC2 -
AC2: 'Reply on RC2', Qi Guan, 10 Mar 2023
The comment was uploaded in the form of a supplement: https://bg.copernicus.org/preprints/bg-2022-197/bg-2022-197-AC2-supplement.pdf
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AC2: 'Reply on RC2', Qi Guan, 10 Mar 2023
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EC1: 'Comment on bg-2022-197', Sébastien Fontaine, 13 Feb 2023
Dear Authors,
I have just received a new comment from a referee who was sick during these last weeks explaining the delay. Usually no more referee comments are accepted after the closue of discussions. Nevertheless, in this special case, and because the referee did a good job, I would ask you to consider the referee comments I post you below. Thank you for your cooperation. Sébastien
This study focused on the dynamics of land-based nitrogen in 50 large lakes in the Yangtze River basin over the past 40 years, and used LPJ-GUESS model to study the driving factors of lake eutrophication. Based on the principal component analysis (PCA) , the authors divided the 50 lakes into three types according to two principal components. This work is interesting because the authors have identified a driving mechanism for lake eutrophication. On the whole, I find it easy to understand and interesting. However, there are several issues in this manuscript that need to be corrected.
- In line 31: It is suggested that the introduction should be supplemented with an explanation of the current state of eutrophication-driven research. There are some relevant studies in this area. Could you explain the innovation of your research.
- In line 253：The simulated and observed responses of the nitrogen leaching to different levels of fertilizer application rates for three main crop types response in Figure 3. What do the dotted lines in Figure 3 mean? Please add the explanation.
- In line 236：Observations of crop yields and GPP are used to assess the accuracy of the LPJ model in simulating the nitrogen leaching. Does this effectively evaluate the reliability of the model? Please explain the reason.
- In line 274：In Figure 4 (b), check for missing units (%) in the vertical coordinates. Please check it.
- In line 281：In Figure 6 (b) (d) and (f), the vertical coordinates lack units (Kg N/ha). Please check it.
- In Figure S3, the position of the legend coincides with the picture. Please check and adjust the position of the legend.
- In line 324: Figure 7 (c) is not found in the manuscripts, and I assume you mean Figure 8 (c). Please check it.
- In line 335: In Figures 8 (a) and 8 (b), there are only relationships for type I and II lakes are found, but there no relationships for type III lakes. Please check it.
- In line 327: The significantly negative correlations between the PEO and IW Anomalies were found for Class I and II (Fig. 8C) .This conclusion is very interesting and I hope the author can explain it.
Citation: https://doi.org/10.5194/bg-2022-197-EC1 -
AC3: 'Reply on EC1', Qi Guan, 10 Mar 2023
The comment was uploaded in the form of a supplement: https://bg.copernicus.org/preprints/bg-2022-197/bg-2022-197-AC3-supplement.pdf
Qi Guan et al.
Qi Guan et al.
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