the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 09 Jan 2025
Human Activities Caused Hypoxia Expansion in a Large Eutrophic Estuary: Non-negligible Role of Riverine Suspended Sediments
Abstract. Increase in riverine nutrient loads was generally recognized as the primary cause of coastal deoxygenation, whereas the role of other riverine factors, especially suspended sediments, has received less attention. This study aims to discern the impacts of anthropogenic alterations in various riverine inputs on the subsurface deoxygenation over the past three decades in a large river-dominated estuary, the Pearl River Estuary (PRE). By utilizing the physical-biogeochemical model, we reproduced the observed dissolved oxygen (DO) conditions off the PRE in the historical period (the 1990s with high-suspended sediments-DO and low-nutrient inputs) and the present period (the 2010s with low-suspended sediments-DO and high-nutrient inputs). Due to the decadal changes in riverine inputs, the PRE has witnessed more extensive and persistent low-oxygen events during summer in the 2020s, with larger spatial extents of ~2926 km2 for low oxygen (DO < 4 mg/L, increased by ~148 % relative to the 1990s) and 617 km2 for hypoxia (DO < 3 mg/L, by 192 %) and longer duration (by ~15–35 days), evolving into three distinct hypoxic centers controlled by different factors. Model experiments suggested that the decreased riverine DO content (46 %) has led to a low-oxygen expansion in the upper regions, accounting for 44 % to the total increment. Meanwhile, the increased nutrient levels (100 % in nitrogen and 225 % in phosphorus) and the declined suspended sediment concentration (60 %) have jointly promoted the primary production and bottom oxygen consumptions (dominated by sediment oxygen uptake), thus resulting in a substantial enlargement of low-oxygen area (104 %) and hypoxic area (192 %) in the lower reaches. Our results revealed a more critical role of the riverine suspended sediment decline in the exacerbation of eutrophication and deoxygenation off the PRE via improving light conditions to support higher local productivity, which could further amplify the effect combined with the growth in nutrients and confound the effectiveness of hypoxia mitigation under nutrient controls. Overall, in the context of global changes in riverine suspended sediments, it is imperative to reassess the contribution of riverine inputs to the coastal deoxygenation worldwide over the past decades, given that the impact of suspended sediments has been constantly overlooked in relevant investigations.
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2024-4013', Anonymous Referee #1, 20 Feb 2025
This manuscript attempts to quantify the role of riverine nutrient and sediment changes on long term deoxygenation off the PRE by a coupled physical-biogeochemical model, and emphasize the importance of declining sediment transport on hypoxia extension which has been overlooked before. As the decrease of riverine sediment load is common partly due to the dam constructions, its influences on coastal ecosystems (including hypoxia) need a comprehensive understanding. This study would advance the knowledge of the linkage between terrestrial transport and coastal deoxygenation dynamics. But I find shortcomings in the manuscript that need to be improved or addressed.
This study is process-oriented, and using sensitivity experiments to explore the controlling factors of hypoxia changes between 1990s and 2010s. The authors should confirm simulated results in these two periods are reasonable through model-observation comparisons. It is also noted that riverine organic matter/OM is non-neglectable for PRE hypoxia formation, the authors need to elucidate the long-term change of riverine OM and evaluate its potential influence.
Major comments:
Introduction: The authors should cite more international papers to provide a comprehensive review, especially in the paragraph of line70-86.
Model settings and validation: The “1D-3D coupled physical-biogeochemical model” including the river network and estuary, actually is a continuum model. The authors are advised to rewrite the model introduction to better address the advantage of this model.
The validations here are all from published papers, and model-observation comparison is not done in this study. Do these published papers use the same parameters’ values? As they focus on different time periods. In addition, this study needs a model-observation comparison to indicate reasonable simulations in 1990s and 2010s.
Section3.1.2: The nutrient limitation index here is the of competitive result of N, P, and Si. It is more meaningful to specify the separate limitation of the three kinds of nutrients, especially for N and P. In addition, the changes of nutrient ratio can be addressed by the way.
Section4.1: Long-term variations of oxygen and the controlling factors of PRE and other hypoxic regions have been discussed in several published studies. Discussions of similarities and differences between them and this study are lacking.
Section4.2: This study reveals a more important role of SSC then nutrients in long term deoxygenagtion off PRE. But their relatively importance should depend on their variation amplitude. It is better to point out and discuss that. Climate changes involves a variety of aspects. In addition to ocean warming, other factors like wind changes and extreme flood, can also influence oxygen dynamics.
Specific comments:
Line65: What is “increased intensity” meaning? Please specify.
Line106 “the mechanisms controlling the low-oxygen conditions are different”, the different mechanisms should be addressed here.
Line117-118: Please double-check here. the Pearl River should be the second largest river according to the freshwater discharge. The annual runoff should be ~3000×108m3. I guess your supposed value is 3.26×1011 m³.
Line121: It is better to specify the source name and the website.
Fig.1 caption: “(d-f) the nutrients and DO in the outlets” means their average of all the eight outlets or just some of them?
Line138-139: the year “1980” can be ambiguous here. As we know, China's reform and opening up was initiated in 1978.
Section2.2.1: A description of“A 1D-3D coupled physical-biogeochemical model” is needed here: explain frameworks of 1D- and 3D- components.
The coupling of 1D and 3D models is offline or online?
Line360: Hypoxia is more extensive in 2010s without doubt. But “the observed shift” is confusing, is there a regime shift of hypoxic area that has been verified?
Line495: It should be 2010s.
Citation: https://doi.org/10.5194/egusphere-2024-4013-RC1 -
RC2: 'Comment on egusphere-2024-4013', Anonymous Referee #2, 24 Feb 2025
The authors provide a quantitative analysis of various impacts on hypoxia in the Pearl River estuary. I think this is a worth topic and a nice analysis, but some key aspects of the model need to be better described and the discussion could better cite the global literature. Some general and specific comments are provided below:
Graphical abstract: The way you have included light in this document, it gives the impression that the amount of light forced on the water has gone up. I think you should express this as the same downward light flux to the surface, but more light reaching into the water to fuel additional primary production
General Comments:
- What is the 1D part of the 1D-3D model?
- Figure 4 should have a difference plot like figure 3 and 5. This is especially important given that the differences in these growth factors are far smaller than those variables in figs 3 and 5
- I found the first paragraph of the discussion, lines 488-505 to be simply a repetition of material already presented. I think it could be deleted.
- I think the authors point about the importance of turbidity in influencing hypoxia in particular is an interesting finding, and worth highlighting. But I do think they authors overstate it’s potential importance in other estuaries. The changes in sediment concentrations in the PRE were quite high, and I am not convinced that similar changes have occurred in many other hypoxic systems within the time of hypoxia expansion. The text on line 554-570 is helpful, but it would be better if hypoxia-specific details from the literature could be added to the discussion.
- Paragraph on lines 571-579: Can you report any information about temperature trends that have been seen in the PRE that could be cited here?
- I think my major comment is that the authors need to bring out the validation of their light model into the paper. The entire model analysis hinges on how well the light model performs, and how realistic it is. How was the base kd estimated? Was CDOM considered? Does the model get the photic depth correct? These are essential details that need to be discussed.
- Following on #6 above, I think the authors need to discuss their light model in the context of other light models out there. Would their result be different if they used a spectral light model that was less empirical?
Minor edits:
L107: “Use” should be “used”, assuming past tense.
L118: Should the annual runoff estimate have a time unit? If it is indeed per year, you could indicate that in the unit.
L122: “has” should be “have”
Figure 1: The graph in this figure is really tiny. Please make it larger so the axis labels are easier to read
Line 137: “Until the late 1990s…” is confusing as written. Can you specify the period in which the reservoirs were built? This is important because you say that there were no hydraulic facilities in the 1990s. How are these two periods different?
Figure 2: This figure is also far too small and difficult to read
Line 188: “ dissolve” should be “dissolved”
Line 205: “instant” should be “instantaneous”
Line 272: “consecutive sinking” doesn’t make sense. You could replace “consecutive sinking along with water transport,” to “particle sinking as waters advected downstream,”
Line 331: “has” should be “was”
Figure 1 caption: Please add a unit for the hypoxia frequency
Line 354-355: you could probably mention in this first sentence that surface DO went down in the landward region before you mention the increase in the ocean region. Fig 5b clearly shows a decline in the landward section.
Line 409: “enhanced” should be increased“
Line 561: “predominated” should be “predominant” (see also line 597)
Citation: https://doi.org/10.5194/egusphere-2024-4013-RC2 -
RC4: 'Reply on RC2', Anonymous Referee #2, 25 Feb 2025
My apologies, in the comment: "Figure 1 caption: Please add a unit for the hypoxia frequency", I was referring to Figure 5
Citation: https://doi.org/10.5194/egusphere-2024-4013-RC4
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RC3: 'Comment on egusphere-2024-4013', Anonymous Referee #3, 25 Feb 2025
In this contribution, the authors evaluate the overlooked role of riverine suspended sediments in driving hypoxia in an estuary, using model experiments. The study looks in particular at the case of the Pearl River Estuary in China. The authors use controlled model experiments in a 3D model with a biogeochemistry module to evaluate the role of three drivers of hypoxia: dissolved oxygen (DO) concentrations, nutrient levels and suspended sediment concentrations (SSC) in river export. They find that SSC plays a significant role, and that the sensitivity of hypoxia to each of these factors varies with distance to the river mouth. The authors finish by discussing how this has important implications for hypoxia mitigation strategies in estuaries, as overlooking SSC can lead to an overestimation of the role of nutrient loading.
This manuscript represents a valuable contribution, showing the importance of a previously overlooked driver of hypoxia in coastal areas. The figures support the findings very well. This manuscript would be ready for publication after correcting some deficiencies in the description of the data and of the model forcing. The presentation of the results could also benefit from more quantitative evaluations and from a better synthesis.
General comments
1. Even if the goal of this study is first and foremost to present the results of modeling experiments, the authors present some results or figures based on data (Fig. 1c-f. Fig. 2). Hence, a method section describing the data and how it was processed is currently missing.
- The data used should be presented. In Table S1, some datasets refer to “This study”, but the data is not described.
- How are the time series in Fig. 1d-f obtained? Is it an average? Is it at a specific depth? Also, error bars are missing on Fig. 1c-f.
- How are bottom waters defined in producing Fig. 2? Is this the concentration at a specific depth or vertically integrated over a specific range? What method is used to estimate the area, in particular in years in which the sampling is less extensive?
- A description of how the nutrient limitation factor and the euphotic depth are calculated is missing. From my general understanding, nutrient limitation evaluates which nutrient is limiting, so a few words on how this is linked with whether productivity is limited by nutrients or light would be useful.
2. The authors mention that this model has been used many times previously. Hence, I would suggest that this contribution does not need a full description of the model in Section 2.2.1, which could be shortened, replacing it with a short description of the model’s specificity. Instead, what was not clear to me was the model forcing. I suggest improving the description at L244-246, providing more details about what inputs are required by the model, what the data source is used, and how the data is processed. Here are some specific points:
- From the text it seems like there is one river input to the model. Is this the case, since this is a 3D model and since from Fig. 1a it looks like there are multiple outlets into the region?
- What data is used for the physical conditions?
- Are the physical conditions inputs (winds, river output, stratification) the same in all experiments or do they vary?
3. The objective of the mode experiments is to evaluate the sensitivity of the system’s bottom DO to different factors. Hence, I suggest to significantly reduce the description of the oxygen and hypoxia extent results of the model in section 3.2.1 to talk more and more quickly about the processes (3.2.3).
4. The analysis of the model results should be improved by making it more quantitative and by putting forward some of the important findings.
- First, at L468-474, I suggest to make it more clear that the effects of nutrient loading and SSC are not linearly additive, and to discuss why. The authors could also use Fig. 7 to show how the two effects sometimes add up linearly in some regions and not in others. In some regions the effect is even amplified (sum of the two experiments > two individual experiments, as mention at L524), while in others the sum is lower (currently not mentioned/discussed). This should be discussed.
- Second, the authors offer a quantification for the role of DO river input (44%), but not for the other factors. Even if this quantification varies spatially and the effect is not linearly additive, I suggest to provide some sort of quantitative assessment. This would help put forward the main result of this manuscript, which is that SSC plays an important role in driving hypoxia.
Specific comments:
Make sure to use a high enough resolution when extracting the figures.
On the graphical abstract, we get the impression that sunlight is stronger under human activity. I suggest modifying to make it more clear that it is the light penetration that is stronger.
L79: I suggest specifying how human activity can reduce suspended sediment loads (what they say at L136). Also, human activity can sometimes act in the other direction and increase suspended sediment load (for instance under land change use that contributes to erosion, for during deforestation). The authors should acknowledge this possible scenario, perhaps discussing it in the discussion in the light of their findings (how this would reduce hypoxia).
When we read section 2.2.2 on model validation, it gives the impression that the authors do not perform model validation in their specific setting. However, they do so in the results section, for instance comparing hypoxic areas at L365. I suggest to move this to the model validation section, and perhaps add a comparison of DO concentrations.
In the introduction, the authors should cite more international studies discussing the processes behind deoxygenation, for instance (but not restricted to) Fennel & Testa 2019 (10.1146/annurev-marine-010318-095138); Rabalais et al. (2010), Dynamics and distribution of natural and human-caused hypoxia; Chan et al. 2019 (https://www.jstor.org/stable/26760084).
Fig. 1: The colorbar title on Fig. 1a says “Depth (m) relative to Pearl River Datumn”, what is that reference point?
On Fig. 1, I suggest adding the main circulation features on the shelf on the map, and use it to discuss why SSC and nutrient loading impacts DO differently in different regions.
If kept, eq.1 can be written in a more concise way using vectorial notation.
L173: If you keep the details about each term, please also include some information about the type of parameterization used for the Rea term.
L269: I’m not sure I understand this claim, given that SSC is an input of the model.
L272: If I understand correctly, the authors run the model for 8 months, once with the 1990s conditions, and once with the 2010s conditions. This sentence suggests that the suspended sediments from the 1990s has sunk by 2010s, but the two simulations are not connected.
Related to this previous comment, I suggest being careful with the wording throughout this section, since the model is not providing true estimates of changes from 2010s to 1990s, but rather showing how the prescribed changes in riverine input are reflected downstream.
Table 2: What is the definition of bottom waters?
L311 and L322: Use the present tense.
Fig. 4: I strongly suggest adding the difference between the two periods, as in Fig. 3.
Fig. 5: I suggest showing the line on Fig. 5a instead of Fig. 1.
Fig. 6: I suggest adding contours showing the hypoxic and low-oxygen zones, so we can see if the changes are felt in low-oxygen zones or in well-oxygenated areas.
Fig. 7: I suggest not using a diverging colorscale since the values are not centered on zero. The current colors give the impression that in some areas the values are increasing and in others they are decreasing. I also suggest labeling 2010s as High nutrient + Low SSC, similarly to Fig. 6.
L521: Since you provide a quantification for the role of low-DO input, I suggest also providing a number for the role of SSC versus nutrient loading.
I suggest commenting on why the impact on production is so much downstream of the changes in SSC and nutrient concentration.
There are some repetitions between the first part of the discussion and the conclusion. I think the first part of the discussion could be removed.
Data availability: The authors say in the text that all data are publicly available or coming from other studies. Please provide in this section the link to access each dataset.
Citation: https://doi.org/10.5194/egusphere-2024-4013-RC3
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