Spatiotemporal Shifts in Organic Carbon Sources in Cascade Reservoirs &ndash; a case study in the Lancang River

Sun, Huimin; Zhou, Xudong; Jiang, Bingcan; Lin, Yuqing; Chen, Yuchen; Yan, Xingcheng

doi:10.5194/egusphere-2026-3912

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https://doi.org/10.5194/egusphere-2026-3912

Preprints

21 Jul 2026

| 21 Jul 2026

Spatiotemporal Shifts in Organic Carbon Sources in Cascade Reservoirs – a case study in the Lancang River

Huimin Sun, Xudong Zhou, Bingcan Jiang, Yuqing Lin, Yuchen Chen, and Xingcheng Yan

Abstract. Dam construction profoundly alters sediment organic matter regimes in large rivers. Yet, the underlying mechanisms and how cascade reservoirs jointly shape organic matter sources remain insufficiently understood. Here, we quantified organic matter sources across five cascade reservoirs in the middle–lower Lancang River using stable isotopes with a Bayesian mixing model. We found that algal-derived organic matter dominated during the dry season and in reservoirs with longer retention, whereas terrestrial organic matter prevailed during the wet season and intensified downstream with increasing watershed inputs. The structural equation model analyses demonstrated that reservoir regulation and seasonality influenced organic matter sources indirectly through nutrient dynamics rather than through direct hydrological forcing. Hydrodynamic conditions, represented by a composite index derived from hydraulic retention time and backwater length, were positively associated with nutrient enrichment in both water and sediments, whereas temperature showed a negative relationship with sediment nutrients; these nutrient variations were further linked to increased contributions of terrestrial, algal, and sewage-derived organic matter. Complementary boosted regression tree analyses further identified the key environmental predictors shaping organic matter partitioning. Water temperature together with sediment nutrients formed the core controls on the balance between terrestrial and algal organic matter (> 48 % cumulative influence). Hydrodynamic factors were crucial for sewage-derived organic matter, with water depth and retention time jointly contributing 35.2 % of its variability. Together, these results reveal that organic matter provenance in cascade systems emerges from the coupled effects of reservoir-induced nutrient regulation and temperature–hydrology interactions, producing source dynamics distinct from single-reservoir systems. This study provides mechanistic insights needed to improve reservoir ecosystem management and underscores the importance of integrating cascade-scale nutrient regulation into future assessments of human impacts on riverine carbon cycling.

Received: 01 Jul 2026 – Discussion started: 21 Jul 2026

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Huimin Sun, Xudong Zhou, Bingcan Jiang, Yuqing Lin, Yuchen Chen, and Xingcheng Yan

Status: final response (author comments only)

RC1:
'Comment on egusphere-2026-3912', Anonymous Referee #1, 11 Aug 2026
General comments
This manuscript investigates the spatiotemporal variability of sediment organic matter sources in five cascade reservoirs along the middle–lower Lancang River using stable isotope analysis combined with Bayesian mixing modeling, structural equation modeling, and boosted regression tree analysis. The topic is highly relevant to current discussions regarding anthropogenic impacts on inland water carbon cycling. The manuscript provides valuable insights into how cascade reservoir regulation and seasonal variability jointly influence organic matter provenance.
The manuscript is generally well structured and the methodology is appropriate. The conceptual framework linking hydrological regulation, nutrient dynamics, and organic matter source shifts is particularly interesting. I recommend publication after addressing the following issues.
Specific comments
Lines 25–35, Lines 90–110：Throughout the manuscript, the terms “organic matter (OM)”, “organic carbon (OC)”, “sedimentary organic matter (SOM)”, and “sedimentary organic carbon (SOC)” are sometimes used interchangeably. Because the isotope-based mixing model estimates contributions from different organic matter sources, whereas the ecological implications are discussed mainly in terms of carbon cycling, the authors should clarify whether the estimated contributions represent: sedimentary organic matter fractions; organic carbon source contributions; or carbon contributions inferred from organic matter isotopic signatures? Consistent terminology throughout the manuscript would improve clarity.

Lines 105–125, Lines 420–450: The manuscript frequently emphasizes the importance of “cascade effects” in regulating organic matter dynamics. However, the specific meaning of cascade effects should be clarified. Do the authors refer primarily to: cumulative sediment trapping; downstream modification of nutrient transport; progressive changes in hydraulic residence time; or combined effects among these processes? A more explicit definition would strengthen the conceptual framework.

Lines 155–185: The selection of isotopic end-members is a critical component of the Bayesian mixing model. The authors state that end-member values were determined by integrating published literature values and constraints from measured isotope compositions in this study. However, some selected values, especially forautochthonous algae (δ¹³C = −16.0 ± 2.5‰)and sewage-derived organic matter (δ¹³C = −4.5 ± 2.5‰), which are relatively enriched compared with commonly reported freshwater systems. Although the authors provide explanations related to carbonate-rich dissolved inorganic carbon and C₄ agricultural inputs, additional information is needed regarding: 1. how measured samples constrained these values; 2. whether alternative end-member combinations were tested; 3. how sensitive source contribution estimates were to end-member uncertainty.

Lines 330–350: Several statements in the manuscript imply direct causal relationships based on statistical relationships. For example, phrases such as:“nutrient variations increased organic matter contributions”Or “hydrological conditions controlled organic matter sources” may be stronger than supported by observational data. Although structural equation modeling provides pathway analysis, the authors should consider using more cautious wording, such as: “were associated with” “potentially mediated through” or “were linked to”.

Lines 280–300: The manuscript introduces a composite hydrological index derived from hydraulic retention time and backwater length. Please clarify: whether higher Hydro-index values indicate stronger hydrological regulation; the proportion of variance explained by the first principal component; why this integrated index was preferred over using individual hydrological variables. This information would facilitate interpretation of the SEM results.

Minor comments
Lines 23-25: “Dam construction profoundly alters sediment organic matter regimes in large rivers.”is somewhat broad. I suggest revising it to:“Dam construction profoundly alters sediment organic matter sources and cycling processes in large rivers.” This would better reflect the focus of the manuscript.

Lines 70: The term “hydrodynamics” is used broadly. Because the SEM analysis uses a composite hydrological index rather than direct hydrodynamic measurements, the authors should clarify this distinction.

Lines 75–95: The Introduction provides a comprehensive description of reservoir impacts on carbon cycling. However, the transition from general carbon cycling processes to organic matter source identification could be strengthened. The authors may consider adding a clearer statement explaining why identifying organic matter sources is necessary for understanding carbon cycling in reservoirs.

Lines 103-113: Please provide additional information regarding sampling comparability:Were the same locations sampled during wet and dry seasons?How many sediment samples were collected from each reservoir? Was sediment depth standardized among sampling sites? These details are important for evaluating spatial and seasonal comparisons.

Lines 140: Additional analytical details should be provided:isotope measurement precision;laboratory reference standards; analytical reproducibility. These parameters are essential for isotope-based source apportionment studies.

Lines 180-190: Please clarify the rationale for selecting the three-end-member model. In particular: Were other potential sources considered? Was isotopic overlap among end-members evaluated? How was uncertainty propagated in the Bayesian model?

Lines 247: The manuscript reports that algal-derived organic matter became dominant during the dry season. The authors should clarify that this represents a relative contribution to sediment organic carbon rather than absolute algal biomass or productivity. A short clarification would prevent possible misunderstanding.

Lines 374: The manuscript attributes increased algal-derived organic matter during the dry season to prolonged residence time and enhanced primary production. However, isotopic mixing models cannot directly distinguish between:increased algal productionor enhanced preservation or decreased terrestrial input. Please acknowledge this uncertainty.

Lines 432-439: The manuscript discusses implications for carbon cycling. However, the connection between organic matter source changes and actual carbon burial efficiency remains somewhat indirect. Please avoid implying changes in carbon burial rates unless directly quantified.

Lines 437:The manuscript suggests that increased algal-derived organic matter may enhance greenhouse gas production. Since greenhouse gas fluxes were not measured in this study, this interpretation should be presented as a potential implication rather than a demonstrated mechanism.

Figure 4 isotope diagram: Please clarify:whether the confidence ellipses represent standard deviation, confidence intervals, or only visual guidance;whether all sediment samples fall within the defined mixing space.

Figure 6 and Figure 7:The figures contain substantial information but some labels are difficult to read. Please consider: increasing font size; explaining abbreviations more clearly; reducing redundant variables where possible.

Several minor language issues should be corrected: Maintain consistent use of: “wet season” and “dry season” instead of alternative expressions. Ensure isotope notation consistency: δ13C → δ¹³C, δ15N → δ¹⁵N. Ensure consistent abbreviations: terrestrial organic matter; autochthonous algal organic matter; sewage-derived organic matter.

Several sentences are relatively long and contain multiple clauses. For example, sentences describing SEM and BRT results could be divided into shorter sentences to improve readability.
Citation: https://doi.org/10.5194/egusphere-2026-3912-RC1
RC2: 'Comment on egusphere-2026-3912', Anonymous Referee #2, 29 Aug 2026

This manuscript summarizes research on the distribution characteristics of organic carbon concentrations and the estimation of their sources within a cascade reservoir system. Understanding the dynamics of organic matter—even in complex cascade reservoir systems—is essential for elucidating the global carbon cycle. In this context, the study addresses a topic relevant to current global environmental issues, focusing on a region along the Lancang River featuring a series of five reservoirs, with field surveys conducted during both the dry and wet seasons.
A key aspect of this manuscript is the analysis of organic matter dynamics and source estimation. However, only Total Carbon (TC) measurement results are presented; data for Total Organic Carbon (TOC) are missing. Furthermore, the description of the measurement process does not mention a carbonate removal step during sample pretreatment. Is TC assumed to be equivalent to TOC, or does separate TOC data exist? The manuscript does not clarify this point. If TOC was indeed measured, the data should be presented and incorporated into the discussion. This issue also affects the results shown in Figures 4 and 5. Figure 4 refers to the δ¹³C of sedimentary organic carbon; if TOC has been measured, those data should be presented, and the discussion regarding Figure 5 should compare the results with the sedimentary organic carbon data, rather than relying solely on percentage values. Additionally, while the sediment samples were collected from the surface layer (0–20 cm), they indicate vastly different organic matter sources between the dry and wet seasons. Basic information regarding sediment transport and deposition is required to explain this: is it the result of the erosion and relocation of the existing 20 cm sediment layer within each reservoir, or does a new 20 cm layer of sediment accumulate during the wet season? This should be explained, perhaps by citing existing research. Basic sediment data, such as grain size and water content, should also be provided, as differences in sediment characteristics between the wet and dry seasons constitute crucial baseline information.
Using carbon and nitrogen isotope ratios to estimate sources is a standard approach. Although this manuscript employs a three-component calculation model for source estimation, many of the measured data points fall outside the range defined by the three end-members. You can assess the validity of the results by presenting a table that details the calculations performed—showing either the estimation results based on individual data points or the analysis results derived from mean values. Furthermore, carbon content and carbon/nitrogen isotope ratios vary even within a single reservoir; the patterns of variation from the inlet to the outlet of a reservoir constitute a crucial dataset for examining the supply and transport of organic matter. I look forward to a detailed examination of these aspects.
Based on the above, the current explanation of the data is insufficient to verify the validity of the arguments presented. Consequently, I cannot recommend publication of the manuscript in its current form as an EGUsphere paper.

Minor comments:
Please provide detailed descriptions of the methods used to measure inorganic nitrogen components in the sediments and the sediment pretreatment procedures.
Fig. 1: The spatial relationship between the reservoirs is unclear. Additionally, the text is too small to read; the figure requires adjustment. The overview of the reservoir cascade is also difficult to understand; a diagram similar to Fig. 8 should be included. Revision is recommended.
Fig. 2: The text is too small to read easily. Increasing the font size is recommended.
Fig. 3: The text is too small to read easily. Increasing the font size is recommended.
Fig. 4: An explanation is needed regarding the criteria used to define the boundaries of the boxes shown.
Fig. 7: It is unclear what this figure is intended to illustrate.
Fig. 8: Panel (b) is not visible. Revision is required.

Citation: https://doi.org/10.5194/egusphere-2026-3912-RC2

Huimin Sun, Xudong Zhou, Bingcan Jiang, Yuqing Lin, Yuchen Chen, and Xingcheng Yan

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https://doi.org/10.5194/egusphere-2026-3912-supplement

Huimin Sun, Xudong Zhou, Bingcan Jiang, Yuqing Lin, Yuchen Chen, and Xingcheng Yan

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Short summary

Hydropower dams change how rivers store and recycle carbon, but their effects on sediment organic matter remain unclear. We studied five reservoirs in the Lancang River during wet and dry seasons using natural chemical fingerprints. Land-derived material dominated in the wet season, while algae became more important in the dry season. These findings improve our understanding of how dams influence carbon cycling and may support better river management under environmental change.


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