the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 02 Jun 2025
Implementing Riverine Biogeochemical Inputs in ECCO-Darwin: a Critical Step Forward for a Pioneering Data-Assimilative Global-Ocean Biogeochemistry Model
Abstract. Resolving riverine biogeochemical inputs in ocean biogeochemistry models is pivotal for capturing the spatiotemporal variability of nutrients and carbon in coastal regions and in the global ocean. ECCO-Darwin is a pioneering data-assimilative global-ocean biogeochemistry model, which, to date, has focused on the pelagic zone. As a key step towards improving the representation of coastal regions in ECCO-Darwin, we add lateral inputs of carbon, nitrogen, and silica and evaluate the model response with regard to primary production and ocean carbon cycling. We generate riverine inputs by combining point-source freshwater discharge from JRA55-do with the Global NEWS 2 watershed model, accounting for lateral inputs from 5171 watersheds worldwide. While adding carbon and nutrients along with freshwater improves biogeochemical skill in river plume regions and coastal waters, the open-ocean response may be overestimated due to an excess of carbon and nutrients advected offshore. This highlights the need for a more nuanced representation of land-to-ocean and nearshore processes for quantifying how global-ocean primary production and carbon cycling respond to land-to-ocean inputs.
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2025-1707', Anonymous Referee #1, 04 Sep 2025
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AC1: 'Reply on RC1', Raphael Savelli, 17 Oct 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-1707/egusphere-2025-1707-AC1-supplement.pdf
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AC1: 'Reply on RC1', Raphael Savelli, 17 Oct 2025
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RC2: 'Comment on egusphere-2025-1707', Anonymous Referee #2, 22 Sep 2025
The manuscript describes impacts of adding observationally constrained rates of riverine input of DIC, DOC, DIN, DON and DSi to the global multi-functional type biogeochemical ECCO-Darwin model. The impact of various combinations of riverine carbon and nutrient supplies on model-data misfits with respect to surface pCO2 and air-sea CO2 fluxes are investigated, and some improvements are found, particularly when riverine DOC supply is simulated.
The study adds some information to other recent efforts to address the historical lack of realistic descriptions of the land-ocean interface in current global marine biogeochemical models. Results are relatively unsurprising, i.e. CO2 emissions from the ocean increase when DOC with a lifetime of 100 days is added to the ocean surface at river mouths, and CO2 uptake by the ocean increases in some regions where additional nutrients are added by rivers. The design of the study results in only limited gain in terms of scientific understanding. I have three main concerns about the present version of the study that limit the gain in scientific understanding:- First, the riverine input of biogeochemical tracers is added to a calibrated model run without riverine input, which -presumably- tries to make up for the missing river input by adjusting model parameters or other control variables. The model configuration with riverine input is not calibrated. Thus, the comparison is between a calibrated and an uncalibrated model version. Difficult to asses. Results are more a sensitivity analysis rather than an assessment of structural model improvements.
- Second, the simulations with riverine inputs are, if I understand correctly, run only from year 1992 to 2019, i.e. 28 years, of which the first 8 years are taken as spin-up, and 2000-2019 as analysis period. Particularly for the addition of nutrients, this is likely insufficient to reach a steady state. Some time series of relevant model output (NPP in different regions, nutrient and carbon concentrations) needs to be shown to allow the reader to assess the issue of inferring general results from short decadal-scale simulations only.
- Third, several implicit and explicit assumptions may have relevant impacts on the results shown. Some assumptions are stated, e.g. the assumed 100 day lifetime of riverine DOC, or the assumption of zero phosphorus input from land while dissolve silica is included, others are not, such as the presence of denitrification and/or nitrogen fixation. In order to provide “a critical step forward’, as stated in the title of the manuscript, a more comprehensive sensitivity analysis with respect to major assumptions would be required, possibly extending the analysis to riverine supply of phosphorus.
Overall, I find the direction of the manuscript scientifically useful, but the results and the analysis shown do not match the high ambitions raised by the title of the manuscript. There are a number of individual points that need attention, as listed below. I recommend a major revision before the manuscript should be accepted for publication.
Individual points:l.17 ‘slower’ than what?
l.24/25 ‘excess of alkalinity relative to DIC’ Does this refer to concentrations or to fluxes? How does this fit to outgassing (a flux)?
l.27 There does not always have to be alkalinity production, e.g. when calcifiers are involved.
l.28 ‘estimated coastal-ocean sink’ of what ? Total carbon, riverine carbon, marine carbon?
l.84 does ‘particulate organic matter’ mean detritus or phytoplankton and zooplankton as well?
l.93. Does this mean there is only 8 years of spin-up? Is the biogeochemistry in some form of steady state after such a short period, and if so, in what regions?
l.96ff The model evaluation addresses surface pCO2 and air-sea fluxes of CO2 only. It would be useful to provide some assessment of simulated NPP, biomass and nutrient distributions.
l.138 Would be good to add if the extreme value was high or low, and also provide a very brief explanation for why (only) this value had to be corrected.
Table 2: The units are unclear and likely wrong. If Tg/yr, then the assumed stoichiometry of at least DOC, DIN needs to be provided. References provided in Table 2 are too generic, e.g. some labeled 1-3 do not even mention DSi.
Fig.3: color scale does not seem optimal. A log-scale might allow easier interpretation.
Table 3. Air-sea CO2 fluxes seem to have the wrong sign
l.186. Presumably t_DIC plays only a small role compared to t_DOC because of the assumed compensation to DIC input by ALK input? Might be good to say this here.
l.224 ‘and freshwater discharge’ is misleading. If I understand correctly, freshwater discharge is identical in all simulations?
l.235 ‘of dissolved carbon input’ - should it read dissolved organic carbon input?
l.237 please provide a brief explanation of why model skill decreases here.
l.248 why do you think input might be overestimated rather than underestimated? Could there be positive feedbacks, for example via redox-sensitive Fe and P cycling?
l.282ff would be good to mention possible effects of explicitly accounting for denitrification, as done in some previous studies cited by the authors.
l.296 why overestimated and not underestimated?
l.297 why only faster degradation and not slower?
l.332 I do not understand ‘lack of nitrogen and silica-limited taxa’ The model explicitly resolves diatoms and 4 other phytoplankton species. Aren’t diatoms nitrogen and silica-limited in your model?
l.362. I do see that this ‘study is a critical step forward’. This would have to be justified in more detail.
l.403 why only overestimated and not underestimated?Citation: https://doi.org/10.5194/egusphere-2025-1707-RC2 -
AC2: 'Reply on RC2', Raphael Savelli, 17 Oct 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-1707/egusphere-2025-1707-AC2-supplement.pdf
Data sets
Compiled outputs and code R. Savelli https://doi.org/10.5281/zenodo.15512392
Model code and software
ECCO-Darwin biogeochemical runoff GitHub R. Savelli https://github.com/MITgcm-contrib/ecco_darwin/blob/master/v05/1deg_runoff
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- 1
In their manuscript, Savelli et al. describe their implementation of river fluxes in the ECCO-Darwin model, and evaluate the performance of the model after this implementation. The paper is well written, the methods are generally sound, and the analysis of the effects of river fluxes in the model is well reflected and seems robust. The manuscript is also well suited for GMD. While I think the paper is close to publication, it might lack a bit of really novel aspects, since the implementation of river fluxes has been described in a few GOBMs in recent years, as cited in the study. I believe it would be relatively straight forward to add a few more interesting aspects originating from the implemention into the ECCO-Darwin model specifically, and would strongly recommend to do this (phytoplankton species shifts? More detailed process-based explanations of divergent FCO2 responses in the different regions?). I also have a few major points that should be clarified and I hope they will also improve the manuscript.
Regnier, P., Resplandy, L., Najjar, R.G. et al. The land-to-ocean loops of the global carbon cycle. Nature 603, 401–410 (2022). https://doi.org/10.1038/s41586-021-04339-9
Liu, X., Dunne, J. P., Stock, C. A., Harrison, M. J., Adcroft, A., & Resplandy, L. (2019). Simulating Water Residence Time in the Coastal Ocean: A Global Perspective. Geophysical Research Letters, 46, 13910–13919. https://doi.org/10.1029/2019GL085097
Lacroix, F., Ilyina, T., Laruelle, G. G., & Regnier, P. (2021). Reconstructing the preindustrial coastal carbon cycle through a global ocean circulation model: was the global continental shelf already both autotrophic and a CO2 sink?. Global Biogeochemical Cycles, 35, e2020GB006603. https://doi.org/10.1029/2020GB006603
Specific Comments
L17 “At the same time, most of the refractory part of riverine organic carbon is transported offshore from river mouth regions as it is remineralized at slower turnover rates.” This is a bit of a jump from the previous sentence. Did you mean to add that river transports play a central role for biogeochemical processes in the coastal ocean first?
L25 I would also add that terrestrial OC is thought to cause a source of CO2 to the atmosphere (after degradation).
L27 “Globally, this lateral input increases ocean primary productivity and contributes to an estimated coastal-ocean sink of∼ 0.25 Pg C yr−1, which is roughly 17% of the global-ocean sink (Cai, 2011; Lacroix et al., 2021; Gao et al., 2023).”
I would use Dai et al. (2022) and Resplandy et al. (2024) here as more recent estimates:
Dai, M., Su, J., Zhao, Y., Hofmann, E. E., Cao, Z., Cai, W. J., ... & Wang, Z. (2022). Carbon Fluxes in the Coastal Ocean: Synthesis, Boundary Processes, and Future Trends. Annual Review of Earth and Planetary Sciences, 50, 593-626.
Resplandy, L., Hogikyan, A., Müller, J. D., Najjar, R. G., Bange, H. W., Bianchi, D., ... & Regnier, P. (2024). A Synthesis of Global Coastal Ocean Greenhouse Gas Fluxes. Global Biogeochemical Cycles, 38(1), e2023GB007803.
L157 “Additionally, the data-based products exhibited lower surface-ocean pCO2 compared
to ECCO-Darwin Baseline (Figure 1i) in the Arctic Ocean and near the periphery of Antarctica; regions where observations are highly limited in space and time.”
Could this potentially also be a sea ice representation problem?
L193 “the increase of NPP” -> The areal increase in NPP?
L197 “In Baseline, ARCT results in a CO2 uptake of roughly 0.21 Pg C yr−1.” This reads as if ARCT was a simulation, would slightly revise the wording.
Table 4. In terms of global FCO2, I would add the estimates of Aumont et al., 2002 and Lacroix et al., 2020. The table also only shows model derived estimates, whereas some budget-derived estimates also exist and are, as of now, preferably used in assessments (e.g. Regnier et al., 2022).
Aumont, O., J. C. Orr, P. Monfray, W. Ludwig, P. Amiotte-Suchet, and J.-L. Probst (2001), Riverine-driven interhemispheric transport of carbon, Global Biogeochem. Cycles, 15(2), 393–405, doi:10.1029/1999GB001238.