the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 03 Jul 2025
Wave-induced sediment resuspension in the Finnish Archipelago, Baltic Sea: Combining small-scale in situ measurements and large-scale numerical model simulations
Abstract. Sediment resuspension, driven by wind-wave-induced shear stresses, plays a crucial role in coastal water quality, biogeochemical cycles, and the dispersal of pollutants and organisms. If the shear stress from waves exceeds an erosion threshold, or critical shear stress, sediments are resuspended from the seabed. This critical shear stress is an essential parameter in sediment transport models, as it determines sediment erodibility. In this study, we implemented a high-resolution (20 m) spectral wave model to simulate wave-induced near-bottom velocities across the complex archipelago of southwestern Finland. Near-bottom shear stresses from the model and their respective critical values were estimated using seabed data, with results compared to critical shear stress values obtained through laboratory testing of in situ sediment samples. Model data suggested that the critical shear stress could be exceeded over 70 % of the time in certain areas. However, laboratory-determined critical shear stresses were 3–8 times higher than those derived from the model based on median grain size, with modelled shear stresses rarely exceeding the measured critical values. These discrepancies likely stem from unaccounted-for biological and biogeochemical properties of the sediments, which cannot be captured by a simple grain size-based model. We estimate that the accuracy of the wave model data used in this study are of secondary importance compared to the uncertainty of determining the critical shear stress.
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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2025-2936', Anonymous Referee #1, 07 Aug 2025
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RC2: 'Comment on egusphere-2025-2936', Anonymous Referee #2, 06 Oct 2025
General comments
Mixed sediments are a complex problem and not well integrated into numerical models of sediment dynamics and transport. In situ data are limited and often site specific due to the variability of biogeochemical properties of mobile sediment. Improving understanding of the differences between modelled and observed sediment erosion and resuspension should lead to the development of better models of sediment processes. This work uses a novel high spatial resolution model to highlight the amount of uncertainty in coastal models of hydrodynamics and sediment processes, when compared to in situ samples, and variability on small spatial scales.
The figures could be better thought out, to make it easier for the reader to compare and interpret them. Many statements are given without references to support them and the reader cannot follow them up. The work of Joensuu et al. is relied on for the in-situ data, but their contribution and the authors contribution is not always clear. Key information on the source of the bathymetry and its accuracy and quality is missing.
Specific comments
Line 26: Exceeding the critical shear stress for motion doesn’t always lead to resuspension, it might just be bedload. It implies here that once the critical limit is exceeded suspension will happen. Please clarify.
Section 2.1.2 mentions ‘variation in sediment surface characteristics (e.g. bedforms, biofilms) across sites’, but this data is not shown or used. Grain size class % and biological factors are key factors in sediment resuspension, which were measured by Joensuu et al. (2018; 2020), but not fully integrated into this work.
Section 4 – Discussion: What was the bathymetry source used? And were there any problems with it? Also, the section could be better referenced, many statements are made that aren’t supported by the results. Joensuu et al. give % clay fraction but there is no mention of how cohesive sediment could affect these results. Biological factors are highly variable, and effects difficult to account for, but as the clay has been measured could it be used to reduce uncertainty in the model results? The EMODNET data set is not explicitly mentioned in the discussion and, given that this represents the greatest uncertainty, I wanted to know more about where the data came from and how it was put together. Although it is out of scope of this work, examining or re-analysing the raw data used by EMODNET could result in a better understanding of the problem of sediment variability. What survey work would be needed to get a data set that could significantly reduce the uncertainty of a resuspension model?
Access to the in-situ sediment sample data set was not made available for the reviewers to check, though the Zenodo record exists. The details of where the wave buoy data is archived were not given.
Technical corrections
Lines 17-20: citations?
Line 80: Citation for DWR-G4 Directional Waverider? Is it the same for the Waverider Mk-III?
Figure 2: What is the data source of the bathymetry contours and coastline? The area of this figure doesn’t correspond to the bottom classification and model figures, which is a bit confusing when trying to link the bathymetry to the bed type and model results. Site 13 isn’t listed in Table 2.
Line 93: citations here for those unfamiliar with EROMES coring.
Lines 109-110: What is the data source of the bathymetric data and land-sea mask?
Figure 4: where are the latitude and longitude tick marks, and land-sea mask? It is difficult to relate this to figure 2. Marking the sites of the cores would be useful to understand how good the EMODNET data is?
Line 141: Citation to back this up. Finer grains are generally the first to be suspended, but coarser grains will be mobilized first as bedload. Please clarify that you are writing about wave suspension. Is this just for waves and non-cohesive sediment? This statement seems a bit over simplified without a citation to back it up.
Line 149: citation for this equation.
Line 165: citation please.
Line 168: Soulsby and Whitehouse improved Shield’s curve with extra data, not the parameter.
Line 193: Tvärminne research station is not marked on the model data figures. 23° 06’ -23° 12’is easier to find. Please mark the areas you are writing about on the figures so that readers can understand better. Bathymetry contour lines would help with the interpretation of shallow and deep areas, though this could clutter up the figure, contours every 10- 20 m depth could make the interpretation easier than switching between figures 1 & 4 and model figures.
Figure 6: The figure has a title of Tvärminne but it is not shown in the figure. Place labels, e.g. for Tvärminne and Täktbukten could be used to highlight interesting areas where the exceedance is high (as mentioned in line 200) and discuss these individual sites.
Lines 252-4: Were these measurements carried out by Joensuu et al.? Cite them if so.
Line 259: The sample sites aren’t marked on figures 7 or 8, so it is hard to see this.
Table 2: the grain size measurements are from Joensuu et al. (2018; 2020) and should be cited here.
Line 299: remove ID from ‘stIDress’.
Lines 340-367: Appendix A - Citations please.
Line 442: ‘https://doi.org/’ is duplicated.
Line 445: Full reference so that it may be found. An English translation can be found here: http://authors.library.caltech.edu/25992/1/Sheilds.pdf
Citation: https://doi.org/10.5194/egusphere-2025-2936-RC2
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- 1
Review of: “Wave-induced sediment resuspension in the Finnish Archipelago, Baltic Sea: Combining small-scale in situ measurements and large-scale numerical model simulations”
Dear Editor,
The authors present an interesting case study on wave resuspension of sediment in the Finnish Archipelago. The authors have used a spectral wave model to calculate bottom orbital velocities and bed shear stresses, and use this to estimate the threshold of motion for the sediments in the region. Interestingly, the authors have also measured the threshold of motion from sediment samples using a laboratory which has been published (Joensuu et al. 2020). As I have little experience of spectral wave modelling, I will keep my reviews focused on the sediments. However I would ask if wind forcing at a temporal resolution of 3 hours is enough to adequately resolve the storms?
The authors find a large discrepancy between the predicted and measured critical shear stresses, and attribute this to biological and/or biogeochemical properties of the sediments. Concerningly, there is no reporting of the biogeochemical properties of the sediments, so it is difficult assess how accurate their claim is.
The authors seem to think this is the only way to explain the differences in measured and predicted threshold of motion for the sediments – but this is unfounded. Bulk density of sediment has been shown to have the largest effect on the threshold of motion (Thompson et al. 2019). Mixed grain sizes (for example, a bimodal distribution) can increase the threshold of motion (Staudt et al. 2017; McCarron et al. 2019). In short, the manuscript is, at present, not representing the state of the science. The authors need to address their simplification of the problem.
Upon reading (Joensuu et al. 2020), I see that all the relevant information has been collected, but not used in the present work. I encourage the authors to utilise this information, particularly to follow the work of Thompson et al. (2019), who were able to adjust the threshold of motion for their sediment based upon an array of sedimentary and biological variables. As such, I recommend major revisions as a reanalysis of the data is necessary for the manuscript to be up to date with the state of the science.
Comments to the authors.
Dear authors, I read your manuscript with interest. This is tricky subject, and I think you need to include some of the sedimentary information from (Joensuu et al. 2020) into your estimate of the threshold of motion of the sediments and use the work of (Thompson et al. 2019) to recalculate your thresholds of motion - it seems like an approach similar to their “model 1” would work well. You seem to have limited your explanation of the difference between modelled and measured threshold of motion to only biological processes, yet there is little reason given in the manuscript to justify this. There are numerous reasons why such a difference could occur, much of this is covered in Thompson et al. 2019, and other papers.
Some specific comments:
Equation 8 – the Soulsby Whitehouse equation is incorrectly written, it should be:
(see attached image)
I also highlight to the authors that this is the equation for initiation of bedload, not suspended load. There is a Soulsby-Whitehouse like equation for this, fitted by Van Rijn (unpublished, the source is his website):
(see attached image)
I have calculated the suspension values for their grain sizes (Their table 1, my numbers in red). It would appear they have used the correct version of the Soulsby Whitehouse equation, and it was just written wrong in the manuscript.
Sediment class
Grain size (mm)
theta crit (N m−2)
theta sus(N m−2)
Mud to muddy sand
0.09
0.14
0.16
Sand
0.34
0.21
0.37
Coarse sediments
2.00
1.20
3.06
Mixed sediments
0.15
0.16
? mixed ? (0.21)
Boulders
200.00
178.10
323
The difference between theta crit and theta sus could account for most of the discrepancy the authors have found, especially for the larger grain sizes. It is unclear how they have arrived at their bed shear stress estimate for “mixed” sediments, it appears to be just using the median particle size, which is unjustified. This is unwise as larger clasts (such as gravels and boulders) can “armor” the bed and reduce mobility of all sediments (Wiberg et al. 1994; Vericat et al. 2006). Likewise fine sediments (< sand size) can add cohesion to the bed and reduce hyporheic flow, impacting sediment mobility (Blois et al. 2014; Fox et al. 2014; Parsons et al. 2016; Perret et al. 2018; 2023).
In particular, i recommend to the authors that they read the paper by Thompson et al., (2019), as this paper works through many of the issues with defining a threshold of motion in complicated sediments, including those with biological controls (for instance, Thompson et al., include the concentration chlorophyll-A in their “Model 1”). Moreover, that work found that the bulk density and porosity of the sediment was the overriding control on benthic resuspension, I suggest you try and include this in your work based on the data available in (Joensuu et al. 2020).
References.
Blois, Gianluca, James L. Best, Gregory H. Sambrook Smith, and Richard J. Hardy. 2014. ‘Effect of Bed Permeability and Hyporheic Flow on Turbulent Flow over Bed Forms’. Geophysical Research Letters 41 (18): 6435–42. https://doi.org/10.1002/2014GL060906.
Fox, Aryeh, Fulvio Boano, and Shai Arnon. 2014. ‘Impact of Losing and Gaining Streamflow Conditions on Hyporheic Exchange Fluxes Induced by Dune‐shaped Bed Forms’. Water Resources Research 50 (3): 1895–907. https://doi.org/10.1002/2013WR014668.
Joensuu, Mari, Conrad A. Pilditch, and Alf Norkko. 2020. ‘Temporal Variation in Resuspension Potential and Associated Nutrient Dynamics in Shallow Coastal Environments’. Estuaries and Coasts 43 (6): 1361–76. https://doi.org/10.1007/s12237-020-00726-z.
McCarron, Connor J., Katrien J.J. Van Landeghem, Jaco H. Baas, Laurent O. Amoudry, and Jonathan Malarkey. 2019. ‘The Hiding-Exposure Effect Revisited: A Method to Calculate the Mobility of Bimodal Sediment Mixtures’. Marine Geology 410 (April): 22–31. https://doi.org/10.1016/j.margeo.2018.12.001.
Parsons, Daniel R., Robert J. Schindler, Julie A. Hope, et al. 2016. ‘The Role of Biophysical Cohesion on Subaqueous Bed Form Size’. Geophysical Research Letters 43 (4): 1566–73. https://doi.org/10.1002/2016GL067667.
Perret, Emeline, Céline Berni, Benoît Camenen, Albert Herrero, and Kamal El Kadi Abderrezzak. 2018. ‘Transport of Moderately Sorted Gravel at Low Bed Shear Stresses: The Role of Fine Sediment Infiltration’. Earth Surface Processes and Landforms 43 (7): 1416–30. https://doi.org/10.1002/esp.4322.
Perret, Emeline, Benoit Camenen, Céline Berni, Kamal El kadi Abderrezzak, and Benjamin Renard. 2023. ‘Uncertainties in Models Predicting Critical Bed Shear Stress of Cohesionless Particles’. Journal of Hydraulic Engineering 149 (4): 04023002. https://doi.org/10.1061/JHEND8.HYENG-13101.
Staudt, Franziska, Julia C. Mullarney, Conrad A. Pilditch, and Katrin Huhn. 2017. ‘The Role of Grain-Size Ratio in the Mobility of Mixed Granular Beds’. Geomorphology 278 (February): 314–28. https://doi.org/10.1016/j.geomorph.2016.11.015.
Thompson, C.E.L., M.E. Williams, L. Amoudry, et al. 2019. ‘Benthic Controls of Resuspension in UK Shelf Seas: Implications for Resuspension Frequency’. Continental Shelf Research 185 (September): 3–15. https://doi.org/10.1016/j.csr.2017.12.005.
Vericat, Damia, Ramon J. Batalla, and Celso Garcia. 2006. ‘Breakup and Reestablishment of the Armour Layer in a Large Gravel-Bed River below Dams: The Lower Ebro’. Geomorphology 76 (1–2): 122–36. https://doi.org/10.1016/j.geomorph.2005.10.005.
Wiberg, Patricia L., David E. Drake, and David A. Cacchione. 1994. ‘Sediment Resuspension and Bed Armoring during High Bottom Stress Events on the Northern California Inner Continental Shelf: Measurements and Predictions’. Continental Shelf Research 14 (10–11): 1191–219. https://doi.org/10.1016/0278-4343(94)90034-5.