SEDIMENT DYNAMICS UNDER REAL WAVES

Noemie Fritsch, Guillaume Fromant, France Floc'H, Stephane Fischer, Yohan

Cobac, Charles Poitou, Christophe Prunier, Stephane Bertin, Emmanuel

Augereau, Marion Jaud, et al.

► To cite this version:

Noemie Fritsch, Guillaume Fromant, France Floc'H, Stephane Fischer, Yohan Cobac, et al. SEDIMENT DYNAMICS UNDER REAL WAVES. Coastal Sediment 2023, Apr 2023, Nouvelle Orléans (Louisiane), France. pp.1940-1951. hal-04974813

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https://hal.science/hal-04974813v1

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Distributed under a Creative Commons Attribution 4.0 International License
SEDIMENT DYNAMICS UNDER REAL WAVES

NOEMIE FRITSCH¹, GUILLAUME FROMANT², FRANCE FLOC’H¹, STEPHANE FISCHER³, YOHAN COBAC¹, CHARLES POITOU¹, CHRISTOPHE PRUNIER¹, STEPHANE BERTIN¹, EMMANUEL AUGEREAU¹, MARION JAUD¹, JONATHAN TANRIN¹

1. Laboratoire Géosciences Océan, Institut Universitaire Européen de la Mer, Rue Dumont d'Urville, Brest, France . noemie.fritsch@univ-brest.fr; france.floch@univ-brest.fr

2. Laboratoire d'Informatique Signal et Image de la Côte d'Opale, Université du Littoral Côte d'Opale, Calais, France. guillaume.fromant@univ-littoral.fr

3. Ubertone, Schiltigheim, France. stephane.fischer@ubertone.fr

**Abstract:** In order to improve sand transport models, the coastal engineering community needs data collected in natural conditions. In particular, sand transport processes in the wave boundary layer still need to be investigated, but the high temporal and spatial variability observed in this area make it complicated to monitor it properly. In order to address this issue, the first worldwide in situ deployment of UB-Lab 3C ©, based on Acoustic Concentration and Velocity Profiler technology, took place at Porsmilin beach, in 2022. First data collected with this instrument are processed, and averaged in order to obtain intra-wave velocity, concentration and flux for two categories of waves in the shoaling zone: low and high orbital velocity waves. Sediment concentrations under higher orbital velocity waves are stronger than under lower orbital velocity waves. This preliminary data set is promising, and further analysis should allow to extend existing knowledge on sand concentration and transport under real in situ waves in shallow environment.

**Introduction**

Beaches are among the most dynamic areas on Earth. In order to predict beach morpho dynamics, the coastal engineering community needs robust and reliable sand transport models, all the more so since water level rise due to climate change is bound to reshape the shoreline and to impact its dynamics in the years to come. Depending on the wave conditions and their initial state, beaches erode or accrete. While erosion mechanisms have been the focus of numerous publications in the last decade and are therefore quite well quantified in predictive models (van Rijn et al. 2011), mechanisms leading to accretion still remain poorly understood in comparison. Up until now, most data concerning sediment transport processes were collected in U-Tube facilities, which neglect free surface effects (Ribberink et al. 2008; Nielsen et al. 2002), or in large scale wave flumes, which also present a number of limitations (Hughes, 1993). It is known for instance that onshore-directed transport mainly occurs in the wave boundary layer via bed load, under moderate wave conditions (Mieras et al. 2019), but the relative contribution of different transport mechanisms leading to onshore-directed transport still needs
to be clarified. Furthermore, understanding suspended sediment load as well as bed load is necessary in order to predict morphological changes of beaches (Aagaard and Jensen, 2013).

Technical difficulties accounting for the lack of in situ sediment transport data are twofold: first, the complex logistic needed to deploy instruments in the field in such energetic environments and second, the lack of appropriate mean of colocalized velocity and concentration measurements. Indeed, in order to investigate boundary layer transport processes, high spatial temporal resolution is needed for an accurate quantification of these highly variable processes. Likewise, the investigation of turbulence in this very area also requires high temporal resolution. Colocalized measurements of sediment velocity and concentration are necessary to compute transport. In this frame, the Acoustic Concentration and Velocity Profiler (ACVP) technology has been developed and allows to obtain high resolution profiles of velocity and concentration (O(ms), O(mm)) (Hurther et al. 2011). Since then, the instrument has been turned into a prototype, the UB-Lab 3C ©, by Ubertone. This novel instrument, which has been made suitable for the marine environment, has been deployed for the first time in 2022 at Porsmilin Beach, Brittany, France, with the aim to better understand sediment conditions under waves. Targeting the observation of sand transport in the boundary layer, data collected with this instrument seem very promising and should allow to improve predictive sand transport models.

First, the deployment site and methods are presented. Then, preliminary results are revealed, based on first observations of velocity, concentration and cross-shore flux in the boundary layer under waves in the shoaling zone.

## Study sites and methods

### Study area

UB-Lab 3C © deployment took place on October 27th, 2022 at Porsmilin beach, Brittany, France (see Fig. 1 for localization). It is a pocket Beach located 15 km West of Brest. It is submitted to moderate south-west swell. It is a macrotidal sandy beach, with a median sand particle radius D50 = 320 micrometers (Dehouck, 2009). The long-shore dynamic observed on the beach is negligible compared to cross-shore dynamic.
<figure><img src="image_2.png" /><figcaption>Fig. 1. Localization of Porsmilin beach in Brittany, France. The right panel is a zoom on the area, and the location of the beach is depicted by the small black square.</figcaption></figure>

<figure><img src="image_3.png" /><figcaption>Fig. 2. Mooring (left) and focus on UB-Lab 3C © (right), circled in red.</figcaption></figure>

## UB-Lab 3C deployment method

UB-Lab 3C © is part of a whole set of instruments deployed on a dedicated platform, (Fritsch et al. 2022) in order to study hydrodynamics and sediment transport in the water column (see Fig. 2).

The mooring was deployed at low tide in the intertidal zone of the beach. Its location is represented by the big red dot on the map of Fig. 3. Instruments
then recorded hydrodynamic and sediment transport data during one tidal cycle, and the platform was retrieved during the following low tide. That day, the wave height was approximately 0.75 m at the beach and 1.25 m offshore.

<figure><img src="image_4.png" /><figcaption>Fig. 3. Localization of the mooring on the beach (red dot).</figcaption></figure>

<figure><img src="image_5.png" /><figcaption>Fig. 4. Water elevation</figcaption></figure>
## UB-Lab 3C features

Using UB-Lab3C, which relies on Doppler effect, allowed to obtain velocity profiles (Hurther et al. 2011). We applied acoustical inversion techniques on backscattered intensities (Thorne and Hanes, 2002), to retrieve sediment concentration in the boundary layer. Since concentration and velocity are measured in the same volume, they can be regarded as colocalized measurements. Quasi instantaneous cross-shore fluxes were then computed by multiplying colocalized concentration and velocity profiles. The sand bed is defined as corresponding to the location of the maximum backscattered intensity.

## Studied data

In Fig. 4, the water elevation above the mooring over high-tide is represented. It was obtained thanks to pressure data (collected at 5Hz rate). The water height reached 4.5m above the mooring during the deployment. The time series studied below were recorded in the shoaling zone. They are represented in Fig. 4. Those specific time series were chosen because separation between waves was possible. The first studied time series (green curve and dot in Fig. 4) starts at 14h48min53s (UTC) and stops at 4H51min10s. The second studied time series (red curve and dot on Fig. 4) starts at 14H54min5s and stops at 14H56min11s. The ‘free stream’ velocity time series corresponding to those recordings are displayed next to the water elevation curve, in the boxes on Fig. 4. The ‘free stream’ velocity corresponds to the cross-shore velocity average of the cells 30 to 35 in the profile recorded by the UB-Lab 3C (those cells that are quite high in the velocity profile, there are 100 cells in a profile recorded by the UB-Lab 3C ©).

## Data processing

Since measurements are quasi instantaneous, they are submitted to noise problems. In order to remain consistent with previous studies realized under waves (Fromant et al 2019, Hurther and Thorne 2011), data were averaged on several waves. Waves from both time series were cut with a zero-crossing method. Then, indices retrieved from this velocity cutting were applied on concentration and velocity profiles recorded by the UB-Lab 3C. This method is explained on Fig. 5. This way, concentration and velocity profiles under each studied wave were obtained. Then, those waves were divided into two groups based on the value of their orbital velocity.
<figure><img src="image_6.png" /><figcaption>Fig. 5. First line: free stream velocity of the first time series, and second line: corresponding concentration under the waves. The concentration profiles are cut following the indices retrieved after the wave cutting thanks to a zero-crossing method (vertical dotted thick black lines).</figcaption></figure>

## Wave characteristics

The first group of waves corresponds to the ‘low orbital velocity’ waves (category 1), and the second group the ‘high orbital velocity’ waves (category 2). The characteristics of the mean free stream of each category are displayed in Table 1. T is the wave period in seconds, Asy is the wave asymmetry computed as:

$$Asy = a_{max}/(a_{max}-a_{min}) (1),$$

with $a_{max}$ the maximum acceleration value during the studied wave cycle, and $a_{min}$, the minimum acceleration value. Sk is the wave skewness computed as:

$$Sk = u_{max}/(u_{max}-u_{min}) (2),$$

with $u_{max}$ the maximum velocity value during the studied wave cycle and $u_{min}$ the minimum velocity value. Aorb is the orbital velocity, computed following Ribberink et al. (2008):

$$Aorb = \sqrt{2}U_{rms}T/(2\pi) (3),$$

with $U_{rms}$ the root mean square of the wave velocity.
<table><caption>Table 1. Wave parameters for both categories.</caption><thead><tr><th>Parameter</th><th>Value for cat. 1</th><th>Std</th><th>Value for cat. 2</th><th>Std</th></tr></thead><tbody><tr><td>T (s)</td><td>9.2</td><td>1.4</td><td>9</td><td>1.4</td></tr><tr><td>Asy (1)</td><td>0.52</td><td>0.11</td><td>0.51</td><td>0.07</td></tr><tr><td>Sk (2)</td><td>0.53</td><td>0.12</td><td>0.53</td><td>0.13</td></tr><tr><td>Aorb (m/s) (3)</td><td>0.12</td><td>0.05</td><td>0.27</td><td>0.07</td></tr></tbody></table>

For each category of waves, velocity, concentration and flux data are studied. Those quantities are represented on Figures 6, 7 and 8 for the category 1 (waves with low orbital velocity) and on Figures 9, 10 and 11 for the category 2 (waves with high orbital velocity).

## Results

<figure><img src="image_7.png" /><figcaption>Fig. 6. Free stream wave velocity (first line), intra wave mean velocity color plot (middle graph) and mean wave-averaged velocity profile (right panel) for the low orbital velocity waves.</figcaption></figure>
<figure><img src="image_8.png" /><figcaption>Fig. 7. Free stream wave velocity (first line), intra wave mean concentration color plot (middle graph, in logarithmic scale) and mean wave-averaged concentration profile (right panel) for the low orbital velocity waves.</figcaption></figure>

<figure><img src="image_9.png" /><figcaption>Fig. 8. Free stream wave velocity (first line), intra wave mean flux color plot (middle graph) and mean wave-averaged flux profile (right panel) for the low orbital velocity waves.</figcaption></figure>
<figure><img src="image_10.png" /><figcaption>Fig. 9. Free stream wave velocity (first line), intra wave mean velocity color plot (middle graph) and mean wave-averaged velocity profile (right panel) for the high orbital velocity waves.</figcaption></figure>

<figure><img src="image_11.png" /><figcaption>Fig. 10. Free stream wave velocity (first line), intra wave mean concentration color plot (middle graph, in logarithmic scale) and mean wave-averaged concentration profile (right panel) for the high orbital velocity waves.</figcaption></figure>
<figure><img src="image_12.png" /><figcaption>Fig. 11. Free stream wave velocity (first line), intra wave mean velocity color plot (middle graph) and mean wave-averaged velocity profile (right panel) for the high orbital velocity waves.</figcaption></figure>

## Structure of the figures

On each of the above-displayed figures (Fig. 6 to 11), the free stream wave velocity cycle is displayed in the first line, then the color plot represents the intrawave velocity (Fig. 6 and 9), concentration (Fig. 7 and 10) and cross-shore flux (Fig. 8 and 11). The vertical profiles on the color plots correspond to the phase-averaged profiles at specific wave events inside a wave cycle: the crest to trough flow reversal, the maximum offshore velocity, the trough to crest flow reversal and the maximum onshore velocity events. The thick black horizontal line corresponds to the bed, detected as explained earlier. Finally, the panel on the right corresponds to the wave-averaged profile of velocity, concentration or cross-shore flux.

## Velocity data

In terms of velocity, it can be observed that in the 'high orbital velocity' case (Fig. 9), the intrawave velocity values are higher than in the 'low orbital velocity' case (Fig. 6).
## Concentration data

The intrawave concentration dynamics under the category 2 mean wave (Fig. 10) are more important than under the category 1 mean wave (Fig. 8). Notably, there is a high concentration patch at $t/T = 0.8-1$ for the high orbital velocity waves, after the trough to crest flow reversal and during the onshore half cycle of the wave. In this case, since sediment has not had time to resettle before the end of the onshore half cycle, phase lagging effects might be observed (Ribberink et al. 2008, O'Donoghue and Wright 2004). Sediment mobilized during the onshore half cycle might be advected offshore during the offshore half wave cycle. This phenomenon does not seem to be observed for the low orbital velocity case.

## Flux data

The measured intrawave cross shore flux values are higher for the category 2 mean wave (Fig. 8) than for the category 1 mean wave (Fig. 11). This is consistent with the higher concentration values observed in Fig. 10 than in Fig. 7. On the mean flux profile (right panel of Fig. 10), it is clear that a strong wave-averaged onshore flux can be observed close to the sand bed, whereas an offshore-directed flux can be observed higher in the water column. This result is consistent with previous studies (Mieras et al, 2019; Brenner et al., 2018).

## Discussion and Conclusion

UB-Lab 3C © first deployments allowed to obtain colocalized high resolution measurements of velocity and concentration profiles in natural conditions. First data collected at Porsmilin beach, Brittany, France, show how promising this technology is in terms of boundary layer transport observations. For a better understanding of sand transport processes, UB-Lab 3C © data should be processed in the light of data recorded higher in the water column (for instance, with acoustic Doppler velocimeters and concentration profilers). This is why UB-Lab 3C © is deployed on a platform containing a whole set of instruments. Data set collected with the mooring (Fig. 2) should offer a complete overview of cross-shore sediment processes on sandy beaches.

Several deployments are yet to be done, in particular in the coming winter at Porsmilin Beach in Brittany, France. Those specific deployments aim at targeting the observation of seasonal accretive conditions that can be observed after stormy events on sandy beaches. It is hoped that data collected with this UB-Lab 3C ©, associated with data from other instruments deployed in the mooring will deepen knowledge on cross-shore sand transport in natural conditions,
particularly under accretive conditions.

## Acknowledgements

This work is part of ANR project WEST (ANR-20-CE01-0009), it was also supported by Geo-Ocean lab (UMR6538), ISblue project (ANR-17-EURE-0015) and co-funded by a grant from the French government under the program "Investissements d'Avenir". Part of the equipment used in this experiment was funded by the French Government, the European Fund for Economic and Regional Development, the Regional Council of Brittany, and authorities of Finistère as part of the CPER project O3DO (2016-2020). Special thanks to ODYSC team for support on field experiments, P2I, Albert Lucas sailors and IUEM divers.

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