Nearshore sediment resuspension and bed morphology.

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1 Nearshore sediment resuspension and bed morphology Nearshore sediment resuspension and bed morphology. Charlie E. L. Thompson, Hachem Kassem, and Jon Williams Ocean and Earth Science, University of Southampton, National Oceanography Centre Southampton, European Way, Southampton, SO14 3RE, UK ABP Marine Environmental Research Ltd, Quayside Suite, Medina Chambers, Town Quay, Southampton, SO14 2AQ, UK ABSTRACT Thompson, C.E.L., Kassem, H. and Williams, J., BARDEX II: Nearshore sediment resuspension and bed morphology. In: Conley, D.C., Masselink, G., Russell, P.E. and O Hare, T.J. (eds.), Proceedings 12 th International Coastal Symposium (Plymouth, England), Journal of Coastal Research, Special Issue No. 65, pp , ISSN Sediment resuspension in the region outside the surf zone is known to contribute to the morphological response of barrier beaches to wave forcing, such as onshore bar migration processes. However, few measurements in this region exist, limiting our ability to quantify its contribution. These processes are complicated by the presence of bedforms in the nearshore, which alter the sand transport processes while modifying bed roughness in a complex feedback mechanism. The Hydralab IV funded BARDEX II experiments, which took place in the Delta Flume in 2012, were used to provide measurements of these processes in the nearshore of a sandy barrier beach (D 50 = 0.42mm) under a range of wave conditions (Hs = m; Tp = 4 12 s) and water levels, through deployment of a suite of acoustic instruments measuring flow velocity, near-bed turbulence, sediment resuspension profiles and bed morphology in crosssection and plan view. Initial findings indicate that sediment suspension in the nearshore appears to be controlled by a combination of near-bed turbulent bursting processes which results in near-instantaneous low concentration suspensions restricted to the bottom boundary layer, and vortex shedding from bedforms which results in higher concentration suspensions which are larger in scale than vertical eddy sizes, and perpetuate outside of the bottom boundary layer. ADDITIONAL INDEX WORDS: Nearshore sediment transport, near-bed turbulence, bed roughness. INTRODUCTION Understanding beach sediment transport processes is essential to predicting their long-term evolution, assessing sediment budgets, and monitoring a wide range of coastal engineering activities (e.g. beach nourishment, coastal protection, and aggregate dredging). A growing body of literature is emerging for the highly complex swash and surf zones (e.g. Butt and Russel, 1999; Elfrink and Baldock, 2002; Aagaard et al., 2006) that show how these influence cross-shore morphology, but what is less clear are the processes that link these regions with the sediment transport and morphology within the nearshore region, offshore of wave breaking (Davidson-Arnott, 2011). These processes include transport in the form of bedload and bedform migration, and the suspension of sediment due to orbital flows and turbulent processes. Suspended sediment transport in particular has been shown to contribute a large proportion of the total cross-shore transport on beaches (Aagard et al., 1998), which in turn influences bar formation and migration processes. And bedforms, while associated with bedload transport, also influence the overlying flow through a complex feedback system of altering bed roughness, affecting the turbulent structures within the bottom boundary layer (BBL). Data collected on a prototype scale sandy barrier beach as part of the Hydralab IV funded Bardex II project, aim to relate sediment dynamics and wave-induced flows in the nearshore region of a DOI: /SI received 07 December 2012; accepted 06 March Coastal Education & Research Foundation 2013 beach profile to changing wave conditions, water levels and exchanges of sediment with the upper beach profile. In particular, we will address these linkages by determining i) how turbulent processes and asymmetry in the nearshore region results in sediment suspension and mass transport in the on- or offshore directions; and, ii) how changing bedform morphology (e.g. crest shape and orientation) affect the effective roughness of the bed, an essential parameter for the accurate modelling of sediment transport. This paper reports some initial findings from these investigations, and outlines the future direction of the research. Turbulent Processes and Sediment Suspension Turbulence plays a fundamental role in both bed-load and suspended sediment transport mechanisms (Gordon, 1975), controlled by shear stresses within the bottom boundary layer (BBL) (Cloutier et al., 2006). Both field and laboratory observations have confirmed that instantaneous sediment suspension is largely controlled by the micro-scale bursting events near the bed (Heathershaw, 1974; Jackson, 1976; Sumer and Deigaard, 1981; Kawanisi and Yokosi, 1993; Yuan et al., 2009), which may be related to the vortices generated from roughness elements such as bedforms. However, limited studies have been carried out on the role these bursting events play in the shoaling wave region, focussing more on the structural features of the BBL (e.g. Grass, 1971; Cox and Kobayashi, 1998). Under waves, suspended sediment is usually limited to the thin wave boundary layer. Where bedforms are present, however,

2 1594 Thompson, et al. vortex generation can lead to resuspension higher into the water column (Li et al., 1996; Amos et al., 1999; Li and Amos, 1999). Cross-shore Skewness Skewness in both acceleration and velocity under waves is a key controlling factor of sediment transport and morphological response. The onshore migration of bars has been associated with near-bed skewness in acceleration under small shoaling waves (e.g. Thornton et al, 1996; Hoefel and Elgar, 2003), where water accelerates shoreward under steep front wave faces, and decelerates slowly under more gently sloping rear faces. This results in a larger onshore acceleration than offshore, leading to erosion offshore and deposition on the bar crest. This implies a supply of sediments from the nearshore region. In the nearshore, skewness in the velocity field itself is key to sediment transport (e.g. Trowbridge and Young, 1989; Crawford and Hay, 2001), with onshore sediment transport controlled by short wave velocity skewness (Mariño-Tapia et al., 2007). These skewnesses may manifest as an asymmetry in the turbulent fluctuations near the bed, as shown by Bakhtyar et al. (2009) who identified an enhanced vertical gradient of flow velocity near the bed for the uprush in the swash zone, implying increased bed friction, which persists into the nearshore region outside of the swash zone. Bedform Morphology and Roughness These turbulent processes will both inform the morphology of the bedforms in the nearshore region, and be influenced by them through the effective bed roughness, a key factor when modelling sediment transport processes on barrier beach systems. The bedforms increase the roughness of the bed and change the structure of the boundary layer though the introduction of rhythmic vortices into the flow (Nielsen, 1992), which increases the thickness of the wave boundary layer. Our current lack of knowledge on bed roughness (e.g. Buscombe and Masselink, 2006) limits our ability to accurately predict the short-term dynamic behaviour of sediments and thus the morphodynamic response of the beach. When modelling sediment transport under waves, the bed roughness is generally incorporated into a friction factor, f w, which is used to relate wave orbital velocities, U w, to shear stress at the bed t 0 = 0.5r f w U w 2, where is the fluid density. While a statistically significant relationship has been established between f w and bed roughness for flat beds (e.g. Lowe et al., 2007; Madsen, 1994; Nielsen, 1992; Smith and Hay, 2002; Swart, 1974), bed roughness is complicated in the presence of bedforms (Kim, 2004). Roughness is often defined in terms of bedform wavelength or steepness, but in reality, will be affected by the three dimensional morphology of the bedforms (Ganju and Sherwood, 2010) and temporal changes in bedform morphology and wave conditions are likely to result in large variations in the roughness (and therefore the friction factor) in response to changes in the wave conditions, water level or combinations of the two. It has been suggested that there is an almost instantaneous equilibrium between small-scale bedforms (e.g. ripples) to changes in hydrodynamic conditions (van Rijn, 1993) and so most ripple predictors consider that the bed morphology is in equilibrium with the hydrodynamics. Contrary to this, Traykovski (2007) showed that this is true only during moderate wave energy conditions. In fact non-equilibrium, relict wave ripples associated with peak wave events can persist until the start of a new wave event. This relaxation time effect, the time taken for bedforms to adjust to hydrodynamic changes, is key to accurately modelling bed roughness under wave conditions. METHODS Experimental Set-Up and Programme A sandy barrier beach was constructed within the Delta Flume from 0.42 mm (D 50 ) fluvial sand (Figure 1). The barrier crest was 4.5 m high, and positioned 1.5 m above mean sea level, and the barrier consisted of a 1:15 slope on the seaward side between m from the wave paddle (x = 0) leading into a 20 m wide, horizontal section 0.5 m thick and a further 5 m wide concrete toe. The crest itself was 5m wide and flat (x = m), and backed by a 1:5 landward slope ( m), separated from a 10 m lagoon by a retaining wall (full details can be found in Masselink et al., 2013). Computer-controlled pumps regulated water levels in both the sea and lagoon, and a wave paddle steered by a JONSWAP spectrum generated random waves. The wave paddle incorporated an automatic reflection compensator (ARC) to suppress wave reflection and low frequency resonance. Tides were simulated using a sinusoidal signal with an amplitude of 0.75 m and a period of 12 hours, broken into 30-cm segments. The test programme consisted of five series, designed to test: A) beach response to variations in wave conditions and lagoon levels in the absence of tides; B) bar dynamics in response to sea level in the absence of tides; C) beach response under varying wave conditions with a tide; D) Overtopping and overwash thresholds and E) barrier overwash dynamics. This resulted in a full range of significant wave heights (Hs) of 0.3, 0.6 and 0.8 m, and peak periods (Tp) of 4, 5, 6, 7, 8, 9, 10 and 12 s. The full programme is summarized in Masselink et al. (2013, Table 1). Instruments and measurements A suite of instruments was positioned in the nearshore region of the barrier 49 m from the wave paddle, at the break of slope of the barrier (Figure 1) on a scaffold frame (Figure 2(A) and (B)). The instrumentation comprised of: (C) Marine Electronics 1.1 MHz dual sand ripple profiling system (SRPS) recording sequential cross-shore profiles of bed morphology every minute at positions of 0.9 m (near wall) and 1.9 m (central flume) from the flume wall; (D) Two coupled, downward-looking Nortek Vectrino Acoustic Doppler velocimeters (ADVs) with a vertical offset of 26 cm and a cross-flume horizontal offset of 36 cm. These measured velocity in the along-flume (u), cross-flume (v) and vertical (w) axis at 25Hz, initially at 10 and 36 cm above the bed, with sampling volumes of 7mm. (E) An Aquatec Aquascat 1000 acoustic backscatter sensor (ABS), with 1, 2 and 4 MHz channels measuring between 5-95 cm below the instrument in 5 mm bins. Sampling occurred at 64 Hz for user determined burst intervals of 2, 5, 8 or 20 minutes, depending on the wave conditions; (F) A Marine Electronics 500 khz Sector Scanning Sonar (SSS) providing 360º plan-view images of bedforms with a 10 m range, affording an overview of the three-dimensional Figure 1. Delta Flume cross-section with barrier profile at the start of the experiment and location of the nearshore instrument frame.

3 Nearshore sediment resuspension and bed morphology Figure 2. Schematic and photographs of the instrument frame. (A) Plan view, with distance from paddle along the left hand wall and distance from flume centre below each instrument. (B) Cross section, showing heights of instruments above initial bed level. Both show the relative positions of the (C) Sand Ripple Profiling System (SRPS); (D) Acoustic Doppler Velocimeter (ADV); (E) Acoustic Backscatter Sensor (ABS); and (F) Sector Scanning Sonar (SSS). Not to Scale. nature of the bed. Figure 2 shows the frame and instrument layout. All instruments were logged in real-time, and were time synched to a precision GPS clock network. Analysis Techniques Near-bed orbital velocities were calculated according to linear waver theory (van Rijn, 1993). The maximum orbital amplitude (A) and the velocity to the edge of the boundary layer (u ow ) are expressed as: ph u ow = wa = s (1) T p sinh(kh) given that is the angular frequency, k is the wavenumber and h the water depth. Turbulence and momentum fluxes The instantaneous ADV velocity records for all three axes (u, v and w) were assessed for quality (correlation > 65%), filtered where data was missing using a moving average algorithm, and adjusted for sensor misalignment by application of an axis-rotation algorithm. The turbulence signals (u, v and w ) were then extracted using a low-pass filter (following the methodology of Thompson et al., 2012), and the data despiked using the true 3D phase space method (Goring and Nikora, 2002; 2003, Mori et al., 2007). Momentum fluxes were calculated as Reynolds stresses ( RS = -u'w'), and the turbulent kinetic energy (TKE = 0.5r(u' 2 + v' 2 + w' 2 )). The contribution of the different types of turbulent fluctuation to this momentum flux was assed using a combination of probability distributions (e.g. Yuan et al., 2009) and quadrant analysis (after Willmarth and Lu, 1972). Spectral analysis was used to calculate dominant eddy sizes (Soulsby et al., 1984), the integral scale of the turbulence, and to assess the size of sediment suspension clouds where present (Yuan et al., 2009). Suspended sediment and bed morphology The Aquatec AQUAscat MATLAB toolbox was used to rangecorrect the raw acoustic amplitude (for spreading loss and attenuation) from the three ABS transducers. One-dimensional vertical profiles of suspended sediment concentration and particle size distribution were then constructed given the minimum and maximum sizes, plus the sorting of the bed sediment. This allowed the construction of a time series of vertical sediment concentration at 64 Hz, which was down-sampled to 25Hz for comparison with the ADV turbulence data during spectral analysis. It should be noted that direct calibration of the ABS wasn t possible during the experiments, and so relative rather than absolute concentrations are considered. Bedform heights and wavelengths were measured from bed level data given by the sand ripple profilers (SRPS). Bed detection was carried out using the Marine Electronics software, using a threshold value (20) above the average backscatter intensity, and exported as (x, z) ASCII files. These were detrended to remove the bed slope, and de-spiked to remove outliers resulting from high concentration suspensions. A zero-crossing algorithm was used to determine wavelength and ripple heights. The SSS backscatter intensity data was used in raw form (db) to assess crest shape and orientation. This allowed any cross-flume variations in bedform shape to be evaluated, in a way not possible with the SRPS. PRELIMINARY RESULTS Data was recorded from a total of 117 wave runs as part of the BARDEX II experiments, and some preliminary findings from a selection of those forming series A are presented here. Conditions throughout the experiments were verified as rough turbulent, based on the wave Reynolds number (Dyer, 1986): Re w = A k s, where the Nikuradse roughness, k s = 25H r2 l r. r is the bedform wavelength, and H r is the height (as obtained from the SRPS, Figure 3). During the initial wave run (Hs = 0.8 m, Tp = 8 s), ripples were formed and adjusted to the wave conditions over the first 5 minutes of forcing to a wavelength of ~ 0.5m, and wave height of ~ m. These migrated onshore at approximately 1.2 m/hr for the duration of the wave run. The SSS data (Figure 4) confirmed the wavelength of 0.5 m, and showed an essentially two-dimensional pattern of bedforms in the acrossflume direction at the location of the instrument frame. Results from two wave conditions underwent initial investigation for turbulence (Kassem, 2012), one representing erosive processes on the shoreface (Hs = 0.6 m, Tp = 12 s), and the second representing accretive wave conditions (Hs= 0.8 m, Tp = 8 s). Average near-bed orbital velocities were similar for both, being 0.59 and 0.58 m/s respectively. The wave boundary layer thickness was estimated according to Grant and Madsen (1989) d w = 2ku w* w, where is von Karman s constant (0.41), and u w* is the wave shear velocity, to approximate 20 cm under these wave conditions, and the ADV measured at 1 cm above the bed, within the lower portion of the bottom boundary layer. Statistical analysis of the turbulent fluctuations u and w during erosive conditions showed quasi-gaussian, near-symmetrical, leptokurtic distributions, while the distribution of the momentum flux (u w ) was asymmetrical (negatively skewed) and highly leptokurtic, implying a high degree of intermittency in the turbulent bursting processes (Yuan et al., 2009), and a greater proportion of sweeps and bursts than outward or inward ejections.

4 1596 Thompson, et al. Figure 3. The evolution of ripple height and wavelength over time during the first 10 minutes of the initial wave run. Profiles are 1 minute apart, and have been vertically offset for clarity. Quadrant analysis (with zero threshold) confirmed that sweeps and bursts occupied approximately 63% of the record. Under accretive wave conditions, momentum flux distributions were less negatively skewed and less leptokurtic. Visual assessments of the association between turbulent momentum fluxes and suspended sediment concentrations indicated that the largest amplitude Reynolds Stresses did not always coincide with the largest suspended sediment events, although greater correlation was observed if the highest concentration events are filtered from the signal (Figure 5). It appears that the majority of lower concentration background suspensions are related to the Reynolds stresses in terms of turbulent bursting processes, while the higher concentration suspension events are controlled by an alternative mechanism. DISCUSSION Cross-correlation of the Reynolds stress and suspended sediment concentration signals at 1 cm above the bed show a strong (72%) correlation at a time-lag of 0.04 seconds (i.e. the sampling frequency of the instrument) indicating near instantaneous suspension in relation to the Reynolds stress, and confirming the role played by turbulent bursting in the resuspension processes described by Heathershaw and Thorne (1985) and others (e.g. Kawanisi and Yokosi, 1993; 1997 and Yuan et al, 1997). However, the larger concentration events are not seen to correlate with these bursting events, and also extend beyond the thickness of the boundary layer, commonly assumed to be the limit of suspension (Nielsen, 1992; Soulsby, 1997). As such, an alternative mechanism for suspension must be considered. Spectral analysis was used to calculate dominant eddy sizes, and investigate how the energy of the flow evolves in time and space scales. Suspended sediment concentrations very close to the bed (z = 0.01 m) showed a deviation from the typical k -5/3 inertial dissipation rate seen in the spectra of u and w and characteristic of natural flows (e.g. Soulsby et al., 1984; Foster et al., 2008, Grasso et al., 2012). Outside the boundary layer (z = 0.34 m), the suspended sediment concentration spectra showed a closer fit to the rate of inertial dissipation, evidence that the suspended sediment behaves similarly to the other scalar properties of the turbulence once outside of the boundary layer. The dominant vertical eddy sizes of both the vertical momentum fluxes (u w ) and vertical suspension fluxes (Cw ) were inferred from the nondimensional wave number (k*) at the peak of the spectrum, and corresponded to eddy sizes in the range m for vertical momentum fluxes, with the dominant length scale of the vertical turbulence being 0.10 m. The maximum vertical length scales of the turbulence therefore corresponds reasonably well to the thickness of the boundary layer. However, the inferred length scale range of the suspended sediment fluxes was between m, much in excess of the vertical eddy sizes, and greater than the thickness of the boundary layer. Whilst large given the sediment size, it should be noted that the size of material in suspension is likely closer to the d 10 (0.25) of the sediment (Whitehouse, 1995) and that visual inspection shows suspension clouds extending to the limit of detection of both the SRPS (0.5 m) and ABS (0.7 m). The mechanism for these larger, higher amplitude suspensions is likely related to form roughness due to the bedforms present on the bed. Form roughness is known to influence the structure of the bottom boundary layer, and it has been suggested that suspended load transport contributes significantly to ripple migration (Ribberink, 1998). In the presence of vortex ripples, momentum transfer over bedforms is dominated by coherent structures (van de Werf et al., 2007), specifically the formation and shedding of vortices around flow reversal. These structures are highly efficient at entraining sediment. The evolution of bedforms under the initial wave conditions (Figure 3) began with the formation of rolling grain ripples (Bagnold and Taylor, 1946), small bedforms separated by an almost horizontal bed, which evolved into triangular shaped vortex ripples over the first 5-7 minutes of waves. These vortex ripples were observed to undergo sequences of flattening and re-building throughout the experimental runs, dependant on the flow conditions. Bedform dimensions were consistent in the across-flume direction (Figure 4), and so the flume was treated as an essentially two-dimensional system. Observations from the SRPS backscatter data (figure 6) showed that intermittent suspension clouds were clearly associated with this underlying bed morphology, with cloud sizes corresponding to those implied by the spectral scaling. Figure 4. Sector Scanning Sonar image showing bedforms in the cross and along-shore directions from an instrument position of 49m from the wave paddle. Average wavelength is 0.5m. High noise localised near the instrument is related to surface waves.

5 Nearshore sediment resuspension and bed morphology Figure 5. Time series of turbulent kinetic energy, instantaneous Reynolds stress (-u w ), and concentration (SSC) below 300g/l at 1cm above the bed. u ow = 0.58 ms -1. FURTHER WORK Initial results indicate that a considerable amount of sediment is being transported in suspension in the nearshore region, and that this is being controlled by two processes i) turbulent bursting in the bottom boundary layer, and ii) vortex shedding from bedforms. Further work will therefore aim to confirm these processes under the full range of wave and tidal conditions tested, and determine their relative importance to the overall sediment transport between the nearshore and the surf zone. These processes will then be linked to the relaxation times of the bedforms, changes to the effective bed roughness, and large-scale morphological changes on the bar. CONCLUDING REMARKS Sediment suspension associated with turbulent bursting processes and bedform morphology was investigated in the nearshore region of a sandy barrier beach as part of the BARDEX II experiments. Momentum fluxes were found to be asymmetrical under both accretive and erosive conditions. Turbulent bursting was associated with near-instantaneous, low concentration suspensions restricted to the height of the bottom boundary layer, whereas vortex shedding from bedforms was associated with much higher concentrations of suspended sediment in clouds extending up to an inferred maximum of 1.2 m in the vertical. Initial bedform relaxation times were in the order of 3-5 minutes. Further work will determine the relative importance of the two suspension processes to bedform relaxation times, effective bed roughness, exchanges of sediment with the surf zone, and to largescale morphological changes on the beach profile. ACKNOWLEDGEMENT The work described in this publication was supported by the European Community's 7th Framework Programme through the grant to the budget of the Integrating Activity HYDRALAB IV, contract no Thanks go to the University of Plymouth for provision of the SRPS and ABS instruments, and in particular to Peter Ganderton, Martin Austin and Dan Buscombe for their technical support during the experiments. Figure 6. Suspension clouds associated with bed morphology (left: centre flume; Right: near wall). SPRS data, high backscatter in yellow. LITERATURE CITED Aagaard, T. and Hughes, M.G., Breaker turbulence and sediment suspension in the surf zone. Marine Geology, 271, Aagaard, T., Hughes, M., Møller-Sørensen, R. and Andersen, S., Hydrodynamics and sediment fluxes across an onshore migrating intertidal bar. Journal of Coastal Research, 22, Amos, C. L., Bowen, A. J., Huntley, D. A., Judge, J. T. and Li, M. Z., Ripple migration and sand transport under quasi-orthogonal combined flows on the Scotian shelf. Journal of Coastal Research, vol. 15, 1-14.

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