On the wave and current interaction with a rippled seabed in the coastal ocean bottom boundary layer

Nayak, Aditya R.; Li, Cheng; Kiani, Bobak; Katz, Joseph

doi:10.1002/2014jc010606

Cited by 21 publications

(26 citation statements)

References 98 publications

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“…This was validated by Nayak et al. (), who found that, even though the combination of waves and currents affects the roughness layer, the log layer is not much affected. The roughness layer is approximately twice the roughness element height (Florens et al.…”

Section: Methodssupporting

confidence: 52%

“…The depth-averaged current velocity u c was calculated from U using a logarithmic velocity profile on the lowest two available ADVs. This was validated by Nayak et al (2015), who found that, even though the combination of waves and currents affects the roughness layer, the log layer is not much affected. The roughness layer is approximately twice the roughness element height (Florens et al, 2013), which is in our case a few centimetres.…”

Section: Data Processing and Analysismentioning

confidence: 69%

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Spatio‐temporal characteristics of small‐scale wave–current ripples on the Ameland ebb‐tidal delta

Brakenhoff

Kleinhans

Ruessink

et al. 2020

Earth Surf Processes Landf

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Ebb‐tidal deltas are highly dynamic environments affected by both waves and currents that approach the coast under various angles. Among other bedforms of various scales, these hydrodynamics create small‐scale bedforms (ripples), which increase the bed roughness and will therefore affect hydrodynamics and sediment transport. In morphodynamic models, sediment transport predictions depend on the roughness height, but the accuracy of these predictors has not been tested for field conditions with strongly mixed (wave–current dominated) forcing. In this study, small‐scale bedforms were observed in the field with a 3D Profiling Sonar at five locations on the Ameland ebb‐tidal delta, the Netherlands. Hydrodynamic conditions ranged from wave dominated to current dominated, but were mixed most of the time. Small‐scale ripples were found on all studied parts of the delta, superimposed on megaripples. Even though a large range of hydrodynamic conditions was encountered, the spatio‐temporal variations in small‐scale ripple dimensions were relatively small (height η≈ 0.015 m, length λ≈ 0.11 m). Also, the ripples were always highly three‐dimensional. These small dimensions are probably caused by the fact that the bed consists of relatively fine sediment. Five bedform height predictors were tested, but they all overestimated the ripple heights, partly because they were not created for small grain sizes. Furthermore, the predictors all have a strong dependence on wave‐ and current‐related velocities, whereas the ripple heights measured here were only related to the near‐bed orbital velocity. Therefore, ripple heights and lengths in wave–current‐dominated, fine‐grained coastal areas ( D50<0.25 mm) may be best estimated by constant values rather than values dependent on the hydrodynamics. In the case of the Ameland ebb‐tidal delta, these values were found to be η=0.015 m and λ=0.11 m. ©2019 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd.

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Section: Methodssupporting

confidence: 52%

Section: Data Processing and Analysismentioning

confidence: 69%

Spatio‐temporal characteristics of small‐scale wave–current ripples on the Ameland ebb‐tidal delta

Brakenhoff

Kleinhans

Ruessink

et al. 2020

Earth Surf Processes Landf

View full text Add to dashboard Cite

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“…Here, turbulence is quantified by calculating the TKE dissipation rate, ε , from the velocity field recorded by the ADV. While several approaches could be used to compute TKE dissipation estimates in spatially resolved oceanic flows (Nayak et al ), the use of an ADV (single point sensor) necessitated estimating dissipation by fitting a line with a −5/3 slope to the inertial subrange of the velocity frequency spectrum and using Taylor's “frozen turbulence” hypothesis.…”

Section: Resultsmentioning

confidence: 99%

Evidence for ubiquitous preferential particle orientation in representative oceanic shear flows

Nayak

McFarland

Sullivan

et al. 2017

Limnology & Oceanography

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In situ measurements were undertaken to characterize particle fields in undisturbed oceanic environments. Simultaneous, co‐located depth profiles of particle fields and flow characteristics were recorded using a submersible holographic imaging system and an acoustic Doppler velocimeter, under different flow conditions and varying particle concentration loads, typical of those found in coastal oceans and lakes. Nearly one million particles with major axis lengths ranging from ∼14 μm to 11.6 mm, representing diverse shapes, sizes, and aspect ratios were characterized as part of this study. The particle field consisted of marine snow, detrital matter, and phytoplankton, including colonial diatoms, which sometimes formed “thin layers” of high particle abundance. Clear evidence of preferential alignment of particles was seen at all sampling stations, where the orientation probability density function (PDF) peaked at near horizontal angles and coincided with regions of low velocity shear and weak turbulent dissipation rates. Furthermore, PDF values increased with increasing particle aspect ratios, in excellent agreement with models of spheroidal particle motion in simple shear flows. To the best of our knowledge, although preferential particle orientation in the ocean has been reported in two prior cases, our findings represent the first comprehensive field study examining this phenomenon. Evidence of nonrandom particle alignment in aquatic systems has significant consequences to aquatic optics theory and remote sensing, where perfectly random particle orientation and thus isotropic symmetry in optical parameters is assumed. Ecologically, chain‐forming phytoplankton may have evolved to form large aspect ratio chains as a strategy to optimize light harvesting.

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“…where overbar denotes the 10-min averaging and −u ′ w ′ , −u ′ t w ′ t and −u ′ w w ′ w denote TSS, TRS, and WS, respectively (Bian et al, 2018;Bricker & Monismith, 2007;Nayak et al, 2015). Similar decomposition can be applied to the other component of the TSS, −v ′ w ′ .…”

Section: Estimation Of Bottom Shear Stressmentioning

confidence: 99%

Impacts of Currents and Waves on Bottom Drag Coefficient in the East China Shelf Seas

Fan

Zhao

et al. 2019

JGR Oceans

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High-frequency measurements of waves, currents, and turbulence were made using the bottom-mounted tripod equipped with the Nortek 6-MHz acoustic Doppler velocimetry at eight mooring stations in the East China Shelf Seas. The observational data are analyzed to estimate the bottom drag coefficient and also the contributions from currents and waves. Variations of bottom drag coefficient caused by currents show no obvious relationship with water depth. Generally, the current-induced drag coefficient decreases with the strengthening currents, and the wave-induced drag coefficient increases with the enhancing waves. Synthesis analyses of the observational data reveal a scale relationship between the current-induced drag coefficient and the turbulent Reynolds number and that between the wave-induced drag coefficient and the bottom wave orbital velocity. The analyses show no significant impacts of waves on turbulent Reynolds stress, and the total bottom drag coefficient is the sum of that due to currents and waves. The empirical formula for bottom drag coefficient derived from this study may help to improve the simulation of tides, storm surges, and sediment transport in coastal seas.Plain Language Summary Ocean floor exerts a frictional force on ocean currents, and this force is particularly important in coastal oceans. This force is difficult to measure directly and is usually parameterized using the near-bottom currents and a bottom drag coefficient. In this study, we derive estimates of bottom drag coefficient from observed currents and turbulence at eight mooring stations in the East China Shelf Seas. The estimated bottom drag coefficient is not a constant. Empirical relationships are established to link the impacts of currents and waves on bottom drag coefficient to separate dynamic parameters, that is, the turbulent Reynolds number and the bottom wave orbital velocity. The total bottom drag coefficient can be taken as the sum of the two components. The empirical formula for bottom drag coefficient derived from this study may help to improve the simulation of tides, storm surges, and sediment transport in coastal seas.

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On the wave and current interaction with a rippled seabed in the coastal ocean bottom boundary layer

Cited by 21 publications

References 98 publications

Spatio‐temporal characteristics of small‐scale wave–current ripples on the Ameland ebb‐tidal delta

Spatio‐temporal characteristics of small‐scale wave–current ripples on the Ameland ebb‐tidal delta

Evidence for ubiquitous preferential particle orientation in representative oceanic shear flows

Impacts of Currents and Waves on Bottom Drag Coefficient in the East China Shelf Seas

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