Wave sediment interaction on a muddy inner shelf during Hurricane Claudette

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1 Estuarine, Coastal and Shelf Science 63 (5) Wave sediment interaction on a muddy inner shelf during Hurricane Claudette A. Sheremet a, ), A.J. Mehta b, B. Liu c, G.W. Stone a a Coastal Studies Institute & Department of Oceanography and Coastal Sciences, Louisiana State University, Baton Rouge, LA 783, USA b Department of Civil & Coastal Engineering, University of Florida, Gainesville, FL 36, USA c Coastal Studies Institute, Louisiana State University, Baton Rouge, LA 783, USA Received August 4; accepted 3 ovember 4 Abstract Measurements of wave and suspended sediment concentration (SSC) were conducted near the 5-m isobath on the muddy inner shelf fronting Atchafalaya Bay, Louisiana, during Hurricane Claudette. The data show that wave and current activity resuspended large quantities of sediment, with SSC R.5 kg/m 3 throughout the water column. In the waning phase of the storm, settling generated a suspension layer, with concentrations over.7 kg/m 3 measured as high as m above the bottom. umerical simulations of post-storm sediment settling showed that observations are consistent with a high-density fluid mud layer (SSC between and kg/m 3 ), and separated from the upper water column by a lutocline located at about m above the bottom. The formation of the fluid-mud layer is correlated with strong, broad-spectrum wave dissipation, consistent with the hypothesis that surface interface wave interaction plays an important part in the energy transfer from the surface to the soft bottom. Ó 4 Elsevier Ltd. All rights reserved. Keywords: fluid mud; hurricane waves; wave dissipation; resuspension; settling velocity. Introduction Understanding wave evolution in the muddy inner shelf environment forms the basis of modeling wavedriven mud streaming and erosion/accretion patterns at muddy coasts. Compared with sandy environments, the coupling between flow and sediment motion is significantly stronger over muddy sea beds. Studies have shown that waves experience substantial damping, with important consequences for wave refraction and other wave properties (Rodriguez and Mehta, ). For example, Mathew et al. (995) reported 95% wave energy reduction onshore from the 5-m isobath off the ) Corresponding author. address: ashere@lsu.edu (A. Sheremet). coast of Kerala along the west coast of India. During Hurricane Camille seabed failure of catastrophic proportion was recorded at the inner shelf of the Gulf of Mexico by Sterling and Strohbeck (975). Observations like these have produced noteworthy but sporadic efforts to formulate theoretical models for the interaction between waves and soft, fine-grained sediment beds. The muddy bed has been modeled using a variety of rheological descriptions such as viscoelastic material (Jiang and Mehta, 995) and Bingham plastic (Mei and Liu, 987), and the coupled water mud motion has been described using soft mud layers of varying thickness and rheological properties. Some recent works include those of Hill and Foda (999), g () and Jamali et al. (3). However, as noted by Mei and Liu (987), divergent theoretical formulations seem to have their 7-774/$ - see front matter Ó 4 Elsevier Ltd. All rights reserved. doi:.6/j.ecss.4..7

2 6 A. Sheremet et al. / Estuarine, Coastal and Shelf Science 63 (5) 5 33 own realms of applicability, which remain largely unknown due to the scarcity of validating field data. Despite rather successful efforts to account for the special properties of mud, the problem of mud-induced wave dissipation has been traditionally approached as a minor modification of the sandy inner-shelf physics. The prevalent long-wave paradigm (LWP) assumes that only long wave motions penetrate deep enough into the water column to interact with the bottom. Lee (995) provides a coherent review of the variety of LWP-based dissipation functions used in wave mud interaction modeling. Experimental studies following the LWP approach (Tubman and Suhayda, 976; Forristall and Reece, 985; and others) typically use a pair of observation stations, one in deep and another one in shallow water, e.g. respectively 3 m and m in Forristall and Reece (985), along the probable path of long waves. The long wave evolution problem is formulated neglecting processes active in the short-wave range, such as energy input from wind and wave breaking. If quadruplet (four-wave) interactions are the only nonlinear mechanism assumed to be active, the coupling between the long- and short-wave bands of the spectrum is weak over short scales, and long waves evolve almost linearly. These assumptions have been applied consistently, ignoring possibly significant nonlinearities and sediment liquefaction effects even in highly energetic hurricane conditions (Forristall and Reece, 985). However, there is substantial evidence that in finitedepth water triad (three-wave) interactions are an order of magnitude more effective than four-wave interactions (Elgar and Guza, 985; Herbers et al., 994; Agnon and Sheremet, ; and others), so the decoupling of longand short-wave bands probably does not occur. Recent observations of strong sediment reworking by waves also question the applicability of LWP for muddy sea beds. A different experimental setting, using sites near the same isobath, but located in different sedimentary environments, has been used by Sheremet and Stone (3) to study short-wave propagation along the Louisiana coast. Observations show unexpected shortwave sensitivity to sediment type. In the waning phase of a storm, short waves dissipate considerably faster over muddy sea beds, an effect not explained by breaking or refractive scattering. Since short-wave motion is negligible near the bottom, a different, indirect type of dissipation mechanism must be active in the short-wave band, suggesting that water and sediment motions are coupled in muddy environments by a more complex mechanism than the LWP. Measurements of sediment motion by Allison et al. () conducted on the Louisiana shelf do point to a strong correlation between wave-current activity and sediment resuspension and deposition. However, simultaneous observations of water and sediment motions are scarce, and the implications of bed reworking on wave propagation (and coastal hydrodynamics in general), are poorly understood. Recently, an additional cluster of instruments, including optical backscatter sensors (OBS), has been deployed at the muddy location studied in Sheremet and Stone (3), to monitor suspended sediment concentration (SSC). In conjunction with existing wave-current measuring capabilities, the system allows for continuous monitoring of the coupled wavecurrent-sediment dynamics typical of muddy coasts. This paper discusses hydrodynamic and sediment concentration data collected at a muddy site off the Louisiana coast, from summer of 3 through spring of 4. It reports measurements during a single event, Hurricane Claudette. This was the first energetic event to test the observation system, which recorded continuously during the storm and provided a comprehensive set of waves, current and suspended sediment concentration (SSC) data. The instrumentation used and the experimental site is presented in Section, followed by a summary of the data (Section 3). In the last section we discuss some implications of the observations.. Instrumentation and experimental sites The core of the observation system used in this study is WAVCIS, described in detail in Stone et al. (). For this discussion we focus on data collected at two sites characterized by different sedimentary environments. The sediment type at the location of station CSI 3 is dominated by cohesive sediment of largely inorganic origin derived ultimately from the Mississippi River (fine silt, with median grain size of 6.34 mm and mean size of 6.7 mm). The sediment type at station is dominated by fine quartz sand. The two sites are about 5 km apart, located along the 5-m isobath, on a very mildly sloping shelf (!., Fig. ). The similarities of wave and wind conditions at these two sites, and related data processing procedures are discussed in detail in Sheremet and Stone (3). To correlate sediment dynamics with wave evolution, three instrument clusters were deployed at during the summer of 3, at, and 3 m above the bottom (mab), to monitor suspended sediment concentration. Each cluster included an Analite95/4/3-G (McVan Instruments) OBS, a SeaBird Electronics SBE-4 salinity sensor, and a temperature sensor. OBS data used in this paper consist of averages of 6-s time series sampled at Hz, once every min. The instruments were mounted on a specially designed arm, which allowed for easy retrieving and cleaning of the sensors. The OBS typically needed cleaning once every two weeks in summer, slightly less frequently during the cold seasons. The accumulation of sediment on the OBS is easily detectable in the time series as a spurious nearly-monotonic

3 A. Sheremet et al. / Estuarine, Coastal and Shelf Science 63 (5) Fig.. Terra- MODIS satellite image (Earth Scan Lab, LSU) of Louisiana coast and shelf with the location of WAVCIS stations and 5. Areas of high surface concentration of suspended sediments (light gray) can be seen along the coast, fronting Atchafalaya Bay. Coordinates are in kilometers, with respect to UTM 983, Zone 5. Bathymetric contours are given in meters. increase in the signal, eventually ending at the instrument saturation level (474 TU). The calibration of OBS sensors was conducted by correlating readings to corresponding true suspended sediment concentration data. A turbidity sensor and a Campbell Scientific, Inc. CR3X Micrologger data logger were set up and operated exactly in the same way as they are in the field. Surface samples were collected from sea floor around station. Water samples for OBS measurement were prepared by mixing surface sediments with distilled water, at intervals of about TU. After an initial reading for pure distilled water, small amounts of surface sediment were successively added to the sample. In this way, the SSC was slowly increased until it reached the saturation value. Measurements of true sediment mass and water volume in the sediment water mixture then yielded the SSC value for the sample. Filters with a diameter of.7 mm were first dried under low temperature (4 C) in an oven. Filters and sediment masses were measured with a high accuracy ( ÿ3 g) balance. For the linear part of the signal (which extends to about 4 TU), a linear regression between suspended sediment concentration (kg/m 3 ) and TU yielded a slope of. with a correlation coefficient of.99. The relation became nonlinear at very high TU values, with saturation at approximately.7 kg/m 3. Information about the current velocity distribution in the water column was derived from an upward-looking RDI Rio Grande Workhorse ( khz) ADCP (acoustic Doppler current profiler), located at about 6 cm above the bottom, which uses a 35-cm height bin, starting from approximately 65 cm above the instrument. o current velocity information was available in the first. m layer above the bottom. Wave data were provided by a Paroscientific pressure sensor, located at about m above the bottom (.5 m below the water surface) sampling at Hz, with a 6-min measurement burst. Water depth, current velocity, and current direction were averaged over the 6-min sampling interval. More information about the instrumentation and data sampling procedures can be found in Stone et al. (). 3. Observational results The observation system was operational when Hurricane Claudette passed near the station, and recorded data throughout the event. Fig. a shows a satellite image of the hurricane. Claudette was a storm of relatively small extent, which also accelerated as it passed by the experiment site, producing perturbations in the sea and sediment state of relatively short duration. Fig. b shows the best estimate of the path of the eye of the storm (Beven, 3). Claudette formed on July near the coast of Africa as a tropical wave, and became increasingly organized as it moved westward. It entered the southern Gulf of Mexico on July as a disorganized system after it made its first landfall on the northeastern Yucatan Peninsula of Mexico near July, : UTC. As it moved north-northwestward Claudette strengthened slowly to reach hurricane status when it made landfall on the Texas coast at Matagorda Island east of Port O Connor, on July 5, 5:3 UTC. With estimated maximum winds as high as 5 km/h and the central pressure down to 979 mb, at landfall, the storm was very close to a Category hurricane on the Saffir-Simpson Scale. At landfall, storm surge flooding of m above normal tide level was reported near the location of the

4 8 A. Sheremet et al. / Estuarine, Coastal and Shelf Science 63 (5) 5 33 (a) 3 3 TX LA MS AL GA FL (b) Latitude (degrees) /5 7/4 7/3 4 7/ CUBA YUCATA 7/ Longitude (degrees) Fig.. (a) Grayscale Terra- MODIS image (Earth Scan Lab, LSU) of Hurricane Claudette taken on July, 3, 6:8 UTC. The cloud cover (bright white) illustrates the spatial extent of the storm. (b) Best estimate of Claudette s track in the Gulf of Mexico (Beven, 3). The locations of DBC buoys 4 and 4 9 and of WAVCIS stations and are marked on the plot. The storm reached hurricane status on July 5, as it approached the Texas coast. eye, and storm tides (surge plus astronomical tide) of 3 m were measured in the Galveston-Freeport area. Tides were.3.6 m above normal along the southwestern Louisiana coast. Fig. 3 illustrates wave conditions during the storm based on directional and frequency wave spectrum estimates at the locations of DBC buoys and WAVCIS stations (Fig. b). The storm had passed H sig (m) Spectral density (m /Hz) / 7/ 7/3 7/4 7/5 7/6 7/7 7/8 Time (Month/Day) Frequency (Hz) W.4.3 E W.3. E... W. E W. E SW SE SW SE S S Fig. 3. A summary of wave conditions during Claudette as recorded at two DBC stations (4 and 4 9) and two WAVCIS stations ( and ). (a) Time evolution of significant wave height. (b) Frequency spectra at the moment the storm peaked along the Louisiana coast, 4 July, : UTC. (c) and (d) Estimated directional wave spectra on 4 July, : UTC at the location of DBC buoys 4 and 4 9, respectively. Darker tones indicate higher spectral density values. Spectra are normalized (the integral over angles and frequencies of the spectra is ). Wave direction is defined as the direction waves are propagating to.

5 A. Sheremet et al. / Estuarine, Coastal and Shelf Science 63 (5) Wind speed (m/s) (b) (a) W S E Direction Height (mab) (c) 66 Height (mab) Speed (cm/s) 7/ 7/ 7/3 7/4 7/5 7/6 7/7 7/8 Time (Month/Day) Fig. 4. Wind and vertical distribution of current velocity versus time during Hurricane Claudette. (a) Wind direction and speed m above the water level measured at WAVCIS stations and 5. (b) Direction of horizontal current velocity at. Here, the direction of current as well as wind is defined as the direction of the flow (for wind also, means velocity vector directed to ). (c) Vertical distribution of current velocity at. DBC buoy 4 and was intensifying and accelerating toward 4 9. Waves at 4 (Fig. 3c) are short (period about 5 s) and are roughly aligned with wind direction (see also Fig. 4). Waves at 4 9 are typical swells with period about s. The large waves recorded at the peak of the storm at DBC buoy 4 9 are associated with the intensification of the hurricane to almost Category just before landfall. As observed in both WAVCIS stations CSI3 and CSI5 (Fig. 3a), significant wave heights (H sig ) in shallow water never exceeded m. Although was closer to the path of the storm, waves were lower there, a trend which is in general consistent with expectations of stronger wave dissipation effects in the mud-dominated environment at. The peak of the storm on the Louisiana coast occurred sometime between 6: and 4: h on July 4. At that time the storm was beginning to intensify and accelerate toward buoy 4 9 (Fig. b). Low frequency swells were recorded at locations in front of the storm (buoy 4 9, Fig. 3b and d) and near its front-right quadrant (WAVCIS stations, Fig. 3b). At buoy 4, behind the storm, the short waves dominate the wave field and the energy is decreasing (Fig. 3c). With the exception of some ADCP down-time, the instrumentation monitoring water and suspended sediment motion at was operational and recorded continuously during Claudette s passage. Fig. 4 shows details of wind and current measurements. As noted in Sheremet and Stone (3), wind direction and speed m above the mean sea level (Fig. 4a) are nearly identical at stations and. ADCP measurements of the vertical distribution of current velocity at are summarized in Fig. 4b and c. To allow for a direct comparison of wind and current directions, we switched from the meteorological wind direction convention to the direction of flow. Before the arrival of the storm (July ), winds blowing to the southeast generated a relatively strong southerly circulation in the first m below the surface. As the storm approached, the wind turned and blowed continuously toward W during the storm for the next 4 days towards W. At its peak Claudette generated strong currents of about 6 cm/s from as deep as.5 m above the bottom to the water surface, in the direction of the wind. About one day after landfall (evening of July 6), with winds below 5 m/s, currents also decay to an almost complete standstill, followed for a brief period by a strong return flow near the bottom in the first few hours of July 7. Time series of SSC are shown in Fig. 5 together with estimates of wave variance in the long- and short-wave bands (as in Sheremet and Stone (3), a frequency

6 3 A. Sheremet et al. / Estuarine, Coastal and Shelf Science 63 (5) 5 33 Long waves (a) SSC (kg/m 3 ) Variance (m ) mab mab mab Short waves Resuspension Settling Dewatering (b) (c) Speed (m/s).6.4. Critical speed for resuspension 7/ 7/ 7/3 7/4 7/5 7/6 7/7 7/8 Time (Month/Day) (d) W S E Direction Fig. 5. Estimates of wave variance, suspended sediment concentration and mean current direction and speed versus time, at station. (a) Long wave (frequency!. Hz) variance. (b) Short wave variance (frequency R. Hz). (c) Suspended sediment concentration at three levels (roughly, and 3 m above bottom). (d) Speed and direction of the mean current in the first mab. Currents direction is defined as the direction of the flow (e.g., means current velocity vector directed to ). otional subdivisions marked by vertical dashed lines are in reference to dominant sediment transport processes (panel c). value of. Hz is used to separate them), and the mean current velocity and direction below mab. Throughout the storm duration measurements of SSC at and 3 mab are almost identical, indicating a well mixed upper layer of the water column, which is consistent with previous SSC measurements in this area (Wells and Kemp, 984). Typical concentrations recorded during the storm at the upper sensors are between. and. kg/m 3. The highest concentration, about.5 kg/m 3, was recorded near the peak of wave activity (Fig. 5a c). The evolution of the lower water column is markedly different. With Claudette s approach, a brief spike in concentration at mab early on July 3 jumpstarts the resuspension phase, coinciding with the mean current exceeding the estimated 3 cm/s critical speed for resuspension (Fig. 5d), and a temporary increase in wave activity. At the onset of the storm (July 4), winds turn and start blowing toward W forcing a strong northwestern circulation. The SSC levels in the first mab (Fig. 5c) stay above.9 kg/m 3 throughout the storm, with a slight increase (around. kg/m 3 ) during the peak of wave activity. Sediment resuspension phase lasts roughly until midday July 5. With the decrease in wave activity, turbulence in the wave boundary layer decreases, resuspension is suppressed and sediment settling begins to dominate sediment motion, bringing values of SSC in the upper layers back to normal levels (about. kg/m 3 ). As sediment drains out of the upper layer and clarifies it, the material accumulates in the bottom layer, where SSC values increase abruptly beyond the saturation value of the -mab sensor (approximately.7 kg/m 3 ) over a period of about 8 h (from 5 Jul 7: to 6 Jul : Fig. 5c). This behavior is consistent with observations by Allison et al. (), with concentrations up to 5 kg/m 3 and the simulations of near-bottom high concentration mud layer formation by Ross and Mehta (99) and Winterwerp (). The peak of the storm is dominated by intense wind forcing (Figs. 4a and 5a and b), which keeps short waves at comparable energy levels at both inner shelf sites (CSI3 and 5), consistent with previous observations (Sheremet and Stone, 3). The remarkable element of these plots is the waning phase of the storm (roughly coinciding with the region marked settling in Fig. 5c),

7 A. Sheremet et al. / Estuarine, Coastal and Shelf Science 63 (5) when details of wave sediment interaction become discernible. The significant difference between wave dissipation efficiency over sandy () and muddy () beds becomes evident as wind forcing decreases (Fig. 5a and b). The decay in wave-current activity results in the formation of a fluid-mud layer, which likely accelerates wave decay. In the final stage, the thickness of the fluid-mud layer slowly decreases as the mud undergoes dewatering and consolidation. In the early hours of July 7 the layer shrank below mab and as a result the SSC declined rapidly from about.7 to.5 kg/m 3. o SSC measurements are available within the highdensity fluid mud layer, but numerical models can be used to reconstruct the full SSC vertical distribution in a way consistent with observations. Simulations can also be used to estimate characteristic parameters of sediment dynamics not measured directly (in particular bed erosion and settling of the suspended particulate matter). While the low spatial resolution of existing SSC data does not allow for a rigorous application of methods such as inverse modeling, some estimates can be derived by comparing model output to measurements. Here, we use a one-dimensional numerical model reported by Li and Parchure (998) to simulate a nonequilibrium suspension profile. The model is based on the general mass-conservation equation: vc vt Z v K vc vz vz CW sc ; ðþ 8 >< K vc vz CW scz >: K vc vz CW scz ÿ F n atzzh; at zz: ðþ with boundary conditions for the mass flux given at the water surface z Z h, and at the bottom of the water layer z Z, where z is the vertical coordinate, with the axis origin at the interface between the water layer and the fluid mud (or bed). The vertical distribution of sediment concentration is denoted by C Z C(z, t), K is the diffusion coefficient and W s is the settling velocity. The net flux of mass ÿf n is normal through the interface z Z, directed away from the water layer. Details of the parameterizations schemes involved in the definitions of the diffusion coefficient, and the mass flux through z Z are given in Li and Parchure (998). The net mass flux F n was estimated using numerical simulations, and based on data reported by Kemp and Wells (987) on the response of SSC to weather fronts in the study area (but in shallower depths). In the waning phase of the storm, dominated by settling, the structure of the function W s (C ) is particularly important for understanding sediment motion. Following Wolanski et al. (989) and Hwang (989), settling is parameterized in the model in three regimes, free, flocculation and hindered: 8 forc!c ðfreeþ W sf >< W s Z C n a >: ÿ C ÿ ~C m forc!c!c m ; ð3þ ðflocculation=hinderedþ where W sf is the free-settling (Stokes) particle velocity, a is a scaling coefficient and ~C is the hindered settling term. Free settling occurs at low concentrations (C! C ). For C! ~C the velocity increases with the concentration as a result of floc formation (region controlled by the exponential n). The settling velocity decreases with the further increase of C beyond C (hindered settling domain, with W s controlled by the exponential m). The different regions are marked on Fig. 6a, which plots W s as a function of sediment concentration. The concentration C m at which the regime changes from flocculation to hindered settling is given by the relationship rffiffiffiffiffiffiffiffiffiffiffiffiffi n C m Z ~C: ð4þ mÿn The runs focused on the approximately 8-h interval (5 Jul 7: to 6 Jul :), when the fluid-mud layer is formed (Fig. 5c). The model is used to simulate the settling which occurs as wave activity decreases to approximately.5 m significant wave height, with an estimated mean period of 6. s and a mean current of. m/s. The curve in Fig. 6a corresponds to W sf Z. m/s, a Z.37, ~C Z. kg/m 3, m Z.5, n Z.33, and C Z. kg/m 3. The transition from flocculation to hindered settling occurs at C m Z.78 kg/m 3. Initial values for SSC were interpolated from measured values of.,.5, and.5 kg/m 3 at, and 3 mab, respectively. With these values, the vertical distribution of the sediment concentration evolves in approximately h as shown in Fig. 6b. The final measured value at mab is the saturation value, given only as reference, as the actual measurement is rather an interval (C O.7 kg/m 3 ). The model forms a lutocline at the top of a layer with concentrations higher than kg/m 3 and thickness about m. 4. Discussion Observations during Hurricane Claudette support the hypothesis that sediment reworking is strongly related to wave dissipation in all the frequency bands. Long wave attenuation mechanisms (Lee, 995) are fairly well studied, but mud-induced short-wave dissipation is not well understood. Short-wave motion does not penetrate

8 3 A. Sheremet et al. / Estuarine, Coastal and Shelf Science 63 (5) 5 33 Settling Velocity (m/s) 3 4 Free Settling Flocculation Settling Hindered Settling (a) initial (measured) initial (model) final (measured) final (model) (b) Elevation (mab) SSC (kg/m 3 ) SSC (kg/m 3 ) Fig. 6. umerical simulation results: (a) settling velocity versus suspended sediment concentration (SSC). The three regions of qualitatively different settling behavior are separated by dashed lines. (b) Vertical distribution of sediment concentration. Initial measured SSC (blue circles) correspond to concentrations at the beginning of the settling period (vertical line, July 5, Fig. 5). Final SSC values are. kg/m 3 for sensors at and 3 mab. The SSC value for the -mab sensor (.7 kg/m 3, the saturation value) is given only for reference. deep enough into the water column to interact directly with the soft bottom. Our observations of sediment resuspension and settling suggest that dissipation is strongly correlated to the formation of a high-density layer in the first mab, likely due to sediment settling during the waning phase of the storm. As the storm approaches, nearshore currents and long waves traveling ahead of the approaching storm create the bottom turbulence necessary to resuspend and advect bed sediment. During the storm, sediment is mixed throughout the water column. In the waning phase, sediment settling increases flow viscosity near the bottom, which in turn accelerates settling by suppressing turbulence and therefore resuspension. umerical simulation conducted with a nonstationary one-dimensional model suggests that the high turbidity pulse recorded by the sensors located at mab was associated with the formation of a high-density mud layer (SSC O kg/m 3 ), separated from the water layer by a lutocline where concentration varies by two orders of magnitude (from. to higher than kg/m 3 ). The corresponding increase in viscosity may be as much as two orders of magnitude and higher; if so, what is properly defined as fluid mud having very low rates of dewatering would have sustained a dissipative mud layer of about 6-cm thickness above the bottom for several hours. Similar layers have resulted in simulations (Ross and Mehta, 99; Winterwerp, ); this behavior is consistent with previous measurements (Wells and Kemp, 984; Allison et al., ), but has never been observed at the present time resolution. The consequence of these processes for wave propagation could be significant beyond the interest in understanding wave dissipation mechanisms. Mud layers could act as a mediator of energy transfer from surface waves (including the short wave band) to the soft muddy bottom, modifying the spectral energy balance and wave propagation processes in nontrivial ways. umerical simulations show a clearly defined lutocline associated with the formation of the high-density mud layer, a central element in several models which explain surface wave dissipation by surface interface wave interactions. This type of interaction is resonant, and thus, very efficient (Hill and Foda 999; Jamali et al. 3). In addition, three-wave interactions in finitedepth and shallow water can be an order of magnitude more efficient at transferring energy across the spectrum (nonlinear shoaling can change wave shape over wave lengths (Elgar and Guza, 985; Agnon and Sheremet, 997). This suggests that a path of direct energy transfer from surface to the soft bottom could be the excitation of both free and forced wave modes at the water/mud interface (Jiang and Mehta, ), where the energy is then dissipated by viscosity within the fluid mud layer. The importance of this mechanism in real-life processes is not known, but our observations clearly suggest it as a possibility. It is worthy of note that surface interfacial wave interactions are directional, and to our knowledge there is no theoretical formulation capable to describe correctly directional propagation of nonlinear (threewave) surface waves. Acknowledgements Funding was provided by the Office of aval Research, award number 4-3--, and Louisiana Board of Regents, grant number LEQSF(- 5)-RD-A-. Coastal Studies Institute Field Support Group and the WAVCIS team provided essential data collection support. References Agnon, Y., Sheremet, A., 997. Stochastic nonlinear shoaling of directional spectra. Journal of Fluid Mechanics 345,

9 A. Sheremet et al. / Estuarine, Coastal and Shelf Science 63 (5) Agnon, Y., Sheremet, A.,. Stochastic evolution models for nonlinear gravity waves over uneven topography. In: Liu, P.L.-F. (Ed.), Advances in Coastal and Ocean Engineering. World Scientific, Singapore, pp Allison, M.A., Kineke, G.C., Gordon, E.S., Goni, M.A.,. Development and reworking of a seasonal flood deposit on the inner continental shelf off the Atchafalaya River. Continental Shelf Research (6), Beven, J., 3. Tropical Cyclone Report: Hurricane Claudette. ational Hurricane Center, Miami. Elgar, S., Guza, R.T., 985. Observations of bispectra of shoaling surface gravity waves. Journal of Fluid Mechanics 6, Forristall, G.Z., Reece, A.M., 985. Measurements of wave attenuation due to a soft bottom: the SWAMP experiment. Journal of Geophysical Research 9 (C), Herbers, T.H.C., Elgar, S., Guza, R.T., 994. Infragravity-frequency (.5.5 Hz) motions on the shelf. Part. Forced waves. Journal of Physical Oceanography 4 (5), Hwang K.-., 989. Erodibility of fine sediment in wave dominated environments. MS thesis, University of Florida, Gainesville FL, 66 pp. Hill, D.F., Foda, M.A., 999. Effects on viscosity on the nonlinear resonance of internal waves. Journal of Geophysical Research 4 (C5), Jamali, M., Lawrence, G.A., Seymour, B., 3. A note on the resonant interaction between a surface wave and two interfacial waves. Journal of Fluid Mechanics 49, 9. Jiang, F., Mehta, A.J., 995. Mudbanks of the southwest coast of India IV: mud viscoelastic properties. Journal of Coastal Research (3), Jiang, J., Mehta, A.J.,. Lutocline behavior in a high-concentration estuary. Journal of Waterway, Port, Coastal and Ocean Engineering 6 (6), Kemp, G.P., Wells, J.T., 987. Observations of shallow water waves over a fluid mud bottom: implications to sediment transport. In: Kraus,.C. (Ed.), Proceedings of Coastal Sediments 87. ASCE, ew York, pp Lee, S.C., 995. Response of mudshore profiles to waves. PhD thesis, University of Florida, Gainesville. Li, Y., Parchure, T.M., 998. Mudbanks of the southwest coast of India VI: suspended sediment profiles. Journal of Coastal Research 4 (4), Mathew, J., Baba, M., Kurian,.P., 995. Mudbanks of the southwest coast of India I: wave characteristics. Journal of Coastal Research (), Mei, C.C., Liu, K.-F., 987. A Bingham-plastic model for a muddy seabed under long waves. Journal of Geophysical Research 9 (C3), g, C.-O.,. Water waves over a muddy bed: a two layer Stokes boundary layer model. Coastal Engineering 4, 4. Rodriguez, H.., Mehta, A.J.,. Modeling muddy coast response to waves. Journal of Coastal Research SI7, Ross, M.A., Mehta, A.J., 99. Fluidization of soft estuarine mud by waves. In: Bennett, R.H., Bryant, W.R., Hulbert, M.H. (Eds.), The Microstructure of Fine-grained Sediments: From Mud to Shale. Springer-Verlag, ew York, pp Sheremet, A., Stone, G.W., 3. Observations of nearshore wave dissipation over muddy sea beds. Journal of Geophysical Research 8 (C), 4, doi:.9/3jc885. Sterling, G.H., Strohbeck, G.E., 975. Failure of South Pass 7 Platform B in Hurricane Camille. Journal of Petroleum Technology 7, Stone, G.W., Zhang, X.P., Gibson, W., Fredericks, R.A.,. ew Wave-current On-line Information System for Oil Spill Contingency Planning (WAVCIS), Proceedings of the 4 Arctic and Marine Oilspill Program Technical Seminar, Edmonton, Alberta, Canada, pp Tubman, M.W., Suhayda, J.., 976. Wave action and bottom movements in fine sediments. Proceedings of the 5th Coastal Engineering Conference. ASCE, ew York, pp Wells, J.T., Kemp, G.P., 984. Interaction of surface waves and cohesive sediments: field observations and geologic significance. In: Mehta, A.J. (Ed.), Estuarine Cohesive Sediment Transport. Lecture otes on Coastal and Estuarine Studies, vol. 4, pp Winterwerp, J.C.,. Stratification effects by cohesive and noncohesive sediment. Journal of Geophysical Research 6 (C), Wolanski, E., Asaeda, T., Imberger, J., 989. Mixing across a lutocline. Limnology and Oceanography 34 (5),