Vertical and Horizontal Length Scales of Suspended Sediment in the Nearshore

Abstract

Suspended sediment measurements acquired using acoustic and optical sensors are analyzed to determine the vertical and horizontal coherence length scales in the nearshore zone across a barred beach during the SandyDuck experiment. Suspended sediments over the vertical, from the seafloor to approximately 65 cm above the bed, are inferred from acoustical backscatter of a 1.3 MHz signal at discrete 1.7 cm bins. The height of the bedload layer ranged from 1.7 - 3.4 cm above the bed floor for all stations investigated, which is twice the height of the theoretical wave boundary layer. The vertical coherence length was found to be an order of magnitude greater than the wave boundary layer and had a weak dependence with wave height, depth of water and orbital excursion (linear correlation coefficient of 0.6 statistically significant at 95% confidence). The cross-shore horizontal coherence length scale of suspended sediment was determined using a two meter lagged array of six optical backscatter sensors at an elevation of approximately 18 cm above the bed. The horizontal coherence length scale was approximately 0.8 times the rms wave orbital excursion length for all cross shore stations. Both the vertical and horizontal coherence length scales are longest for infragravity waves and decrease with increasing frequency.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1998
Accession Number
ADA354985

Entities

People

  • Michael P. Huck

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Altimeters
  • Backscattering
  • Boundaries
  • Boundary Layer
  • Civil Engineering
  • Coordinate Systems
  • Elevation
  • Frequency
  • Frequency Bands
  • Layers
  • Measurement
  • Research Facilities
  • Seabed
  • Sedimentation
  • Sediments
  • Suspended Sediments
  • United States Naval Academy

Readers

  • Coastal Oceanography
  • Mathematics or Statistics
  • Radar Systems Engineering.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • Space