Bed shear stress estimation under wave conditions using near-bottom measurements: Comparison of methods

Journal of Coastal Research
By: , and 



Understanding the influence of waves on bed shear stress is critical for predicting morphodynamical behaviours in coastal areas. Near-bed flow was measured on the middle and lower intertidal mudflats along the Jiangsu coast, China, using a three-dimensional acoustic velocimeter that collected a 3.5-cm vertical profile at 1mm resolution and sample rate of 25 Hz. On the lower and middle tidal flats, velocities from ~2.5-6 cmab (cm above bed) and ~0-3 cmab were measured, respectively. Current-induced bed shear stresses were calculated from turbulent kinetic energy (TKE) at the 11th measurement layer (i.e., 5.1 cm below the probe) using wave-turbulence decomposition and from a logarithmic fit to the horizontal mean velocity profile (LP). A wave boundary layer extended from the bed up to 3 cmab when the significant wave height was 0.23 m; when it was present the near-bed mean velocity profile was non-logarithmic. Waves suppress the development of a vertical velocity gradient and lead to an overestimation of bed shear stress when calculated using the log profile assumption. The TKE method is more accurate than the LP method when waves are present and measurements are at least partially within the wave boundary layer. Accurate calculation of current-induced bed shear stress depends on probe height and wave conditions.

Study Area

Additional publication details

Publication type Article
Publication Subtype Journal Article
Title Bed shear stress estimation under wave conditions using near-bottom measurements: Comparison of methods
Series title Journal of Coastal Research
DOI 10.2112/SI85-049.1
Volume Special issue 85
Year Published 2018
Language English
Publisher Coastal Education and Research Foundation
Contributing office(s) Pacific Coastal and Marine Science Center
Description 5 p.
First page 241
Last page 245
Country China
Other Geospatial Jiangsu coast
Additional Online Files (Y/N) Y
Google Analytic Metrics Metrics page
Additional metadata about this publication, not found in other parts of the page is in this table