Evaluation of nearshore bathymetric inversion algorithms using camera observations and synthetic numerical input of surface waves during storms

Coastal Engineering
By: , and 

Links

Abstract

Nearshore bathymetry is difficult to measure using survey methods when wave heights approach the breaking limit. Remote sensing using digital cameras offers a way to observe the surf zone and calculate water depths based on phase speed but comes with its challenges of potentially noisy data that can introduce error into estimates of frequency and wavenumber used in phase speed calculation. This study investigates the robustness of a new version of a bathymetric inversion algorithm (cBathy, version 2.0) in moderate to energetic wave conditions by comparing depth estimates from timeseries’ of pixel intensity with depth estimates from synthetic water level data. The synthetic data are generated by the phase-resolving numerical model, SWASH, and optical data were collected during a field experiment in 2015. Model results from SWASH computed with known bathymetry are used as input to cBathy, and depth estimates are compared to nearshore surveys. Argus camera observations are also used as input to cBathy for the same times as the SWASH simulations. The SWASH simulations resolve breaking waves and do not include (optical) changes to the relation between water surface slope and pixel intensity, termed modulation transfer function, that occur during wave breaking, enabling better estimates from bathymetric inversion algorithms near morphologic features like sand bars. The results indicate that improvements result from eliminating of disruptions to the modulation transfer function caused by wave breaking and residual foam. We show that the use of synthetic wave data is a valuable means of isolating errors in bathymetric inversion algorithms.

Study Area

Publication type Article
Publication Subtype Journal Article
Title Evaluation of nearshore bathymetric inversion algorithms using camera observations and synthetic numerical input of surface waves during storms
Series title Coastal Engineering
DOI 10.1016/j.coastaleng.2023.104338
Volume 184
Year Published 2023
Language English
Publisher Elsevier
Contributing office(s) St. Petersburg Coastal and Marine Science Center
Description 104338, 14 p.
Country United States
State North Carolina
City Duck
Google Analytic Metrics Metrics page
Additional publication details