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Coastal vulnerability assessment based on video wave run-up observations at a mesotidal, steep-sloped beach

Ocean Dynamics volume 62, pages 123–137 (2012)Cite this article

Abstract

Coastal imagery obtained from a coastal video monitoring station installed at Faro Beach, S. Portugal, was combined with topographic data from 40 surveys to generate a total of 456 timestack images. The timestack images were processed in an open-access, freely available graphical user interface (GUI) software, developed to extract and process time series of the cross-shore position of the swash extrema. The generated dataset of 2% wave run-up exceedence values R 2 was used to form empirical formulas, using as input typical hydrodynamic and coastal morphological parameters, generating a best-fit case RMS error of 0.39 m. The R 2 prediction capacity was improved when the shore-normal wind speed component and/or the tidal elevation η tide were included in the parameterizations, further reducing the RMS errors to 0.364 m. Introducing the tidal level appeared to allow a more accurate representation of the increased wave energy dissipation during low tides, while the negative trend between R 2 and the shore-normal wind speed component is probably related to the wind effect on wave breaking. The ratio of the infragravity-to-incident frequency energy contributions to the total swash spectra was in general lower than the ones reported in the literature E infra/E inci > 0.8, since low-frequency contributions at the steep, reflective Faro Beach become more significant mainly during storm conditions. An additional parameterization for the total run-up elevation was derived considering only 222 measurements for which η total,2 exceeded 2 m above MSL and the best-fit case resulted in RMS error of 0.41 m. The equation was applied to predict overwash along Faro Beach for four extreme storm scenarios and the predicted overwash beach sections, corresponded to a percentage of the total length ranging from 36% to 75%.

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Acknowledgments

The authors gratefully acknowledge European Community Seventh Framework Programme funding under the research project MICORE (grant agreement No. 202798). We are also indebted to the Restaurant “Paquete” for allowing us to deploy the cameras on their rooftop and for supplying electric power and space for our equipment. We are also thankful to Dr. Oscar Ferreira for the help and support, to Dr. Rui Taborda for providing the video cameras, and to Dr. Andre Pacheco, Umberto Andriolo, and Fotis Psaros for their contributions in the fieldwork.

Author information

Authors and Affiliations

  1. Forschungszentrum Küste, Merkurstraße, 11, 30419, Hannover, Germany

    Michalis Ioannis Vousdoukas

  2. CIMA, University of Algarve, Campus de Gambelas, 8005, Faro, Portugal

    Michalis Ioannis Vousdoukas & Luis Pedro Almeida

  3. Leibniz University Hannover, Welfengarten 1 A, 30167, Hannover, Germany

    Dagmara Wziatek

Authors
  1. Michalis Ioannis Vousdoukas
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  2. Dagmara Wziatek
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  3. Luis Pedro Almeida
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Corresponding author

Correspondence to Michalis Ioannis Vousdoukas.

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Responsible Editor: Michel Rixen

This article is part of the Topical Collection on Maritime Rapid Environmental Assessment

Appendix: The graphical user interface timestack processing application

Appendix: The graphical user interface timestack processing application

Application window

The GUI MATLAB application is freely available from the following link: https://sourceforge.net/projects/guitimestack.

The program is initiated by the GUI_timestack command though the MATLAB command prompt, and the main window consists of five panels, the options of which are described below:

  • Timestack panel

    The upper panel displaying the timestack, the extracted swash excursion tracks, and the individual peaks expressing the extrema points of each identified sash front

  • Additional plots panel

    Includes (a) a plot showing the beach profile, the R 2, R max, and η tide levels, as well as the limits of the profile section considered for beach-face slope estimation and (b) a plot showing the wave run-up spectra

  • General options panel

    Involves basic settings before the actual timestack processing steps:

    • “Select data path”—setting the path of the input data files

    • “Select file”—selecting a specific data file to process

    • “Start from”—selecting the number of the initial data file to process (valid for the “Select data path” option)

    • “Next”, “Previous”—allow browsing through the data files. Important: All extracted information are discarded

  • Swash tracking panel

    Gives the possibility to the user to enhance check the quality of the extracted data:

    • “Set limit”—the user can reduce the “vertical dimensions” of the active timestack area for image processing by clicking twice with the mouse. It is useful since in zooming on the image section containing the swash motions, the performance of the swash extraction algorithm increases significantly.

    • “Clear”—deletes all the swash tracking results

    • “Restart”—restarts the timestack processing procedure, deleting the existing data for the specific data file

    • “Manual mode”—allows manual corrections on the extracted swash lines; after “Clear,” it allows completely manual identification

  • Export options panel

    Involves actions following the data extraction procedure related to data export:

    • “Clean R_2”—deletes the estimated R 2 value from the data file with the final results

    • “Flag”—is an option to mark bad quality images and export them in a separate “Flagged” directory

    • “Save & continue”—exports the data output file to the “Exports” directory and initiates the processing of the following input data file

    • “Quit”—terminates the program

Import data files

In order to process timestack images using the GUI MATLAB application, the data have to be organized in separate MATLAB structure files named “stack.” Once the data path is set, the program will search and open and contained .mat files so only the timestack files should be included in the data directory. The “stack” structure should include the following variables:

stack:

the time stack image nx × nt, where nx expresses the number of grid points along the beach transect considered for timestack generation and nt the number of individual snapshots processed to generate the timestack image

x, z :

cross-shore real-world coordinates and elevation of the beach transect considered for timestack generation

Hs:

corresponding significant wave height

Tp:

corresponding peak wave period

Dir:

corresponding wave direction

lev:

corresponding tidal elevation

date:

corresponding date

time:

corresponding time

gen_sdate:

corresponding MATLAB serial date (one value)

sdate:

time series of MATLAB serial date corresponding to the acquisition time of the individual snapshots processed to generate the timestack image

Export data files

The data output is included in an “exprt” structure file with the following variables:

R:

time series of the wave run-up elevation

tsecs:

time series of the corresponding time in seconds

R2:

estimated R 2 value

Rmax:

estimated R max value

spectra.f:

frequency variable of the estimated wave run-up spectra

spectra.Y:

spectral density variable of the estimated wave run-up spectra

Rx:

time series of the cross-shore swash excursion position

R2x:

2% exceedence value of the cross-shore swash excursion position

Rmax_x:

maximum cross-shore swash excursion position

meta:

timestack metadata including the basic data input variables

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Vousdoukas, M.I., Wziatek, D. & Almeida, L.P. Coastal vulnerability assessment based on video wave run-up observations at a mesotidal, steep-sloped beach. Ocean Dynamics 62, 123–137 (2012). https://doi.org/10.1007/s10236-011-0480-x

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  • DOI: https://doi.org/10.1007/s10236-011-0480-x

Keywords

  • Wave run-up
  • Beach dynamics
  • Swash zone
  • Nearshore waves
  • Video imaging of waves
  • Image processing