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Fig. 4 Scatter plots showing the three more accurate Ry wave run-up parameterizations (a—c; x-axis; see label for equation), as well as the values estimated with the Stockdon06 formula (d), versus the measurements (y-axis)

Figure 4 Scatter plots showing the three more accurate Ry wave run-up parameterizations (a—c; x-axis; see label for equation), as well as the values estimated with the Stockdon06 formula (d), versus the measurements (y-axis)

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Table 1 Significant wave height and direction, peak wave period, surge height, maximum tidal elevation, and duration of the tested extreme events with return period of 5, 10, and 25 years
Table 1 Significant wave height and direction, peak wave period, surge height, maximum tidal elevation, and duration of the tested extreme events with return period of 5, 10, and 25 years
the cross-shore transect considered for swash motion monitoring are shown, along with the main parking area and another section where the wall is discontinuous and overwash events are frequent Fig. 1 a Map of the Algarve region (S Portugal) showing the locations of the study area (rectangle), the IH wave buoy, and the Huelva tidal gauge. b Mosaic of aerial photographs of the study area, rotated by 39° counterclockwise. The location of the video station and
the cross-shore transect considered for swash motion monitoring are shown, along with the main parking area and another section where the wall is discontinuous and overwash events are frequent Fig. 1 a Map of the Algarve region (S Portugal) showing the locations of the study area (rectangle), the IH wave buoy, and the Huelva tidal gauge. b Mosaic of aerial photographs of the study area, rotated by 39° counterclockwise. The location of the video station and
Fig. 2. Snapshot of the GUI timestack processing software used. Red lines indicate the swash front motions, and yellow dots the discrete maxim: considered for the estimation of 2% exceedence values For this study, timestack images for wave run-up measurements were generated on an hourly basis. Standard transformation from image to world coordinates (image geo-rectification) took place after applying a lens distortion correction (Bouguet 2007) and considering the 3x4 perspective transformation matrix P, using homogeneous coordinates (Hartley and Zisserman 2006). The procedure followed is described in detail in Vousdoukas et al. (2011) and in the extensive literature on coastal video monitoring (e.g., Holman and Stanley 2007; Smith and Bryan 2007; Pearre and Puleo 2009 and references therein). Geo-rectification errors due to camera movement have been corrected following an automatic procedure based on feature matching (Vousdoukas et al. 2011b). All timestack images were processed in an open-access GUI software (https://sourceforge.net/projects/guitimestack; see “Appendix” and Fig. 2), specially developed in MATLAB to extract and process time series of the cross-
Fig. 2. Snapshot of the GUI timestack processing software used. Red lines indicate the swash front motions, and yellow dots the discrete maxim: considered for the estimation of 2% exceedence values For this study, timestack images for wave run-up measurements were generated on an hourly basis. Standard transformation from image to world coordinates (image geo-rectification) took place after applying a lens distortion correction (Bouguet 2007) and considering the 3x4 perspective transformation matrix P, using homogeneous coordinates (Hartley and Zisserman 2006). The procedure followed is described in detail in Vousdoukas et al. (2011) and in the extensive literature on coastal video monitoring (e.g., Holman and Stanley 2007; Smith and Bryan 2007; Pearre and Puleo 2009 and references therein). Geo-rectification errors due to camera movement have been corrected following an automatic procedure based on feature matching (Vousdoukas et al. 2011b). All timestack images were processed in an open-access GUI software (https://sourceforge.net/projects/guitimestack; see “Appendix” and Fig. 2), specially developed in MATLAB to extract and process time series of the cross-
Fig. 3. Histograms of the significant wave height (a), peak wave period (b), beach-face slope (c), Iribarren number (d), non-dimensional sediment fall velocity (e), and 2% exceedence wave run-up height for the measurements considered. The number of bins considered is 100
Fig. 3. Histograms of the significant wave height (a), peak wave period (b), beach-face slope (c), Iribarren number (d), non-dimensional sediment fall velocity (e), and 2% exceedence wave run-up height for the measurements considered. The number of bins considered is 100
Table 2 Summary of efforts to parameterize the 2% exceedence for the run-up height R» on the grounds of the deep water significant wave height H, offshore wavelength L,, the Iribarren number €, the The values express RMS errors (meters) after iterative fitting and p, express fitting coefficients. Iterative fitting was applied to all parameters apart from the Stockdon06 formula beach slope (3, the tidal elevation 7iae, and the cross-shore wind speed component U,,,.
Table 2 Summary of efforts to parameterize the 2% exceedence for the run-up height R» on the grounds of the deep water significant wave height H, offshore wavelength L,, the Iribarren number €, the The values express RMS errors (meters) after iterative fitting and p, express fitting coefficients. Iterative fitting was applied to all parameters apart from the Stockdon06 formula beach slope (3, the tidal elevation 7iae, and the cross-shore wind speed component U,,,.
Fig. 5 Scatter plots showing the best-fit R. wave run-up parameter- izations (x-axis; see label for equation) vs the measurements (y-axis), corresponding to water levels above (a) and below MSL (b)
Fig. 5 Scatter plots showing the best-fit R. wave run-up parameter- izations (x-axis; see label for equation) vs the measurements (y-axis), corresponding to water levels above (a) and below MSL (b)
Fig. 7 Scatter plot of infragravity (Einfra) vs incident band (Ejnc;) wave run-up energy contributions. Color scale expresses the tidal level researchers, which, however, has several limitations and may involve inaccuracies. The above is also shown by the scatter of the values when compared to the ones estimated from formulations (Figs. 4 and 5), as well as from the fact that maximum absolute errors often reached | m. Waves interact
Fig. 7 Scatter plot of infragravity (Einfra) vs incident band (Ejnc;) wave run-up energy contributions. Color scale expresses the tidal level researchers, which, however, has several limitations and may involve inaccuracies. The above is also shown by the scatter of the values when compared to the ones estimated from formulations (Figs. 4 and 5), as well as from the fact that maximum absolute errors often reached | m. Waves interact
Fig. 6 Histograms (number of bins=100) of the infragravity-to- incident band wave run-up energy contributions ratio Eintia/Einci (a) and the peak run-up frequency (b) for all the studied time series
Fig. 6 Histograms (number of bins=100) of the infragravity-to- incident band wave run-up energy contributions ratio Eintia/Einci (a) and the peak run-up frequency (b) for all the studied time series
Fig. 9 Scatter plot of the peak run-up frequency vs the non- dimensional sediment fall velocity Q (e). Color scale expresses the tidal level Predicting swash motions when the wave characteristics at the shoreline are known is relatively straightforward, and swash excursions have been well described by ballistic models. The above approach is based on translating swash energy/momentum into wave run-up height, considering the beach-face friction and slope (e.g., Hunt 1959) and has been proved to be accurate, despite uncertainties, i.e. the ones related to the interaction of individual waves (e.g., Larson et al. 2004). On the other hand, wave energy dissipation due to shoaling/breaking is more difficult to quantify, especially since the surf zone is often a denied environment for field measurements.
Fig. 9 Scatter plot of the peak run-up frequency vs the non- dimensional sediment fall velocity Q (e). Color scale expresses the tidal level Predicting swash motions when the wave characteristics at the shoreline are known is relatively straightforward, and swash excursions have been well described by ballistic models. The above approach is based on translating swash energy/momentum into wave run-up height, considering the beach-face friction and slope (e.g., Hunt 1959) and has been proved to be accurate, despite uncertainties, i.e. the ones related to the interaction of individual waves (e.g., Larson et al. 2004). On the other hand, wave energy dissipation due to shoaling/breaking is more difficult to quantify, especially since the surf zone is often a denied environment for field measurements.
Fig. 8 Scatter plot of the ratio of the peak run-up period to peak offshore wave period vs the Iribarren number €
Fig. 8 Scatter plot of the ratio of the peak run-up period to peak offshore wave period vs the Iribarren number €
Fig. 10 Scatter plots of the wave run-up height R» error vs the significant wave height (a), peak wave period (b), beach-face slope (c), Iribarren number (d), non-dimensional sediment fall velocity (e), shore-normal wind velocity component (f), tidal elevation (g), and the peak run-up frequency (h)
Fig. 10 Scatter plots of the wave run-up height R» error vs the significant wave height (a), peak wave period (b), beach-face slope (c), Iribarren number (d), non-dimensional sediment fall velocity (e), shore-normal wind velocity component (f), tidal elevation (g), and the peak run-up frequency (h)
Fig. 11 Overwash maps of Faro Beach for storms with return period of 5 (a), 10 (b), 25 (c), and 50 years (d). Color scale indicates the excess total run-up height, relative to the maximum dune/seawall elevation, and white lines express the maximum swash excursion limit, in cases of no overwash The main advantage of the methodology followed is that it is simple, and it can be applied at the numerous study sites where data from coastal video monitoring stations exist. Moreover, the GUI timestack processing application has been designed in a way to easily allow modifications and different image-processing algorithms, which poten- tially could be more efficient at sites with different
Fig. 11 Overwash maps of Faro Beach for storms with return period of 5 (a), 10 (b), 25 (c), and 50 years (d). Color scale indicates the excess total run-up height, relative to the maximum dune/seawall elevation, and white lines express the maximum swash excursion limit, in cases of no overwash The main advantage of the methodology followed is that it is simple, and it can be applied at the numerous study sites where data from coastal video monitoring stations exist. Moreover, the GUI timestack processing application has been designed in a way to easily allow modifications and different image-processing algorithms, which poten- tially could be more efficient at sites with different
Related topics:
GeologyOceanographyImage ProcessingWave EnergyGraphic User Interface DesignOcean DynamicsSwash ZoneSignificant Wave Height
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