Wave run-up observations in microtidal, sediment-starved pocket beaches of the Eastern Mediterranean

Vousdoukas, Michalis; Velegrakis, Adonis F.; Dimou, K. Nadia; Zervakis, Vassilis; Conley, Daniel

doi:10.1016/j.jmarsys.2009.01.009

Cited by 47 publications

(41 citation statements)

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“…where η tide and η su are the tidal and surge heights, respectively; η s is the maximum wave set-up height; and S sw (t) is the swash-induced water-level fluctuation (Vousdoukas et al 2009a(Vousdoukas et al , 2011aStockdon et al 2006). Wave run-up height R is usually defined as a discrete-intime variable, containing the local maxima of the water-level fluctuation time series η sw (t), with respect to still water level:…”

Section: Timestack Processingmentioning

confidence: 99%

“…where H o is the deep water significant wave height and ξ the Iribarren number (Battjes 1974;Iribarren and Nogales 1949), given by: Holman 1986;Douglass 1992;Synolakis 1987;Ruggiero et al 2004), while the use of coastal video monitoring systems allowed the acquisition of wave run-up measurements for longer periods at various sites (Holman and Stanley 2007;Velegrakis et al 2007;Vousdoukas et al 2009a). Most of the above measurements are based on "timestack" images (e.g., Aagaard and Holm 1989;Holland and Holman 1993), which are representing the temporal pixel intensity variations (x-axis) along a cross-shore transect of contiguous pixels that span the swash zone (y-axis).…”

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confidence: 99%

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

2011

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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 shorenormal wind speed component is probably related to the wind effect on wave breaking. The ratio of the infragravityto-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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Section: Timestack Processingmentioning

confidence: 99%

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confidence: 99%

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

2011

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“…Following wave breaking, different short-term dynamic processes occur on a beach, mostly wave-induced high/low-frequency swash motions [2], groundwater/bed interactions [3,4], and scouring [5]. The beach morphology usually tends toward an equilibrium slope resulting from an onshore/offshore sediment transport induced by waves and currents [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

LiDAR Validation of a Video-Derived Beachface Topography on a Tidal Flat

et al. 2017

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Increasingly used shore-based video stations enable a high spatiotemporal frequency analysis of shoreline migration. Shoreline detection techniques combined with hydrodynamic conditions enable the creation of digital elevation models (DEMs). However, shoreline elevations are often estimated based on nearshore process empirical equations leading to uncertainties in video-based topography. To achieve high DEM correspondence between both techniques, we assessed video-derived DEMs against LiDAR surveys during low energy conditions. A newly installed video system on a tidal flat in the St. Lawrence Estuary, Atlantic Canada, served as a test case. Shorelines were automatically detected from time-averaged (TIMEX) images using color ratios in low energy conditions synchronously with mobile terrestrial LiDAR during two different surveys. Hydrodynamic (waves and tides) data were recorded in-situ, and established two different cases of water elevation models as a basis for shoreline elevations. DEMs were created and tested against LiDAR. Statistical analysis of shoreline elevations and migrations were made, and morphological variability was assessed between both surveys. Results indicate that the best shoreline elevation model includes both the significant wave height and the mean water level. Low energy conditions and in-situ hydrodynamic measurements made it possible to produce video-derived DEMs virtually as accurate as a LiDAR product, and therefore make an effective tool for coastal managers.

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“…Thus, the COV of the left camera was considered as the origin of the Cartesian coordinate system. The above coordinates can be easily transformed to a fixed system by indentifying three or more points of known locations to the desired system and using them as reference to estimate the P matrix [see also [13]]. …”

Section: Stereo-triangulationmentioning

confidence: 99%

SVMT: A MATLAB toolbox for stereo-vision motion tracking of motor reactivity

Vousdoukas

Perakakis

Idrissi

et al. 2012

Computer Methods and Programs in Biomedicine

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ARTICLE IN PRESS No. of Pages 12 c o m p u t e r m e t h o d s a n d p r o g r a m s i n b i o m e d i c i n e x x x( 2 0 1 2 ) xxx-xxx j o u r n a l h o m e p a g e : w w w . i n t l . e l s e v i e r h e a l t h . IntroductionIn experimental psychophysiology, human motor reactivity to sensory stimulation is usually indexed by surface electromyography (EMG), which requires the placement of several electrodes on the skin surface [1]. This limits the mobility of the subject and reduces the possible contexts in which motor responses can be recorded and evaluated. In * Corresponding author. addition, EMG captures only the activity of specific muscle groups, whereas certain motor reflexes to sensory stimuli, such as the startle reflex, involve a global motor response characterized by complex muscle contraction patterns at different body areas [2]. A detailed investigation of these global motor reactivity patterns, in relation to underlying physiological control mechanisms, could result in a more systematic mapping of psychophysiological processes under sensory stimulation.0169-2607/$ -see front matter

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Wave run-up observations in microtidal, sediment-starved pocket beaches of the Eastern Mediterranean

Cited by 47 publications

References 40 publications

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

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

LiDAR Validation of a Video-Derived Beachface Topography on a Tidal Flat

SVMT: A MATLAB toolbox for stereo-vision motion tracking of motor reactivity

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