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Rip System Reset Table, Based on Manual Assessments of Four Experienced Investigators and an Objective Statistic a
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copyrighted by American Geophysical Union Four years of daily time exposure images from an embayed beach were examined to study the spacing, persistence, and location preferences of rips in a natural rip channel system. A total of 5271 rip channels was observed on 782 days. Occurrence statistics showed no evidence of the preferred location pattern...
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... it was found that initial conditions such as offshore distance to the sandbar and magnitudes of alongshore bathymetric variability at the time of a potential reset storm introduced substantial variation, and no single criterion was adequate to objectively identify all reset events. The final reset times were determined as any event chosen by at least three of the five criteria (four manual assessments plus the wave parameter criterion; Table 2). The 15 selected reset events are shown as vertical lines on Figure 4. ...
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... characterized by a large tidal range (>1 m) and a high-energy wave climate-e.g., Refs. [17,20,21]. There are fewer studies of crescentic bars in low-energy environments with a small tidal range (such as in the Mediterranean Sea), but we can cite the following studies that provide an overview of sandbar dynamics in the Mediterranean: Spain [22,23], France [12,13], Israel [24] and Italy [25][26][27]. ...
... Regarding the specific dynamics of crescentic bars (RBB) on an event scale, numerical models can satisfactorily reproduce field observations. For example, models can simulate the formation of crescentic bars for shore normal waves-e.g., , and their linearization during periods of oblique incidence waves [17,20,45,46]. Models also predict that the formation of crescentic bars is strongly linked to the underlying bathymetry [47][48][49][50]. ...
... Low-energy waves (i.e., waves < 1 m) generate transverse bar typologies, while more energetic waves generate crescentic bars (Figure 14), revealing a seasonal signature. However, the slope, granulometry and energy characteristics of the Leucate site prevent the formation of linear bars, which represent the most energetic stage of the intermediate beach state [5,20,45,46,59,78]. The bars are thus always crescentic (Figure 14), unlike other more exposed Mediterranean sites outside the Gulf of Lions where the bars are only intermittently crescentic [51,79]. ...
The morphodynamics of the Leucate double-crescent bar system was studied over twenty years using bathymetric data supplemented by satellite images and video monitoring. Eleven different bar typologies were identified, mostly based on existing beach state classifications (Low-Tide Terrace, Transverse Bar and Rip, Rhythmic Bar and Beach), also including new heterogeneous typologies (TBR/LTT, RBB HP/RBB, TBR/RBB). The inner bar shows greater variability, with 10 different typologies observed, while the outer bar shows only three different typologies. Summer low-energy periods are dominated by TBR/LTT and TBR typologies, while RBB, although common throughout the year, dominates winter periods along with disrupted bar configurations. The return to less energetic periods in spring is associated with the establishment of heterogeneous typologies. The outer bar has a fairly stable position, although breaches at the embayments and slight movements of its horns can occur following particularly energetic episodes. The inner bar, on the other hand, is much more dynamic, with more common breaches at the embayments and significant cross-shore movement of the horns. Seasonal changes in bar typology do not lead to bar renewal through destruction/reconstruction. Overall, the morphological and typological characteristics of the bar system described here seem somewhat unique compared to the existing literature.
... Due to outcrops and morphological structures, beaches, accounting for about 50% of the world's coastline, bend to form "embayed beaches" (Short 1999;Ratliff and Murray 2014). To investigate the modern shoreline change of embayed beaches, numerous studies have been carried out based on short-term monitoring (Ranasinghe et al. 2004;Holman et al. 2006;McCarroll et al. 2016;Blossier et al. 2017;Burvingt et al. 2018). Shoreline rotation, a common phenomenon in the formation of embayed beaches, results in beaches eroding and narrowing at one end while accreting and widening at the other (Short 1999). ...
Lacustrine beach ridges are often used to reconstruct past lake levels. However, the sedimentary architecture involved in their sedimentary evolution remains unclear, particularly for embayed beaches. To better understand the sedimentary processes, the sedimentary architecture and geomorphology of an embayed beach on the southern of Qinghai Lake were investigated using ground penetrating radar (GPR), trenches, and modern beach observation. The embayed beach's deposits are composed of three major sedimentary facies: washover deposition, fair-weather swash deposition, and lagoonal deposition. According to the variations in sedimentary facies, the formation of the embayed beach can be divided into two stages: lake-level highstand and lake-level lowstand. During lake-level highstand stage, geomorphic changes primarily occur in the cross-shore direction. A single beach ridge with washover lobes and sheets developed along the entire embayed beach. During lake-level lowstand stage, the sediments are mainly transported alongshore within the embayed beach. The northern end shows progradational complex deposits including beach ridge, lagoon and beach system, while only a beach ridge is present at the southern end. Hydrodynamic changes in two stages lead to the heterogeneity of sediment distribution, reflected in the morphology and the sedimentary architecture. The interaction of topography and hydrodynamics controls the formation and evolution of the embayed beach. This study improves the understanding of the sedimentary processes involved in embayed beaches.
... This product essentially smooths out fast-moving coastal processes such as wave swash. Timex imagery provides a consistent representation of rip currents (Holman, Symonds et al. 2006) and sand bars (Armaroli, Ciavola et al. 2012). The video monitoring system relies on geometric techniques to transform and rectify the oblique images captured by the camera into a plan view of the beach. ...
Coastal managers recognize that beach areas are crucial to their effective use for tourism and recreational purposes. Therefore, beaches in tourist areas are constantly maintained and nourished by local authorities to increase beach area. However, studies focusing on the evolution of small gravel pocket beaches are scarce. In this paper, the effects of energetic wave events on beach area change are investigated using video imagery system at an artificial gravel pocket beach Ploče in Rijeka, Croatia. The temporal evolution of beach width was investigated by considering video-derived shorelines at the eastern and western cells of Ploče beach over a period of six months, and during this period, wave energy was calculated using various expressions. The results of this study indicate that there is a reasonable correlation between the energy of wave events and the decrease in beach area. The results of the correlation between the expressions for wave energy and beach area change depend on the beach side. The smallest RMSE is between the expression for wave peak energy and the western cell, and the expression for storm power index and the eastern cell. The results of this study also show that the Ploče beach proved to be relatively stable throughout the camera observation period, with the beach area fluctuating within ±15% of its average value, with a general tendency to decrease after severe wave events.
... Low light intensities (local minima) in video images can be used to identify rip channels. Based on these criteria, Ranasinghe et al. (1999); Ranasinghe et al. (2000); Bogle et al. (2000); Holman et al. (2006) and Turner et al. (2007) have conducted various studies to locate rip channels manually and automatically from Timex images. ...
Rip currents are one of the most well-known coastal hazards on the world's beaches. Identification and continuous monitoring of these currents are essential for the safety of beachgoers and prevent the number of drowning cases. Studies on the diversity of rip currents in space and time off the Indian coast are minimal. However, these have long been the subject of research worldwide. Based on the earlier rip current-related works in Visakhapatnam beaches, RK Beach is known for highest recorded number of drowning deaths. Albeit, much attention is not given to monitor and safeguard beachgoers from these furious currents. In this work, a preliminary experimental study has been initiated with an objective of continuous monitoring and identification of significant rip channels along Visakhapatnam beaches from video imagery data by adopting and implementing an open-source, Quantitative Coastal Imaging Toolbox (QCIT). Ten minutes of video data were collected from temporarily installed camera for different months. Later, QCIT was used to pre-process the video data, camera calibration, domain definition followed by rectification products. Rectification products contain single image products and pixel instruments. Single-image products such as Timex, and bright and dark images are obtained by calculating the average, maximum, and minimum intensity on the rectified frames, respectively. The phenomenon of persistent gaps in wave-breaking events that appear as dark spots on bright background from Timex images shows quasi-permanent rip channels. The locations of the rip channels extracted from the Timex images were accurately well matched to the hotspot maps of the rip currents obtained from the high-resolution satellite images, drifter and die experiments at the study site. However, once the video camera is permanently set up, further statistical analysis with continuous data availability is also possible. Further implementation of this study would be helpful in the continuous monitoring of coastal rip currents, other coastal parameters (i.e., alongshore currents, shoreline mapping, wave run-up, and up-to-date nearshore estimated bathymetry), and implementation of numerical modeling of coastal processes by supplying better inputs. With these essential results, ESSO-INCOIS and SAC-ISRO have embarked on a project with the primary objective of continuous monitoring and issuing operational forecasting alerts of rip currents by developing a coastal video surveillance system that also provides information on complex coastal and nearshore processes.
... Using the two bathymetric datasets, we estimated the volume of sediment that was eroded through the rip channels and found that more than 1500 cubic meters were removed during the 5-month period. The shape of nearshore bedforms is further controlled by the geometric characteristics of the beach (i.e., length) [68] and the occurrence of hard seafloor areas that influence sediment deposition. ...
... Using the two bathymetric datasets, we estimated the volume of sediment that was eroded through the rip channels and found that more than 1500 cubic meters were removed during the 5-month period. The shape of nearshore bedforms is further controlled by the geometric characteristics of the beach (i.e., length) [68] and the occurrence of hard seafloor areas that influence sediment deposition. It has been suggested that the crescentic bar oscillates between straight and crescentic form at various time scales, depending on the intensity and incidence angle of waves [69]. ...
... When wave energy is increasing, the crescentic bar becomes straight again, through a process which is called a morphological reset [65]. Recent studies have shown that the crescentic bar is formed preferentially under normal wave incidence angles to the shore, while oblique wave angles lead mainly to morphological reset [68,[70][71][72]. Such a behavior was not observed in the duration of the study. ...
Short-term changes in shallow bathymetry affect the coastal zone, and therefore their monitoring is an essential task in coastal planning projects. This study provides a novel approach for monitoring shallow bathymetry changes based on drone multispectral imagery. Particularly, we apply a shallow water inversion algorithm on two composite multispectral datasets, being acquired five months apart in a small Mediterranean sandy embayment (Chania, Greece). Initially, we perform radiometric corrections using proprietary software, and following that we combine the bands from standard and multispectral cameras, resulting in a six-band composite image suitable for applying the shallow water inversion algorithm. Bathymetry inversion results showed good correlation and low errors (<0.3 m) with sonar measurements collected with an uncrewed surface vehicle (USV). Bathymetry maps and true-color orthomosaics assist in identifying morphobathymetric features representing crescentic bars with rip channel systems. The temporal bathymetry and true-color data reveal important erosional and depositional patterns, which were developed under the impact of winter storms. Furthermore, bathymetric profiles show that the crescentic bar appears to migrate across and along-shore over the 5-months period. Drone-based multispectral imagery proves to be an important and cost-effective tool for shallow seafloor mapping and monitoring when it is combined with shallow water analytical models.
... Sandbars, in particular subtidal sandbars, are responsible for significant spatiotemporal variations in nearshore bathymetric profiles [1,2]. They are fundamental to various nearshore processes: they can reduce beach-dune erosion through wave dissipation [3][4][5][6]; exchange sand with the subaerial beach [7]; control advection, mixing and distribution of nutrients and pollutants [8]; and determine recreational safety [9]. Hence, monitoring and understanding the spatiotemporal variability of nearshore morphology is essential to both scientists and coastal managers. ...
Nearshore sandbars characterize many sandy coasts, and unravelling their dynamics is crucial to understanding nearshore sediment pathways. Sandbar morphologies exhibit complex patterns that can be classified into distinct states. The tremendous progress in data-driven learning in image recognition has recently led to the first automated classification of single-barred beach states from Argus imagery using a Convolutional Neural Network (CNN). Herein, we extend this method for the classification of beach states in a double-barred system. We used transfer learning to fine-tune the pre-trained network of ResNet50. Our data consisted of labelled single-bar time-averaged images from the beaches of Narrabeen (Australia) and Duck (US), complemented by 9+ years of daily averaged low-tide images of the double-barred beach of the Gold Coast (Australia). We assessed seven different CNNs, of which each model was tested on the test data from the location where its training data came from, the self-tests, and on the test data of alternate, unseen locations, the transfer-tests. When the model trained on the single-barred data of both Duck and Narrabeen was tested on unseen data of the double-barred Gold Coast, we achieved relatively low performances as measured by F1 scores. In contrast, models trained with only the double-barred beach data showed comparable skill in the self-tests with that of the single-barred models. We incrementally added data with labels from the inner or outer bar of the Gold Coast to the training data from both single-barred beaches, and trained models with both single- and double-barred data. The tests with these models showed that which bar the labels used for training the model mattered. The training with the outer bar labels led to overall higher performances, except at the inner bar. Furthermore, only 10% of additional data with the outer bar labels was needed for reasonable transferability, compared to the 20% of additional data needed with the inner bar labels. Additionally, when trained with data from multiple locations, more data from a new location did not always positively affect the model’s performance on other locations. However, the larger diversity of images coming from more locations allowed the transferability of the model to the locations from where new training data were added.
... Using the two bathymetric datasets, we estimated the volume of sediment that was eroded through the rip channels and found that more than 1500 cubic meters were removed during the 5-month period. The shape of nearshore bedforms is further controlled by the geometric characteristics of the beach (i.e., length) [68] and the occurrence of hard seafloor areas that influence sediment deposition. ...
... Using the two bathymetric datasets, we estimated the volume of sediment that was eroded through the rip channels and found that more than 1500 cubic meters were removed during the 5-month period. The shape of nearshore bedforms is further controlled by the geometric characteristics of the beach (i.e., length) [68] and the occurrence of hard seafloor areas that influence sediment deposition. It has been suggested that the crescentic bar oscillates between straight and crescentic form at various time scales, depending on the intensity and incidence angle of waves [69]. ...
... When wave energy is increasing, the crescentic bar becomes straight again, through a process which is called a morphological reset [65]. Recent studies have shown that the crescentic bar is formed preferentially under normal wave incidence angles to the shore, while oblique wave angles lead mainly to morphological reset [68,[70][71][72]. Such a behavior was not observed in the duration of the study. ...
Short-term changes in shallow bathymetry affect the coastal zone and therefore their monitoring is an essential task in coastal planning projects. This study provides a novel approach for monitoring shallow bathymetry change based on drone multispectral imagery. Particularly we apply a shallow water inversion algorithm on two composite multispectral datasets being acquired five months apart in a small Mediterranean sandy embayment (Chania, Greece). Initially, we perform radiometric corrections using proprietary software and following we combine the bands from standard and multispectral cameras resulting in a six-band composite image suitable for applying the shallow water inversion algorithm. Bathymetry inversion results showed good correlation and low errors (< 0.3m) with sonar measurements collected with an uncrewed surface vehicle (USV). Bathymetry maps and true-color orthomosaics assist in identifying morphobathymetric features representing crescentic bars with rip channel systems. The temporal bathymetry and true-color data reveal important erosional and depositional patterns, which were developed under the impact of winter storms. Furthermore, bathymetric profiles show that the crescentic bar appears to migrate across and along-shore over the 5-months period. Drone-based multispectral imagery proves to be an important and cost-effective tool for shallow seafloor mapping and monitoring when it is combined with shallow water analytical models.
... Previous studies also found a large variety in crescentic bar characteristics, with average wavelengths varying from 100 m to several km and average cross-shore amplitudes (defined as half the cross-shore distance between successive horns and bays) varying from 5 to 50 m (e.g., Van Enckevort et al., 2004;Arifin and Kennedy, 2011;Athanasiou et al., 2018). Furthermore, crescentic bar patterns were found to migrate alongshore at rates up to 100 m/day, presumably due to strong alongshore currents (Ruessink et al., 2000;Van Enckevort et al., 2004;Holman et al., 2006;Orzech et al., 2010). ...
... Apart from that, existing observational studies on crescentic bars are often limited in duration (e.g., Van Enckevort et al., 2004) or temporal resolution (e.g., Athanasiou et al., 2018). Moreover, they generally focus on beaches that are either characterized by significant tidal range (> 1 m) and highly-energetic (H m0 > 1 m) waves (Van Enckevort et al., 2004;Holman et al., 2006;Price and Ruessink, 2011) or a long fetch (e.g., Contardo and Symonds, 2015). Furthermore, crescentic bar studies in low-energetic environments with almost no tides and small fetches (such as the Mediterranean Sea) are scarce. ...
... Crescentic bar events and specifically the formation/straightening moments were detected visually in this study (analogous to Holman et al., 2006) by two experienced researchers to prevent bias and increase accuracy. However, previous studies on crescentic bars often employed an automatic algorithm using either the standard deviation of the detrended barline (σ B , e.g., Price and Ruessink, 2011;Contardo and Symonds, 2015) or the sinuosity of the barline (Sin B , Ojeda et al., 2011). ...
... The rip positions were manually identified by visually characterizing the intensity minima. Holman et al. [15] also observed rip spacing by considering the trajectories of rip currents alongshore. Gallop et al. [13] created algorithms to locate sandbar crests that are depicted by light intensity maxima and rip channels (depicted by light intensity minima) in rectified, time-averaged images of the surf-zone. ...
Rip Currents are contributing around 25 fatal drownings each year in Australia. Previous research has indicated that most of beachgoers cannot correctly identify a rip current, leaving them at risk of experiencing a drowning incident. Automated detection of rip currents could help to reduce drownings and assist lifeguards in supervision planning; however, varying beach conditions have made this challenging. This work presents the effectiveness of an improved lightweight framework for detecting rip currents: RipDet+¹, aided with residual mapping to boost the generalization performance. We have used Yolo-V3 architecture to build RipDet+ framework and utilize pretrained weight by fully exploiting the detection training set from some base classes which in result quickly adapt the detection prediction to the available rip data. Extensive experiments are reported which show the effectiveness of RipDet+ architecture in achieving a detection accuracy of 98.55%, which is significantly greater compared to other state-of-the-art methods for Rip currents detection.
... Low light intensities (local minima) in video images can be used to identify rip channels. Based on these criteria, Ranasinghe et al. (1999); Ranasinghe et al. (2000); Bogle et al. (2000); Holman et al. (2006) and Turner et al. (2007) have conducted various studies to locate rip channels manually and automatically from Timex images. ...
Rip currents are one of the most well-known coastal hazards on the world’s beaches. Identification and continuous monitoring of these currents are essential for the safety of beachgoers and prevent the number of drowning cases. Studies on the diversity of rip currents in space and time off the Indian coast are minimal. However, these have long been the subject of research worldwide. Based on the earlier rip current-related works in Visakhapatnam beaches, RK Beach is known for highest recorded number of drowning deaths. Albeit, much attention is not given to monitor and safeguard beachgoers from these furious currents. In this work, a preliminary experimental study has been initiated with an objective of continuous monitoring and identification of significant rip channels along Visakhapatnam beaches from video imagery data by adopting and implementing an open-source, Quantitative Coastal Imaging Toolbox (QCIT). Ten minutes of video data were collected from temporarily installed camera for different months. Later, QCIT was used to pre-process the video data, camera calibration, domain definition followed by rectification products. Rectification products contain single image products and pixel instruments. Single-image products such as Timex, and bright and dark images are obtained by calculating the average, maximum, and minimum intensity on the rectified frames, respectively. The phenomenon of persistent gaps in wave-breaking events that appear as dark spots on bright background from Timex images shows quasipermanent rip channels. The locations of the rip channels extracted from the Timex images were accurately well matched to the hotspot maps of the rip currents obtained from the high-resolution satellite images, drifter and die experiments at the study site. However, once the video camera is permanently set up,
further statistical analysis with continuous data availability is also possible. Further implementation of this study would be helpful in the continuous monitoring of coastal rip currents, other coastal parameters (i.e., alongshore currents, shoreline mapping, wave run-up, and up-to-date nearshore estimated bathymetry), and implementation of numerical modeling of coastal processes by supplying better inputs. With these essential results, ESSO-INCOIS and SAC-ISRO have embarked on a project with the primary objective of continuous monitoring and issuing operational forecasting alerts of rip currents by developing a coastal video surveillance system that also provides information on complex coastal and nearshore processes.
