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Storm-driven changes in rip channel patterns on an embayed beach
Geomorphology 127 (2011) 179–188
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Geomorphology j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / g e o m o r p h
Storm-driven changes in rip channel patterns on an embayed beach S.L. Gallop a,⁎, K.R. Bryan a, Giovanni Coco b, S.A. Stephens b a b
Department of Earth and Ocean Sciences, Faculty of Science and Engineering, The University of Waikato, Hamilton 3240, New Zealand National Institute of Water and Atmospheric Research, P.O. Box 11-115, Hamilton 3240, New Zealand
a r t i c l e
i n f o
Article history: Received 5 May 2010 Received in revised form 10 December 2010 Accepted 12 December 2010 Available online 21 December 2010 Keywords: Rip currents Rip channels Video imagery Beach state Sand bars Nearshore morphology
a b s t r a c t This paper introduces a semi-automatic computer algorithm designed to detect rip current channels in video imagery. As a case study, this method is applied to 3.3 years of video data from an embayed beach to demonstrate the link between antecedent surf zone morphology, wave energy and up/down transitions in beach state. An objective measure of rip channel change was developed to define six significant rip reconfiguration events and relate these events to wave energy. Over the period of study no complete resets of the nearshore morphology occurred. The analysis indicates that direct correlation of rip patterns with the instantaneous wave conditions is not a useful way to demonstrate how rips and waves interact. The average wave energy over a period of ten days, combined with storm duration were good indicators of rip channel change, demonstrating that in general, beach morphology responds with a time lag to changes in forcing. Rip channels with a short cross-shore length and narrow alongshore spacing responded faster to changes in wave conditions than rips with a long cross-shore length and wider alongshore spacing. To force changes in the rip morphology, longer rip channels required wave events of higher energy and/or a longer duration. Offshore islands protect the beach under certain wave approach angles, sometimes resulting in a dual-width surf zone, which was narrow at the sheltered end and wide at the exposed end of the beach. The wider surf zone end was characterised by three dominant and persistent rip channels, whereas the narrow surf zone section contained a number of smaller rips which evolved rapidly under wave forcing. Our observations demonstrate the importance of rip channel size in controlling the response time of nearshore morphology. © 2010 Elsevier B.V. All rights reserved.
1. Introduction Rip currents are fast, narrow currents that traverse the surf zone, generally in a seaward direction. Rips are driven by radiation stress gradients (Longuet-Higgins and Stewart, 1964) generated by temporal and spatial patterns in wave breaking (MacMahan et al., 2006). There are also weaker currents heading onshore adjacent to rip currents contributing to rip feeder currents (MacMahan et al., 2006). The orientation, size and strength of rip currents depend on the offshore wave conditions such as wave height, period and direction of propagation, and on the underwater topography. The underwater topography influences wave breaking patterns and subsequent steering of rip currents, so rip characteristics depend on the interaction between both the nearshore topography and incident waves. It is commonly assumed that after high wave events, the rip channel morphology ‘resets’ forming a shore-parallel bar (Holman et al., 2006), where this assumption is the basis of most theories of rip current generation.
⁎ Corresponding author. Present address: School of Environmental Systems Engineering, The University of Western Australia, 35 Stirling Highway, MO15, Crawley, WA, 6019, Australia. Tel.: +61 8 6488 8117; fax: +61 8 6488 7279. E-mail addresses: [email protected] (S.L. Gallop), [email protected] (K.R. Bryan), [email protected] (G. Coco), [email protected] (S.A. Stephens). 0169-555X/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.geomorph.2010.12.014
Embayments or ‘mega-cusps’ have been shown to be associated with rip currents. Such embayments contribute to the coastal erosion hazard by causing ‘hot-spots’ of erosion. For example, at Monterey Bay, California alongshore variations in the shoreline were significantly correlated with the alongshore variations in rip spacing and dune erosion volume (Thornton et al., 2007). Moreover, permanent dune recession occurred in unison with these quasi-stable mega-cusps (erosion ‘hot-spots’) leading to enhanced shoreline erosion compared to a uniform coast. This type of erosion scarps make the coast more susceptible to erosion during extreme events such as combinations of large storm waves, surge, and high tide, an outcome which will worsen with projected sea-level rise. Therefore quantifying rip channel size and spacing and how these characteristics change with wave conditions is central to understanding patterns of beach erosion. There have been many attempts to link wave conditions such as height to rip channel characteristics, in particular, to alongshore rip spacing. Field observations and numerical models both indicate that larger inputs of energy into the surf zone will result in the development of larger morphology with larger rip channel spacing (McKenzie, 1958; Short, 1985; Huntley and Short, 1992; Calvete et al., 2005). More recent research based on the analysis of video observations has not found a clear relationship between rip current patterns and waves. In particular, Ranasinghe et al. (2000) and Whyte et al. (2005) found that alongshore rip channel spacing did not increase or decrease with changes in wave
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height. Turner et al. (2007) found no clear relationship between the number of rips and mean alongshore rip channel spacing to the offshore wave conditions. Van Enckevort et al. (2004) and Holman et al. (2006) also could not explain variations in rip channel alongshore spacing. This has lead to the conclusion that rips, once formed, are topographically controlled (Ranasinghe et al., 2000; Whyte et al., 2005; Calvete et al., 2007; Turner et al., 2007). In terms of numerical modeling, recent work based on linear stability analysis (Calvete et al., 2007) has shown that growth and geometry of rips is critically controlled by the pre-existing cross-shore profile. Also, numerical modeling based on the solution of the shallow water equations (Smit et al., 2008) indicates that preexisting channels can dictate the morphological response and evolution of the system if wave forcing changes. To date, there are no definitive results indicating when rip channels might be regularly or irregularly spaced alongshore and what drives rip channel pattern change. Early work on the generation of rip currents suggested that an alongshore standing edge wave might cause the required flow pattern (Bowen and Inman, 1971), in which case one might expect the alongshore pattern to be regular and reflect the wave form of the edge wave. Indeed, Huntley and Short (1992), Short and Brander (1999), and MacMahan et al. (2005) have found that rips were relatively regularly spaced alongshore. Numerical models of rip current generation have shown that rip currents can also be the result of selforganization processes, and can develop from random small-scale seabed perturbations into a regularly spaced pattern (Caballeria et al., 2002). Assessing the regularity (or lack of) of rips has been considered as a potential diagnostic tool to test between rip generation processes. Using a large data set of video imagery from the embayed, 2 km-long Palm Beach, Australia, Holman et al. (2006) concluded that rips were irregularly spaced alongshore. Symonds et al. (1997) noted periods of quasi-regular alongshore spacing and periods of irregular spacing on this beach. At the northern Gold Coast, an open coast, rips were found to be irregularly spaced alongshore (Turner et al., 2007). On the embayed Durras Beach in Australia, Eliot (1973) found that there were places where rip currents tended to occur frequently and that these locations were regularly spaced alongshore. Relevant to the present study is the case of rips associated with headlands which have been found to be persistent (Short, 1985, 2007; Eliot, 1973) and partly controlled by headlands (Short, 2007). One of the impediments to solving some of the controversies on the drivers of rip current morphology is the lack of data. Some early work was done by simple surveying and visual observations of rip current location from the shore, although detailed and objective identification was difficult. Video imagery has been used successfully to study large scale patterns in alongshore sandbars/rip channels
(van Enckevort et al., 2004) and beach cusps (Almar et al., 2008). The relationship between white light in video time-exposure images and the position of submerged sand bar crests was first demonstrated by Lippmann and Holman (1989). The light color associated with preferential wave breaking is used to detect sand bars, and the darker areas where no waves are breaking are associated with rip channels. However, the challenge is in developing automated computer routines to detect the dark areas associated with rip channels in these vast databases of imagery. Past attempts to create such a method have typically focused on minima in lighting variations along only one alongshore transect in the surf zone. However, day-to-day lighting variations can confound these routines, and rip research is still largely based on labour-intensive video imagery digitization. The research presented in this paper has three aims: first, to present a semi-automatic method of detecting rip channels in video imagery; second, to use the video imagery to demonstrate the link between wave conditions, up/downstate transitions in beach morphology and reset events; and third to identify relationships between antecedent nearshore morphology and rip current behavior.
2. Methods and algorithm development 2.1. Study site Tairua Beach is a steep, embayed beach composed of mediumcoarse sands on the Coromandel Peninsula of New Zealand (Fig. 1) that is often dominated by the formation of rhythmic bars and rips (Bogle et al., 2001). Tides are diurnal with a range of 1–2 m with little spring-neap variation and waves consist of storm and swell arriving from the north and the east, while Shoe Island (Fig. 1) partially shelters the beach (Trembanis et al., 2004). Mean significant wave height (Hs) offshore from Tairua Beach is 0.56 m with a mean wave period of 5.8 s, derived using a 20-year WAM wave hind cast model (Gorman et al., 2003a). Hs can reach more than 6 m during extreme storm events. A video camera overlooks the beach from Paku Hill at the southern end of the beach, at 70.5 m above chart datum. This camera was part of Cam-Era, a network of computer-controlled video cameras installed for monitoring the New Zealand coast for research, resource management, swimmers and surfers. The camera in this study was deployed by Environment Waikato (Waikato Regional Council) and NIWA (National Institute of Water and Atmospheric Research) in New Zealand. The camera was set up to take a snapshot every hour, along with a 15-minute sequence of video footage, which was subsequently averaged by an on-site computer. Video imagery of
Fig. 1. Map of New Zealand showing the location of Tairua Beach and Cam-Era video image of Tairua Beach study site on Julian Day 87 at 1000 hours in 2008.
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the entire alongshore and cross-shore expanse of the surf zone was used to investigate rip channel behavior at Tairua Beach.
2.2. Rip channel detection We here introduce a new method of detecting rip channels in video imagery that builds on techniques used by Lippmann and Holman (1989), Ranasinghe et al. (1999), Bogle et al. (2001) and Orzech et al. (2010). These authors used areas of preferential wave breaking in video imagery to detect rip channels. Until now there has been no computer algorithm that automatically searches the entire surf zone in video images to detect rip channels. This means that timeconsuming, labour-intensive and subjective methods have been used to create rip channel data sets. In this study, time-averaged video images were used for rip channel detection as they provide better contrast than instantaneous snapshots between rip channels and sand bar crests. These images were ortho-rectified using the method of Heikkila and Silven (1997) and the resulting rectified images provided near complete coverage of the Tairua beach and surf zone area, approximately 1.6 km alongshore and 500 m cross-shore. The portion of the database used covered the time period between January 1999 and April 2002. A suite of computer algorithms was created to automatically find local light intensity maxima (sand bar crests) and minima (rip channels) in the rectified, time-averaged images of the surf zone. Rip channels were assumed to exist only between the shoreline and the barline. Apart from rip channels being restricted by their definition as a surfzone phenomenon, their signature is also particularly clear between the barline and the shoreline where the waves are breaking. In order to impose this restriction, the shoreline (Fig. 2a,c) was found using the method presented in Salmon et al. (2008) and Smith and Bryan (2007), where gradients in the ratio between red and blue (or green) light were used to detect the shoreline. The barline (Fig. 2a,c) was detected by finding the furthest seaward light intensity maximum for each alongshore location. A seventh-order polynomial was fitted to the light intensity data along each cross-shore transect prior to barline detection to smooth enough of the variability while still retaining the local light intensity maxima associated with the barline. Shoreline and barline measurements were used as a measure of surf zone width and were used to discard rip channel points that were outside the surf zone.
Fig. 2. Sequence of how algorithms detected rip channels in video images. a. shows local light intensity minima (dots), the shoreline (solid line) and the barline (dashed line), b. the number of minima present in cells in a 7.5 by 7.5 m grid, and c. the shoreline and barline and cleaned up rip channel locations.
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Local extremes (maxima and minima) in light intensity in alongshore and cross-shore transects were automatically found by an algorithm searching every image in which a sandbar was evident, and hence possibly rip channels. Maxima and minima that were not above a threshold and not between the shoreline and the barline were removed. Following the procedure outlined above, a cluster of local minima is obtained (Fig. 2a) with no separation of clusters belonging to different rip currents. In order to divide the clusters of local minima into distinct rip channels, a connectivity algorithm was developed using a 7.5 m by 7.5 m grid (Fig. 2b). Minima in connected cells in this coarse grid were considered part of the same rip. At this point, it was necessary to define rules to objectively remove clusters of points that were clearly not related to rip channels. In order of application, these were: (1) a rip channel must be defined by more than five connected grid cells or else was automatically or manually removed; (2) segments of rip channels where the seaward end was less than 40 m from the landward end of another rip were joined; (3) rip channels that contained sections that were shore-parallel, were split at the parallel section (this removed sections of alongshore trough that were occasionally included); and (4) rip channels were removed if they were not accompanied by a perturbation in the corresponding part of the shoreline and/or barline (e.g. an embayment or crescentic feature), a feature supported by Ranasinghe et al. (2004), Whyte et al. (2005) and Turner et al. (2007). This refining process resulted in the data set shown in Figs. 2c and 3. The 2000 rip channel data set is discontinuous (Fig. 3b) with long periods of time when no data were obtainable due to low wave conditions. The 2000 data were largely omitted from this study due to low wave conditions, except for a case study of a large storm on Julian Days 170–200 since the focus is on storm driven changes to rip channels. There are cases when rip channels were present but not included in the data set, for example the rip channel at the southern headland is generally not included because the associated perturbation in the barline is beyond the field of view of the camera. The manual part of the rip channel refining process was tested with multiple users to ensure that consistent results were achieved. 2.3. Rip reconfiguration event definition While there is no evidence that the rip channels at Tairua ever reset completely, it is clear from Fig. 3 that the rip channels mapped during the 3.3 year period underwent a number of significant changes, from irregularly spaced alongshore to highly alongshoreregular patterns, where the regularly spaced pattern was either associated with 5 or 8–9 rip channels. For example, in 1999 on Julian Day 100 the pattern of 8 rip channels that were relatively regularly spaced alongshore was disrupted, and in 2000 between Julian Days 150–200 the 5 relatively stable rip channels changed considerably in their alongshore positions with time. A key objective was to characterize the wave conditions associated with these rip channel pattern changes—the ‘reconfiguration events’. In order to objectively detect the rip reconfiguration events, a new measure of change was devised. We define a ‘reconfiguration event’ as a time when the channels rapidly migrated in often-different alongshore directions and changed in number. Examination of the video images during reconfiguration events gives no evidence that all the rip channels ever completely disappeared during a storm event over the period of study. The algorithm for detecting rip channel reconfiguration events was based on the degree of movement that occurred between two time steps. Other ways to measure rip channel pattern change were explored, obviously including standard deviation of alongshore rip channel spacing, but due to the high degree of alongshore variability in rip channel behavior this proved difficult (e.g. a stable irregular configuration would have a high standard deviation in spacing). The degree of movement between two time steps was measured by calculating the histogram of the alongshore distances between every
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combination of rip channels at these two consecutive times. This approach was suitable because it did not necessitate tracking individual rip currents through time. If there was no alongshore rip movement, the histogram had the highest frequency in the zero bin and peaks at multiples of the alongshore rip channel spacing; conversely, if rips changed in their alongshore position, the bin spanning zero would have a lower frequency count than higher bins. Thus the measure of change was defined as the frequency count in the 7.5 and 15 m bin (where results were found to be non-sensitive to bin width). If this method was used on higher energy beaches wider bin ranges would be needed as the rips would likely move further during reconfiguration events. Rip channel reconfiguration events corresponded to instances when this measure of change (Fig. 4b) reached a local maximum accompanied by an approximately coincident change in the number of rip channels (Fig. 4c). Change in the number of rip channels was also used so that events, when all the rip channels were simply migrating simultaneously in the alongshore direction, were excluded. Over the period of study (excluding the year 2000), there were six rip reconfiguration events (Fig. 3). The 1999 rip channel data in Fig. 4 provides an example of when rip reconfiguration events occurred. The maximum in the measure of change and the change in the number of rip channels did not always coincide. It is possible that when the rip channels get closer or further apart they experience a higher alongshore migration rate and when they finally merge (which corresponds to a change in the number of rip channels), the migration rate slows. Because of the limited number of events available for analysis and the noise that accompanies detection during storms, it is difficult to determine the exact details of the process of reconfiguration. Video images and rip channel locations before and after each reconfiguration event are shown in Fig. 5.
To demonstrate how the rip channel detection method may be used, the technique was applied to a 3.3-year database of video imagery. The resulting rip channel locations were used to determine the wave conditions under which rip channels were regularly or irregularly spaced alongshore, the role of the cross-shore length of rip channel patterns in determining response rate, the role of wave event history and finally, the thresholds of wave event energy and duration compared to rip channel cross-shore length that control the occurrence of downstate (less rips) versus upstate (more rips) transitions. 3. Algorithm application 3.1. Wave condition comparisons Wave data was provided by NIWA, and consisted of a hindcast using the WAM global wave model. This model has been calibrated against buoy and satellite data around New Zealand (Gorman et al. 2003a,b). Model results calibrated well to a directional wave-rider buoy deployed in the Mokohinau Islands, 120 km north of Tairua. The model was used to hindcast significant wave height, direction, and period on a 3-hourly sampling interval. Similar to previous works (Turner et al., 2007), a direct day-by-day correlation between wave characteristics and alongshore rip channel spacing was not significant, however one can expect that the reconfiguration events were related to weather-driven changes in wave conditions. Therefore, new timeseries of averaged wave energy were defined. Different wave averaging periods were tested, where the rip reconfiguration events corresponded best to the average of the previous 10 days wave energy (Fig. 4f). In addition to average wave energy, storm duration timeseries were generated, which consisted of the number of hours since the beginning of a storm greater than a threshold. A threshold of
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Fig. 4. Rip channel and offshore wave data in 1999. a: rip channel positions found with algorithms (stars). Light grey areas indicate periods of low or high wave conditions when rip channel were not visible. Dark grey areas indicate reconfiguration events 1, 2 and 3 (see Fig. 5). b: measure of change (number of rips that moved 7.5–15 m apart with time); c: number of rips; d: mean surf zone width; e: mean rip channel orientation; f: wave energy averaged over ten days; g: duration of wave energy exceeding 5000 Jm− 2 (averaged over ten days).
5000 Jm− 2 best related to the occurrence of reconfiguration events (Fig. 4f). The exact timing of the reconfiguration events and the maxima in duration and averaged wave energy do not coincide exactly, due to a lag time in rip channel response to a change in wave conditions. Reconfiguration events were associated with increased wave energy (Fig. 4f). However, there were times when mean wave energy over ten days reached high magnitudes but there were no rip channel reconfiguration events indicated such as in 2001 on Julian Days 180, 250 and 340 when mean wave energy over ten days reached 5000 Jm− 2 or more. There were also reconfiguration events when there was not a large increase in the mean wave energy such as in 2001 on day 50 when mean wave energy over ten days reached more than 3000 Jm− 2, considerably less than the mean energy during other rip reconfiguration events. These occurrences indicate that wave energy is not the sole factor driving changes in alongshore rip channel patterns. 3.2. Rip channel size Although the large 2000 storm was not associated with a reconfiguration event, there was a rapid change in the orientation of the sand bar where it switched from being wider at the southern end to wider at the northern end between days 184–191 (Fig. 6b, c). This change in orientation of the bar provided an interesting case with which to demonstrate the role of cross-shore surf zone length scales in the dynamics of the rip channels. Between days 176 and 193 in 2000 there was high wave energy when on days 176, 182 and 193 in 2000 Hs reached 5 m, 4 m and 4 m respectively (Fig. 7b). On day 183 between the two high wave events the sand bar was wider at the southern end (Fig. 6b) and by day 192 the orientation had switched to wider at the northern end (Fig. 6c). After this change in orientation of the bar, rip channels on the northern half of the beach subsequently evolved as three large rips with a long cross-shore length. The
southern part of the beach had a considerably narrower surf zone so the beach had a dual-width surf zone (Fig. 6d). Before the storm, the opposite configuration was observed (Fig. 6b). During the storm event, the mean wave direction had an unusually strong easterly component (Fig. 7d) combined with Hs around 3 m (Fig. 7b) causing a strong alongshore energy flux. As previously shown, Tairua Beach is shadowed to the south by Shoe Island (Fig. 1). To demonstrate the role of wave shadowing, the SWAN wave model was run on a 45 m × 45 m grid extending to the location of the deep water wave hindcast, using a 2 m wave height and wave angle approaches from the southeast, north, northeast and east. These model runs confirm that wave heights are nearly halved in amplitude at the southern end compared to the northern end of the beach during easterly wave events (Fig. 6a). The greater wave energy reaching the northern half of the beach appeared to cause the sand bar position to be forced seawards into deeper water and subsequent rip channels had a large cross-shore extent while the rips on the southern half remained small (Fig. 6d). The evolution of the rip channels during the period when the dualwidth surf zone was present in 2000, showed that under the same input of wave forcing, the rip channel and sand bar morphology were more dynamic in the narrow portion of the beach (Fig. 6). Conversely, the three large rips on the northern half of the beach in the wide surf zone were stable, persisting until day 108 the following year (2001). This case is shown in Fig. 6d–f, when the wave conditions were large enough to break over the shallow, southern half of the bar and re-work the rip channel morphology so that these rips were controlled by the hydrodynamics. However, the wave conditions were not large enough to break over the deeper, northern half of the bar and rework the three northern rips so that these rips were topographically controlled. It is also worth noting the presence of two rips at each of the headlands of Tairua Beach that had a large cross-shore length and were persistent throughout the 3.3 year dataset.
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Fig. 5. Rectified, time-averaged video images of Tairua Beach. Black dots indicate rip channels (as obtained from the detection algorithm). Left and right hand columns show the beach before and after each reconfiguration event. Event 1 images are from 1999 on days 94 at 1500 hours (prior) and 149 at 1200 hours (after), Event 2 from 1999 on days 251 at 1100 hours and 299 at 1400 hours, Event 3 in 1999 on days 306 at 0700 hours and 331 at 1601 hours, Event 4 in 2001 on days 43 at 1600 hours and 65 at 1000 hours, Event 5 in 2001 on days 112 at 1200 hours and 127 at 1200 hours, and Event 6 in 2002 on days 69 at 1000 hours and 74 at 1400 hours. Note that the ‘V’ shaped rip channels are counted as separate rips according to rule No. 4 in section 2.2.
3.3. Headland rips Headland rips are known to be topographically controlled and can be persistent in their location and morphology (Short, 1985). The two persistent rip channels along the headlands of Tairua Beach were orientated obliquely at opposite angles (Fig. 8). Often the southernmost rip channels were outside the field of view of the camera, and hence the distinctive orientation of the headland rips is more apparent at the northern rip rather than the southern. When the beach was dominated by headland rips, the mean rip channel angle was also dominated by the orientation of the headland rips (Fig. 4e). For example, in 1999 (Fig. 4) and 2002 (not shown), when rips along the northern headlands dominated the system, the mean rip channel angle became strongly negative and vice versa when the system was dominated by rips at the southern headlands. These headland rip channels channelled water away from the centre of the beach. This is in contrast to recent modeling studies on headland-embayed beaches which suggest that the water accumulates at the centre of the beach to make one large seaward rip (Silva et al., 2010). 3.4. Upstate and downstate nearshore morphology transitions Sand bar and rip channel morphology can be used to define beach state. Upstate transitions are associated with higher wave events
when the rip channels become fewer and more widely spaced whereas downstate transitions are associated with lower waves and more, narrowly-spaced rip channels are formed. Some of the rip channel reconfiguration events were associated with upstate transitions in nearshore morphology and some with downstate transitions (Fig. 9) (see Wright and Short, 1984 for a detailed explanation of transitions and beach state). Reconfiguration events three, four and six were associated with a decrease in mean alongshore rip channel spacing and an increase in the number of rips (a downstate transition). Events one, two and five were associated with an increase in mean alongshore rip channel spacing and either no change or a decrease in the number of rip channels (an upstate transition). The upstate transitions were associated with longer duration wave events and the downstate transitions with shorter duration wave events (Fig. 9). 4. Discussion The algorithm developed for detecting rip channels in video imagery can be used to relatively easily, and accurately detect and measure rip channels. This method is an improvement on past methods as it can detect rip channels across the entire surf zone rather than across a single averaged profile (Bogle et al., 2001) and thus provide information on channel orientation and sinuosity. It is hoped
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Fig. 6. a: significant wave height at 5 m water depth modeled using SWAN and assuming 2 m, 8 s offshore waves approaching from the east. b. and c. show video images from 2000 from Julian Days 183 at 1200 hours and 192 at 0800 hours. d., e. and f. show images from 2001 on Julian Days 32 at 1800 hours (d.), 43 at 1600 hours (e.) and 59 at 1600 hours (f.). Black lines show the position of the barline.
that the present method can be applied at other sites to create quantitative rip channel datasets from the tens of years of video imagery data available worldwide through other systems (e.g., Holman and Stanley, 2007). If rip channel data sets can be extracted from these images in a time and cost effective manner, it will revolutionise efforts to relate rip channel behavior to wave conditions and antecedent morphology and ultimately help to develop forecasts of rip occurrence. Over the period of study, there were long periods of time when the alongshore rip channel locations were fairly regularly spaced and stable with time. These stable periods were punctuated by six reconfiguration events when the alongshore rip channel configuration changed, at times becoming irregular. Each of the reconfiguration events was easily identified as an upstate or downstate transition in beach morphology by an increase or decrease in the number of rip channels and alongshore rip spacing (Short, 1985). Three of the events were downstate transitions and three upstate where there was a clear division in wave energy during these events. Short duration high energy events were associated with downstate transitions and long duration wave events with upstate transitions (Fig. 9). Surprisingly there is no evidence that a complete reset event (resulting in the development of an alongshore uniform sandbar) in nearshore morphology occurred over the period of study. A lack of reset events is unusual, for example at the 2 km-long embayed Palm Beach in Australia, reset events occurred on average four times per year (Holman et al., 2006) and at Monterey Bay in California 1–2 times per year (Orzech et al., 2010). Lack of reset events is significant as most rip current generation models assume the occurrence of such
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morphology resets. The lack of reset events at Tairua Beach could be due in part to the absence of a wave event large enough to reset the morphology and also the nature of this small, embayed beach leading to the headlands playing a dominant role in influencing rip channel behavior. The rip channel time-series (Fig. 3) shows that at least one of these headland rips is present throughout the entire 3.3 year data set. A possibility is that the evolution of stable (in time), evenly spaced rip channel patterns begins at the dominant headland rip channel, which gradually stabilizes the neighboring rip channels until the beach has rips regularly spaced along its entire length. This occurred in 2001, when the 3 northern large rips that were part of the dualwidth surf zone gradually evolved alongshore into a system of evenly spaced rip channels. More case studies of rip channel evolution are needed to confirm this hypothesis, which is actually in contrast with both the edge wave approach and present self-organization model results (in both cases rip channels appear more or less concomitantly). These results also have implications with respect to several numerical studies (e.g. Calvete et al., 2005) that use linear stability analysis and that, given a specific set of wave conditions, predict an alongshore regular rip channel spacing. As shown in the observations presented in Fig. 6, the alongshore spacing is never regular and it nearly halves (from 4 to 7 rip channels) over time so that even if some sort of average spacing could be predicted using linear stability analysis, the nonlinear dynamics associated with changes in spacing are not captured. Sand bars and rip current channels in the surf zone are seldom, if ever, in equilibrium with the instantaneous wave conditions (Smit et al., 2008). In line with past studies (e.g. Holman et al., 2006; Turner et al., 2007), little correlation existed between rip channels and immediate, instantaneous measures of the wave conditions. The rip channels at Tairua beach exhibited a lag time between high wave events and upstate changes in nearshore morphology, which is expected considering the considerable volume of sand that must be shifted to move a rip channel. There was also a longer lag time between low wave conditions and downstate changes in nearshore morphology in agreement with Short (1985) who noted that under low energy, rips can become fixed in their location in the Longshore Bar-Trough (LBT) and Rhythmic Bar and Beach (RBB) states and can persist for long periods if waves are constant. Conversely, during high energy waves alongshore rip spacing increases with rips becoming more intense. Rips may reconfigure by shifting, disappearing and more can reappear (Short, 1985). The importance of wave energy and duration was also noted by Ortega-Sánchez et al. (2008) and Jiménez et al. (2008). In line with our findings, Ortega-Sánchez et al. (2008) found that beach morphology type generally did not change simultaneously with a change in wave forcing and that transition time was dependent on the wave energy. In particular, longer morphology transition time was required for low energy waves. Jiménez et al. (2008) also noted the importance of lag time in morphodynamic response to wave forcing, and stressed the importance of both wave event duration and intensity in nearshore morphodynamic response. The antecedent rip channel morphology was important in influencing if and to what extent the Tairua rip channel system changed during high energy wave events. For rip current channels at Tairua with large cross-shore extents, the response time for rip morphology was 5–10 days, and for rip channel systems of smaller size i.e. with shorter cross-shore lengths and narrow spacing (such as what occurred in 2002), wave energy averaged over shorter periods of time (1–5 days as opposed to 5–10 days) showed a better relationship to rip reconfiguration events. These smaller rip channels are more easily moved, as this requires shifting lesser volumes of sand. Wright and Short (1984) also noted that during low intensity (energy) events surf zone morphology will take longer to respond than during high intensity events. Interestingly, in 2001 on days 190 and 250, wave energy events occurred of a magnitude and duration than in other
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years was sufficient to cause at least two reconfiguration events. However, in this case the rip channels remained stable. Close examination indicated that the mean surf zone width was ~ 40 m wider in 2001 than these other cases. The cross-shore extent of the rip channel system relative to the duration and magnitude of the event is critical to determining the possibility of a reconfiguration event; systems with larger cross-shore extents have longer lag-times. The existence of a dual-width surf zone allowed the role of rip channel cross-shore length to be qualitatively examined. Both ends of the beach were exposed to the same energy after the development of the dual-width surf zone, yet the large crossshore extent rips at the northern headland remained in the same location but the short cross-shore extent rip channels at the southern end shifted. This is consistent with the ideas of Eliot (1973) and Short (1985) that only some rips persist for long periods of time and that persistent rip channels are created during high energy events (such as is shown in Fig. 6). There is scope to extend this study by examining, for example, the orientation of the rip channels in the centre of the beach, where there were times when the rip channels were shore-perpendicular, and other times when they had alternating orientations, suggesting that these were recently split feeder channels. The extent of the rip
channel system across the surf zone also varied, where some rip channels caused a strong perturbation in the sandbar, some caused a large perturbation in the shoreline, and some evenly affect both sandbar and shoreline. Such patterns could be used to infer the connection of shoreline and sandbar storage of sand, and ultimately determine the resilience of the shoreface to storm erosion. Extending the length of the dataset used and applying the rip channel detection algorithms to video images from other beaches will also help drive rip current research forwards. 5. Conclusion This paper introduces a semi-automatic method of detecting rip channels in video imagery, which offers a promising technique to measure quality, long-term rip channel data sets relatively easily. The database developed using this technique was used to examine reconfiguration events, the role of headland rips and rip channel size using a 3.3 year data set from Tairua Beach in New Zealand as a case study. Results from this study as well as past studies suggest that antecedent rip channel size, wave energy averaged over a wave event and the duration of the event are three equally important factors whose interaction ultimately determines how rip channels respond to
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a change in the wave conditions. Beach protection from waves by an offshore island was found to influence the cross-shore extent of rip channels, where under certain wave directions the exposed half of the beach developed longer rip channels than the protected half. Topographically controlled headland rips were found to play a dominant role in the rip channel system, where they were persistent, even through high wave energy events. The dependence of rip channel dynamics on the wave conditions that occurred some 2– 10 days prior indicates a delayed response time, the length of which is determined by the cross-shore length of the rip channel. There was a longer lag time between an increase in wave energy and rip channel change for rip channels with a longer cross-shore length. In contrast to previous studies, there was no evidence that the rip channel morphology at Tairua ever completely reset during the 3.3 year study period which is important since this assumption is what most rip generation models are based on. Both upstate and downstate transitions in rip channel morphology occurred during the study where upstate transitions were associated with longer duration high wave events and downstate with short duration wave events. To increase understanding of rip channel behavior there is a need to come away from traditional rip-wave correlation techniques and consider instead the antecedent nearshore morphology where rip channel cross-shore length plays a pivotal role in determining wave
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Acknowledgements This study was undertaken by S.L.G. as part of a MSc degree at the University of Waikato. S.L.G. acknowledges funding from the University of Waikato Masters Research Scholarship, the University of Waikato Maori Excellence Awards, the Whakatane Historical Society Scholarship and the Broad Memorial Fund. G.C. and S.S. were funded by the Foundation for Research, Science and Technology (WRHC102). The camera is part of the Cam-Era programme implemented and coordinated by Environment Waikato (Waikato Regional Council) and NIWA (National Institute of Water and Atmospheric Research) in New Zealand. Thank you also to Dr. Ivan
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event energy and duration thresholds for driving change in the nearshore morphology. Wave energy in the days leading up to the existing rip channel configuration as well as the duration of high energy wave events must be considered. Many recent studies have modeled the variation of rip channels' formation and evolution both as a response to persistent low wave energy input, and episodic storm conditions. Our methodology and dataset allow critical validation data for these models, showing the timescale over which rip systems respond, and the critical role of antecedent rip channel morphology.
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Fig. 9. a: difference in mean rip channel spacing alongshore before and after reconfiguration events 1–6 versus duration of Hs exceeding 2.5 m; b. shows difference in number of rip channels before and after reconfiguration events 1–6 and duration of mean wave energy averaged over ten days exceeding 5000 Jm− 2. Vertical dashed line indicates boundary between upstate and downstate transitions.
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Haigh and the two anonymous reviewers for comments which helped improve the manuscript. References Almar, R., Coco, G., Bryan, K.R., Huntley, D.A., Short, A.D., Senechal, N., 2008. Video observations of beach cusp morphodynamics. Mar. Geol. 254, 216–223. Bogle, J.A., Bryan, K.R., Black, K.P., Hume, T.M., Healy, T.R., 2001. Video observations of rip formation and evolution. J. Coast. Res. 34, 117–127 Special Issue No. Bowen, A.J., Inman, D.L., 1971. Edge waves and crescentic bars. J. Geophys. Res. 76, 8662–8671. Caballeria, M., Coco, G., Falquès, A., Huntley, D.A., 2002. Self-organization mechanisms for the formation of nearshore crescentic and transverse bars. J. Fluid Mech. 465, 379–410. Calvete, D., Coco, G., Falques, A., Dodd, N., 2007. (Un)predictability in rip channel systems. Geophys. Res. Lett. 34 (L05605). Calvete, D., Dodd, N., Falqués, A., Van Leeuwen, S.M., 2005. Morphological development of rip channel systems: normal and near-normal wave incidence. J. Geophys. Res. 110, C10006. Eliot, I., 1973. The persistence of rip current patterns on sandy beaches. Proceedings of the first Australian Conference on Coastal Engineering. Institute of Australian Engineers, Sydney, pp. 29–34. Gorman, R.M., Bryan, K.R., Laing, A.K., 2003a. Wave hindcast for the New Zealand region: deep-water wave climate. NZ J. Mar. Freshw. Res. 37, 589–612. Gorman, R.M., Bryan, K.R., Laing, A.K., 2003b. Wave hindcast for the New Zealand region: nearshore validation and coastal wave climate. NZ J. Mar. Freshw. Res. 37, 567–588. Heikkila, J., Silven, O., 1997. A four-step camera calibration procedure with implicit image correction. Proceedings–Computer Vision and Pattern Recognition. Conference Proceedings IEEE Computer Society Conference, Puerto Rico, pp. 1106–1112. Holman, R.A., Stanley, J., 2007. The history and technical capabilities of Argus. Coastal Eng. 54 (6–7), 477–491. Holman, R.A., Symonds, G., Thornton, E.V., Ranasinghe, R., 2006. Rip spacing and persistence on an embayed beach. J. Geophys. Res. 111, C01006. Huntley, D.A., Short, A.D., 1992. On the spacing between observed rip currents. Coastal Eng. 17, 211–225. Jiménez, J.A., Guillén, J., Falqués, A., 2008. Comment on the article ‘Morphodynamic classification of sandy beaches in low energetic marine environment’ by GómezPujol, L., Orfila, A., Canellas, B., Alvarez-Ellacuria, A., Méndez, F.J., Medina, R., Tintoré, J. Marine Geology, 242, pp. 235–246, 2007. Marine Geology 255, 96–101 Lippmann, T.C., Holman, R.A., 1989. Quantification of sand-bar morphology: a video technique based on wave dissipation. J. Geophys. Res. 94 (C1), 995–1011. Longuet-Higgins, M.S., Stewart, R.W., 1964. Radiation stresses in water waves, a physical discussion with applications. Deep Sea Res. 11, 529–563. MacMahan, J.H., Thornton, E.B., Reniers, A.J.H.M., 2006. Rip current review. Coastal Eng. 53, 191–208. MacMahan, J.H., Thornton, E.B., Stanton, T.P., Reniers, A.J.H.M., 2005. RIPEX: observations of a rip current system. Mar. Geol. 218, 113–134.
McKenzie, P., 1958. Rip-current systems. J. Geol. 66, 103–113. Ortega-Sánchez, M., Fachin, S., Sancho, F., Losada, M.A., 2008. Relation between beachface morphology and wave climate at Trafalgar beach (Cádiz, Spain). Proc. Geomorph. 99, 171–185. Orzech, M.D., Thornton, E.B., MacMahan, J.H., O'Reilly, W.C., Stanton, T.P., 2010. Alongshore rip channel migration and sediment transport. Mar. Geol. 271, 278–291. Ranasinghe, R., Symonds, G., Black, K., Holman, R., 2000. Processes Governing Rip Spacing, Persistence, and Strength in a Swell Dominated, Microtidal Environment. Proc. International Conference on Coastal Engineering ASCE, Sydney, pp. 454–467. Ranasinghe, R., Symonds, G., Black, K., Holman, R., 2004. Morphodynamics of Intermediate Beaches: a Video Imaging and Numerical Modeling Study. Coastal Eng. 52, 629–655. Ranasinghe, R., Symonds, G., Holman, R., 1999. Quantitative characterization of rip dynamics via video imaging. Proceedings of Coastal Sediments. ASCE, Virginia. pp. 987–1002. Salmon, S.A., Bryan, K.R., Coco, G., 2008. The use of video systems to measure run-up on beaches. J. Coast. Res. 50, 211–215 Special Issue No. 50. Short, A.D., 1985. Rip current type, spacing and persistence, Narrabeen Beach, Australia. Mar. Geol. 65, 47–71. Short, A.D., 2007. Australian rip systems—friend or foe? J. Coast. Res. 7–11 Special Issue No. 50. Short, A.D., Brander, R.W., 1999. Regional variations in rip density. J. Coast. Res. 15, 813–822. Silva, R., Baquerizo, A., Losada, M.A., Mendoza, E., 2010. Hydrodynamics of a headland-bay beach—Nearshore current circulation. Coastal Eng. 57, 160–175. Smit, M.W.J., Reniers, A.J.H.M., Ruessink, B.G., Roelvink, J.A., 2008. The morphological response of a nearshore double sandbar system to constant wave forcing. Coastal Eng. 55, 761–770. Smith, R.K., Bryan, K.R., 2007. Monitoring beach face volume with a combination of intermittent profiling and video imagery. J. Coast. Res. 23, 892–898. Symonds, G., Holman, R.A., Bruno, B., 1997. Rip currents. Proceedings of Coastal Dynamics '97. ASCE, pp. 584–593. Thornton, E.B., MacMahan, J., Sallenger Jr., A.H., 2007. Rip-currents, mega-cusps, and eroding dunes. Mar. Geol. 240, 151–167. Trembanis, A.C., Wright, L.D., Friedrichs, C.T., Green, M.O., Hume, T., 2004. The effects of spatially complex inner shelf roughness on boundary layer turbulence and current and wave friction: Tairua embayment, New Zealand. Cont. Shelf Res. 24, 1549–1571. Turner, I.L., Whyte, D., Ruessink, B.G., Ranasinghe, R., 2007. Observations of rip spacing, persistence and mobility at a long, straight coastline. Mar. Geol. 236, 201–211. van Enckevort, I.M.J., Ruessink, B.G., Coco, G., Suzuki, K., Turner, I.L., Plant, N.G., Holman, R.A., 2004. Observations of nearshore cresentic sandbars. J. Geophys. Res. 109, C06028. Whyte, D., Turner, I.L., Ranasinghe, R., 2005. Rip Characterization on the Gold Coast, Australia: An Analysis using Coastal Imaging Techniques. Proceedings of the 17th Australasian Coastal and Ocean Engineering Conference. Institute of Engineering, Adelaide, pp. 233–238. Wright, L.D., Short, A.D., 1984. Morphodynamic variability of surf-zones and beaches: a synthesis. Mar. Geol. 56, 93–118.
Contents lists available at ScienceDirect
Geomorphology j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / g e o m o r p h
Storm-driven changes in rip channel patterns on an embayed beach S.L. Gallop a,⁎, K.R. Bryan a, Giovanni Coco b, S.A. Stephens b a b
Department of Earth and Ocean Sciences, Faculty of Science and Engineering, The University of Waikato, Hamilton 3240, New Zealand National Institute of Water and Atmospheric Research, P.O. Box 11-115, Hamilton 3240, New Zealand
a r t i c l e
i n f o
Article history: Received 5 May 2010 Received in revised form 10 December 2010 Accepted 12 December 2010 Available online 21 December 2010 Keywords: Rip currents Rip channels Video imagery Beach state Sand bars Nearshore morphology
a b s t r a c t This paper introduces a semi-automatic computer algorithm designed to detect rip current channels in video imagery. As a case study, this method is applied to 3.3 years of video data from an embayed beach to demonstrate the link between antecedent surf zone morphology, wave energy and up/down transitions in beach state. An objective measure of rip channel change was developed to define six significant rip reconfiguration events and relate these events to wave energy. Over the period of study no complete resets of the nearshore morphology occurred. The analysis indicates that direct correlation of rip patterns with the instantaneous wave conditions is not a useful way to demonstrate how rips and waves interact. The average wave energy over a period of ten days, combined with storm duration were good indicators of rip channel change, demonstrating that in general, beach morphology responds with a time lag to changes in forcing. Rip channels with a short cross-shore length and narrow alongshore spacing responded faster to changes in wave conditions than rips with a long cross-shore length and wider alongshore spacing. To force changes in the rip morphology, longer rip channels required wave events of higher energy and/or a longer duration. Offshore islands protect the beach under certain wave approach angles, sometimes resulting in a dual-width surf zone, which was narrow at the sheltered end and wide at the exposed end of the beach. The wider surf zone end was characterised by three dominant and persistent rip channels, whereas the narrow surf zone section contained a number of smaller rips which evolved rapidly under wave forcing. Our observations demonstrate the importance of rip channel size in controlling the response time of nearshore morphology. © 2010 Elsevier B.V. All rights reserved.
1. Introduction Rip currents are fast, narrow currents that traverse the surf zone, generally in a seaward direction. Rips are driven by radiation stress gradients (Longuet-Higgins and Stewart, 1964) generated by temporal and spatial patterns in wave breaking (MacMahan et al., 2006). There are also weaker currents heading onshore adjacent to rip currents contributing to rip feeder currents (MacMahan et al., 2006). The orientation, size and strength of rip currents depend on the offshore wave conditions such as wave height, period and direction of propagation, and on the underwater topography. The underwater topography influences wave breaking patterns and subsequent steering of rip currents, so rip characteristics depend on the interaction between both the nearshore topography and incident waves. It is commonly assumed that after high wave events, the rip channel morphology ‘resets’ forming a shore-parallel bar (Holman et al., 2006), where this assumption is the basis of most theories of rip current generation.
⁎ Corresponding author. Present address: School of Environmental Systems Engineering, The University of Western Australia, 35 Stirling Highway, MO15, Crawley, WA, 6019, Australia. Tel.: +61 8 6488 8117; fax: +61 8 6488 7279. E-mail addresses: [email protected] (S.L. Gallop), [email protected] (K.R. Bryan), [email protected] (G. Coco), [email protected] (S.A. Stephens). 0169-555X/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.geomorph.2010.12.014
Embayments or ‘mega-cusps’ have been shown to be associated with rip currents. Such embayments contribute to the coastal erosion hazard by causing ‘hot-spots’ of erosion. For example, at Monterey Bay, California alongshore variations in the shoreline were significantly correlated with the alongshore variations in rip spacing and dune erosion volume (Thornton et al., 2007). Moreover, permanent dune recession occurred in unison with these quasi-stable mega-cusps (erosion ‘hot-spots’) leading to enhanced shoreline erosion compared to a uniform coast. This type of erosion scarps make the coast more susceptible to erosion during extreme events such as combinations of large storm waves, surge, and high tide, an outcome which will worsen with projected sea-level rise. Therefore quantifying rip channel size and spacing and how these characteristics change with wave conditions is central to understanding patterns of beach erosion. There have been many attempts to link wave conditions such as height to rip channel characteristics, in particular, to alongshore rip spacing. Field observations and numerical models both indicate that larger inputs of energy into the surf zone will result in the development of larger morphology with larger rip channel spacing (McKenzie, 1958; Short, 1985; Huntley and Short, 1992; Calvete et al., 2005). More recent research based on the analysis of video observations has not found a clear relationship between rip current patterns and waves. In particular, Ranasinghe et al. (2000) and Whyte et al. (2005) found that alongshore rip channel spacing did not increase or decrease with changes in wave
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height. Turner et al. (2007) found no clear relationship between the number of rips and mean alongshore rip channel spacing to the offshore wave conditions. Van Enckevort et al. (2004) and Holman et al. (2006) also could not explain variations in rip channel alongshore spacing. This has lead to the conclusion that rips, once formed, are topographically controlled (Ranasinghe et al., 2000; Whyte et al., 2005; Calvete et al., 2007; Turner et al., 2007). In terms of numerical modeling, recent work based on linear stability analysis (Calvete et al., 2007) has shown that growth and geometry of rips is critically controlled by the pre-existing cross-shore profile. Also, numerical modeling based on the solution of the shallow water equations (Smit et al., 2008) indicates that preexisting channels can dictate the morphological response and evolution of the system if wave forcing changes. To date, there are no definitive results indicating when rip channels might be regularly or irregularly spaced alongshore and what drives rip channel pattern change. Early work on the generation of rip currents suggested that an alongshore standing edge wave might cause the required flow pattern (Bowen and Inman, 1971), in which case one might expect the alongshore pattern to be regular and reflect the wave form of the edge wave. Indeed, Huntley and Short (1992), Short and Brander (1999), and MacMahan et al. (2005) have found that rips were relatively regularly spaced alongshore. Numerical models of rip current generation have shown that rip currents can also be the result of selforganization processes, and can develop from random small-scale seabed perturbations into a regularly spaced pattern (Caballeria et al., 2002). Assessing the regularity (or lack of) of rips has been considered as a potential diagnostic tool to test between rip generation processes. Using a large data set of video imagery from the embayed, 2 km-long Palm Beach, Australia, Holman et al. (2006) concluded that rips were irregularly spaced alongshore. Symonds et al. (1997) noted periods of quasi-regular alongshore spacing and periods of irregular spacing on this beach. At the northern Gold Coast, an open coast, rips were found to be irregularly spaced alongshore (Turner et al., 2007). On the embayed Durras Beach in Australia, Eliot (1973) found that there were places where rip currents tended to occur frequently and that these locations were regularly spaced alongshore. Relevant to the present study is the case of rips associated with headlands which have been found to be persistent (Short, 1985, 2007; Eliot, 1973) and partly controlled by headlands (Short, 2007). One of the impediments to solving some of the controversies on the drivers of rip current morphology is the lack of data. Some early work was done by simple surveying and visual observations of rip current location from the shore, although detailed and objective identification was difficult. Video imagery has been used successfully to study large scale patterns in alongshore sandbars/rip channels
(van Enckevort et al., 2004) and beach cusps (Almar et al., 2008). The relationship between white light in video time-exposure images and the position of submerged sand bar crests was first demonstrated by Lippmann and Holman (1989). The light color associated with preferential wave breaking is used to detect sand bars, and the darker areas where no waves are breaking are associated with rip channels. However, the challenge is in developing automated computer routines to detect the dark areas associated with rip channels in these vast databases of imagery. Past attempts to create such a method have typically focused on minima in lighting variations along only one alongshore transect in the surf zone. However, day-to-day lighting variations can confound these routines, and rip research is still largely based on labour-intensive video imagery digitization. The research presented in this paper has three aims: first, to present a semi-automatic method of detecting rip channels in video imagery; second, to use the video imagery to demonstrate the link between wave conditions, up/downstate transitions in beach morphology and reset events; and third to identify relationships between antecedent nearshore morphology and rip current behavior.
2. Methods and algorithm development 2.1. Study site Tairua Beach is a steep, embayed beach composed of mediumcoarse sands on the Coromandel Peninsula of New Zealand (Fig. 1) that is often dominated by the formation of rhythmic bars and rips (Bogle et al., 2001). Tides are diurnal with a range of 1–2 m with little spring-neap variation and waves consist of storm and swell arriving from the north and the east, while Shoe Island (Fig. 1) partially shelters the beach (Trembanis et al., 2004). Mean significant wave height (Hs) offshore from Tairua Beach is 0.56 m with a mean wave period of 5.8 s, derived using a 20-year WAM wave hind cast model (Gorman et al., 2003a). Hs can reach more than 6 m during extreme storm events. A video camera overlooks the beach from Paku Hill at the southern end of the beach, at 70.5 m above chart datum. This camera was part of Cam-Era, a network of computer-controlled video cameras installed for monitoring the New Zealand coast for research, resource management, swimmers and surfers. The camera in this study was deployed by Environment Waikato (Waikato Regional Council) and NIWA (National Institute of Water and Atmospheric Research) in New Zealand. The camera was set up to take a snapshot every hour, along with a 15-minute sequence of video footage, which was subsequently averaged by an on-site computer. Video imagery of
Fig. 1. Map of New Zealand showing the location of Tairua Beach and Cam-Era video image of Tairua Beach study site on Julian Day 87 at 1000 hours in 2008.
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the entire alongshore and cross-shore expanse of the surf zone was used to investigate rip channel behavior at Tairua Beach.
2.2. Rip channel detection We here introduce a new method of detecting rip channels in video imagery that builds on techniques used by Lippmann and Holman (1989), Ranasinghe et al. (1999), Bogle et al. (2001) and Orzech et al. (2010). These authors used areas of preferential wave breaking in video imagery to detect rip channels. Until now there has been no computer algorithm that automatically searches the entire surf zone in video images to detect rip channels. This means that timeconsuming, labour-intensive and subjective methods have been used to create rip channel data sets. In this study, time-averaged video images were used for rip channel detection as they provide better contrast than instantaneous snapshots between rip channels and sand bar crests. These images were ortho-rectified using the method of Heikkila and Silven (1997) and the resulting rectified images provided near complete coverage of the Tairua beach and surf zone area, approximately 1.6 km alongshore and 500 m cross-shore. The portion of the database used covered the time period between January 1999 and April 2002. A suite of computer algorithms was created to automatically find local light intensity maxima (sand bar crests) and minima (rip channels) in the rectified, time-averaged images of the surf zone. Rip channels were assumed to exist only between the shoreline and the barline. Apart from rip channels being restricted by their definition as a surfzone phenomenon, their signature is also particularly clear between the barline and the shoreline where the waves are breaking. In order to impose this restriction, the shoreline (Fig. 2a,c) was found using the method presented in Salmon et al. (2008) and Smith and Bryan (2007), where gradients in the ratio between red and blue (or green) light were used to detect the shoreline. The barline (Fig. 2a,c) was detected by finding the furthest seaward light intensity maximum for each alongshore location. A seventh-order polynomial was fitted to the light intensity data along each cross-shore transect prior to barline detection to smooth enough of the variability while still retaining the local light intensity maxima associated with the barline. Shoreline and barline measurements were used as a measure of surf zone width and were used to discard rip channel points that were outside the surf zone.
Fig. 2. Sequence of how algorithms detected rip channels in video images. a. shows local light intensity minima (dots), the shoreline (solid line) and the barline (dashed line), b. the number of minima present in cells in a 7.5 by 7.5 m grid, and c. the shoreline and barline and cleaned up rip channel locations.
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Local extremes (maxima and minima) in light intensity in alongshore and cross-shore transects were automatically found by an algorithm searching every image in which a sandbar was evident, and hence possibly rip channels. Maxima and minima that were not above a threshold and not between the shoreline and the barline were removed. Following the procedure outlined above, a cluster of local minima is obtained (Fig. 2a) with no separation of clusters belonging to different rip currents. In order to divide the clusters of local minima into distinct rip channels, a connectivity algorithm was developed using a 7.5 m by 7.5 m grid (Fig. 2b). Minima in connected cells in this coarse grid were considered part of the same rip. At this point, it was necessary to define rules to objectively remove clusters of points that were clearly not related to rip channels. In order of application, these were: (1) a rip channel must be defined by more than five connected grid cells or else was automatically or manually removed; (2) segments of rip channels where the seaward end was less than 40 m from the landward end of another rip were joined; (3) rip channels that contained sections that were shore-parallel, were split at the parallel section (this removed sections of alongshore trough that were occasionally included); and (4) rip channels were removed if they were not accompanied by a perturbation in the corresponding part of the shoreline and/or barline (e.g. an embayment or crescentic feature), a feature supported by Ranasinghe et al. (2004), Whyte et al. (2005) and Turner et al. (2007). This refining process resulted in the data set shown in Figs. 2c and 3. The 2000 rip channel data set is discontinuous (Fig. 3b) with long periods of time when no data were obtainable due to low wave conditions. The 2000 data were largely omitted from this study due to low wave conditions, except for a case study of a large storm on Julian Days 170–200 since the focus is on storm driven changes to rip channels. There are cases when rip channels were present but not included in the data set, for example the rip channel at the southern headland is generally not included because the associated perturbation in the barline is beyond the field of view of the camera. The manual part of the rip channel refining process was tested with multiple users to ensure that consistent results were achieved. 2.3. Rip reconfiguration event definition While there is no evidence that the rip channels at Tairua ever reset completely, it is clear from Fig. 3 that the rip channels mapped during the 3.3 year period underwent a number of significant changes, from irregularly spaced alongshore to highly alongshoreregular patterns, where the regularly spaced pattern was either associated with 5 or 8–9 rip channels. For example, in 1999 on Julian Day 100 the pattern of 8 rip channels that were relatively regularly spaced alongshore was disrupted, and in 2000 between Julian Days 150–200 the 5 relatively stable rip channels changed considerably in their alongshore positions with time. A key objective was to characterize the wave conditions associated with these rip channel pattern changes—the ‘reconfiguration events’. In order to objectively detect the rip reconfiguration events, a new measure of change was devised. We define a ‘reconfiguration event’ as a time when the channels rapidly migrated in often-different alongshore directions and changed in number. Examination of the video images during reconfiguration events gives no evidence that all the rip channels ever completely disappeared during a storm event over the period of study. The algorithm for detecting rip channel reconfiguration events was based on the degree of movement that occurred between two time steps. Other ways to measure rip channel pattern change were explored, obviously including standard deviation of alongshore rip channel spacing, but due to the high degree of alongshore variability in rip channel behavior this proved difficult (e.g. a stable irregular configuration would have a high standard deviation in spacing). The degree of movement between two time steps was measured by calculating the histogram of the alongshore distances between every
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combination of rip channels at these two consecutive times. This approach was suitable because it did not necessitate tracking individual rip currents through time. If there was no alongshore rip movement, the histogram had the highest frequency in the zero bin and peaks at multiples of the alongshore rip channel spacing; conversely, if rips changed in their alongshore position, the bin spanning zero would have a lower frequency count than higher bins. Thus the measure of change was defined as the frequency count in the 7.5 and 15 m bin (where results were found to be non-sensitive to bin width). If this method was used on higher energy beaches wider bin ranges would be needed as the rips would likely move further during reconfiguration events. Rip channel reconfiguration events corresponded to instances when this measure of change (Fig. 4b) reached a local maximum accompanied by an approximately coincident change in the number of rip channels (Fig. 4c). Change in the number of rip channels was also used so that events, when all the rip channels were simply migrating simultaneously in the alongshore direction, were excluded. Over the period of study (excluding the year 2000), there were six rip reconfiguration events (Fig. 3). The 1999 rip channel data in Fig. 4 provides an example of when rip reconfiguration events occurred. The maximum in the measure of change and the change in the number of rip channels did not always coincide. It is possible that when the rip channels get closer or further apart they experience a higher alongshore migration rate and when they finally merge (which corresponds to a change in the number of rip channels), the migration rate slows. Because of the limited number of events available for analysis and the noise that accompanies detection during storms, it is difficult to determine the exact details of the process of reconfiguration. Video images and rip channel locations before and after each reconfiguration event are shown in Fig. 5.
To demonstrate how the rip channel detection method may be used, the technique was applied to a 3.3-year database of video imagery. The resulting rip channel locations were used to determine the wave conditions under which rip channels were regularly or irregularly spaced alongshore, the role of the cross-shore length of rip channel patterns in determining response rate, the role of wave event history and finally, the thresholds of wave event energy and duration compared to rip channel cross-shore length that control the occurrence of downstate (less rips) versus upstate (more rips) transitions. 3. Algorithm application 3.1. Wave condition comparisons Wave data was provided by NIWA, and consisted of a hindcast using the WAM global wave model. This model has been calibrated against buoy and satellite data around New Zealand (Gorman et al. 2003a,b). Model results calibrated well to a directional wave-rider buoy deployed in the Mokohinau Islands, 120 km north of Tairua. The model was used to hindcast significant wave height, direction, and period on a 3-hourly sampling interval. Similar to previous works (Turner et al., 2007), a direct day-by-day correlation between wave characteristics and alongshore rip channel spacing was not significant, however one can expect that the reconfiguration events were related to weather-driven changes in wave conditions. Therefore, new timeseries of averaged wave energy were defined. Different wave averaging periods were tested, where the rip reconfiguration events corresponded best to the average of the previous 10 days wave energy (Fig. 4f). In addition to average wave energy, storm duration timeseries were generated, which consisted of the number of hours since the beginning of a storm greater than a threshold. A threshold of
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5000 Jm− 2 best related to the occurrence of reconfiguration events (Fig. 4f). The exact timing of the reconfiguration events and the maxima in duration and averaged wave energy do not coincide exactly, due to a lag time in rip channel response to a change in wave conditions. Reconfiguration events were associated with increased wave energy (Fig. 4f). However, there were times when mean wave energy over ten days reached high magnitudes but there were no rip channel reconfiguration events indicated such as in 2001 on Julian Days 180, 250 and 340 when mean wave energy over ten days reached 5000 Jm− 2 or more. There were also reconfiguration events when there was not a large increase in the mean wave energy such as in 2001 on day 50 when mean wave energy over ten days reached more than 3000 Jm− 2, considerably less than the mean energy during other rip reconfiguration events. These occurrences indicate that wave energy is not the sole factor driving changes in alongshore rip channel patterns. 3.2. Rip channel size Although the large 2000 storm was not associated with a reconfiguration event, there was a rapid change in the orientation of the sand bar where it switched from being wider at the southern end to wider at the northern end between days 184–191 (Fig. 6b, c). This change in orientation of the bar provided an interesting case with which to demonstrate the role of cross-shore surf zone length scales in the dynamics of the rip channels. Between days 176 and 193 in 2000 there was high wave energy when on days 176, 182 and 193 in 2000 Hs reached 5 m, 4 m and 4 m respectively (Fig. 7b). On day 183 between the two high wave events the sand bar was wider at the southern end (Fig. 6b) and by day 192 the orientation had switched to wider at the northern end (Fig. 6c). After this change in orientation of the bar, rip channels on the northern half of the beach subsequently evolved as three large rips with a long cross-shore length. The
southern part of the beach had a considerably narrower surf zone so the beach had a dual-width surf zone (Fig. 6d). Before the storm, the opposite configuration was observed (Fig. 6b). During the storm event, the mean wave direction had an unusually strong easterly component (Fig. 7d) combined with Hs around 3 m (Fig. 7b) causing a strong alongshore energy flux. As previously shown, Tairua Beach is shadowed to the south by Shoe Island (Fig. 1). To demonstrate the role of wave shadowing, the SWAN wave model was run on a 45 m × 45 m grid extending to the location of the deep water wave hindcast, using a 2 m wave height and wave angle approaches from the southeast, north, northeast and east. These model runs confirm that wave heights are nearly halved in amplitude at the southern end compared to the northern end of the beach during easterly wave events (Fig. 6a). The greater wave energy reaching the northern half of the beach appeared to cause the sand bar position to be forced seawards into deeper water and subsequent rip channels had a large cross-shore extent while the rips on the southern half remained small (Fig. 6d). The evolution of the rip channels during the period when the dualwidth surf zone was present in 2000, showed that under the same input of wave forcing, the rip channel and sand bar morphology were more dynamic in the narrow portion of the beach (Fig. 6). Conversely, the three large rips on the northern half of the beach in the wide surf zone were stable, persisting until day 108 the following year (2001). This case is shown in Fig. 6d–f, when the wave conditions were large enough to break over the shallow, southern half of the bar and re-work the rip channel morphology so that these rips were controlled by the hydrodynamics. However, the wave conditions were not large enough to break over the deeper, northern half of the bar and rework the three northern rips so that these rips were topographically controlled. It is also worth noting the presence of two rips at each of the headlands of Tairua Beach that had a large cross-shore length and were persistent throughout the 3.3 year dataset.
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Fig. 5. Rectified, time-averaged video images of Tairua Beach. Black dots indicate rip channels (as obtained from the detection algorithm). Left and right hand columns show the beach before and after each reconfiguration event. Event 1 images are from 1999 on days 94 at 1500 hours (prior) and 149 at 1200 hours (after), Event 2 from 1999 on days 251 at 1100 hours and 299 at 1400 hours, Event 3 in 1999 on days 306 at 0700 hours and 331 at 1601 hours, Event 4 in 2001 on days 43 at 1600 hours and 65 at 1000 hours, Event 5 in 2001 on days 112 at 1200 hours and 127 at 1200 hours, and Event 6 in 2002 on days 69 at 1000 hours and 74 at 1400 hours. Note that the ‘V’ shaped rip channels are counted as separate rips according to rule No. 4 in section 2.2.
3.3. Headland rips Headland rips are known to be topographically controlled and can be persistent in their location and morphology (Short, 1985). The two persistent rip channels along the headlands of Tairua Beach were orientated obliquely at opposite angles (Fig. 8). Often the southernmost rip channels were outside the field of view of the camera, and hence the distinctive orientation of the headland rips is more apparent at the northern rip rather than the southern. When the beach was dominated by headland rips, the mean rip channel angle was also dominated by the orientation of the headland rips (Fig. 4e). For example, in 1999 (Fig. 4) and 2002 (not shown), when rips along the northern headlands dominated the system, the mean rip channel angle became strongly negative and vice versa when the system was dominated by rips at the southern headlands. These headland rip channels channelled water away from the centre of the beach. This is in contrast to recent modeling studies on headland-embayed beaches which suggest that the water accumulates at the centre of the beach to make one large seaward rip (Silva et al., 2010). 3.4. Upstate and downstate nearshore morphology transitions Sand bar and rip channel morphology can be used to define beach state. Upstate transitions are associated with higher wave events
when the rip channels become fewer and more widely spaced whereas downstate transitions are associated with lower waves and more, narrowly-spaced rip channels are formed. Some of the rip channel reconfiguration events were associated with upstate transitions in nearshore morphology and some with downstate transitions (Fig. 9) (see Wright and Short, 1984 for a detailed explanation of transitions and beach state). Reconfiguration events three, four and six were associated with a decrease in mean alongshore rip channel spacing and an increase in the number of rips (a downstate transition). Events one, two and five were associated with an increase in mean alongshore rip channel spacing and either no change or a decrease in the number of rip channels (an upstate transition). The upstate transitions were associated with longer duration wave events and the downstate transitions with shorter duration wave events (Fig. 9). 4. Discussion The algorithm developed for detecting rip channels in video imagery can be used to relatively easily, and accurately detect and measure rip channels. This method is an improvement on past methods as it can detect rip channels across the entire surf zone rather than across a single averaged profile (Bogle et al., 2001) and thus provide information on channel orientation and sinuosity. It is hoped
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Fig. 6. a: significant wave height at 5 m water depth modeled using SWAN and assuming 2 m, 8 s offshore waves approaching from the east. b. and c. show video images from 2000 from Julian Days 183 at 1200 hours and 192 at 0800 hours. d., e. and f. show images from 2001 on Julian Days 32 at 1800 hours (d.), 43 at 1600 hours (e.) and 59 at 1600 hours (f.). Black lines show the position of the barline.
that the present method can be applied at other sites to create quantitative rip channel datasets from the tens of years of video imagery data available worldwide through other systems (e.g., Holman and Stanley, 2007). If rip channel data sets can be extracted from these images in a time and cost effective manner, it will revolutionise efforts to relate rip channel behavior to wave conditions and antecedent morphology and ultimately help to develop forecasts of rip occurrence. Over the period of study, there were long periods of time when the alongshore rip channel locations were fairly regularly spaced and stable with time. These stable periods were punctuated by six reconfiguration events when the alongshore rip channel configuration changed, at times becoming irregular. Each of the reconfiguration events was easily identified as an upstate or downstate transition in beach morphology by an increase or decrease in the number of rip channels and alongshore rip spacing (Short, 1985). Three of the events were downstate transitions and three upstate where there was a clear division in wave energy during these events. Short duration high energy events were associated with downstate transitions and long duration wave events with upstate transitions (Fig. 9). Surprisingly there is no evidence that a complete reset event (resulting in the development of an alongshore uniform sandbar) in nearshore morphology occurred over the period of study. A lack of reset events is unusual, for example at the 2 km-long embayed Palm Beach in Australia, reset events occurred on average four times per year (Holman et al., 2006) and at Monterey Bay in California 1–2 times per year (Orzech et al., 2010). Lack of reset events is significant as most rip current generation models assume the occurrence of such
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morphology resets. The lack of reset events at Tairua Beach could be due in part to the absence of a wave event large enough to reset the morphology and also the nature of this small, embayed beach leading to the headlands playing a dominant role in influencing rip channel behavior. The rip channel time-series (Fig. 3) shows that at least one of these headland rips is present throughout the entire 3.3 year data set. A possibility is that the evolution of stable (in time), evenly spaced rip channel patterns begins at the dominant headland rip channel, which gradually stabilizes the neighboring rip channels until the beach has rips regularly spaced along its entire length. This occurred in 2001, when the 3 northern large rips that were part of the dualwidth surf zone gradually evolved alongshore into a system of evenly spaced rip channels. More case studies of rip channel evolution are needed to confirm this hypothesis, which is actually in contrast with both the edge wave approach and present self-organization model results (in both cases rip channels appear more or less concomitantly). These results also have implications with respect to several numerical studies (e.g. Calvete et al., 2005) that use linear stability analysis and that, given a specific set of wave conditions, predict an alongshore regular rip channel spacing. As shown in the observations presented in Fig. 6, the alongshore spacing is never regular and it nearly halves (from 4 to 7 rip channels) over time so that even if some sort of average spacing could be predicted using linear stability analysis, the nonlinear dynamics associated with changes in spacing are not captured. Sand bars and rip current channels in the surf zone are seldom, if ever, in equilibrium with the instantaneous wave conditions (Smit et al., 2008). In line with past studies (e.g. Holman et al., 2006; Turner et al., 2007), little correlation existed between rip channels and immediate, instantaneous measures of the wave conditions. The rip channels at Tairua beach exhibited a lag time between high wave events and upstate changes in nearshore morphology, which is expected considering the considerable volume of sand that must be shifted to move a rip channel. There was also a longer lag time between low wave conditions and downstate changes in nearshore morphology in agreement with Short (1985) who noted that under low energy, rips can become fixed in their location in the Longshore Bar-Trough (LBT) and Rhythmic Bar and Beach (RBB) states and can persist for long periods if waves are constant. Conversely, during high energy waves alongshore rip spacing increases with rips becoming more intense. Rips may reconfigure by shifting, disappearing and more can reappear (Short, 1985). The importance of wave energy and duration was also noted by Ortega-Sánchez et al. (2008) and Jiménez et al. (2008). In line with our findings, Ortega-Sánchez et al. (2008) found that beach morphology type generally did not change simultaneously with a change in wave forcing and that transition time was dependent on the wave energy. In particular, longer morphology transition time was required for low energy waves. Jiménez et al. (2008) also noted the importance of lag time in morphodynamic response to wave forcing, and stressed the importance of both wave event duration and intensity in nearshore morphodynamic response. The antecedent rip channel morphology was important in influencing if and to what extent the Tairua rip channel system changed during high energy wave events. For rip current channels at Tairua with large cross-shore extents, the response time for rip morphology was 5–10 days, and for rip channel systems of smaller size i.e. with shorter cross-shore lengths and narrow spacing (such as what occurred in 2002), wave energy averaged over shorter periods of time (1–5 days as opposed to 5–10 days) showed a better relationship to rip reconfiguration events. These smaller rip channels are more easily moved, as this requires shifting lesser volumes of sand. Wright and Short (1984) also noted that during low intensity (energy) events surf zone morphology will take longer to respond than during high intensity events. Interestingly, in 2001 on days 190 and 250, wave energy events occurred of a magnitude and duration than in other
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years was sufficient to cause at least two reconfiguration events. However, in this case the rip channels remained stable. Close examination indicated that the mean surf zone width was ~ 40 m wider in 2001 than these other cases. The cross-shore extent of the rip channel system relative to the duration and magnitude of the event is critical to determining the possibility of a reconfiguration event; systems with larger cross-shore extents have longer lag-times. The existence of a dual-width surf zone allowed the role of rip channel cross-shore length to be qualitatively examined. Both ends of the beach were exposed to the same energy after the development of the dual-width surf zone, yet the large crossshore extent rips at the northern headland remained in the same location but the short cross-shore extent rip channels at the southern end shifted. This is consistent with the ideas of Eliot (1973) and Short (1985) that only some rips persist for long periods of time and that persistent rip channels are created during high energy events (such as is shown in Fig. 6). There is scope to extend this study by examining, for example, the orientation of the rip channels in the centre of the beach, where there were times when the rip channels were shore-perpendicular, and other times when they had alternating orientations, suggesting that these were recently split feeder channels. The extent of the rip
channel system across the surf zone also varied, where some rip channels caused a strong perturbation in the sandbar, some caused a large perturbation in the shoreline, and some evenly affect both sandbar and shoreline. Such patterns could be used to infer the connection of shoreline and sandbar storage of sand, and ultimately determine the resilience of the shoreface to storm erosion. Extending the length of the dataset used and applying the rip channel detection algorithms to video images from other beaches will also help drive rip current research forwards. 5. Conclusion This paper introduces a semi-automatic method of detecting rip channels in video imagery, which offers a promising technique to measure quality, long-term rip channel data sets relatively easily. The database developed using this technique was used to examine reconfiguration events, the role of headland rips and rip channel size using a 3.3 year data set from Tairua Beach in New Zealand as a case study. Results from this study as well as past studies suggest that antecedent rip channel size, wave energy averaged over a wave event and the duration of the event are three equally important factors whose interaction ultimately determines how rip channels respond to
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a change in the wave conditions. Beach protection from waves by an offshore island was found to influence the cross-shore extent of rip channels, where under certain wave directions the exposed half of the beach developed longer rip channels than the protected half. Topographically controlled headland rips were found to play a dominant role in the rip channel system, where they were persistent, even through high wave energy events. The dependence of rip channel dynamics on the wave conditions that occurred some 2– 10 days prior indicates a delayed response time, the length of which is determined by the cross-shore length of the rip channel. There was a longer lag time between an increase in wave energy and rip channel change for rip channels with a longer cross-shore length. In contrast to previous studies, there was no evidence that the rip channel morphology at Tairua ever completely reset during the 3.3 year study period which is important since this assumption is what most rip generation models are based on. Both upstate and downstate transitions in rip channel morphology occurred during the study where upstate transitions were associated with longer duration high wave events and downstate with short duration wave events. To increase understanding of rip channel behavior there is a need to come away from traditional rip-wave correlation techniques and consider instead the antecedent nearshore morphology where rip channel cross-shore length plays a pivotal role in determining wave
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Acknowledgements This study was undertaken by S.L.G. as part of a MSc degree at the University of Waikato. S.L.G. acknowledges funding from the University of Waikato Masters Research Scholarship, the University of Waikato Maori Excellence Awards, the Whakatane Historical Society Scholarship and the Broad Memorial Fund. G.C. and S.S. were funded by the Foundation for Research, Science and Technology (WRHC102). The camera is part of the Cam-Era programme implemented and coordinated by Environment Waikato (Waikato Regional Council) and NIWA (National Institute of Water and Atmospheric Research) in New Zealand. Thank you also to Dr. Ivan
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event energy and duration thresholds for driving change in the nearshore morphology. Wave energy in the days leading up to the existing rip channel configuration as well as the duration of high energy wave events must be considered. Many recent studies have modeled the variation of rip channels' formation and evolution both as a response to persistent low wave energy input, and episodic storm conditions. Our methodology and dataset allow critical validation data for these models, showing the timescale over which rip systems respond, and the critical role of antecedent rip channel morphology.
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