Hydrodynamic Measurements of Propagating Waves at Different Nearshore Depths in Hujeong Beach, Korea

Journal of Marine Science and Engineering

Article Hydrodynamic Measurements of Propagating Waves at Diﬀerent Nearshore Depths in Hujeong Beach, Korea

Jong Dae Do 1 , Yeon S. Chang 2,* , Jae-Youll Jin 1, Weon Mu Jeong 2 , Byunggil Lee 1 and Ho Kyung Ha 3,* 1 East Sea Environment Research Center, Korea Institute of Ocean Science and Technology, 385 Haeyang-ro, Yeongdo-gu, Busan 49111, Korea; [email protected] (J.D.D.); [email protected] (J.-Y.J.); [email protected] (B.L.) 2 Maritime ICT R&D Center, Korea Institute of Ocean Science and Technology, 385 Haeyang-ro, Yeongdo-gu, Busan 49111, Korea; [email protected] 3 Department of Ocean Sciences, Inha University, Incheon 22212, Korea * Correspondence: [email protected] (Y.S.C.); [email protected] (H.K.H.); Tel.: +82-51-664-3566 (Y.S.C.); +82-32-860-7702 (H.K.H.) Received: 4 August 2020; Accepted: 3 September 2020; Published: 7 September 2020

Abstract: This paper reports the results of hydrodynamic measurements at two different water depths to observe wave properties in the course of wave propagation, especially during storm periods, in Hujeong Beach, Korea. In addition to hydrodynamic measurements, video monitoring data and satellite images from Sentinel-II were employed to compare the temporal changes in shoreline positions and shallow water bathymetry during the storms. Through combination of a variety of observational data sets, the accuracy of analysis could be enhanced by preventing possible misinterpretation. Two significant storms were observed from two experiments conducted at different times and locations of the beach. The hydrodynamic conditions were similar in both of the periods in terms of wave and current conditions as well as wave nonlinearity such as skewness. However, the response of shoreline during the two storms was the opposite because it was eroded during the first storm but advanced during the second storm. This suggests that other controlling factors such as storm duration need to be investigated to support the analysis of cross-shore sediment transport and consequent shoreline evolution for future studies.

Keywords: wave propagation; coastal erosion; wave skewness; wave asymmetry; video monitoring; satellite images; Hujeong Beach

1. Introduction Coastal erosion is a critical issue as it may cause impacts on human life when the sand in recreational beaches or sediments used to protect coastal facilities are lost permanently. The retreat or accretion process of the shorelines is a result of coastal sediment transport that occurs mainly in the surf zone where the wave energy is transferred to kinetic energy due to wave breaking. There are two modes of sediment transport according to the direction of their motions—longshore and cross-shore sediment transport. When the waves are obliquely incident, the momentum of breaking waves generates shore-parallel radiation stresses that produce longshore current and the consequent longshore sediment transport. Therefore, the direction of longshore transport corresponds to that of the wave incidence, which can be predicted without difficulty. The cross-shore transport refers to the motions of sediments perpendicular to the shoreline due to waves, currents, and their combined motions. Unlike the longshore transport, the direction of cross-shore transport is not easily predictable as it depends on a variety of wave and current conditions that are difficult to be precisely measured. In general, sediments move offshore under energetic wave conditions causing sediment erosions from

J. Mar. Sci. Eng. 2020, 8, 690; doi:10.3390/jmse8090690 www.mdpi.com/journal/jmse J. Mar. Sci. Eng. 2020, 8, 690 2 of 18 the shore, which occurs in short time period during such as storm events [1,2]. Onshore sediment motion prevails under mild wave conditions and it occurs over relatively longer periods at the month scale [2,3]. The net cross-shore sediment transport is the result of a balance between these onshore- and offshore-directed components, and thus an accurate description of them is important in predicting the dynamic evolution of beach profiles [4]. The nonlinearity of shoaling waves have been commonly studied using numerical models (e.g., [3,5–8]) and/or lab experiments (e.g., [9,10]). For example, new formulations for seabed shear stress, a fundamental component to calculate sediment transport, have been developed by incorporating Sk and As using model [11] and lab data [9]. Although it is not easy to observe the nonlinear wave shape parameters in the field where wave irregularity prevails, data measured with wave gauges have been applied to elucidate the nonlinear wave dynamics in various ways. From the measurements of shoaling surface gravity waves, Sk and As were estimated as the real and imaginary parts of bispectra respectively [12]. The bispectral analysis was also applied to investigate the spatial variation of Sk and As of orbital velocities for shoaling and breaking waves in terms of Ursell parameter [13]. Since Sk and As vary as waves propagate over the shoaling area, it is important to understand their spatial variation along the propagation path. Using an array of flow meter across a surf zone, velocity acceleration field was observed to be strongly skewed in the shoreward direction [14]. In addition, hydrodynamic measurements along cross-shore profiles were used to develop empirical formulations to describe wave nonlinearity in terms of depth and other wave parameters [4]. The impact of velocity skewness on the sediment transport was investigated in terms of the seabed ripple movement to observe that the wave spectra in the storm growing/decaying phase were closely related with the signs of Sk and the direction of ripple migration [15,16]. In the offshore outside the surf zone, laser altimeters could be applied to measure the wave asymmetry and steepness [17]. Recently, the impact of seabed roughness on the wave transformation was studied by measuring Sk and As over rocky platforms where the wave energy was dissipated [18]. In the present study, we measured the hydrodynamics and wave nonlinearity at two different depths of a field site to examine the spatial changes by the shoaling and breaking during wave propagation under various wave conditions. Previously, we observed a rapid seabed erosion at a water depth of 8–9 m during an extreme wave condition over an approximately two-day period in Hujeong Beach [19]. This paper contains the results from follow-up studies with additional data sets measured at different locations and times in order to mainly examine the spatial variation of wave parameters under such extreme conditions as well as normal wave conditions. In addition to the hydrodynamic measurements, we employed two additional data sets. First, the shoreline data obtained from a video monitoring system (VMS) installed in the middle of the experimental site were analyzed in the corresponding experimental period. The VMS provides the beach width calculated from the shoreline positions averaged over 10 min video data, which have been usefully applied to understand the characteristic process in the Hujeong Beach [20]. In addition, Sentinel-II satellite images were employed to observe nearshore morphology that supported the results from the hydrodynamic data. Recently, the Sentinel satellite data with high spatial resolution and short orbital cycle were used to detect nearshore sandbar in shallow coastal waters [21]. We also used the satellite images to show their movement in accordance with the wave measurements. The purpose of this study is then to examine the coastal processes associated with cross-shore sediment movement in terms of the wave nonlinearity in various wave conditions, using on-site and remotely sensed measurements.

2. Materials and Methods

2.1. Field Experiments In this study, we used two data sets measured at December 2016–January 2017 and at December 2018–January 2019 in Hujeong Beach, east coast of Korea (Figure1a). At Hujeong Beach, the East Sea Research Institute (ESRI) of Korea Institute of Ocean Science and Technology (KIOST) is located. J. Mar. Sci. Eng. 2020, 8, x FOR PEER REVIEW 3 of 18

the average wave height is usually not higher than 1.0 m. During winter, however, severe storm waves frequently attack the site from the northeast with waves higher than 4 m. In addition, this area is influenced by typhoons occasionally in summer. The sediment size in the nearshore area of the beach is coarse sand as ~0.5 mm. The beach is vulnerable to erosion since the construction of Hanul nuclear power plant in the north of the beach [19,20]. Figure 1b shows an aerial photo over the Hujeong Beach in 1980 when the beach was in equilibrium before the construction of the power plant. One of the missions of ESRI is to perform studies on coastal processes including measurements of seabed bathymetry using echosounders as the beach is characterized with its pocket shape and nearshore crescentic sandbars as shown in Figure 1c. As one of the outcomes, an unexpected severe erosion of seabed was observed by deploying a set of instruments in the depth of ~8 m [19]. In this study, parts of data from [19] have been used to estimate wave and current properties at the same location (designated as L1 for this study). The hydrodynamic data were also measured at J.shallower Mar. Sci. Eng. depth2020, (L2)8, 690 using a set of acoustic instruments during the same period, which were able3 of 18to compare with the data for propagating waves. Figure 1c shows the two locations of the deployed Theinstruments Hujeong Beachof L1 isand amicro-tidal L2 of the areaexperiment where thedu tidalring rangeDecember is ~0.2 2016 m. Theand waveJanuary climate 2017 is (hereafter, moderate asExp#1). the average The water wave depths height measured is usually at not the higherinitial time than of 1.0 deployment m. During were winter, 8.1 however, m and 3.3 severe m at L1 storm and wavesL2 respectively. frequently Detailed attack the specification site from the of northeastthe measur withed data waves during higher Exp#1 than is 4 listed m. In in addition, Table 1. thisAnother area isfield inﬂuenced experiment by typhoons was performed occasionally ~2 years in summer.later from The Exp#1 sediment at the sizesimilar in thelocations nearshore of the area Hujeong of the beachBeach isin coarse December sand 2018 as ~0.5 and mm. January The 2019 beach (hereafter is vulnerable, Exp#2). to erosion The locations since the of two construction measurements of Hanul (L3 nuclearand L4) power during plant Exp#2 in the are north also of marked the beach in [19 Figure,20]. Figure 1c, and1b shows its specification an aerial photo is listed over the in HujeongTable 2. BeachUnfortunately, in 1980 when the instruments the beach was in inL4 equilibrium were buried before under the ground construction at 29 December of the power 2018 plant. and thus One L4 of thedata missions were not of available ESRI is to after perform that. studiesSince the on purpose coastal processesof this paper including is to compare measurements the difference of seabed of bathymetryhydrodynamics using of echosounders propagating aswaves the beachat two is characterizedlocations of different with its pocketdepths, shape the damage and nearshore on the crescenticmeasurement sandbars in L4 asprevented shown in further Figure 1analysisc. As one regard of theless outcomes, of the data an unexpectedavailability severein L3 for erosion a longer of seabedperiod. was observed by deploying a set of instruments in the depth of ~8 m [19].

Figure 1. (a) Google map of Korean peninsula with location of Hujeong Beach, (b) aerial photo over Figure 1. (a) Google map of Korean peninsula with location of Hujeong Beach, (b) aerial photo over Hujeong Beach in 1980 when the beach was in equilibrium before construction of Hanul Nuclear Power Hujeong Beach in 1980 when the beach was in equilibrium before construction of Hanul Nuclear Plant (NPP), (c) locations of deployed instruments (L1 & L2 for Exp#1, L3 & L4 for Exp#2) on google Power Plant (NPP), (c) locations of deployed instruments (L1 & L2 for Exp#1, L3 & L4 for Exp#2) on map of Hujeong Beach. The red dot marks the location where the VMS was installed, and the red google map of Hujeong Beach. The red dot marks the location where the VMS was installed, and the rectangle marks the coverage of the VMS. The map also shows that crescentic sandbars are actively red rectangle marks the coverage of the VMS. The map also shows that crescentic sandbars are developed in the nearshore areas of the beach. actively developed in the nearshore areas of the beach. In this study, parts of data from [19] have been used to estimate wave and current properties at the same location (designated as L1 for this study). The hydrodynamic data were also measured at shallower depth (L2) using a set of acoustic instruments during the same period, which were able to compare with the data for propagating waves. Figure1c shows the two locations of the deployed instruments of L1 and L2 of the experiment during December 2016 and January 2017 (hereafter, Exp#1). The water depths measured at the initial time of deployment were 8.1 m and 3.3 m at L1 and L2 respectively. Detailed specification of the measured data during Exp#1 is listed in Table1. Another field experiment was performed ~2 years later from Exp#1 at the similar locations of the Hujeong Beach in December 2018 and January 2019 (hereafter, Exp#2). The locations of two measurements (L3 and L4) during Exp#2 are also marked in Figure1c, and its specification is listed in Table2. Unfortunately, the instruments in L4 were buried under ground at 29 December 2018 and thus L4 data were not available after that. Since the purpose of this paper is to compare the difference of hydrodynamics J. Mar. Sci. Eng. 2020, 8, 690 4 of 18 of propagating waves at two locations of different depths, the damage on the measurement in L4 prevented further analysis regardless of the data availability in L3 for a longer period.

Table 1. Speciﬁcation of measurements ate L1 and L2 during Exp#1.

L1 L2 37 04 45.82” N 37 04 42.49” N Location (Lat, Lon) ◦ 0 ◦ 0 129◦24028.32” E 129◦24014.10” E Water depth 8.1 m 3.3 m VECTOR (Nortek), Instruments ADV (SonTek) ADCP (RD Instruments) Measurement height above seabed 0.25 m Time for t = 0 (day) 20 December 2016 11:00 Measurement burst interval 60 min Sampling frequency 2 Hz Burst duration 20 min Data points in one burst 2400

Table 2. Speciﬁcation of measurements ate L3 and L4 during Exp#2.

L3 L4 37 04 42.90” N 37 04 38.19” N Location (Lat, Lon) ◦ 0 ◦ 0 129◦24027.39” E 129◦24022.22” E Water depth 5.5 m 3.5 m VECTOR, Signature 500 Instruments ADV (SonTek) (Nortek) Measurement height above seabed 0.25 m Time for t = 0 (day) 21 December 2018 07:00 Measurement burst interval 60 min Sampling frequency 4 Hz Burst duration 10 min Data points in one burst 2400

The measured flow data were processed to calculate representative values for each burst. First, the velocities were decomposed into the cross-shore and longshore directions as +u indicated the onshore direction and +v directed to the left of the shore shown in Figure1. Due to the contamination on the raw data by acoustic instruments, especially for those moored at shallower depths in L2 and L4, despiking and filtering were necessary to exclude the unordinary data for the analysis. When the number of despiked data exceeded 20% of the whole data in the burst, the analysis was not performed, and the representative values of that burst were not estimated because of the high possibility of data contamination. For this reason, the analyzed data are available only for t = 2–18 and 24–32 for Exp#1 (time was set 0 at 20 December 2016 for Exp#1). For Exp#2, the instruments in L4 were buried under ground since t = 7 (time was set 0 at December 21, 2018 for Exp#2) and its data were only available for t = 0–7 for Exp#2. The three periods with valid data in both Exp#1 and Exp#2 are set as T1, T2 and T3 respectively. In addition, there were times when data were not available even during T1–T3 when the despiked and filtered data were still contaminated. For example, the data in t = 6–8 were not available in T1. From the flow measurements, five parameters were estimated based on the horizontal q 2 2 velocity components. The velocity magnitude was defined as Vmag = u(t) + v(t) , and the mean velocity components were calculated as u = u(x) and v = v(x). The skewness was estimated from the u(t)3 H[u(t)]3 cross-shore velocity component as Sk = and asymmetry was computed as As = where u(t)23/2 u(t)23/2 H is the Hilbert transform [22]. J. Mar. Sci. Eng. 2020, 8, x FOR PEER REVIEW 5 of 18

𝑢(𝑡) 𝑣(𝑥) 𝑆 = . The skewness was estimated from the cross-shore velocity component as / 𝑢(𝑡) 𝐻[𝑢(𝑡)] 𝐴 = 𝐻 J.and Mar. asymmetry Sci. Eng. 2020 was, 8, 690 computed as / where is the Hilbert transform [22].5 of 18 𝑢(𝑡)

2.2. Video Monitoring System VMS images have been usefully applied for de decadescades to monitor long-term beach process process [23]. [23]. Recently, newnew VMSVMS methodologiesmethodologies such as surf cameras have been developed to provide more eefficientfficient ways for shoreline data data co collectionllection [23,24]. [23,24]. In In this this study, study, a aconventional conventional VMS VMS was was used used as as it itwas was constructed constructed on on the the top top of of30 30 m-high m-high monitoring monitoring tower tower in inthe the middle middle of ofHujeong Hujeong Beach Beach on on 9 9December December 2016, 2016, 11 11 days days before before the the field field measurem measurementsents for for Exp#1 Exp#1 started. started. The The VMS VMS data have been usefully employed to understand shoreline processesprocesses ofof thethe ~2.4~2.4 km long beach by using eight video cameras [[20].20]. The The VMS VMS provides provides shoreline shoreline position positionss per per hour hour on on a a clear day during the daytime, whichwhich havehave been usedused toto calculatecalculate thethe beachbeach areaarea outsideoutside the water.water. Under harsh wave conditions, the shorelineshoreline datadata cannotcannot bebe obtainedobtained duedue toto thethe contaminationcontamination of wave breaking that makesmakes the shoreline positionspositions blurred.blurred. The im imagesages taken by each video camera were combined into a 2-D 2-D image. image. In thisthis process,process, the the angle angle of of each each camera camera was was considered considered to calibrateto calibrate the the tilted tilted image image to the to verticalthe vertical line. Afterline. After that, that, 600 snapshot 600 snapshot images images were were averaged averaged for 10 for min 10 min per per hour hour to remove to remove the the noise noise produced produced by waveby wave breaking, breaking, and the and shoreline the shoreline positions position were extracteds were manually, extracted providing manually, metric providing measurements metric ofmeasurements shoreline data. of shoreline data. In FigureFigure2 2,, the the shoreline shoreline datadata measuredmeasured fromfrom the the VMS VMS on on 19 19 December December 20162016 andand 2929 DecemberDecember 2016 are compared. It shows that the shoreline was not straight along the beach, but had undulations as there were several locations where thethe shoreline waswas protrudedprotruded toto thethe sea.sea. These protrusions were likelylikely related to the nearshore sandbars that were ob observedserved at 3–5 m water depth [20]. [20]. In In this this study, study, the shorelineshoreline positionspositions will will be be compared compared at at di differefferentnt times times to to understand understand the the beach beach process process during during the experimentalthe experimental period. period.

Figure 2.2. ComparisonComparison of of shoreline shoreline positions positions in Hujeongin Hujeong Beach Beach measured measured by VMS. by VMS. Black Black solid linesolid marks line themarks shoreline the shoreline measured measured on 19 December on 19 December 2016 and 2016 black and dashed black marks dashed the marks shoreline the onshoreline 29 December on 29 2016.December The di2016.ﬀerence The betweendifference these between two linesthese is two colored lines with is colored red or with blue asred it or denote blue theas it accretion denote the or retreataccretion area or duringretreat thearea period during respectively. the period respectively. 2.3. Sentinel-II Satellite Images 2.3. Sentinel-II Satellite Images An additional dataset was obtained from the satellite images. Sentinel-II is an Earth observation An additional dataset was obtained from the satellite images. Sentinel-II is an Earth observation mission to acquire optical imagery over land and coastal waters with high spatial resolution (10 m to mission to acquire optical imagery over land and coastal waters with high spatial resolution (10 m to 60 m), developed and operated by European Space Agency since 2015 [25]. Figure3 shows a sentinel-II 60 m), developed and operated by European Space Agency since 2015 [25]. Figure 3 shows a sentinel- image taken over the experimental site of Hujeong Beach on 11 December 2016, downloaded from II image taken over the experimental site of Hujeong Beach on 11 December 2016, downloaded from Creodias (creodias.eu), a platform that provides Sentinel-II images for free. It shows that the shorelines and the wave breaking lines are clearly captured in the image. Owing to the high spatial resolution (~10 m), the crescentic sandbars larger than 100 m can be detected, which provides big advantage to apply the Sentinel-II data in the nearshore studies. Moreover, the shortest revisit cycle of the Sentinel-II J. Mar. Sci. Eng. 2020, 8, x FOR PEER REVIEW 6 of 18

Creodias (creodias.eu), a platform that provides Sentinel-II images for free. It shows that the shorelines and the wave breaking lines are clearly captured in the image. Owing to the high spatial resolution (~10 m), the crescentic sandbars larger than 100 m can be detected, which provides big J. Mar. Sci. Eng. 2020, 8, 690 6 of 18 advantage to apply the Sentinel-II data in the nearshore studies. Moreover, the shortest revisit cycle of the Sentinel-II is 5 days by employing two identical satellites (Sentinel-IIA and IIB) as each of them ishas 5 10-day days by revisit employing cycle. Therefore, two identical changes satellites in the (Sentinel-IIA coastal features and with IIB) months as each are of measurable them has 10-day using revisitthe satellite cycle. Therefore,data, if weather changes condition in the coastal permits. features The with shoreline months feature are measurable in Figure using 3 confirms the satellite the data,shoreline if weather positions condition measured permits. by VM TheS in shoreline Figure feature2. The shoreline in Figure 3was conﬁrms not straight the shoreline but protruded positions at measuredseveral locations by VMS along in Figure the2 .shore. The shoreline In addition, was notthough straight it is but not protruded distinct, atthe several features locations of crescentic along thesandbars shore. can In addition,be seen in though the shallow it is not area distinct, of the thewater. features Specifically, of crescentic the horns sandbars of the can sandbars be seen are in theconnected shallow to area the ofprotruded the water. locations Speciﬁcally, in the the shorel hornsine of showing the sandbars an example are connected of out-of-phase to the protruded coupling locations[26]. in the shoreline showing an example of out-of-phase coupling [26].

FigureFigure 3.3. Image onon HujeongHujeong BeachBeach measuredmeasured byby Sentinel-IISentinel-II onon DecemberDecember 11,11, 2016,2016, downloadeddownloaded fromfrom CreodiasCreodias platformplatform (creodias.eu).(creodias.eu). TheThe redred rectanglerectangle marksmarks thethe coveragecoverage ofof thethe VMSVMS shownshown inin FigureFigure2 2.. 3. Results 3. Results 3.1. Wave and Hydrodynamic Measurements 3.1. Wave and Hydrodynamic Measurements In panels a–c of Figures4–6, three wave parameters—significant wave height ( Hs), Peak wave In panels a–c of Figures 4–6, three wave parameters—significant wave height (𝐻 ), Peak wave period (Tp), and peak wave direction (Dp)—are plotted for selected periods (T1, T2 and T3) of Exp#1 andperiod Exp#2. (𝑇), and The peak wave wave parameters direction were (𝐷)—are estimated plotted based for onselected the wave periods spectra (T1, calculatedT2 and T3) fromof Exp#1 the burstand Exp#2. data, whichThe wave gave parameters averaged valuewere estimated per burst. base Thed time on the is set wave zero spectra at December calculated 20, 2016 from for the Exp#1 burst anddata, Figure which4 gaveshows averaged the time value variation per burst. of the The wave time data is set for zero T1. at In December this period, 20, the2016 data for Exp#1 in L1 areand characterizedFigure 4 shows with the the time distinctive variation periods of the of wave storm data waves for (Figure T1. In4 ).this Three period, extreme the eventsdata in (t L1= 3–6,are characterized with the distinctive periods of storm waves (Figure 4). Three extreme events (t = 3–6, 8–10) with Hs > 3 m in L1 were clearly identified. The wave period also varied similarly with the wave 8–10) with 𝐻 > 3 m in L1 were clearly identified. The wave period also varied similarly with the height as it increased with increasing height. Specifically, Tp became maximum reaching to 15 s at wave height as it increased with increasing height. Specifically, 𝑇 became maximum reaching to 15 t = 5–6, corresponding to the high Hs in this time. The wave propagation direction shows different s at t = 5–6, corresponding to the high 𝐻 in this time. The wave propagation direction shows pattern as the waves generally approached the shore in the normal direction (Dp = 0) during the storm periodsdifferent except pattern for as the the sharpwaves changes generally in appr t = 2–3.oached In Figurethe shore5, the in the same normal wave direction data are ( plotted𝐷 = 0) forduring T2 duringthe storm which periods another except storm for the wave sharp attacked changes the in beach t = 2–3. with In FigureHs > 3 5, for the longer same wave time (tdata= 26–30) are plotted with wavefor T2 periods during ofwhich ~10 sanother and with stor nearlym wave normal attacked wave the direction. beach with For 𝐻 Exp#2, > 3 for the longer initial time (t was = 26–30) set at 21with December wave periods 2018, andof ~10 Figure s and6 shows with nearly the three normal wave wave parameters direction. for For T3. Exp#2, In L3, thethe waveinitial condition time was wasset at less 21 distinctiveDecember compared2018, and toFigure that in6 L1show ofs Exp#1 the three as H swavewas significantlyparameters for lower T3. thanIn L3 those, the inwave L1, 𝐻 indicatingcondition was that less the wavedistinctive condition compared was milder to that during in L1 of Exp#2, Exp#1 and as storm was wave significantly events in lower which thanHs exceeded 2 m over a period longer than 1 day did not occur (Figure6a). J. Mar. Sci. Eng. 2020, 8, x FOR PEER REVIEW 7 of 18 thoseJ. Mar. Sci.in L1, Eng. indicating2020, 8, 690 that the wave condition was milder during Exp#2, and storm wave events7 of in 18 which 𝐻 exceeded 2 m over a period longer than 1 day did not occur (Figure 6a).

FigureFigure 4. WaveWave and and hydrodynamic hydrodynamic parameters parameters from from 22 22 December December 2016 2016 to to 7 7 January January 2017 2017 of of Exp#1. Exp#1.

((a)) H𝐻s :signiﬁcant significant wave wave height, height, (b) (Dbp) :𝐷 peak : peak wave wave direction, direction, (c) Tp :(c peak) 𝑇 : wavepeak period,wave period, (d) Vmag (:d velocity) 𝑉 : velocitymagnitude, magnitude, (e) u: cross-shore (e) 𝑢 : cross-shore velocity (+ velocionshore),ty (+ onshore), (f) v: longshore (f) 𝑣̅ : velocitylongshore (+ velocityNW, left (+ in NW, the ﬁgure), left in

the(g) Sfigure),k: wave (g skewness,) 𝑆 : wave (h )skewness,As: wave ( asymmetry.h) 𝐴 : wave The asymmetry. data of Hs The, Dp dataand Tofp in𝐻 L1, 𝐷 are and taken 𝑇 from in L1 [19 are]. taken from [19]. In Figure4, the temporal variations of the ﬁve parameters during T1 of Exp#1 are compared betweenIn Figure L1 and 4, L2.the Astemporal shown invariations Figure4 d,of Vthemag fivesharply parameters increased during during T1 theof Exp#1 two storm are compared periods in t = 3–6 and 8–9 in both locations, but Vmag in L2 was lower than that in L1 likely because the wave between L1 and L2. As shown in Figure 4d, 𝑉 sharply increased during the two storm periods in orbital velocity magnitude decreased with decreasing water depth. It might be also because the wave t = 3–6 and 8–9 in both locations, but 𝑉 in L2 was lower than that in L1 likely because the wave orbitalenergy velocity in L3 decreased magnitude due decreased to the wave with breaking decreasing in L2,water though depth. there It might was nobe also clear because indication the ofwave the u energybreaking in duringL3 decreased these storms.due to the It shouldwave breaking be noted inthat L2, thoughin L2 there sharply was increased no clear indication at t = 3–4 of in the u breakingearly stage during of the th ﬁrstese storms. storm whenIt shouldremained be noted closethat 𝑢 to in zero L2 insharply L2 (Figure increased4e), which at t = 3–4 indicates in the early that stagestrong of onshore the first current storm when developed 𝑢 remained in L2 when close the to storm zero developed.in L2 (Figure In 4e), L1, which the onshore indicates current that was strong not onshoreobserved. current Instead, developed longshore in current L2 when developed the storm to the developed. right of the In beachL1, the at tonshore= 3 (Figure current4f). Oncewas thenot storm was fully developed at t = 4–5, the direction of the current in L1 rapidly changed as it u became

J. Mar. Sci. Eng. 2020, 8, x FOR PEER REVIEW 8 of 18

J. Mar. Sci. Eng. 2020, 8, 690 8 of 18 observed. Instead, longshore current developed to the right of the beach at t = 3 (Figure 4f). Once the storm was fully developed at t = 4–5, the direction of the current in L1 rapidly changed as it 𝑢 became negativenegative and andv 𝑣changed̅ changed to to positive, positive, showing showing that that the the current current ﬂowed flowed o offshoreﬀshore to to the the left left of of the the beach.beach.

ItIt should should be be also also noted noted that thatS k𝑆of ofcross-shore cross-shore velocity velocity shows shows opposite opposite pattern pattern between between L1 L1 and and L2 L2 as itas becameit became positive positive in L1 in butL1 but negative negative in L2 in (Figure L2 (Figure4g).As 4g). analyzed As analyzed in the in previous the previous study study [ 19], the [19], high the positivehigh positiveSk in L1 𝑆 likely in L1 increased likely increased the bed stressthe bed to stress cause theto cause seabed the erosion seabed in erosion this time. in this The time. negative The Snegativek in L2 could 𝑆 in be L2 understood could be understood that the wave that steepness the wave increased steepness at L1increased due to shoalingat L1 due of to storm shoaling waves of decreasedstorm waves by wavedecreased breaking by wave when breaking they reached when to th L2.ey reached Contrary to to L2. the Contrary signiﬁcant to changesthe significant in Sk, Achangess remained in close𝑆 , 𝐴 to zeroremained in both close L1 and to zero L2. This in both low magnitudeL1 and L2. in ThisAs during low magnitude extreme wave in 𝐴 condition during wasextreme not clearly wave understoodcondition was as not the waveclearly asymmetry understood usually as the increaseswave asymmetry under breaking usually waveincreases condition under (Figurebreaking4h). wave condition (Figure 4h).

FigureFigure 5. 5.Wave Wave and and hydrodynamic hydrodynamic parameters parameters from from January January 7 7 to to 21, 21, 2017 2017 of of Exp#1. Exp#1. ( a(a))H 𝐻s:: signiﬁcant significant wavewave height, height, ((bb)) D𝐷p:: peakpeak wave direction, direction, ( (cc)) 𝑇Tp:: peak peak wave wave period, period, (d ()d )𝑉Vmag: velocity: velocity magnitude, magnitude, (e)

(e𝑢) u : :cross-shore cross-shore velocity velocity (+ (+ onshore),onshore), (f ()f )𝑣v̅ : : longshore velocity (+ (+ NW,NW, left left in in the the figure), ﬁgure), ( (gg)) S𝑆k: : wave wave

skewness,skewness, ( h(h) )A s𝐴: wave : wave asymmetry. asymmetry.

J. Mar. Sci. Eng. 2020, 8, 690 9 of 18 J. Mar. Sci. Eng. 2020, 8, x FOR PEER REVIEW 9 of 18

Figure 6. Wave and hydrodynamic parameters from 21–28 December 2018 of Exp#2. (a) Hs: significant Figure 6. Wave and hydrodynamic parameters from 21–28 December 2018 of Exp#2. (a) 𝐻 : wave height, (b) Dp: peak wave direction, (c) Tp: peak wave period, (d) Vmag: velocity magnitude, significant wave height, (b) 𝐷: peak wave direction, (c) 𝑇: peak wave period, (d) 𝑉: velocity (magnitude,e) u: cross-shore (e) 𝑢 velocity : cross-shore (+ onshore), velocity (f) v(+: longshoreonshore), velocity(f) 𝑣̅ : longshore (+ NW, left velocity in the figure), (+ NW, (g )leftSk: in wave the skewness, (h) As: wave asymmetry. figure), (g) 𝑆 : wave skewness, (h) 𝐴 : wave asymmetry. Once the storm period ended at t = ~6, the statistics of data in L2 was not available due to Once the storm period ended at t = ~6, the statistics of data in L2 was not available due to contamination until t = ~8 when the second storm waves occurred for shorter time period until contamination until t = ~8 when the second storm waves occurred for shorter time period until t = ~9. t = ~9. The flow pattern was different from that in the first storm as Vmag in L2 was lower during The flow pattern was different from that in the first storm as 𝑉 in L2 was lower during this second this second storm period while V in L1 was similar between them (Figure4d). The direction of storm period while 𝑉 in L1 wasmag similar between them (Figure 4d). The direction of the cross- the cross-shore current was also different as u in L2 directed onshore. The most significant difference shore current was also different as 𝑢 in L2 directed onshore. The most significant difference can be can be found in S as it remained positive not only in L2 but also in L1, which indicates that the found in 𝑆 as it kremained positive not only in L2 but also in L1, which indicates that the wave wave shoaling might be dominant instead of breaking in both locations (Figure4g). In addition, shoaling might be dominant instead of breaking in both locations (Figure 4g). In addition, 𝐴 shows As shows clear difference between L1 and L2 at t = 8–9 as the magnitude of As increased in L2 as it was clear difference between L1 and L2 at t = 8–9 as the magnitude of 𝐴 increased in L2 as it was dispersed in wider range, compared to that in L2 where As remained close to zero similarly to that dispersed in wider range, compared to that in L2 where 𝐴 remained close to zero similarly to that observed in t = 3–5 (Figure4h). Since the positive /negative sign of As means that the waves were tilted observed in t = 3–5 (Figure 4h). Since the positive/negative sign of 𝐴 means that the waves were tilted backward/forward [27], the higher 𝐴 during the second storm indicates that the waves were deformed when they approached from L1 to L2. Another period examined in Figure 4d is t = 12–18

J. Mar. Sci. Eng. 2020, 8, 690 10 of 18

backward/forward [27], the higher As during the second storm indicates that the waves were deformed when they approached from L1 to L2. Another period examined in Figure4d is t = 12–18 when the wave energy became low after the storms. Vmag in L2 shows more severe fluctuations compared to that in L1. It should be also noted that both Sk and As in L2 show higher dispersion around zero that led to their higher magnitude compared to those in L1 (Figure4g,h). Specifically, Sk in L2 tended to be positive, indicating that the waves became steeper as they approached the shore from L1. For As, this tendency was not found as negative values were also observed, showing that the waves were tilted but not necessarily forward. In Figure5, the same five parameters are plotted but for t = 24–32 (T2) during which the third storm had lower Hs compared to the previous two storms developed for longer period (t = 26–29). In this storm period, Vmag increased to ~0.5 m/s in both L1 and L2. Interestingly, a strong onshore current was observed in L2 while no cross-shore currents were detected in L1 as u ~ 0 during the storm period. Difference between L1 and L2 was also observed in the longshore current as v = 0.2 m/s in L1 − at t = 26 but v ~ 0 m/s in L2 at the same time. On the contrary, v ~ 0 m/s in L1 at t = 29 while it increased to ~0.2 m/s in L2. Except for the storm period, u and v were close to zero in both L1 and L2. As for the skewness, Sk slightly increased in L1 during the storm as its maximum value reached to ~0.25 at t = 26 while Sk~0 before and after the storm period. In L2, Sk sharply increased to ~0.5 just before the storm at t = 25–26. During the storm period, however, it became negative as it ranged between 0.1 − and 0.2 at t = 26–29. Therefore, the pattern of positive skewness in L1 and negative skewness in L2 − observed in the first storm (t = 3–5) repeated in the third storm even though its magnitude was lower. Except for the storm period, Sk was remained close to zero in L1 but it was dispersed around zero in L2, increasing its magnitude, as also shown in Figure4. The dispersion in L1 outside the storm period was more clearly observed in the wave asymmetry. During the storm period, As was close to zero in both L1 and L2, which was similarly observed during the first storm (t = 3–6 in Figure4). Except for the storm, however, As was strongly dispersed and its magnitude increased in L2 while it remained close to zero in L1. The characteristic pattern of As is also clearly observed in Exp#2 as shown in Figure6 in which the five hydrodynamic parameters are compared for T3 (December 21–28, 2018). In this time, a period of high waves when Hs reached ~2 m was observed at t = 2–3 (Figure6a). Correspondingly, Vmag increased to reach ~0.5 m/s in both L3 and L4. In case of currents, however, difference was found between L3 and L4 as strong cross-shore and longshore currents were observed at t = 2–3 in L4 while their magnitude was significantly smaller in L3. During the high wave period, the positive/negative Sk in the outer/inner measurement location that was observed in Exp#1 was not detected, but the stronger scattering of Sk in L4, the shallower location closer to the shore, was repeated. As for wave asymmetry, As was significantly reduced during the high wave period in both L3 and L4 as As ~ 0. However, it increased with strong dispersion around zero at other times, as also observed in Exp#1.

3.2. Shoreline Positions Measured by VMS The shoreline changes measured by VMS are analyzed based on the hydrodynamic measurements. Figure7 shows the shorelines measured on four di fferent times around Exp#1, namely 19 December 2016; 29 December 2016; 10 January 2017; 19 January 2017. The shore was retreated between 19 December 2016 and 29 December 2016 in the majority of the sectors along the beach. This data can be compared with the hydrodynamic data in Figure4 (t = – 1–9) in which two severe storms attacked the beach with strong nearshore currents and high wave nonlinearity, indicating that destructive forces might be dominant. However, there were locations where the shoreline was advanced. Specifically, the shoreline in the middle of the beach was significantly advanced during the storm. Comparing the satellite image in Figure3, this location corresponded to the protruded area connected to the horn of the crescentic sandbar. Therefore, the shoreline accretion can be interpreted as the wave energy was reduced over the shallow horn area due to enhanced wave breaking while the wave energy at other areas was relatively higher and the sediments were transported to be cumulated in the horn area. J. Mar. Sci. Eng. 2020, 8, x FOR PEER REVIEW 11 of 18

However, the northern part of the protruded area (left side in the figure) was eroded while the other side of it was advanced, which was likely related to the oblique wave incidence during t = 12–17 as shown in Figure 4b. The shorelines measured at January 10 and 19, 2017 shows the shoreline change pattern corresponding to the period of T2 of Exp#1. Interestingly, the shoreline was generally advanced in most of the sectors along the shore. The accretion of the shoreline in this period could not be understood considering the high wave conditions at t = 26–29 was considered (Figure 5). It may be related to the abnormally strong onshore currents observed in L2 at t = 26–29 (Figure 5b). However, the hydrodynamic condition in this period was similar to that observed at t = 3–6 when the storm waves attacked the shore, but the response of shoreline was opposite as it was advanced at t = 26–29J. Mar. Sci.while Eng. it2020 was, 8 ,retreated 690 at t = 3–6, which may require further investigation. 11 of 18

Figure 7. Comparison of shoreline positions in Hujeong Beach measured by VMS between 19 December Figure 7. Comparison of shoreline positions in Hujeong Beach measured by VMS between 19 2016, 29 December 2016, 10 January 2017 and 19 January 2017 for Exp#1. The google map shows the December 2016, 29 December 2016, 10 January 2017 and 19 January 2017 for Exp#1. The google map corresponding locations of the retreat/accretion areas along the beach. shows the corresponding locations of the retreat/accretion areas along the beach. Figure7 also shows the shorelines measured by VMS at 29 December 2016 and 10 January 2017. ThisThe period shoreline corresponds change to observed the time by at tVMS= 9–18 in inExp# Figure2 is 4shown when in the Figure wave energy8 where became the shoreline much positionslower without are compared storm event. between The shoreline 20 December change 2018 also and shows 02 January no clear 2019 pattern as ofit corresponds retreat or accretion. to the periodHowever, in Figure the northern 6. It should part of be the noted protruded that th areae shoreline (left side feature in the figure) was clearly was eroded different while from the those other observedside of it in was Exp#1, advanced, which whichindicates was that likely the relatedshoreline to had the obliquebeen actively wave changed incidence during during the t =~1-year12–17 periodas shown between in Figure the 4twob. Thefield shorelinesexperiments. measured It is also at interesting January 10 to and find 19, out 2017 that showsthe curved theshoreline shoreline atchange 20 December pattern corresponding2018 became flattened to the period at 2 January of T2 of Exp#1.2019 as Interestingly,the protruded the areas shoreline were waseroded generally while the caved areas were filled with the eroded sediments. Specifically, the eroded sediments moved advanced in most of the sectors along the shore. The accretion of the shoreline in this period could south to fill the caved areas, which was likely due to the obliquity of the incident waves as it can be not be understood considering the high wave conditions at t = 26–29 was considered (Figure5). presumed from the wave direction in the corresponding period (Figure 6b). It may be related to the abnormally strong onshore currents observed in L2 at t = 26–29 (Figure5b). However, the hydrodynamic condition in this period was similar to that observed at t = 3–6 when the storm waves attacked the shore, but the response of shoreline was opposite as it was advanced at t = 26–29 while it was retreated at t = 3–6, which may require further investigation. The shoreline change observed by VMS in Exp#2 is shown in Figure8 where the shoreline positions are compared between 20 December 2018 and 02 January 2019 as it corresponds to the period in Figure6. It should be noted that the shoreline feature was clearly di fferent from those observed in Exp#1, which indicates that the shoreline had been actively changed during the ~1-year period between the two field experiments. It is also interesting to find out that the curved shoreline at 20 December 2018 became flattened at 2 January 2019 as the protruded areas were eroded while the caved areas were filled with the eroded sediments. Specifically, the eroded sediments moved south to fill the caved areas, which was likely due to the obliquity of the incident waves as it can be presumed from the wave direction in the corresponding period (Figure6b). J. Mar. Sci. Eng. 2020, 8, 690 12 of 18 J. Mar. Sci. Eng. 2020, 8, x FOR PEER REVIEW 12 of 18

Figure 8. Comparison of shoreline positions in Hujeong Beach measured by VMS between 20 December Figure 8. Comparison of shoreline positions in Hujeong Beach measured by VMS between 20 2018, 2 January 2019 for Exp#2. The google map shows the corresponding locations of the retreat/accretion December 2018, 2 January 2019 for Exp#2. The google map shows the corresponding locations of the areas along the beach. retreat/accretion areas along the beach. 3.3. Seabed Movement Detected by Satellite Images 3.3. Seabed Movement Detected by Satellite Images The Sentinel-II data in Figure3 were plotted in RGB colors. In order to enhance the visibility of the underwaterThe Sentinel-II crescentic data sandbars, in Figure the 3 image were wasplotted processed in RGB by colors. applying In order the algorithm to enhance developed the visibility in [21 of] bythe which underwater the position crescentic of nearshore sandbars, sandbar the image crests wa wass processed extracted by from applying Sentinel-II the images.algorithm In developed this study, thein [21] same by algorithm which the was position applied of fornearshore the detection sandba ofr sandbarcrests was positions. extracted In from this approach, Sentinel-II calibrations images. In basedthis study, on in-situ the same measurements algorithm was were applied not necessary for the detection to detect theof sandbar positions positions. of underwater In this approach, sandbars. Incalibrations addition, correctionsbased on in-situ of absolute measurements values between were no ditff necessaryerent satellite to detect images the that positions might of have underwater different reflectancesandbars. In were addition, not necessary corrections either of becauseabsolute the values purpose between was todifferent extract thesatellite shape images of response that might over underwaterhave different profiles reflectance perpendicular were not to necessary the shoreline. either because the purpose was to extract the shape of responseThe readers over underwater are referred profiles to [21] perpendicular for the details ofto thethe sandbarshoreline. extraction algorithm from Sentinel-II images,The and readers it is only are brieflyreferred summarized to [21] for the here. details The firstof the step sandbar was to extraction extract the algorithm shoreline usingfrom Sentinel- a simple thresholdII images, applied and it is to only the short-wavebriefly summarized infrared (SWIR)here. The band first because step was the to spectral extract responsethe shoreline of the using water a insimple the SWIR threshold domain applied is almost to the equal short-wave to zero ininfrared low to (SWIR) moderate band turbid because waters the from spectral the resamplingresponse of domainthe water of 10in mthe spatial SWIRresolution. domain is Then,almost a newequal raster, to zerora, wasin low defined to moderate by multiplying turbid allwaters visible from bands the inresampling order to augment domain of the 10 increases m spatial inresolution. the spectral Then, response a new raster, over sandbars, 𝑟, was defined such that by rmultiplyinga = br bg allb ∗ ∗ b wherevisibleb bandsr, bg, and in orderbb represent to augment the bands the increases of red, greenin the andspectral blue response respectively. over Oncesandbars,ra distribution such that was𝑟 = calculated,𝑏 ∗𝑏 ∗𝑏a where network 𝑏 of, 𝑏 profiles, and perpendicular𝑏 represent the to thebands shoreline of red, is green created. and The blue profiles respectively. started fromOnce the 𝑟 estimateddistribution shoreline, was calculated, and the distance a network between of profiles two adjacent perpendicular profiles wasto the set shoreline to 10 m, which is created. used totalThe 210profiles profiles started in this from study. the estimated Along each shoreline, profile, anand exponential the distance model, betweeny = twoA adjacente(B x) + C profiles, was fit was to the set ∗ ∗ profileto 10 m, where which coe usedfficients totalA ,210B, andprofilesC were in this computed study. forAlong each each profile. profile, After an that, exponential normalization model, of they= profile𝐴∗𝑒(∗ was) +𝐶 performed, was fit to by the subtracting profile where the exponentialcoefficients model𝐴, 𝐵, and from 𝐶 the were original computed profile. for The each shape profile. of sandbarAfter that, was normalization then extracted of alongthe profile the profile was performed using moving by subtracting window. the exponential model from the originalFigure profile.9 shows The the shape converted of sandbar Sentinel-II was then image extracted of ra on along 11 December the profile 2016. using In themoving water, window. the white dots denoteFigure the9 shows locations the converted of the crest Sentinel-II of sandbars image as they of 𝑟 were on selected11 December along 2016. each profile,In the water, and they the generallywhite dots correspond denote the to locations the positions of the ofcrest sandbars of sand expressedbars as they by were the ra selecteddistribution. along It each shows profile, that fiveand crescenticthey generally sandbars correspond of similar to sizethe positions were developed of sandbars along expressed the shore inbythe the shallow 𝑟 distribution. nearshore It areashows of thethat beach five crescentic at depth of sandbars 3–5 m (the of similar depths size of bars were were developed observed along from the the shore field measurements,in the shallow nearshore not from satellitearea of the images). beach at In depth the southeast of 3–5 m part(the ofdepths the beach, of bars sandbars were observed could befrom hardly the field formed measurements, due to the not from satellite images). In the southeast part of the beach, sandbars could be hardly formed due to the existence underwater rocks. The horns of the bars (area where the bar is peaked toward the land) extended to the land as they were connected to the shore, on which the waves were breaking.

J. Mar. Sci. Eng. 2020, 8, 690 13 of 18 existence underwater rocks. The horns of the bars (area where the bar is peaked toward the land)

J.extended Mar. Sci. Eng. to the2020 land, 8, x FOR asthey PEERwere REVIEW connected to the shore, on which the waves were breaking. 13 of 18

FigureFigure 9. ConvertedConverted Sentinel-II image of rater r𝑟a==𝑏br ×𝑏bg ×𝑏b on on 11 11 December December 2016 2016 where wherebr, b𝑏g,and 𝑏 × × b andbb represent 𝑏 represent the bands the bands of red, of greenred, green and blueand blue respectively. respectively. The The black black dots dots in the in seathe sea area area denote denote the thelocations locations of crescentic of crescentic sandbar sandbar crest crest extracted extracted following following the the algorithm algorithm by [by21]. [21].

TheThe image image in in Figure 99 waswas takentaken onon 1111 DecemberDecember 2016,2016, ninenine daysdays beforebefore thethe fieldfield experimentexperiment startedstarted on on 20 20 December December 2016. 2016. Although Although the the Sentinel-II Sentinel-II images images are are available available for for interval interval of of 5–10 5–10 days, days, thethe sandbar sandbar data data in in Hujeong Hujeong Beach Beach were were available available on on clear clear days days only only when when the the visible visible light light could could go go throughthrough the the water water column column to to detect detect the the seabed seabed topo topography.graphy. For For this this reason, reason, the the next next Sentinel-II Sentinel-II image image availableavailable in this this site site was was measured measured on on 31 31 December December 2016, 2016, after after the the attacks attacks of of the the two two previous previous storms. storms. The third Sentinel-II image available in the site site wa wass on on 31 31 January January 2017. 2017. Applying Applying the the same same algorithm, algorithm, thethe sandbar sandbar crest crest positions were extracted from the latter two images. FigureFigure 1010 compares the locations of sandbar crest extracted following the the algorithm algorithm by by [21] [21] betweenbetween the the three three Sentinel-II Sentinel-II images images taken taken on on 11 11 De Decembercember (red (red dots), dots), 31 31 December December 2016 2016 (blue (blue dots), dots), andand 31 31 January January 2017 2017 (green (green dots). dots). The The bar bar crest crest locati locationsons of December of December 11 and 11 31 and show 31 show that some that someparts ofparts sandbars of sandbars had moved had movedoffshore o ffforshore maximum for maximum 70 m, which 70 m, indicates which indicatesthe offshore the sediment offshore transport sediment astransport it might as be it caused might be by caused the high by thestorm high waves storm th wavesat attacked that attacked the area the on area23–25 on December 23–25 December and 28–29 and December28–29 December 2016. 2016.The offshore The offshore movement movement of the of thesand sandbarsbars corresponds corresponds to tothe the results results in in the the previous previous studystudy [19] [19] that that reported reported a a severe severe seabed seabed erosion erosion in in L1 L1 during during the the storm storm pe periodriod on on 23–25 23–25 December. December. ItIt is is also closely related related to the hydrodynamic conditions conditions in in Figure Figure 44 asas itit showsshows thatthat thethe magnitudemagnitude ofof wave skewness and asymmetry increased during the two storm periods. This This indicates indicates that that the waves were likely breaking in L2 during the storms and the destructive forces such as undertow currentscurrents could could become become stronger stronger to to migrate the sand sandbarsbars offshore. offshore. Once the wave condition became mildermilder after after the the severe severe storms, storms, th thee movement movement of the the seabed seabed contours contours was reduced. reduced. The The sandbar sandbar crests crests measuredmeasured on 3030 JanuaryJanuary 20172017 shows shows no no clear clear di differencefference with with that that on on 31 December31 December 2016, 2016, indicating indicating that thatthe seabedthe seabed became became stable stable without without severe deformationsevere deformation though though high wave high conditions wave conditions were observed were observedduring the during period. the period. InIn Figure Figure 11,11, the the sandbar sandbar crest crest positions positions are are co comparedmpared between the Sentinel-II images taken on on twotwo days,days, 2626 November November 2018 2018 (blue (blue lines), lines), 26 December 26 December 2018 (red2018 lines) (red by lines) applying by applying the same algorithm.the same algorithm.The two times The two were times chosen were at chosen the dates at the when dates the when Sentinel-II the Sentinel-II images images were available were available around around Exp#2. Exp#2.The figure The showsfigure that,shows though that, though there was there a one-monthwas a one-month time gap time between gap between the two the satellite two satellite images, images,the locations the locations of seabed of contours seabed werecontours similar were indicating similar thatindicating the seabed that morphologythe seabed morphology was stable during was stablethe period, during regardless the period, of theregardless high wave of the conditions high wave observed conditions in Figure observed6. in Figure 6.

J. Mar. Sci. Eng. 2020, 8, 690 14 of 18 J. Mar. Sci. Eng. 2020, 8, x FOR PEER REVIEW 14 of 18 J. Mar. Sci. Eng. 2020, 8, x FOR PEER REVIEW 14 of 18

Figure 10.10. ComparisonComparison of of crescentic crescentic sandbar sandbar crest crest positions positions between between the Sentinel-II the Sentinel-II images on images 11 December on 11 Figure 10. Comparison of crescentic sandbar crest positions between the Sentinel-II images on 11 2016December (red dots 2016), ( 31red December dots), 31 December 2016 (blue 2016 dots )(blue and 30dots January) and 30 2017 January (green 2017 dots (green) extracted dots) usingextracted the December 2016 (red dots), 31 December 2016 (blue dots) and 30 January 2017 (green dots) extracted algorithmusing the algorithm by [21]. It by shows [21]. that, It shows in most that, parts in most of the parts sandbars, of the thesandbars, crests movedthe crests oﬀ shoremoved for offshore maximum for using the algorithm by [21]. It shows that, in most parts of the sandbars, the crests moved offshore for 70maximum m for 20 70 days m for between 20 days 11 between December 11 2016December and 31 2016 December and 31 December 2016. Since 2016. then, Since the barthen, positions the bar maximum 70 m for 20 days between 11 December 2016 and 31 December 2016. Since then, the bar becamepositions stable became without stable showing without severe showing cross-shore severe movementcross-shore until movement 30 January until 2017. 30 January The data 2017. were The not positions became stable without showing severe cross-shore movement until 30 January 2017. The estimateddata were atnot the estimated proﬁles whereat the profiles the peak where was not the detected peak was by not the detected algorithm. by the algorithm. data were not estimated at the profiles where the peak was not detected by the algorithm.

Figure 11. Comparison of crescentic sandbar crest positions between the Sentinel-II images on November 26, Figure 11. Comparison of crescentic sandbar crest positions between the Sentinel-II images on 2018Figure (blue 11. dots Comparison) and December of crescentic 26, 2018 (redsandbar dots ),crest extracted positions using between the algorithm the Sentinel-II by [21]. The images sandbar on November 26, 2018 (blue dots) and December 26, 2018 (red dots), extracted using the algorithm by crestNovember positions 26, showed2018 (blue no dots clear) diandfference December between 26, 2018 the three (red datesdots), exceptextracted some using parts, the indicating algorithm the by [21]. The sandbar crest positions showed no clear difference between the three dates except some seabed[21]. The morphology sandbar crest was positions stable during showed the period.no clear The difference data were between not estimated the three at dates the profiles except where some parts, indicating the seabed morphology was stable during the period. The data were not estimated theparts, peak indicating was not detectedthe seabed by morphology the algorithm. was stable during the period. The data were not estimated at the profiles where the peak was not detected by the algorithm. at the profiles where the peak was not detected by the algorithm. 4. Discussion 4. Discussion 4. DiscussionOne of the most significant findings in this study was that, under high wave conditions, the Sk was reversedOne of the between most significant the two stationsfindings locatedin this study at diff waserent that, water under depths. high wave It was conditions, clearly observed the 𝑆 One of the most significant findings in this study was that, under high wave conditions, the 𝑆 was reversed between the two stations located at different water depths. It was clearly observed duringwas reversed 24–26 Decemberbetween the 2016 two (t =stations4–6 for located Exp#1 inat Figuredifferent6) when water the depths. storm It wave was attackedclearly observed the site during 24–26 December 2016 (t = 4–6 for Exp#1 in Figure 6) when the storm wave attacked the site withduring maximum 24–26 DecemberHs of ~4 m. 2016 In this(t = period,4–6 for SExp#1k in L1 in increased Figure 6) to when become the positivestorm wave while attacked it in L2 becamethe site negative.with maximum The positive 𝐻 of /~4negative m. In thisSk in period, L1/L2 was𝑆 in observed L1 increased for longer to become period positive but with while lower it wavein L2 with maximum 𝐻 of ~4 m. In this period, 𝑆 in L1 increased to become positive while it in L2 heightsbecame (negative.Hs = 2–3 The m) positive/negative during 15–19 January 𝑆 in 2017 L1/L2 (t was= 26–30 observed for Exp#1 for longer in Figure period7). but One with possible lower became negative. The positive/negative 𝑆 in L1/L2 was observed for longer period but with lower explanationwave heights for (𝐻 this = reversed2–3 m) during sign in 15–19Sk between January the 2017 two (t depths= 26–30 can forbe Exp#1 found in inFigure the variation 7). One possible of wave wave heights (𝐻 = 2–3 m) during 15–19 January 2017 (t = 26–30 for Exp#1 in Figure 7). One possible nonlinearityexplanation for of propagatingthis reversed waves. sign in As 𝑆 the between waveshoals the two in especiallydepths can high be found wave energyin the variation conditions, of explanation for this reversed sign in 𝑆 between the two depths can be found in the variation of wave nonlinearity of propagating waves. As the wave shoals in especially high wave energy Swavek would nonlinearity increase as of the propagating shape of surface waves. waves As the become wave sharper. shoals in As especially the waves high further wave propagate energy intoconditions, the surf 𝑆 zone, would the increase high storm as the waves shape would of surface break waves and Sk becomemight change sharper. to As be the negative waves because further conditions, 𝑆 would increase as the shape of surface waves become sharper. As the waves further thepropagate shape ofinto surface the surf waves zone, is the dispersed. high storm The waves changes would in S kbreakalong and the 𝑆 wave might propagation change to maybe negative also be propagate into the surf zone, the high storm waves would break and 𝑆 might change to be negative closelybecause related the shape to the of surface sediment waves motions is dispersed. in the seabed. The changes When Sink increased𝑆 along tothe become wave propagation sharply positive may because the shape of surface waves is dispersed. The changes in 𝑆 along the wave propagation may also be closely related to the sediment motions in the seabed. When 𝑆 increased to become sharply also be closely related to the sediment motions in the seabed. When 𝑆 increased to become sharply positive in L1, the bed shear stress could be also increased to cause seabed erosion, which was positive in L1, the bed shear stress could be also increased to cause seabed erosion, which was observed in the previous study [18]. observed in the previous study [18].

J. Mar. Sci. Eng. 2020, 8, 690 15 of 18 in L1, the bed shear stress could be also increased to cause seabed erosion, which was observed in the previous study [18]. However, the seabed erosion implied from the high waves and the reversed Sk measured at the two different water depths during the storm did not provide any clue to determine the direction of cross-shore sediment transport. As compared in Figures6 and7, the hydrodynamic conditions during the two high wave conditions (t = 4–6 and t = 26–30 of Exp#1) were similar in the pattern of wave skewness as Sk was positive in L1 but negative in L2. In addition, the cross-shore velocity in u showed that strong onshore currents were observed during both of the storm periods. However, the shoreline positions measured by VMS showed opposite pattern as it was generally retreated at t = 4–6 while it was advanced to the sea at t = 26–30. The reason for this discrepancy cannot be clearly understood based on the data available in this study. In fact, the seabed features detected by the satellite images confirmed the shoreline retreat at t = 4–6 because the crescentic sandbars moved offshore in the corresponding period. However, the shoreline accretion at t = 26–30 was not supported by the seabed data from satellite images, and thus the shoreline accretion at this time might not be directly contributed by the cross-shore sediment motions and further investigation may be required to analyze the direction of transport. Although the wave skewness showed a pattern of significant changes in the waves that propagated into the surf zone under the two storm wave conditions, it was not observed at other high waves, which indicates that there might be other controlling factors that were not clarified in the present study. In addition, the wave asymmetry, another parameter for wave nonlinearity, did not show expected pattern by which, under storm wave conditions, As would increase as the waves propagated into the surf zone. However, its magnitude was reduced close to zero under high wave conditions in both deep and shallow locations. Instead, As was scattered with higher magnitude under mild wave conditions, especially when measured in shallower depths. The discrepancy in the wave nonlinearity between As and Sk could not be clearly understood in the present study, and it is suggested to inspect their relationship closely with additional data sets not only not only from this site but also from other sites with similar environment. However, there is a possibility that the high dispersion of As could be contributed by the wider wave spectra in shallow water depths. When wave height became low under mild wave conditions, the wave measurement in shallow depths could be contaminated by the low flow velocities. As described in Tables1 and2, the wave parameters were measured by ADCP and Signature in the deeper locations (L1 and L3) by shooting the soundwaves upward from the bottom, and the data were measured near the water surface. In the shallower locations (L2 and L4), the waves were measured by Acoustic Doppler Velocimeter (ADV) and the flow velocities were measured near the seabed so that their magnitude might be too small to accurately calculate the wave parameters. For example, the wave directions measured by same instruments show higher dispersion as well in the case of L2 and L4, which could be induced from the low flow velocities that might contaminate the accuracy of wave data. Another discussion on the hydrodynamic measurement is the short period of data acquisition in Exp#2 due to burial of instruments at L4. It was unfortunate because the majority of data in Exp#2 could not be used in this study. Instead, it could be useful if the reason for the burial was analyzed based on the data available from the experiment. As shown in Figure5, the instruments were buried in the beginning stage of storm wave period that had maximum wave height of ~2m, which was not extraordinary compared to the storm waves in Exp#1. However, one clue for the burial can be found from the shoreline changes measured by VMS in Figure8 in which the shoreline positions compared for a period that contained the moment of instrument burial. As previously analyzed, the shoreline was flattened during the period mainly due to longshore sediment transport from NW, which was also confirmed from the hydrodynamic measurement in Figure6c where strong longshore current was observed just before the time of burial. Therefore, it was likely that the instruments in L4 was buried by the sediments that were carried alongshore, not by the sediments carried from the shore. J. Mar. Sci. Eng. 2020, 8, 690 16 of 18

One of the advantages of the present study is highlighted by the application of different sets of data available in the site. In addition to the hydrodynamic measurements at different water depths and at different times, the VMS data were useful to support the analysis. The hydrodynamic data alone could not understand the coastal process in general especially during the storm periods. The shoreline changes in the corresponding period could confirm the analysis of hydrodynamic data and thus prevent possible misinterpretation. Recently, the VMS techniques have been developed to various application in coastal areas. For example, it could be used to estimate breaking wave heights [28,29], to distinguish wave transformation domains [30], and to monitor shoreline response to nourishment [31]. These methods could be applied for the analysis of the VMS in the present experiment to extend the understanding of coastal processes in Hujeong Beach, and are thus suggested for future studies. The satellite images were also effective to detect the significant changes of the bathymetry in shallow nearshore areas. Specifically, the Sentinel-II images applied in this study were useful for this type of analysis because of their relatively high spatial resolution and frequent orbital cycle. By applying the algorithm developed by [21] to extract the sandbar crest positions, it showed that the sandbars generally moved offshore for about 20–30 m with maximum 70 m during the period between December 11 and 31, 2016. This corresponds to the results by VMS data that shows the shoreline positions was also generally retreated for ~20 m during the corresponding period. The successful analysis of satellite data in the present study provides insights for the future application of the freely available remote sensing data for various purposes in coastal studies. The satellite images used in this study were taken in times when the wave condition was mild and the wave breaking heights were similar in all dates.

5. Conclusions The hydrodynamics and wave nonlinearity of a field site were examined using the data sets measured at two different water depths and at two different times. Two experiments were performed to observe the changes of wave properties during the course of propagation into the surf zone, especially in storm periods, by mooring acoustic instrument for a couple of months. In addition to the hydrodynamic measurements, the video monitoring data that had recorded shoreline change information and satellite images were employed to support the analyses. The video monitoring data were measured by cameras on top of a 30-m high tower to extract the shoreline positions in the swash zone. The Sentinel-II satellite images, freely available, were useful to detect the changes in nearshore bathymetry on clear days because the satellite has high spatial resolution (~10 m) and frequent revisit cycle (~5 days). The results showed that there were two storm periods (23–30 December 2016 and 15–19 January 2017) in which the maximum wave heights were higher than 2 m. The two cases had similar hydrodynamic conditions as strong onshore currents were observed at only shallower observational location during the storm periods. Specifically, in both storms, the wave skewness was reversed as the waves propagated because the skewness in deeper locations increased to become positive, but it decreased to become negative in the shallower locations, which indicates that the shoaling waves were broken as they propagated into the surf zone. In spite of the similarity in hydrodynamic conditions, the response of shoreline to these storm waves was different. In the period of the first storm, the shoreline was generally retreated. The erosional process was confirmed by the satellite data showing that the seabed was also moved offshore in the corresponding period. In the second storm period, however, the shoreline position was advanced to the sea. The similarity of hydrodynamic conditions but opposing pattern of shoreline responses in the two storms are not clearly understood based on the observational data available in the present study. One possible explanation can be found in the higher wave height in the first storm as its maximum wave height reached ~4 m, while it was less than 3 m for the second storm. In addition, the duration with high waves was longer for the first storm (~7 days), which likely enhanced the role destructive force supporting the erosion. J. Mar. Sci. Eng. 2020, 8, 690 17 of 18

Meanwhile, the wave skewness was signiﬁcantly changed in time and space. The wave asymmetry, another parameter for wave nonlinearity, did not show any special pattern, even during the storm, which requires further investigation in future studies.

Author Contributions: Conceptualization, J.D.D., J.-Y.J. and Y.S.C.; methodology, J.D.D., J.-Y.J. and B.L.; validation, W.M.J. and H.K.H.; investigation, J.D.D., B.L. and Y.S.C.; resources, J.D.D. and J.-Y.J.; data curation, J.D.D., B.L. and Y.S.C.; writing—original draft preparation, J.D.D. and Y.S.C.; writing—review and editing, J.-Y.J., Y.S.C., W.M.J. and H.K.H.; visualization, J.D.D. and B.L.; supervision, J.-Y.J., W.M.J. and H.K.H.; project administration, J.D.D. and Y.S.C.; funding acquisition, Y.S.C. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by Korea Institute of Ocean Science and Technology, grant number PE99831. H.K.H. was supported by Inha University Research Grant. Conﬂicts of Interest: The authors declare no conﬂict of interest.

References

1. Hoefel, F.; Elgar, S. Wave-induced sediment transport and sandbar migration. Science 2003, 299, 1885–1887. [CrossRef][PubMed] 2. Davidson, R.-A. Introduction to Coastal Processes and Geomorphology; Cambridge University Press: Cambridge, UK, 2014; pp. 194–199. 3. Hsu, T.J.; Hanes, D.M. Effects of wave shape on sheet flow sediment transport. J. Geophys. Res. Oceans 2004, 109. [CrossRef] 4. Elfrink, B.; Hanes, D.M.; Ruessink, B. Parameterization and simulation of near bed orbital velocities under irregular waves in shallow water. Coast. Eng. 2006, 53, 915–927. [CrossRef] 5. Sato, S. Sheetflow Sediment Transport Under Skewed-Asymmetric Waves and Currents. Coast. Eng. Proc. 2012, 1, 50. 6. Walstra, D.J.R.; van Rijn, L.C.; van Ormondt, M.; Brière, C.; Talmon, A.M. The Effects of Bed Slope and Wave Skewness on Sediment Transport and Morphology. Coast. Sedim. 2007, 1, 137–150. 7. Filipot, J.-F. Investigation of the bottom-slope dependence of the nonlinear wave evolution toward breaking using SWASH. J. Coast. Res. 2016, 32, 1504–1507. 8. Chella, M.A.; Bihs, H.; Myrhaug, D. Characteristics and profile asymmetry properties of waves breaking over an impermeable submerged reef. Coast. Eng. 2015, 100, 26–36. [CrossRef] 9. Abreu, T.; Michallet, H.; Silva, P.A.; Sancho, F.; van der A, D.A.; Ruessink, B.G. Bed shear stress under skewed and asymmetric oscillatory flows. Coast. Eng. 2013, 73, 1–10. [CrossRef] 10. Abreu, T.; Sancho, F.; Silva, P. Bottom Shear Stress Formulations to Compute Sediment Fluxes in Accelerated Skewed Waves. J. Coast. Res. 2009, 1, 453–457. 11. Gonzalez-Rodriguez, D.; Madsen, O.S. Seabed shear stress and bedload transport due to asymmetric and skewed waves. Coast. Eng. 2007, 54, 914–929. [CrossRef] 12. Elgar, S.; Guza, R.T. Observations of Bispectra of Shoaling Surface Gravity-Waves. J. Fluid Mech. 1985, 161, 425–448. [CrossRef] 13. Doering, J.; Bowen, A. Parametrization of orbital velocity asymmetries of shoaling and breaking waves using bispectral analysis. Coast. Eng. 1995, 26, 15–33. [CrossRef] 14. Elgar, S.; Guza, R.T.; Freilich, M.H. Eulerian Measurements of Horizontal Accelerations in Shoaling Gravity-Waves. J. Geophys. Res. Oceans 1988, 93, 9261–9269. [CrossRef] 15. Crawford, A.M.; Hay, A.E. Linear transition ripple migration and wave orbital velocity skewness: Observations. J. Geophys. Res. Oceans 2001, 106, 14113–14128. [CrossRef] 16. Crawford, A.M.; Hay, A.E. Wave orbital velocity skewness and linear transition ripple migration: Comparison with weakly nonlinear theory. J. Geophys. Res. Oceans 2003, 108, 361–366. [CrossRef] 17. Stansell, P.; Wolfram, J.; Zachary, S. Horizontal asymmetry and steepness distributions for wind-driven ocean waves from severe storms. Appl. Ocean Res. 2003, 25, 137–155. [CrossRef] 18. Poate, T.; Masselink, G.; Austin, M.J.; Dickson, M.; McCall, R. The role of bed roughness in wave transformation across sloping rock shore platforms. J. Geophys. Res. Earth Surf. 2018, 123, 97–123. [CrossRef] 19. Do, J.D.; Jin, J.Y.; Jeong, W.M.; Chang, Y.S. Observation of Rapid Seabed Erosion Near Closure Depth During a Storm Period at Hujeong Beach, South Korea. Geophys. Res. Lett. 2019, 46, 9804–9812. [CrossRef] J. Mar. Sci. Eng. 2020, 8, 690 18 of 18

20. Chang, Y.S.; Jin, J.-Y.; Jeong, W.M.; Kim, C.H.; Do, J.D. Video Monitoring of Shoreline Positions in Hujeong Beach, Korea. Appl. Sci. 2019, 9, 4984. [CrossRef] 21. Tătui, F.; Constantin, S. Nearshore sandbars crest position dynamics analysed based on Earth Observation data. Remote Sens. Environ. 2020, 237, 111555. [CrossRef] 22. Abreu, T.A.M.d.A. Coastal Sediment Dynamics under Asymmetric Waves and Currents: Measurements and Simulations. Ph.D. Thesis, University of Coimbra, Coimbra, Portugal, 2011. 23. Splinter, K.D.; Harley, M.D.; Turner, I.L. Remote sensing is changing our view of the coast: insights from 40 years of monitoring at Narrabeen-Collaroy, Australia. Remote Sens. 2018, 10, 1744. [CrossRef] 24. Andriolo, U.; Sánchez-García, E.; Tarborda, R. Operational use of surfcam online streaming images for coastal morphodynamic studies. Remote Sens. 2019, 11, 78. [CrossRef] 25. Drusch, M.; Del Bello, U.; Carlier, S.; Colin, O.; Fernandez, V.; Gascon, F.; Hoersch, B.; Isola, C.; Laberinti, P.; Martimort, P.Sentinel-2: ESA’s optical high-resolution mission for GMES operational services. Remote Sens. Environ. 2012, 120, 25–36. [CrossRef] 26. Price, T.D.; Ruessink, B.G. State dynamics of double sandbar system. Cont. Shelf Res. 2011, 31, 659–674. [CrossRef] 27. Babanin, A.V.; Chalikov, D.; Young, I.; Savelyev, I. Numerical and laboratory investigation of breaking of steep two-dimensional waves in deep water. J. Fluid Mech. 2010, 644, 433–463. [CrossRef] 28. Almar, R.; Cienfuegos, R.; Cantalán, P.A.; Michallet, H.; Castelle, B.; Bonneton, P.; Marieu, V. A new breaking wave height direct estimator from video imagery. Coast. Eng. 2012, 61, 42–48. [CrossRef] 29. Andriolo, U.; Mendes, D.; Tarborda, R. Breaking wave height estimation from Timex images: two methods for coastal video monitoring systems. Remote Sens. 2020, 12, 204. [CrossRef] 30. Andriolo, U. Nearshore wave transformation domains from video imagery. J. Mar. Sci. Eng. 2019, 7, 186. [CrossRef] 31. Santos, C.J.; Andriolo, U.; Ferreira, J. Shoreline response to a sandy nourishment in a wave-dominated coast using video monitoring. Water 2020, 12, 1632. [CrossRef]

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