# Experimental Observation on Beach Evolution Process with Presence of Artificial Submerged Sand Bar and Reef

^{1}

^{2}

^{3}

^{*}

## Abstract

**:**

## 1. Introduction

## 2. Method

#### 2.1. Experimental Design and Instrumentation

^{3}with grain size ranging from 0.15 to 0.18 mm, which maintained the similitude of the hydrodynamic and sediment process by satisfying the Froude number, the Shields number, and the Rouse number under the geometric scale factor of 10 (prototype/model). The details of the scaling calculations can be found in [75].

#### 2.2. Data Analysis

#### 2.2.1. Hydrodynamics

_{s_long}for wave energy in the low-frequency band (0.004–0.05 Hz, 20–250 s) [77] was calculated using the same method as for H

_{s}with the frequency domain scaled down to the model scale, corresponding to 0.01–0.15 Hz (6.67–100 s).

_{w}) and roller-induced (Q

_{r}) mass flux [80]:

_{0}is the water depth at rest, c is the wave speed, ${\rho}_{r}$ is the density of the fluid in the aerated roller taken as a constant 650 kg/m

^{3}, A

_{r}is the roller area, and T

_{p}is the peak period. Equation (4) is used to estimate Q

_{w}based on the assumption that the orbital velocity does not vary vertically. The roller area is given by A

_{r}= 0.9H

^{2}, where H is the local wave height [82]. The growth of $\overline{u}$ is hereinafter referred to as the growth in its absolute value.

_{w}is the bottom orbital velocity of wave, and f

_{w}is the wave friction coefficient calculated by the method of Soulsby [84], covering the identification of a laminar, smooth turbulent or rough turbulent regime.

_{p}is used for T here. k

_{s}is the Nikuradse equivalent sand grain roughness, being 2.5D

_{50}. The Shields numbers at wave gauges calculated by Soulsby method can be verified by the results calculated from ADV measurement.

#### 2.2.2. Profile Morphology

_{bar}(the maximum elevation relative to the initial bed level) with its location at the horizontal coordinate of x

_{bar}. All above location indicators are shown in Figure 3.

#### 2.2.3. Sediment Transport

_{s}is the instantaneous sediment transport rate, z is the bottom elevation at the cross-shore position x, and p is the sediment bed porosity, assumed to be loosely packed and homogeneous along the beach profile (p = 0.4 used here). The total transport rate at x = 0 is set to be zero. Therefore, the $\overline{{q}_{s}}$ at a given cross-shore location x during a wave climate duration $\mathsf{\Delta}t$ can be obtained by the discrete version of Equation (10) with the measured bed level changes ($\mathsf{\Delta}{z}_{b}$):

## 3. Results

#### 3.1. Hydrodynamics

_{s}, long wave height H

_{s_long}), mean water level ($\overline{\eta}$), mass flux (wave skewness Sk, wave asymmetry Asy, and undertow $\overline{u}$) and the total sediment transport rate $\overline{{q}_{s}}$.

_{s}in B-N decreased as the incident waves propagated onshore, despite slight local increases at W2, W7, and W9. The wave energy of the low frequency domain (Figure 4b1) decreased along the propagation, and a large incident wave generated large H

_{s-long}at each wave gauge. The mean water level $\overline{\eta}$ (Figure 4c1) peaked at W11 for all incident waves, while there was another significant growth at W3‒W5 in B-N-J4. Hence, in addition to the main shoaling zone on the beach slope, there were two local areas with a relatively strong shoaling effect for J4 waves and one for J1‒J3. This was also verified by Sk (Figure 4d1), with peaks at the maximum dissipation. The negative Asy (Figure 4e1) with a large absolute value occurred at W2 and W1, representing intensive breaking. Correspondingly, the absolute value of undertow $\overline{u}$ (Figure 4f1) increased with the incident waves. The results of B-N were set as the basis to analyze the relative changes of results in the other profile types as follows.

_{s}(Figure 4a2) and H

_{s-long}(Figure 4b2) on its leeside were decreased, with maximum reductions of 0.05 m (at W5–W11) and 0.02 m (at W1 and W2), respectively. The reduction in wave energy was heightened with the incident wave energy. The shoaling effect was also reduced compared with B-N, and the peak of $\overline{\eta}$ at W11 was preserved only in B-AR-J4 (Figure 4c2). The Sk values at W1 and W2 were reduced under all wave climates (Figure 4d2). In the shoreface part, the Sk value increased at W4‒W9 and decreased at W10‒W13 in B-AR-J1. Then, as the incident wave grew, the wave gauge points turned to have decreased values relative to the corresponding B-N tests. For the cross-shore pattern of Asy (Figure 4e2), reduction in the absolute value at W1 meant weaker wave breaking relative to B-N. In the leeside of AR, $\overline{u}$ was decreased greatly in the range of 0.003–0.025 m/s, and $\overline{u}$ at W13 was increased by 0–0.009 m/s.

_{s}(Figure 4a3) and H

_{s-long}(Figure 4b3) changed slightly, with the changes less than 0.003 m and 0.006 m, respectively, which showed a small growth in the crest and the fore-slope of the ASB. For the waves of J3 and J4, H

_{s}barely changed at W11 and W13 but increased at W9‒W10 (by less than 0.006 m and 0.004 m for J3 and J4, respectively), covering the fore-slope and the fore-part of the crest, and then decreased significantly at W2‒W8 (by 13% and 23% for J3 and J4). Meanwhile, the cross-shore pattern of H

_{s-long}was similar to that in the B-N test but was different on the beach. In particular, H

_{s}and H

_{s-long}at W1 were increased for J2 and J3, with the maximum growth of 0.011 m in H

_{s-long}in B-ASB-J3. On the basis of $\overline{\eta}$, Sk and Asy (Figure 4c3,d3,e3), wave shoaling, breaking, and bottom friction due to the ASB predominated in the wave transformation of J2‒J4. Hence, there were local peaks of Sk and Asy between W6 and W10 covering the ASB, which indicated a stronger energy dissipation area rather than a beach slope. Moreover, $\overline{u}$ was reduced at W11‒W13 and increased around the ASB (Figure 4f3). Beyond that, the ASB decreased $\overline{u}$ in the lee-side in a wider range for larger incident waves.

_{s}(Figure 4a4) and H

_{s-long}(Figure 4b4) ranged between 39% and 50%. The hydrodynamics at W11‒W13 depended on the AR rather than the ASB. Although $\overline{\eta}$ (Figure 4c4) resembled that in B-AR, Sk, Asy and $\overline{u}$ (Figure 4d4,e4,f4) changed in the same trend as those in B-ASB but with smaller absolute values. This was because the incident waves were attenuated by the AR before passing to the ASB, and bottom friction and wave breaking on the ASB further dissipated the wave energy before attack on the beach slope.

#### 3.2. Beach Profile Behavior

#### 3.2.1. Evolution process

#### 3.2.2. Scarp

_{sx}in each time interval was estimated by calculating the first derivative of the scarp location data sx over time t (V

_{sx}= d(sx)/dt). It can be inferred that sx increased with t until V

_{sx}monotonically reduced to zero, corresponding to the equilibrium state with the maximum sx. As a result, a natural exponential function (exp) was applied to capture this process feature, leading to a scarp retreat model consisting of Equations (11) and (12):

_{e}, which was then used to fit the sx data on Equation (12) to obtain parameters P1 and P2.

_{0}$\times $ T

_{e}. Therefore, V

_{0}is revised by P1/T

_{e}in this exponential scarp retreat model. The exponential part exp(−t/T

_{e}) is practically regarded as a non-dimensional indicator for the time-varying feature, and the dimensions of T

_{e}and V

_{0}are time and speed, respectively. When t exceeds T

_{e}, $\mathrm{exp}(-t/{T}_{e})$ is smaller than 0.36. Parameter T

_{e}indicates the time to reach equilibrium under present hydrodynamics, and V

_{0}represents the initial retreat rate. Thus, P2 is the estimation from experimental data on the maximum sx in the equilibrium state, and P1 represents the distance before the scarp location reaches P2, i.e., the difference between the minimum and the maximum of sx. The scarp model lays the foundation for quantifying the morphodynamic influence on the beach erosion process of the offshore artificial reef and submerged sand bar.

_{e}can be interpreted as a quicker way to equilibrium. Comparing the parameter values in B-AR with those in B-N under the same wave, it was found that the AR decreased P2 (by 0.23‒0.82 m), P1 (by 0.07‒0.56 m), and T

_{e}(by 3–32 min), except for the increased T

_{e}under J4. The same comparison was made between B-ASB and B-N, and P1 and P2 were generally reduced by the ASB but less than the AR, except for the increase in B-ASB-J2. In addition, T

_{e}could be increased and decreased by the ASB. The results in B-ASB-AR were similar to those in B-AR, while T

_{e}was smaller than that in B-N. Overall, the AR showed a more significant effect in preventing scarp recession than the ASB, leading to smaller values of P2 and P1. However, there was no definite trend in the variation of T

_{e}, which is discussed with an explanation referring to the beach state.

#### 3.2.3. Breaker Bar

_{bar}), the bar first grows in height (z

_{bar}) until the local elevation is high enough for the occurrence of wave breaking, which eventually turns into a new trough or terrace with the bar location further offshore (decrease in x

_{bar}). In other words, there is a growth limit of bar height z

_{bar}for a specific location x

_{bar}on the beach, which indicates that the breaker bar moves along a certain space trajectory. Hence, this trajectory can be used to estimate the bar height based on its location.

_{50}= 0.25 mm, d

_{10}= 0.154 mm, d

_{90}= 0.372 mm), which covered our target grain size. Hence, we converted the coordinate system as in Eichentopf et al. [87] and generated Equation (15) based on z

_{bar}= −0.05x

_{bar}+ 1.17 to make the comparison.

_{bar}on x

_{bar}(q1) is −0.05, and the correction is −0.28. Under the wave climate with the significant wave height of 0.47 m, the bar height z

_{bar}is 0.22 m at the point of x

_{bar}= −10 m in the Eichentopf experiment, with the local depth of 0.67 m (calculated from a slope of 1/15), which corresponds to the scaled-down value of 0.022 m in our experiment, located at x

_{bar}= −0.64 m (based on Equation (15)) with a depth of 0.064 m (calculated from a slope of 1/10). The ratio of the two water depths basically meets a geometric scale factor of 10. This result also supports the validity of using this light-weight sediment experiment to simulate fine sediment transport.

#### 3.3. Artificial Submerged Sand Bar (ASB)

## 4. Discussion

#### 4.1. Beach Erosion

_{s}, long wave height H

_{s-long,}and mean water level $\overline{\eta}$, other factors used to estimate the wave run-up included deep water wave length L

_{s}, wave steepness H

_{s}/L

_{s}, the products of wave height and length H

_{s}$\times $L

_{s}and the Irribarren number $\xi $ (with values between 0.64 and 0.92 calculated by Equation (16)). For each profile type, the Pearson’s linear correlation coefficients were calculated separately for P1, P2, and T

_{e}in Table 5.

_{s}, H

_{s-long}, $\overline{\eta}$, L

_{s}, and the Irribarren number $\xi $, with coefficients over 0.90 and significance levels above 0.10, which is in line with the widely-used runup model of Stockdon et al. [88]. The coefficients in B-AR show that not only were these correlations enhanced, but also correlations were induced with the wave steepness and the product of the wave height and length. Nevertheless, the ASB basically maintained the correlations in B-N yet removed the influence of $\overline{\eta}$. The coefficients in B-ASB-AR were similar to those in B-ASB, which revealed that the final influence of the combination may be determined by the ASB. In addition, there was no significant correlation confirmed between T

_{e}and any of the hydrodynamic factors. Therefore, it is speculated that the hydrodynamics alone cannot lead to a definite T

_{e}.

#### 4.2. Beach State

_{b}, $\omega $ is the incident wave radian frequency, g is the acceleration of gravity, and $\beta $ is the beach or surf zone slope gradient. H

_{b}is calculated using Equation (18) [91] with the initial beach slope taken into account.

_{e}changed in the same trend as P1 and P2 in the same beach state, i.e., smaller T

_{e}corresponded to smaller P1 and P2, and larger T

_{e}came with larger P1 and P2 under the same type of beach state. Parameter T

_{e}can be seen as a representative of the hydrodynamic and the morphodynamic patterns, which had a real impact on the scarp retreat process by altering the time duration to the equilibrium state. It also indicated that comparison of the T

_{e}values should be confined within the same beach state, which accounted for the decreased P1 and P2 not necessarily corresponding to reduced T

_{e}.

_{e}were found in cases where the beach state changed, such as B-ASB-J3 and B-AR-J2. All three parameters were decreased by the offshore interventions in the other cases. Overall, the offshore interventions prevented scarp retreat by moving the final position seaward and reducing the time duration or, if not, then by turning into milder beach states toward the reflective state.

## 5. Conclusions

## Author Contributions

## Funding

## Conflicts of Interest

## References

- Van Rijn, L.C. Coastal erosion and control. Ocean Coast. Manag.
**2011**, 54, 867–887. [Google Scholar] [CrossRef] - Luijendijk, A.; Hagenaars, G.; Ranasinghe, R.; Baart, F.; Donchyts, G.; Aarninkhof, S. The State of the World’s Beaches. Sci. Rep.
**2018**, 8, 6641. [Google Scholar] [CrossRef] [PubMed] - Campbell, T.J.; Benedet, L. Beach nourishment magnitudes and trends in the US. J. Coast. Res.
**2006**, 39, 57–64. [Google Scholar] - Hanson, H.; Brampton, A.; Capobianco, M.; Dette, H.H.; Hamm, L.; Laustrup, C.; Lechuga, A.; Spanhoff, R. Beach nourishment projects, practices, and objectives—A European overview. Coast. Eng.
**2002**, 47, 81–111. [Google Scholar] [CrossRef] - Dean, R.G. Beach Nourishment: Theory and Practice; World Scientific: Singapore, 2003. [Google Scholar]
- Cooke, B.C.; Jones, A.R.; Goodwin, I.D.; Bishop, M.J. Nourishment practices on Australian sandy beaches: A review. J. Environ. Manag.
**2012**, 113, 319–327. [Google Scholar] [CrossRef] [PubMed] - Luo, S.; Liu, Y.; Jin, R.; Zhang, J.; Wei, W. A guide to coastal management: Benefits and lessons learned of beach nourishment practices in China over the past two decades. Ocean Coast. Manag.
**2016**, 134, 207–215. [Google Scholar] [CrossRef] - Armstrong, S.B.; Lazarus, E.D.; Limber, P.W.; Goldstein, E.B.; Thorpe, C.; Ballinger, R.C. Indications of a positive feedback between coastal development and beach nourishment. Earths Future
**2016**, 4, 626–635. [Google Scholar] [CrossRef] - Armstrong, S.B.; Lazarus, E.D. Masked shoreline erosion at large spatial scales as a collective effect of beach nourishment. Earths Future
**2019**, 7, 74–84. [Google Scholar] [CrossRef] - Hamm, L.; Capobianco, M.; Dette, H.H.; Lechuga, A.; Spanhoff, R.; Stive, M.J.F. A summary of European experience with shore nourishment. Coast. Eng.
**2002**, 47, 237–264. [Google Scholar] [CrossRef] - Van Duin, M.J.P.; Wiersma, N.R.; Walstra, D.J.R.; van Rijn, L.C.; Stive, M.J.F. Nourishing the shoreface: Observations and hindcasting of the Egmond case, The Netherlands. Coast. Eng.
**2004**, 51, 813–837. [Google Scholar] [CrossRef] - Bougdanou, M. Analysis of the Shoreface Nourishments, in the Areas of Ter Heijde, Katwijk and Noordwijk; TU Delft: Delft, The Netherlands, 2007. [Google Scholar]
- Peterson, C.H.; Bishop, M.J. Assessing the environmental impacts of beach nourishment. Bioscience
**2005**, 55, 887–896. [Google Scholar] [CrossRef] [Green Version] - Fenster, M.S.; Knisley, C.B.; Reed, C.T. Habitat preference and the effects of beach nourishment on the federally threatened northeastern beach tiger beetle, cicindela dorsalis dorsalis: Western Shore, Chesapeake Bay, Virginia. J. Coast. Res.
**2006**, 22, 1133–1144. [Google Scholar] [CrossRef] - Baptist, M.J.; Leopold, M.F. The effects of shoreface nourishments on Spisula and scoters in The Netherlands. Mar. Environ. Res.
**2009**, 68, 1–11. [Google Scholar] [CrossRef] [PubMed] - Rippy, M.A.; Franks, P.J.S.; Feddersen, F.; Guza, R.T.; Warrick, J.A. Beach nourishment impacts on bacteriological water quality and phytoplankton bloom dynamics. Environ. Sci. Technol.
**2013**, 47, 6146–6154. [Google Scholar] [CrossRef] [PubMed] [Green Version] - Hilal, A.H.A.; Rasheed, M.Y.; Hihi, E.A.A.; Rousan, S.A.A. Characteristics and potential environmental impacts of sand material from sand dunes and uplifted marine terraces as potential borrow sites for beach nourishment along the Jordanian coast of the Gulf of Aqaba. J. Coast. Conserv.
**2009**, 13, 247–261. [Google Scholar] [CrossRef] - Finkl, C.W.; Benedet, L.; Andrews, J.L.; Suthard, B.; Locker, S.D. Sediment ridges on the west Florida inner continental shelf: Sand resources for beach Nourishment. J. Coast. Res.
**2007**, 231, 143–159. [Google Scholar] [CrossRef] - Wildman, J.C. Laboratory Evaluation of Recycled Crushed Glass Cullet for Use as an Aggregate in Beach Nourishment and Marsh Creation Projects in Southeastern Louisiana. Ph.D. Thesis, University of New Orleans, New Orleans, LA, USA, 2018. [Google Scholar]
- Ishikawa, T.; Uda, T.; San-nami, T.; Hosokawa, J.-I.; Tako, T. Possibility of offshore discharge of sand volume and grain size composition. In Proceedings of the 36th Conference on Coastal Engineering, Baltimore, MD, USA, 30 December 2018; p. 47. [Google Scholar]
- Harris, L.E. Submerged reef structures for beach erosion control. In Proceedings of the Coastal Structures 2003, Portland, OR, USA, 26–30 August 2003; pp. 1155–1163. [Google Scholar]
- Coastal, E. Impact of Sand Retention Structures on Southern and Central California Beaches; Department of Earth and Planetary Sciences: Cambridge, MA, USA, 2002. [Google Scholar]
- Lamberti, A.; Archetti, R.; Kramer, M.; Paphitis, D.; Mosso, C.; Risio, M.D. European experience of low crested structures for coastal management. Coast. Eng.
**2005**, 52, 841–866. [Google Scholar] [CrossRef] [Green Version] - Sane, M.; Yamagishi, H.; Tateishi, M.; Yamagishi, T. Environmental impacts of shore-parallel breakwaters along Nagahama and Ohgata, District of Joetsu, Japan. J. Environ. Manag.
**2007**, 82, 399–409. [Google Scholar] [CrossRef] - Kim, D.; Woo, J.; Yoon, H.-S.; Na, W.-B. Wake lengths and structural responses of Korean general artificial reefs. Ocean Eng.
**2014**, 92, 83–91. [Google Scholar] [CrossRef] - Srisuwan, C.; Rattanamanee, P. Modeling of Seadome as artificial reefs for coastal wave attenuation. Ocean Eng.
**2015**, 103, 198–210. [Google Scholar] [CrossRef] - Lee, M.O.; Otake, S.; Kim, J.K. Transition of artificial reefs (ARs) research and its prospects. Ocean Coast. Manag.
**2018**, 154, 55–65. [Google Scholar] [CrossRef] - Gysens, S.; Rouck, J.D.; Trouw, K.; Bolle, A.; Willems, M. Integrated coastal and maritime plan for Oostende—Design of soft and hard coastal protection measures during the EIA procedures. In Proceedings of the 32nd International Conference on Coastal Engineering, Shanghai, China, 30 June–5 July 2010; p. 37. [Google Scholar]
- Cappucci, S.; Scarcella, D.; Rossi, L.; Taramelli, A. Integrated coastal zone management at Marina di Carrara Harbor: Sediment management and policy making. Ocean Coast. Manag.
**2011**, 54, 277–289. [Google Scholar] [CrossRef] - Morang, A.; Waters, J.P.; Stauble, D.K. Performance of submerged prefabricated structures to improve sand retention at beach bourishment projects. J. Coast. Res.
**2014**, 30, 1140–1156. [Google Scholar] [CrossRef] - Gu, J.; Ma, Y.; Wang, B.-Y.; Sui, J.; Kuang, C.-P.; Liu, J.-H.; Lei, G. Influence of near-shore marine structures in a beach nourishment project on tidal currents in Haitan Bay, facing the Taiwan Strait. J. Hydrod.
**2016**, 28, 690–701. [Google Scholar] [CrossRef] - Pan, Y.; Kuang, C.P.; Chen, Y.P.; Yin, S.; Yang, Y.B.; Yang, Y.X.; Zhang, J.B.; Qiu, R.F.; Zhang, Y. A comparison of the performance of submerged and detached artificial headlands in a beach nourishment project. Ocean Eng.
**2018**, 159, 295–304. [Google Scholar] [CrossRef] - Ranasinghe, R.; Turner, I.L. Shoreline response to submerged structures: A review. Coast Eng.
**2006**, 53, 65–79. [Google Scholar] [CrossRef] - Marino-Tapia, I.D.J. Cross-Shore sediment Transport Processes on Natural Beaches and their Relation to Sand bar Migration Patterns; University of Plymouth: Plymouth, UK, July 2003. [Google Scholar]
- Archetti, R.; Zanuttigh, B. Integrated monitoring of the hydro-morphodynamics of a beach protected by low crested detached breakwaters. Coast. Eng.
**2010**, 57, 879–891. [Google Scholar] [CrossRef] - Kinsman, N.; Griggs, G.B. California coastal sand retention today: Attributes and influence of effective structures. Shore Beach
**2010**, 78, 64. [Google Scholar] - Kuang, C.; Pan, Y.; Zhang, Y.; Liu, S.; Yang, Y.; Zhang, J.; Dong, P. Performance Evaluation of a Beach Nourishment Project at West Beach in Beidaihe, China. J. Coast. Res.
**2011**, 27, 769–783. [Google Scholar] [CrossRef] - Roberts, T.M.; Wang, P. Four-year performance and associated controlling factors of several beach nourishment projects along three adjacent barrier islands, west-central Florida, USA. Coast. Eng.
**2012**, 70, 21–39. [Google Scholar] [CrossRef] - Do, K.; Kobayashi, N.; Suh, K.-D. Erosion of nourished bethany beach in Delaware, USA. Coast. Eng. J.
**2014**, 56. [Google Scholar] [CrossRef] - Dally, W.R.; Osiecki, D.A. Evaluating the Impact of beach nourishment on surfing: Surf City, Long Beach Island, New Jersey, U.S.A. J. Coast. Res.
**2018**, 34, 793–805. [Google Scholar] [CrossRef] - Grunnet, N.M.; Ruessink, B.G. Morphodynamic response of nearshore bars to a shoreface nourishment. Coast. Eng.
**2005**, 52, 119–137. [Google Scholar] [CrossRef] - Ojeda, E.; Ruessink, B.G.; Guillén, J. Morphodynamic response of a two-barred beach to a shoreface nourishment. Coast. Eng.
**2008**, 55, 1185–1196. [Google Scholar] [CrossRef] - Barnard, P.L.; Erikson, L.H.; Hansen, J.E. Monitoring and modeling shoreline response due to shoreface nourishment on a high-energy coast. J. Coastal Res.
**2009**, SI 56, 29–33. [Google Scholar] - King, P.; McGregor, A. Who’s counting: An analysis of beach attendance estimates and methodologies in southern California. Ocean Coast. Manag.
**2012**, 58, 17–25. [Google Scholar] [CrossRef] - Brutsché, K.E.; Wang, P.; Beck, T.M.; Rosati, J.D.; Legault, K.R. Morphological evolution of a submerged artificial nearshore berm along a low-wave microtidal coast, Fort Myers Beach, west-central Florida, USA. Coast. Eng.
**2014**, 91, 29–44. [Google Scholar] [CrossRef] - Ludka, B.C.; Guza, R.T.; O’Reilly, W.C. Nourishment evolution and impacts at four southern California beaches: A sand volume analysis. Coast. Eng.
**2018**, 136, 96–105. [Google Scholar] [CrossRef] - Leeuwen, S.V.; Dodd, N.; Calvete, D.; Falqués, A. Linear evolution of a shoreface nourishment. Coast. Eng.
**2007**, 54, 417–431. [Google Scholar] [CrossRef] - Pan, S. Modelling beach nourishment under macro-tide conditions. J. Coastal Res.
**2011**, SI 64, 2063–2067. [Google Scholar] - Spielmann, K.; Certain, R.; Astruc, D.; Barusseau, J.P. Analysis of submerged bar nourishment strategies in a wave-dominated environment using a 2DV process-based model. Coast. Eng.
**2011**, 58, 767–778. [Google Scholar] [CrossRef] - Jacobsen, N.G.; Fredsoe, J. Cross-shore redistribution of nourished sand near a breaker bar. J. Waterw. Port. Coast. Ocean. Eng.
**2014**, 140, 125–134. [Google Scholar] [CrossRef] - Jayaratne, M.P.R.; Rahman, R.; Shibayama, T. A Cross-shore beach profile evolution model. Coast. Eng. J.
**2014**, 56. [Google Scholar] [CrossRef] - Tonnon, P.K.; Huisman, B.J.A.; Stam, G.N.; van Rijn, L.C. Numerical modelling of erosion rates, life span and maintenance volumes of mega nourishments. Coast. Eng.
**2018**, 131, 51–69. [Google Scholar] [CrossRef] [Green Version] - Wang, P.; Smith, E.R.; Ebersole, B.A. Large-scale laboratory measurements of longshore sediment transport under spilling and plunging breakers. J. Coastal Res.
**2002**, 18, 118–135. [Google Scholar] - Wang, P.; Kraus, N.C. Movable-bed model investigation of groin notching. J. Coastal Res.
**2004**, SI 33, 342–368. [Google Scholar] - Gravens, M.B.; Wang, P. Data Report: Laboratory Testing of Longshore Sand Transport by Waves and Currents; Morphology Change Behind Headland Structures; Coastal and Hydraulics Laboratory, U.S. Army Engineer Research and Development Center: Vicksburg, MS, USA, 2007. [Google Scholar]
- Smith, E.R.; Mohr, M.C.; Chader, S.A. Laboratory experiments on beach change due to nearshore mound placement. Coast. Eng.
**2017**, 121, 119–128. [Google Scholar] [CrossRef] - Van Thiel de Vries, J.S.M.; van Gent, M.R.A.; Walstra, D.J.R.; Reniers, A.J.H.M. Analysis of dune erosion processes in large-scale flume experiments. Coast. Eng.
**2008**, 55, 1028–1040. [Google Scholar] [CrossRef] - Baldock, T.E.; Alsina, J.A.; Caceres, I.; Vicinanza, D.; Contestabile, P.; Power, H.; Sanchez-Arcilla, A. Large-scale experiments on beach profile evolution and surf and swash zone sediment transport induced by long waves, wave groups and random waves. Coast. Eng.
**2011**, 58, 214–227. [Google Scholar] [CrossRef] - Masselink, G.; Turner, I.L. Large-scale laboratory investigation into the effect of varying back-barrier lagoon water levels on gravel beach morphology and swash zone sediment transport. Coast. Eng.
**2012**, 63, 23–38. [Google Scholar] [CrossRef] - Masselink, G.; Ruju, A.; Conley, D.; Turner, I.; Ruessink, G.; Matias, A.; Thompson, C.; Castelle, B.; Puleo, J.; Citerone, V.; et al. Large-scale Barrier Dynamics Experiment II (BARDEX II): Experimental design, instrumentation, test program, and data set. Coast. Eng.
**2016**, 113, 3–18. [Google Scholar] [CrossRef] [Green Version] - Van der A, D.A.; van der Zanden, J.; O’Donoghue, T.; Hurther, D.; Cáceres, I.; McLelland, S.J.; Ribberink, J.S. Large-scale laboratory study of breaking wave hydrodynamics over a fixed bar. J. Geophys. Res.
**2017**, 122, 3287–3310. [Google Scholar] [CrossRef] - Nwogu, O.; Demirbilek, Z. Infragravity wave motions and runup over shallow fringing reefs. J. Waterw. Port. Coast. Ocean. Eng.
**2010**, 136, 295–305. [Google Scholar] [CrossRef] - Alsina, J.M.; Cáceres, I. Sediment suspension events in the inner surf and swash zone. Measurements in large-scale and high-energy wave conditions. Coast. Eng.
**2011**, 58, 657–670. [Google Scholar] [CrossRef] - Pomeroy, A.W.M.; Lowe, R.J.; Van Dongeren, A.R.; Ghisalberti, M.; Bodde, W.; Roelvink, D. Spectral wave-driven sediment transport across a fringing reef. Coast. Eng.
**2015**, 98, 78–94. [Google Scholar] [CrossRef] [Green Version] - Baldock, T.E.; Birrien, F.; Atkinson, A.; Shimamoto, T.; Wu, S.; Callaghan, D.P.; Nielsen, P. Morphological hysteresis in the evolution of beach profiles under sequences of wave climates—Part 1; observations. Coast. Eng.
**2017**, 128, 92–105. [Google Scholar] [CrossRef] [Green Version] - Rocha, M.V.L.; Michallet, H.; Silva, P.A. Improving the parameterization of wave nonlinearities—The importance of wave steepness, spectral bandwidth and beach slope. Coast. Eng.
**2017**, 121, 77–89. [Google Scholar] [CrossRef] - Yao, Y.; He, W.; Deng, Z.; Zhang, Q. Laboratory investigation of the breaking wave characteristics over a barrier reef under the effect of current. Coast. Eng. J.
**2019**, 61, 210–223. [Google Scholar] [CrossRef] - Grasso, F.; Michallet, H.; Barthélemy, E. Experimental simulation of shoreface nourishments under storm events: A morphological, hydrodynamic, and sediment grain size analysis. Coast. Eng.
**2011**, 58, 184–193. [Google Scholar] [CrossRef] - Grasso, F.; Michallet, H.; Barthélemy, E. Sediment transport associated with morphological beach changes forced by irregular asymmetric, skewed waves. J. Geophys. Res.
**2011**, 116. [Google Scholar] [CrossRef] [Green Version] - Capart, H.; Fraccarollo, L. Transport layer structure in intense bed-load. Geophys. Res. Lett.
**2011**, 38. [Google Scholar] [CrossRef] - Berni, C.; Barthélemy, E.; Michallet, H. Surf zone cross-shore boundary layer velocity asymmetry and skewness: An experimental study on a mobile bed. J. Geophys. Res.
**2013**, 118, 2188–2200. [Google Scholar] [CrossRef] - Rodríguez-Abudo, S.; Foster, D.; Henriquez, M. Spatial variability of the wave bottom boundary layer over movable rippled beds. J. Geophys. Res.-Oceans
**2013**, 118, 3490–3506. [Google Scholar] [CrossRef] [Green Version] - Petruzzelli, V.; Garcia, V.G.; Cobos, F.X.G.i.; Petrillo, A.F. On the use of lightweight mateials in small-scale mobile bed physical models. J. Coastal Res.
**2013**, 65, 1575–1580. [Google Scholar] [CrossRef] - Pan, Y.; Yin, S.; Chen, Y.; Yang, Y.; Xu, Z.; Xu, C. A Practical method to scale the sedimentary parameters in a lightweight coastal mobile bed model. J. Coastal Res.
**2019**, 35, 1351–1357. [Google Scholar] [CrossRef] - Ma, Y.; Kuang, C.; Han, X.; Niu, H.; Zheng, Y.; Shen, C. Experimental study on the influence of an artificial reef on cross-shore morphodynamic processes of a wave-dominated beach. Water
**2020**, 12, 2947. [Google Scholar] [CrossRef] - Roelvink, D.; Reniers, A. A Guide to Modeling Coastal Morphology; World Scientific: Singapore, 2012; p. 292. [Google Scholar]
- Rijnsdorp, D.P.; Smit, P.B.; Zijlema, M. Non-hydrostatic modelling of infragravity waves under laboratory conditions. Coast. Eng.
**2014**, 85, 30–42. [Google Scholar] [CrossRef] - Kennedy, A.B.; Chen, Q.; Kirby, J.T.; Dalrymple, R.A. Boussinesq modeling of wave transformation, breaking, and runup. I: 1D. J. Waterw. Port Coast. Ocean. Eng.
**2000**, 126, 39–47. [Google Scholar] [CrossRef] [Green Version] - Watanabe, A.; Sato, S. A sheet-flow transport rate formula for asymmetric, forward-leaning waves and currents. In Proceedings of the 29th International Conference on Coastal Engineering, Lisbon, Portugal, 19–24 September 2004; pp. 1703–1714. [Google Scholar]
- Michallet, H.; Cienfuegos, R.; Barthélemy, E.; Grasso, F. Kinematics of waves propagating and breaking on a barred beach. Eur J. Mech B-Fluid
**2011**, 30, 624–634. [Google Scholar] [CrossRef] - Elgar, S.; Gallagher, E.L.; Guza, R.T. Nearshore sandbar migration. J. Geophys. Res.
**2001**, 106, 11623–11627. [Google Scholar] [CrossRef] - Dally, W.R.; Brown, C.A. A modeling investigation of the breaking wave roller with application to cross-shore currents. J. Geophys. Res.
**1995**, 100, 24873–24883. [Google Scholar] [CrossRef] - Goring, D.; Nikora, V.I. Despiking acoustic doppler velocimeter data. J. Hydraul. Eng.
**2002**, 128, 117–126. [Google Scholar] [CrossRef] [Green Version] - Soulsby, R. Dynamics of Marine Sands: A Manual for Practical Applications; Thomas Telford Publications: London, UK, 1997. [Google Scholar]
- Alegria-Arzaburu, A.R.d.; Mariño-Tapia, I.; Silva, R.; Pedrozo-Acuña, A. Post-nourishment beach scarp morphodynamics. In Proceedings of the 12th International Coastal Symposium, Plymouth, UK, 8–12 April 2013; pp. 576–581. [Google Scholar]
- Erikson, L.H.; Larson, M.; Hanson, H. Laboratory investigation of beach scarp and dune recession due to notching and subsequent failure. Mar. Geol.
**2007**, 245, 1–19. [Google Scholar] [CrossRef] [Green Version] - Eichentopf, S.; Cáceres, I.; Alsina, J.M. Breaker bar morphodynamics under erosive and accretive wave conditions in large-scale experiments. Coast. Eng.
**2018**, 138, 36–48. [Google Scholar] [CrossRef] [Green Version] - Stockdon, H.F.; Holman, R.A.; Howd, P.A.; Sallenger, A.H., Jr. Emperical parameterization of setup, swash, and runup. Cost. Eng.
**2006**, 53, 573–588. [Google Scholar] [CrossRef] - Wright, L.D.; Short, A.D. Morphodynamic variability of surf zones and beaches: A synthesis. Mar. Geol.
**1984**, 56, 93–118. [Google Scholar] [CrossRef] - Guza, R.T.; Inman, D.L. Edge waves and beach cusps. J. Geophys. Res.
**1975**, 80, 2997–3012. [Google Scholar] [CrossRef] - LeMehaute, B.J.; Koh, R.C.Y. On the breaking of waves arriving at an abgle to the shore. J. Hydraul. Res.
**1967**, 5, 67–88. [Google Scholar] [CrossRef]

**Figure 2.**Experimental layout and four profile types: (

**a**) B-N; (

**b**) B-AR; (

**c**) B-ASB; and (

**d**) B-ASB-AR (W and V indicate the wave gauges and acoustic doppler velocimeters (ADVs), respectively. From the intersection of beach and still water surface to the middle points of ASB and AR, the distances are 10 m and 20 m, respectively. The coordinate system is set in (a) where X and Z indicate horizontal and vertical axes with origin of O).

**Figure 3.**Dimension indicators of the scarp and the breaker bar (dashed line indicates the initial profile, and solid line shows a typical final profile).

**Figure 5.**The beach evolution process (profiles in each test were captured every 10 min for a total of 90 min, as shown with colors changing from light to dark as time progresses).

**Figure 6.**Comparison of time-varying process of V

_{sx}and sx between measurement (marks) and prediction (line) (

**a**–

**h**).

**Figure 7.**Comparison of breaker bar height z

_{bar}and location x

_{bar}between measurement (marks) and prediction (line) (

**a**–

**e**).

**Figure 8.**The profile and the sediment transport of the fore-slope and the partial crest of the ASB: panels (

**a**–

**d**) and (

**i**–

**l**) show the profile captured every 10 min with colors changing from light to dark as time passes; panels (

**e**–

**h**) and (

**m**–

**p**) illustrate the sediment transport rate every 10 min with colors changing from red to blue as time passes.

**Figure 9.**Comparison of the height and the location of the breaker bars under different incident waves (

**a**–

**d**).

**Figure 10.**The morphological state identification of final profiles in all tests based on Wright and Short [89] ($s=tan\beta $ means the beach slope gradient).

**Table 1.**Physical experimental tests (N represents mild profile part without the offshore interventions, and beach with artificial reef (B-AR), beach with artificial submerged sand bar (B-ASB), and B-ASB-AR indicate beach with artificial reef and artificial submerged sand bar).

Test Name | Wave | Profile Type | Test Name | Wave | Profile Type | ||
---|---|---|---|---|---|---|---|

Hs (m) | Tp (s) | Hs (m) | Tp (s) | ||||

B-N-J1 | 0.04 | 1.20 | Beach (B-N) | B-ASB-J1 | 0.04 | 1.20 | Beach with ASB (B-ASB) |

B-N-J2 | 0.07 | 1.44 | B-ASB-J2 | 0.07 | 1.44 | ||

B-N-J3 | 0.10 | 1.57 | B-ASB-J3 | 0.10 | 1.57 | ||

B-N-J4 | 0.13 | 1.77 | B-ASB-J4 | 0.13 | 1.77 | ||

B-AR-J1 | 0.04 | 1.20 | Beach with AR (B-AR) | B-ASB-AR-J1 | 0.04 | 1.20 | Beach with ASB and AR (B-ASB-AR) |

B-AR-J2 | 0.07 | 1.44 | B-ASB-AR-J2 | 0.07 | 1.44 | ||

B-AR-J3 | 0.10 | 1.57 | B-ASB-AR-J3 | 0.10 | 1.57 | ||

B-AR-J4 | 0.13 | 1.77 | B-ASB-AR-J4 | 0.13 | 1.77 |

Profile Type | B-N | B-AR | B-ASB | B-ASB-AR | |
---|---|---|---|---|---|

Wave Gauges | |||||

W1 | 23.30 | 23.30 | 23.30 | 23.30 | |

W2 | 22.65 | 22.65 | 22.03 | 22.03 | |

W3 | 20.78 | 20.78 | 20.78 | 20.78 | |

W4 | 19.80 | 19.80 | 19.80 | 19.80 | |

W5 | 18.12 | 18.12 | 18.12 | 18.12 | |

W6 | 16.25 | 16.25 | 16.25 | 16.25 | |

W7 | 14.50 | 14.50 | 14.50 | 14.50 | |

W8 | 13.12 | 13.12 | 13.12 | 13.12 | |

W9 | 11.47 | 11.47 | 11.47 | 11.47 | |

W10 | 9.67 | 9.67 | 9.67 | 9.67 | |

W11 | 8.00 | 8.00 | 8.00 | 8.00 | |

W12 | 5.21 | 5.21 | 5.21 | 5.21 | |

W13 | 2.01 | 2.01 | 2.01 | 2.01 | |

V1 | 22.03 | 22.03 | 15.72 | 15.72 | |

V2 | 21.44 | 21.44 | 12.51 | 12.51 | |

V3 | 20.33 | 20.33 | 10.23 | 10.23 |

**Table 3.**Fitting parameters with evaluations of the exponential model on scarp evolution. (SSE: The sum of squares due to error; RMSE: Root mean squared error; Adjusted R-square: Degree-of-freedom adjusted coefficient of determination).

Parameters | Equation (11) | Equation (12) | |||||||
---|---|---|---|---|---|---|---|---|---|

Test | V_{0}(m/s) | T_{e}(s) | Adj R-Square | P1 (m) | P2 (m) | SSE | RMSE | Adj R-Square | |

B-N-J1 | 0.0052 | 70.35 | 0.71 | 0.37 | 24.89 | 0.0003 | 0.01 | 0.98 | |

B-AR-J1 | 0.0048 | 38.38 | 0.66 | 0.18 | 24.66 | 0.0004 | 0.01 | 0.96 | |

B-ASB-J1 | 0.0043 | 62.43 | 0.80 | 0.27 | 24.79 | 0.0004 | 0.01 | 0.99 | |

B-ASB-AR-J1 | 0.0042 | 50.17 | 0.86 | 0.21 | 24.69 | 0.0002 | 0.01 | 0.99 | |

B-N-J2 | 0.0132 | 35.47 | 0.83 | 0.47 | 25.19 | 0.0020 | 0.02 | 0.97 | |

B-AR-J2 | 0.0124 | 32.35 | 0.90 | 0.40 | 24.95 | 0.0005 | 0.01 | 0.99 | |

B-ASB-J2 | 0.0121 | 47.38 | 0.82 | 0.57 | 25.27 | 0.0004 | 0.01 | 0.98 | |

B-ASB-AR-J2 | 0.0125 | 22.87 | 0.98 | 0.29 | 24.87 | 0.0004 | 0.01 | 0.98 | |

B-N-J3 | 0.0164 | 52.60 | 0.47 | 0.86 | 25.77 | 0.0049 | 0.04 | 0.98 | |

B-AR-J3 | 0.0124 | 44.41 | 0.93 | 0.55 | 25.25 | 0.0019 | 0.02 | 0.98 | |

B-ASB-J3 | 0.0138 | 62.69 | 0.60 | 0.86 | 25.74 | 0.0070 | 0.04 | 1.00 | |

B-ASB-AR-J3 | 0.0146 | 39.56 | 0.99 | 0.58 | 25.27 | 0.0004 | 0.01 | 1.00 | |

B-N-J4 | 0.0338 | 44.01 | 0.99 | 1.49 | 26.55 | 0.0019 | 0.02 | 1.00 | |

B-AR-J4 | 0.0165 | 56.35 | 0.76 | 0.93 | 25.73 | 0.0006 | 0.01 | 1.00 | |

B-ASB-J4 | 0.0275 | 34.70 | 0.90 | 0.95 | 26.04 | 0.0001 | 0.00 | 0.99 | |

B-ASB-AR-J4 | 0.0194 | 42.16 | 0.74 | 0.82 | 25.58 | 0.0026 | 0.03 | 0.99 |

**Table 4.**Fitting parameters (i.e., dimensionless q1 and q2) with evaluation for linear migration trajectory of breaker bar in different profile types.

Parameters | q1 | q2 | SSE | RMSE | Adj R-Square | |
---|---|---|---|---|---|---|

Profile Type | ||||||

B-N | −0.047 | 1.12 | 0.005 | 0.011 | 0.94 | |

B-AR | −0.047 | 1.12 | 0.002 | 0.007 | 0.94 | |

B-ASB | −0.053 | 1.25 | 0.004 | 0.009 | 0.94 | |

B-ASB-AR | −0.053 | 1.27 | 0.002 | 0.007 | 0.95 | |

All data | −0.049 | 1.17 | 0.015 | 0.009 | 0.94 |

**Table 5.**Pearson correlation coefficients and corresponding significance levels between fitting parameters of scarp model and hydrodynamic factors (H

_{s}/L

_{s}and $\xi $ are dimensionless factors).

Hydrodynamic Factors | H_{s}(m) | H_{s-long}(m) | $\overline{\mathit{\eta}}$ (m) | L_{s}(m) | H_{s}/L_{s} | ${\mathit{H}}_{\mathit{s}}\times {\mathit{L}}_{\mathit{s}}$ (m ^{2}) | $\mathit{\xi}$ | |
---|---|---|---|---|---|---|---|---|

Profile Types with Parameters | ||||||||

B-N-P1 (significance level) | 0.9600 (0.04) | 0.9618 (0.04) | 0.9312 (0.07) | 0.9498 (0.05) | 0.7026 (0.30) | −0.7335 (0.27) | 0.9886 (0.01) | |

B-AR-P1 (significance level) | 0.9774 (0.02) | 0.9811 (0.02) | 0.9951 (0.00) | 0.9678 (0.03) | 0.9495 (0.05) | −0.9413 (0.06) | 0.9923 (0.01) | |

B-ASB-P1 (significance level) | 0.9897 (0.01) | 0.9916 (0.01) | 0.6559 (0.34) | 0.9486 (0.05) | −0.3857 (0.61) | 0.4090 (0.59) | 0.9357 (0.06) | |

B-ASB-AR-P1 (significance level) | 0.9724 (0.03) | 0.9734 (0.03) | 0.8933 (0.11) | 0.9588 (0.04) | 0.4411 (0.56) | −0.4703 (0.53) | 0.9786 (0.02) | |

B-N-P2 (significance level) | 0.9857 (0.01) | 0.9868 (0.01) | 0.8932 (0.10) | 0.9653 (0.03) | 0.7605 (0.24) | −0.7929 (0.21) | 0.9929 (0.01) | |

B-AR-P2 (significance level) | 0.9872 (0.01) | 0.9894 (0.01) | 0.9837 (0.02) | 0.9749 (0.03) | 0.9703 (0.03) | −0.9625 (0.04) | 0.9984 (0.00) | |

B-ASB-P2 (significance level) | 0.9946 (0.01) | 0.9952 (0.00) | 0.7313 (0.27) | 0.9774 (0.02) | −0.4727 (0.53) | 0.4973 (0.50) | 0.9686 (0.03) | |

B-ASB-AR-P2 (significance level) | 0.9823 (0.02) | 0.9841 (0.02) | 0.9114 (0.09) | 0.9730 (0.03) | 0.4378 (0.56) | −0.4709 (0.53) | 0.9870 (0.01) | |

B-N-T_{e}(significance level) | −0.5172 (0.48) | −0.5269 (0.47) | −0.2953 (0.70) | −0.6217 (0.37) | −0.3079 (0.69) | 0.3753 (0.62) | −0.4849 (0.52) | |

B-AR-T_{e}(significance level) | 0.8100 (0.19) | 0.8119 (0.19) | 0.8474 (0.15) | 0.7577 (0.24) | 0.8222 (0.18) | −0.7944 (0.21) | 0.8573 (0.14) | |

B-ASB-T_{e}(significance level) | −0.6430 (0.36) | −0.6321 (0.37) | −0.9133 (0.09) | −0.7086 (0.29) | 0.4635 (0.54) | −0.5137 (0.49) | −0.7156 (0.28) | |

B-ASB-AR-T_{e}(significance level) | −0.0973 (0.90) | −0.0990 (0.90) | −0.2923 (0.71) | −0.0672 (0.93) | −0.2337 (0.77) | 0.2821 (0.72) | 0.0207 (0.98) | |

A negative coefficient indicates the correlation between the fitting parameter and the opposite number of the factor. |

Wave | J1 | J2 | J3 | J4 | |
---|---|---|---|---|---|

Profile Type with Wave Gauges | |||||

B-N-W5 | 7.39 | 7.79 | 9.81 | 8.72 | |

B-N-W1 | 5.56 | 6.47 | 8.39 | 0.07 | |

B-AR-W5 | 5.90 | 6.06 | 6.50 | 6.63 | |

B-AR-W1 | 4.37 | 5.00 | 7.45 | 5.98 | |

B-ASB-W5 | 7.74 | 8.15 | 7.48 | 6.38 | |

B-ASB-W1 | 5.57 | 6.58 | 0.05 | 0.06 | |

B-ASB-AR-W5 | 5.93 | 6.24 | 7.07 | 5.90 | |

B-ASB-AR-W1 | 4.50 | 4.92 | 0.04 | 4.48 |

Profile Types | B-N | B-AR | B-ASB | B-ASB-AR | |
---|---|---|---|---|---|

Wave | |||||

J1 | BT P1 = 0.3662 P2 = 24.89 T _{e} = 70.4 | LT P1 = 0.1830 P2 = 24.66 T _{e} = 38.4 | LT P1 = 0.2699 P2 = 24.79 T _{e} = 62.4 | LT P1 = 0.2126 P2 = 24.69 T _{e} = 50.2 | |

J2 | RB P1 = 0.4666 P2 = 25.19 T _{e} = 35.5 | RB P1 = 0.3999 P2 = 24.95 T _{e} = 32.4 | LT P1 = 0.5724 P2 = 25.27 T _{e} = 47.4 | LT P1 = 0.2869 P2 = 24.87 T _{e} = 22.9 | |

J3 | RB P1 = 0.8644 P2 = 25.77 T _{e} = 52.6 | RB P1 = 0.5500 P2 = 25.17 T _{e} = 44.4 | BR P1 = 0.8621 P2 = 25.74 T _{e} = 62.7 | BR P1 = 0.5770 P2 = 25.27 T _{e} = 39.6 | |

J4 | BR P1 = 1.4871 P2 = 26.55 T _{e} = 44.0 | LT P1 = 0.9273 P2 = 25.73 T _{e} = 56.4 | BR P1 = 0.9536 P2 = 26.04 T _{e} = 34.7 | LT P1 = 0.8186 P2 = 25.68 T _{e} = 42.2 |

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**MDPI and ACS Style**

Kuang, C.; Ma, Y.; Han, X.; Pan, S.; Zhu, L.
Experimental Observation on Beach Evolution Process with Presence of Artificial Submerged Sand Bar and Reef. *J. Mar. Sci. Eng.* **2020**, *8*, 1019.
https://doi.org/10.3390/jmse8121019

**AMA Style**

Kuang C, Ma Y, Han X, Pan S, Zhu L.
Experimental Observation on Beach Evolution Process with Presence of Artificial Submerged Sand Bar and Reef. *Journal of Marine Science and Engineering*. 2020; 8(12):1019.
https://doi.org/10.3390/jmse8121019

**Chicago/Turabian Style**

Kuang, Cuiping, Yue Ma, Xuejian Han, Shunqi Pan, and Lei Zhu.
2020. "Experimental Observation on Beach Evolution Process with Presence of Artificial Submerged Sand Bar and Reef" *Journal of Marine Science and Engineering* 8, no. 12: 1019.
https://doi.org/10.3390/jmse8121019