1. Introduction
Since the 1970s, South Korea’s rapid economic growth has significantly increased the demand for coastal areas to support fishing, leisure, and industry activities. This surge in demand has led to widespread and often indiscriminate coastal development, characterized by the construction of harbors and breakwaters. Such artificial interventions have disrupted sediment supply from rivers, causing imbalances in sediment transport and triggering persistent coastal erosion (Ministry of Oceans and Fisheries, 2022). Moreover, the effects of climate change, including rising sea levels, the prevalence of long-period waves, and the increasing frequency of high-energy waves, have accelerated coastal erosion (KIOST, 2022).
Beaches are critical resources for their economic value and as ecosystems supporting diverse marine life and natural defenses against typhoons and storm surges. Therefore, protecting these environments from erosion is essential. Measurements such as beach nourishment and the construction of coastal structures, including submerged breakwaters, groins, and detached breakwaters, have been implemented to address coastal erosion. Nevertheless, these coastal structures change nearshore currents and sediment transport around the structures, often leading to secondary erosion problems (Komar and McDougal, 1988; Rangel-Buitrago et al., 2018).
Wonpyeong Beach, located in Samcheok-si, Gangwon-do, has been subjected to continuous erosion caused by sediment transport imbalances and wave diffraction effects resulting from the construction of Gungchon Port and the expansion of its breakwater. These interventions have led to secondary erosion around the structures (Ministry of Oceans and Fisheries, 2018). Hence, a detailed understanding of coastal processes and their interactions with these structures is crucial for mitigating further erosion. Coastal processes are inherently dynamic, spatially and temporally variable, and nonlinear, with coastal structures adding layers of complexity. Consequently, several studies have examined coastal processes, the morphological changes induced by structures, and the optimal design and placement of such structures (van Rijn, 2011; Jackson et al., 2015; Scott et al., 2016; Williams et al., 2018; Yoo et al., 2022).
Numerical models such as XBeach have been conducted in coastal beach process research owing to the high cost and spatial-temporal challenges of field observations and hydraulic model experiments. XBeach, an open-source 2DH numerical model developed by Deltares, simulates coastal morphological changes during storms (Roelvink et al., 2009). The model has been applied widely in coastal engineering, particularly in simulating dune and beach erosion (McCall et al., 2010; Roelvink and Costas, 2019). On the other hand, the model incorporates numerous empirical formulae, requiring users to calibrate its parameters appropriately for accurate simulations. Developed initially to simulate barrier island collapses caused by Hurricane Katrina, XBeach has been found to overestimate erosion when the default parameters are used (Do et al., 2018; Jin et al., 2020; Jin et al., 2022). Therefore, studies focusing on parameter calibration to enhance the accuracy of XBeach have been conducted (De Vet, 2014; Simmons et al., 2019; Do and Yoo, 2020; Jin et al., 2020; Bae et al., 2022; Jin et al., 2022). Nevertheless, previous studies focused on simple coastal environments, with limited research focusing on complex coastal areas with coastal structures.
Cho et al. (2025) used the GLUE method for sensitivity analysis of XBeach based on the presence or absence of submerged breakwaters. Their analysis of wave nonlinearity at different breakwater locations confirmed that the facua and gamma values change according to the presence of submerged breakwaters. They also reported that incorporating spatial variations in wave nonlinearity and breaking characteristics is essential for improving the modeling accuracy. Nevertheless, they noted that adjusting these parameters alone has limitations in improving accuracy.
Do and Yoo (2020) emphasized the importance of considering the distribution of the sand layer thickness in XBeach simulations because the absence of sand layer limitations can lead to overestimated erosion. Rahman and Womera (2013) reported that the height of submerged breakwaters influences wave transmission, which affects nearshore currents and sediment transport. Bed shear stress, determined by bottom friction coefficients, is another critical factor because it significantly impacts wave energy dissipation in the surf and swash zones. Various studies highlighted the necessity of accurately calibrating bottom friction coefficients to simulate nearshore processes effectively (Nielsen, 1992; Whitford and Thornton, 1996; Smyth and Hay, 2002; Puleo et al., 2012). Bed shear stress is determined by the bottom friction coefficient; hence, it must be specified in nearshore process modeling. Consequently, several studies have been conducted to select the appropriate values (Whitford and Thornton, 1996; Smyth and Hay, 2002; Puleo et al., 2012). Passeri (2018) converted the Manning roughness coefficients, classified by bed type, into Chezy coefficients and applied spatially varying bottom friction coefficients in XBeach to simulate post-storm barrier island changes, achieving more accurate results.
These findings underscore the importance of considering complex coastal geomorphic features in numerical simulations, such as the height of submerged breakwaters, sediment layer thickness, and bottom friction properties. This study collected field data from Wonpyeong Beach, where various coastal structures have been installed, to simulate the morphological changes in complex coastal environments. The subsidence of submerged breakwaters, identified through coastal erosion monitoring, was incorporated to account for the variations in structural height. The sediment layer thickness was estimated using a combination of satellite imagery and observational data, with additional calculations based on the design drawings of the submerged breakwaters to improve accuracy in areas prone to scouring. Finally, spatially varying bottom friction coefficients were applied to reflect the unique seabed characteristics of Wonpyeong Beach, including numerous structures and underwater reefs. This study aims to enhance the accuracy of XBeach simulations in complex coastal environments using this approach. In addition, it proposed that satellite images can be used effectively in situations where observational data, such as the sand layer thickness, is limited. Hence, this study provides insights for developing effective coastal management strategies.
2. Study Area and Field Data
2.1 Study Area
Wonpyeong Beach, the study area, is a pocket beach located in Geundeok-myeon, Samcheok-si, Gangwon-do, with a coastal orientation of approximately 38° (Fig. 1). The beach is divided into distinct sections based on the location of Gungchon Port to the northwest: Gungchon Beach, Wonpyeong Beach, Chogok Beach, and Munam Beach. Sediment is supplied primarily by the Chu River, situated between Gungchon Port and Gungchon Beach, and is predominantly composed of sand. The total coastline of Wonpyeong Beach is 2.86 km, with an average beach width of 48.3 m. It is a low tidal beach, characterized by an average tidal range of 0.12 m, and is wave-dominated, making it vulnerable to erosion during high wave events. The beach exhibits multiple rip channels, where erosion and deposition occur frequently along the shoreline, and crescentic sandbars are observed underwater. Furthermore, the beach and seabed are highly complex coastal terrain, with numerous granite bedrock formations extensively distributed throughout, as shown in Fig. 2 (Kim and Park, 2024).
Since the construction of the Gungchon Port breakwater in 2010, an imbalance of longshore sediment transport has led to continuous erosion. As a result, Wonpyeong Beach has been classified as Grade D (severe) in the coastal erosion evaluation conducted by the Ministry of Oceans and Fisheries since 2010 (Ministry of Oceans and Fisheries, 2022). Several measurements were implemented between 2012 and 2016 to mitigate severe beach erosion, including dredging and beach nourishment of 80,000 m3, the construction of 96 seawater circulation openings, and the construction of three submerged breakwaters (360 m in total). Nevertheless, these efforts induced changes in nearshore current and sediment transport, resulting in additional secondary erosion in this area. The second-phase coastal maintenance project was undertaken between 2017 and 2022, including additional beach nourishment of 76,000 m3, the construction of three groins (280 m in total), two detached breakwaters (360 m in total), and two artificial island-style detached breakwaters. Further beach nourishment and the construction of coastal structures are planned as part of ongoing efforts to manage coastal erosion in this area. (Fig. 1).
Based on the structural design drawings for Wonpyeong Beach, the crest heights of the installed structures were as follows: the submerged breakwater was designed at DL(−)5 m, Groin 1 at DL(−)2 m, Groin 2 at DL(−)2 m, and Groin 3 at DL(−)3 m. On the other hand, a survey of the crest height of the submerged breakwater at Gungchon Beach conducted in 2020 revealed deviations from the design specifications (The Ministry of Oceans and Fisheries, 2018; Gangwon State East Sea Rim Headquarters, 2021). These discrepancies were presumed to result from seabed subsidence caused by wave loading on the submerged breakwater during repeated typhoon events and high wave intrusions (Ministry of Oceans and Fisheries, 2018; Kang et al., 2013). Fig. 2 and Table 1 present the surveyed area and crest heights, respectively.
2.2 Wave Data
Wonpyeong Beach has no dedicated wave observation station. Therefore, this study used the wave data from the W1 AWAC (Acoustic Waves and Currents, Norteck), located at Maengbang Beach, approximately 10 km away from Wonpyeong Beach (Fig. 1). The W1 AWAC was installed at a depth of −30 m relative to mean sea level (MSL) and has been collecting data on the wave height, period, and direction at hourly intervals since February 2017. Fig. 3 presents the time series of significant wave height, peak period, and peak wave direction observed at W1 AWAC from 2019 to 2020, the period most affected by typhoons over the past five years, along with the wave rose analysis results based on the significant wave height and peak wave direction. An analysis of the wave data showed that waves from the NE direction, which are perpendicular to the shoreline, were predominant due to the coastal orientation of Maengbang Beach and Wonpyeong Beach, both inclined at approximately 40° (Cho and Kim, 2019). Seasonal variations in wave direction were evident, with waves originating primarily from the NE to ENE directions during spring and summer (March to August) and from the NNE to NE directions during fall and winter (September to February). High-energy waves, defined as waves exceeding 2 m in height, accounted for approximately 6.9% of the total wave occurrences. Among these, 41% occurred during the fall and winter, indicating a seasonal concentration of high-energy events. Between 2019 and 2020, Maengbang Beach experienced seven typhoon events. In 2019, Typhoons Lingling, Tapah, Mitag, and Hagibis occurred consecutively over approximately two months, influencing the wave conditions in the region. Among these, Typhoon Tapah produced the highest storm waves, with a significant wave height of 4.5 m, a peak period of 10.2 s, and a peak wave direction of 60.2°. In addition, the highest waves during the study period were recorded on January 8, 2020, with a significant wave height of 5.22 m, a peak period of 11.20 seconds, and a peak wave direction of 50.35°. These extreme wave events highlight the influence of seasonal and storm-induced wave dynamics on the coastal processes at Wonpyeong Beach.
2.3 Bathymetry Data
Bathymetry and beach profile surveys were conducted at Wonpyeong Beach, from Gungchon Beach to Munam Beach. Six surveys, conducted twice annually, were carried out from 2019 to 2021. For the bathymetry survey, a survey vessel equipped with a high-precision global navigation satellite system (GNSS) and an advanced echo sounder (AquaRuler 200S, MIDAS) was used to collect depth data up to MSL(−)15 m. Beach profile surveys were performed at 50 m intervals using RTK-GNSS, covering elevations from MSL to MSL(+)6 m. The surveys revealed the formation of crescentic sandbars, a characteristic feature along Korea’s east coast (Athanasiou et al., 2018; Jin et al., 2020; Do et al., 2021). Minimal morphological changes were observed at depths beyond MSL(−)9 m, suggesting that the depth of closure for sediment movement at Wonpyeong Beach is approximately MSL(−)9 m. During the survey period, coastal structures such as groins and offshore breakwaters were constructed as part of a coastal maintenance project. The natural coastal processes influenced by the installation of these structures were investigated by analyzing bathymetry data collected on November 16, 2019, and March 25, 2020, periods unaffected by artificial impacts from construction (Fig. 4).
The analysis showed that the typhoons Lingling, Tapah, Mitag, and Hagibis, which struck in 2019, contributed to the formation of a linear sandbar at depths of MSL(−)3 to 4 m. Nevertheless, the high wave activity during winter transformed this feature into double sandbars, consisting of a crescent-shaped outer sandbar and a linear inner sandbar closer to the shoreline. The presence of newly installed structures affected the shoreline, which induced localized variations in erosion and deposition. Deposition was predominantly observed in the lee of the submerged breakwater, while erosion dominated the other regions. This pattern can be attributed to the dissipation of wave energy over the submerged breakwater, producing a low-energy environment conducive to sediment deposition in the sheltered area behind the structure. In this zone, a four-cell circulation flow, driven by the prevailing longshore current, contributed to the observed deposition (Ranasinghe and Turner, 2006; Ranasinghe et al., 2010; Hwang et al., 2023).
3. Numerical Modeling
3.1 Numerical Model Setup
This study conducted numerical simulations using XBeach, a 2DH (2-Dimensional Horizontal) wave propagation model based on a phase-averaged wave action equation, to simulate the hydrodynamic and morphodynamic responses of the nearshore under extreme storm conditions (Roelvink et al., 2009). The simulations used XBeach X version 1.23.5527 (Deltares, 2018), applying the Surfbeat mode to capture the hydrodynamic and morphodynamic changes in the surf and swash zones. The computational efficiency was optimized by distributing the simulations across 36 nodes and executed in parallel using OpenMPI (Message passing interface).
The Joint North Sea Wave Project (JONSWAP) spectrum was used for offshore wave boundary conditions, accounting for longshore currents and morphological changes around the structure based on the storm conditions. The input parameters for the JONSWAP spectrum, including significant wave height (Hs), peak period (Tp), and peak direction (Dp), were derived from the wave data observed at the W1 AWAC in Maengbang Beach, the nearest wave observation station to Wonpyeong Beach. Only wave conditions with significant wave heights exceeding 2 m were selected as boundary inputs to reduce the computational time for the relatively long simulation period of 130 days. Tidal data observed at the Donghae Port tide station (the station closest to the study area), provided by the Korea Hydrographic and Oceanographic Agency, were used as the offshore water level boundary condition to account for tides and storm surges.
The model grid was extended offshore to a depth of MSL(−)30 m., including the depth where the AWAC station was installed, to minimize distortions in the initial wave boundary conditions. A curvilinear grid was used, with a grid spacing that gradually increased in the offshore direction to balance the simulation accuracy and computational efficiency (Fig. 5). The grid size was set to 211 (cross-shore) × 361 (alongshore) with the resolution configured as shown in Table 2.
The initial bathymetry for the model was based on the depth data collected on November 16, 2019, before significant morphological changes caused by winter high-wave events, and the struct option was used to activate rigid structures. The locations of the structures and bedrock were identified using satellite images, while the structural heights were based on design specifications. Unrealistic erosion was prevented by setting the sand layer thickness to 0 m for structures, bedrock, and underwater reefs distributed across Wonpyeong Beach, which was identified through satellite imagery. For non-structural areas, the sand layer thickness was set uniformly to 3 m, corresponding to the maximum erosion depths observed during the simulation period. This approach ensured a realistic representation of sediment availability and erosion processes in the numerical simulations.
The key XBeach parameters used in this study (gamma, gamma2, and facua) were derived from the optimal parameter combination proposed by Jin et al. (2022). These parameters were calibrated and validated from storm condition simulations of complex seabed morphology at Maengbang Beach, Gangwon-do. These parameters were considered applicable to Wonpyeong Beach, which is located near Maengbang Beach and exhibits similar wave characteristics because they are determined based on wave characteristics and nonlinearity. Therefore, this study adopted the parameter values proposed by Jin et al. (2022). The parameters fallvelred and dilatancy, as recommended by De Vet (2014), were applied to address excessive erosion resulting from high flow velocities. The median grain size (D50), a critical parameter influencing sediment transport, was set to 0.85 mm based on seabed sediment survey data collected at Wonpyeong Beach on September 27, 2019. The morphological acceleration factor (morfac) was set to 10 to enhance computational efficiency, according to its application in previous studies (Bae et al., 2022; Jin et al., 2022). All other parameters were maintained at their default values to ensure consistency with the baseline model configuration (Table 3).
3.2 Geomorphic Characteristics
3.2.1 Submerged breakwaters subsidence
The height of a submerged breakwater plays a critical role in wave transmission. Higher breakwaters induce earlier wave breaking, reducing the wave energy transmitted to the shoreline. This process affects the nearshore currents and sediment transport around the structure, making it essential to represent the height of a structure accurately in numerical simulations (Rahman and Womera, 2013). On the other hand, subsidence may occur on sandy foundations due to the continuous wave loading, leading to deviations between the actual and design heights of the structure (Kang et al., 2013). The actual crest height of the submerged breakwaters at Wonpyeong Beach deviates from the design specifications, with differences of up to −0.5 m, as shown in Table 1. These surveyed heights were incorporated into the initial bathymetry configuration to improve the accuracy of the numerical simulations (Fig. 6). This adjustment ensures that the effects of submerged breakwater subsidence on wave energy dissipation and sediment dynamics are realistically simulated.
3.2.2 Adjustment of sediment thickness layer
The seabed at Wonpyeong Beach is characterized by a mixture of underwater reefs and sandy layers, with some areas exhibiting thin sand layers or exposed bedrock, depending on temporal variations. Neglecting these geomorphic features in numerical simulations may result in overestimated erosion. Although geological survey data have been used in other studies (Do and Yoo, 2020), no direct survey of the sand layer thickness has been conducted at Wonpyeong Beach.
For example, satellite imagery from February 4, 2020, revealed bedrock exposed in front of Submerged Breakwater 3, while erosion in front of Submerged Breakwater 1 exposed bedrock on February 11, 2021. Based on this analysis, satellite imagery and observational data comparisons allowed for the following sand layer thickness estimates. First, the sand layer thickness in front of Submerged Breakwater 1 was estimated to be approximately 1 m by comparing morphological change data from November 16, 2019, to March 2, 2020, with satellite imagery. In addition, a comparison of the morphological change data from November 16, 2019, to February 25, 2021, with satellite imagery estimated the sand layer thickness in front of Submerged Breakwater 3 to be between approximately 1 m and 1.5 m (Fig. 7). This was addressed by applying limited sand layer thickness was applied for each area in the numerical simulation by comparing satellite data and observational records. High-resolution satellite images from Google Earth were analyzed to identify the exposed bedrock areas and infer the sand layer thickness based on the changes in bathymetry. In addition, the sandbar morphology observed in the Google Earth satellite imagery from February 4, 2020, showed a crest-to-trough difference of approximately 1.5 to 2 m. Considering that the sand layer thickness in the areas where bedrock was exposed was estimated to be approximately 1 m, it can be inferred that the sand layer thickness in the sandbar area is approximately 3 m (Fig. 8).
For submerged breakwaters covered with armor stones, the sand layer thickness could be estimated using the observed depths and the depth of armor stone installation specified in the design drawings. These adjustments, shown in Fig. 8(c), provided a more realistic representation of sediment distribution in the numerical simulations.
3.2.3 Variable bed friction coefficient
Bed shear stress is a key factor influencing wave energy dissipation and nearshore current dynamics, particularly along complex coastlines such as Wonpyeong Beach. Passeri (2018) simulated the use of Manning coefficients, categorized according to the bed type, to simulate storm-induced morphological changes in barrier islands. The Manning formula is expressed in Eq. (1), where C, n, and R are the Chezy coefficient, Manning roughness coefficient, and hydraulic radius (depth), respectively.
In this study, the Chezy coefficients for Wonpyeong Beach were derived using the methodology reported by Passeri (2018), with an additional consideration of the bedrock Manning coefficients from Papaioannou et al. (2018). This allowed for a more accurate representation of bottom friction across various bed types, including sandy seabed, rocky areas, and terrestrial structures (Table 4). For water depth, a minimum depth of 0.1 m, as specified by the formula, was applied to terrestrial structures, while the corresponding depths were used for other areas. For offshore regions, a default value of 55 was applied (Fig. 9). These spatially varying Chezy coefficients were incorporated into the numerical model to enhance the simulation of wave energy dissipation and sediment transport processes.
4. Results
Numerical simulations were conducted for four cases, progressively incorporating the geomorphic characteristics detailed in Section 3.2 (Table 5). These step-by-step simulations were conducted to evaluate the impact of each characteristic on the accuracy of morphodynamic predictions. The analysis was facilitated by dividing the study area into three distinct zones based on the distribution of structures and rock masses along the beach:
- Zone A: Areas with only structures, such as submerged breakwaters and groins.
- Zone B: Areas where both structures and rock masses coexist.
- Zone C: Areas with only rock masses, including exposed bedrock and underwater reefs.
This zonation approach (Fig. 10) enabled a detailed comparison of the simulation results with the observational data. The influence of each geomorphic characteristic within these zones was evaluated to determine its contribution to improving the accuracy of the numerical model in representing the complex coastal processes at Wonpyeong Beach.
In Case 1, where geomorphic characteristics were not applied, high winter waves from the NE to ENE directions were observed during the simulation period, generally inducing sediment transport southward. Although sedimentation caused by a four-cell circulation flow behind the submerged breakwater was simulated, the overall accuracy was limited. The model reasonably predicted the location of coastal sandbars forming at depths of MSL(−)6 to −10 m. On the other hand, excessive scouring in front of the submerged breakwater resulted in significant sand movement, leading to an underestimation of sandbar formation in Zones B and C. In addition, although the erosion and deposition patterns at MSL(−)2 to 4 m were reproduced, the model exhibited limitations in reproducing sediment deposition onshore, resulting in an overestimation of erosion. Consequently, sand that failed to migrate onshore accumulated excessively in the upper foreshore
In Case 2, the subsidence of the submerged breakwater was incorporated, reflecting changes in the height of the breakwater. This adjustment improved the shape of the sandbar forming at MSL(−)6 to −10 m by altering nearshore currents around the structure. However, stronger scouring in front of the breakwater caused eroded sand to be excessively deposited offshore due to the circulation currents generated near the protruding section of the Gungchon Port breakwater. The deposition patterns in the lee of the submerged breakwater also exhibited variations due to changes in nearshore currents, but the accuracy remained relatively low. Zones B and C, which were not directly influenced by the breakwater, showed little change. These results highlight that the shape and height of the submerged breakwater significantly influence nearshore currents and sediment transport (Fig. 10).
Case 3 considered the subsidence of the submerged breakwater and sand layer thickness. Including the sand layer thickness mitigated the excessive scouring in front of the breakwater. On the other hand, considerable erosion still occurred on the left side of the breakwater, likely due to the exclusion of sediment input from the river on the left side of the breakwater in the model, resulting in excessive erosion in that area. Although the shape of the sandbar forming at MSL(−)6 to −10 m improved, excessive erosion along the nearshore remained unresolved. Zones B and C also showed no significant changes compared to earlier cases.
In Case 4, the model incorporated the effects of breakwater subsidence, sand layer thickness, and variable bottom friction coefficients. Stronger nearshore currents in Zone A, influenced by changes in the bottom friction coefficient, caused increased erosion in front of the breakwater. Sediment eroded from Zone A was transported toward Zone B, contributing to the development of an offshore sandbar. Enhanced deposition was observed in the offshore sandbar, while the onshore sediment transport patterns showed no significant changes compared to the previous cases.
These results suggest that estimating the sand layer thickness using satellite imagery, particularly in situations with limited field data, can effectively improve the accuracy of numerical simulations. Furthermore, incorporating variable bottom friction coefficients enhances the representation of the sediment transport dynamics in areas with complex geomorphic features.
5. Conclusions
XBeach simulations were used to model the morphological changes in a complex coastal environment characterized by structures such as submerged breakwaters, groins, and bedrock. This study focused on Wonpyeong Beach in Samcheok-si, Gangwon-do where coastal maintenance projects have been implemented since 2012 to mitigate erosion caused by coastal development and high-energy wave events. Wonpyeong Beach is a low-tidal range, wave-dominated beach with highly complex terrain due primarily to the extensive distribution of bedrock along the beach and seabed. Owing to the absence of dedicated wave observation stations at Wonpyeong Beach, the wave boundary conditions were derived from W1 AWAC data at Maengbang Beach, the nearest station. The data from the Donghae Port tidal observation station, the closest tidal gauge, were used for offshore water level boundary conditions. Bathymetric data were collected six times between 2019 and 2022, and data from November 16, 2019, and March 25, 2020, were used to minimize the external influences from ongoing coastal maintenance projects. The wave conditions with significant wave heights above 2 m were applied to reduce the computation time and address the 130-day simulation period. A variable grid resolution of 211 × 361 was used, with the acceleration parameter set to 10, significantly improving the computational efficiency. The core simulation parameters for XBeach were based on the optimal parameter combination validated for Maengbang Beach by Jin et al. (2022). The fallvelred and dilatancy options were applied to prevent excessive erosion caused by high flow velocities, while other parameters were kept at their default values.
Geomorphic factors such as submerged breakwater subsidence, sand layer thickness, and bottom friction properties were incorporated to reflect the field characteristics of this complex terrain:
(1) Submerged breakwater subsidence was integrated into the initial bathymetry, confirming the significant impact of structural geometry on sediment transport.
(2) The sand layer thickness was estimated using observational data and satellite imagery to identify underwater reefs, compensating for the lack of direct field data.
(3) Spatially varying bottom friction coefficients, as described by Passeri et al. (2018), were applied to consider the diverse seabed characteristics of Wonpyeong Beach.
Stepwise consideration of these geomorphic features showed that the height of structures and the thickness of the sand layer were critical factors influencing nearshore currents and sediment transport. In contrast, the influence of bottom friction coefficients was relatively minor. These findings highlight the importance of incorporating accurate structural heights and sand layer thicknesses for reliable numerical simulations in complex coastal terrains. Adjusting the sand layer thickness and structure heights improved the simulation by mitigating excessive erosion and accurately reproducing the formation of nearshore sandbars and erosion-deposition patterns around structures and bedrock. This study showed that the sand layer thickness can be estimated using observational and satellite data, providing a guideline for incorporating field geomorphic features in situations with limited field data due to time and cost constraints.
Nevertheless, the study results did not accurately simulate accretion processes within the swash zone, making it challenging to assess the overall model performance quantitatively. Therefore, future research should improve the modeling capabilities in the swash zone to address this limitation and enhance numerical predictions in complex coastal environments. In addition, there were limitations in field observation data, such as the wave and bathymetry data for the study area. Hence, continuous field data monitoring is essential to achieving more accurate simulations. This study applied a sand-layer thickness estimation method to Wonpyeong Beach using satellite imagery. Testing the proposed method in other coastal areas in the future could help validate its reliability. Furthermore, this study did not conduct an additional calibration of the specific parameters. Obtaining more accurate simulation results will require calibration of the parameters for the study area based on continuously monitored field data.
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