Field Observation of Morphological Response to Storm Waves and Sensitivity Analysis of XBeach Model at Beach and Crescentic Bar

et al. 2022

J. Ocean Eng. Technol.

Self Cite

<i>The process-based XBeach model has numerous empirical parameters because of insufficient understanding of hydrodynamics and sediment transport on the nearshore; hence, it is necessary to calibrate parameters to apply to various study areas and wave conditions. Therefore, the calibration process of parameters is essential for the improvement of model performance. Generally, the trial-and-error method is widely used; however, this method is passive and limited to various and comprehensive parameter ranges. In this study, the Generalized Likelihood Uncertainty Estimation (GLUE) method was used to estimate the optimal range of three parameters (gamma, facua, and gamma2) using morphological field data collected in Maengbang beach during the four typhoons that struck from September to October 2019. The model performance and optimal range of empirical parameters were evaluated using Brier Skill Score (BSS) along with the baseline profiles, sensitivity, and likelihood density analysis of BSS in the GLUE tools. Accordingly, the optimal parameter combinations were derived when facua was less than 0.15 and simulated well the shifting shape, from crescentic sand bar to alongshore uniform sand bars in the surf zone of Maengbang beach after storm impact. However, the erosion and accretion patterns nearby in the surf zone and shoreline remain challenges in the XBeach model.</i>

Section: Discussionmentioning

confidence: 99%

Section: Seas the Subject Of Researchmentioning

confidence: 99%

Proposal of Parameter Range that Offered Optimal Performance in the Coastal Morphodynamic Model (XBeach) Through GLUE

Bae

et al. 2022

J. Ocean Eng. Technol.

Self Cite

“…The depth and beach section surveys were conducted via a survey ship equipped with a real-time-kinematic global navigation satellite system (RTK GNSS), high-precision GNSS, and a precision echo sounder (AquaRuler 200S, MIDAS) from MSL (−) of 25 m outside the breaking wave zone to the MSL (+) of 6 m, the reference point above sea level. On measuring the depth 22 times for approximately 34 months from March 2017 to December 2019, almost no topographical change was observed outside the MSL (−) of 10 m. Hence, it is believed that the depth of the closure was formed at an MSL (−) of approximately 10 m (Jin et al, 2020) [33]. The analysis result of the depth data indicates that the variability of seasonal wave characteristics and the topographical variability of intermittent high waves and arc-shaped sand bars are significant.…”

Section: Depth Surveymentioning

confidence: 99%

Prediction of Shoreline Change for the Calculation of the Integrated Littoral Sediment Budget

Yoon

2022

Water

The severe coastal erosions are being accelerated along the east coast of South Korea owing to the intermittent erosions and depositions caused by the imbalance between the effective sediment volume supplied from coasts and rivers and the sediment transport rate. Consequently, many studies are being conducted to develop coastal-erosion reduction measures. To accurately determine the cause of coastal erosion, the causes of the erosion and deposition should be accurately diagnosed, and a comprehensive evaluation system for the sediment transport mechanism in the watershed and sea while considering regional characteristics is required. In particular, realizing the evaluation of the effective sediment volume that flows from the river to the sea through observations is a highly challenging task, and various research and developments are required to realize it, as it is still in the basic research stage. The purpose of this study was to systematically analyze the comprehensive sediment budget for coastal areas. First, an analytical system was developed. Then, a shoreline model was constructed by considering the size of the mixed particles. The parameters required for developing the model were determined using the observation data to improve the shoreline model. A sediment runoff model was applied to evaluate the effective sediment volume supplied from the river to the sea, and the applicability of this model was evaluated by comparing it with the sediment supply volume according to the soil and water assessment tool model. The representative wave and the input parameters of the model were set using the observation data of several years. It was found that the prediction performance of the shoreline change model improved when the effective sediment volume was considered, and the particles of the sediment on the shore were assumed to comprise multiple sizes. In particular, the prediction performance improved when the balance of the sediment budget was adjusted by applying a groin having a structurally similar performance to take into consideration the geographic features of the Deokbongsan (island) in front of the river mouth bar. The model demonstrated a good performance in reproducing long-term shoreline changes when the characteristics of the sea waves and the effective sediment volume were considered.

“…However, Rafati et al, 2021 [20] showed a correlation between the optimum parameters and incident wave conditions, although all initial profiles differed. Several studies [11,24,25] simulated storm morphological changes under complex bathymetry where an area model is required but did not elucidate the model sensitivity to various incident wave events.…”

Section: Introductionmentioning

confidence: 99%

Sensitivity Analysis of Event-Specific Calibration Data and Its Application to Modeling of Subaerial Storm Erosion under Complex Bathymetry

Jin

et al. 2022

JMSE

Self Cite

Key parameters in a process-based model depicting the morphological changes during storm events should be adjusted to simulate the hydro- and morphodynamics, leading to site-, profile-, and event-specific calibration. Although area models eliminate variability in calibrated parameters along with each profile in complex bathymetry, the amount of influence datasets with different wave conditions have on model performance is still unclear in an area model in a given parameter space. This study collected hydrodynamic and bathymetric field data over four different storm conditions (two single and two cluster storms) at Maengbang Beach, South Korea. The numerical model XBeach was adopted using four storm datasets with four key parameters to examine the influence of event-specific calibration data on subaerial storm erosion. When using clustered storm data, a relatively limited number of parameter combinations showed higher model sensitivity to different parameter sets as opposed to single storm data with the same parameter sets. Model sensitivity to different storm events was correlated with cumulative storm power and resultant erosion volume in comparison with other features in the datasets. The results are expected to guide the selection of an event-specific dataset with various morphological and hydrodynamic factors in an area model under complex bathymetry.