Numerical Simulation and Large-Scale Physical Modelling of Coastal Sand Dune Erosion

Abstract

Do, K.; Shin, S.; Cox, D., and Yoo, J., 2018. An international comparison of drowning in South Korea. In: Shim, J.- S.; Chun, I., and Lim, H.S. (eds.), Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85, pp. 196–200. Coconut Creek (Florida), ISSN 0749-0208.Coastal sand dune system is important in the nearshore environment for sand supply, ecosystem, and hazard mitigation. In this study, a process-based morphological model was performed and the results were compared with large-scale laboratory experimental data. Two-dimensional large-scale laboratory experiments were conducted with 1:6 geometric scale in the large wave flume (104m (L) × 3.7 m (W) × 4.6 m (D)) of the Hinsdale Wave Research Laboratory at Oregon State University (Maddux et al, 2006). Several different wave conditions were used with different water levels in this experiment including pre-storm, storm, and post storm based on random wave time series by using TMA spectrum. The data set included cross-shore Wave heights, fluid velocities, and the profile changes of the beach and dune. The process based model, XBeach (Roelvink et al., 2009) was used to simulate the nearshore hydrodynamics and bed level change during storm wave condition. Several semi-empirical parameters were used in the XBeach model to predict morphodynamic process (Roelvink et al., 2009) and recently the updated parameters (WTI settings) were suggested based on the results of field observations. The present study ran the XBeach model by using both default and WTI settings and compared with the results from the experiments. The results showed that the model results with WTI settings showed good agreement with the measured beach profile while the model results with default settings over-predicted the offshore sediment transport and dune erosion. Especially, the wave skewness (facSk) and asymmetry (facAs) gave the highest contribution to predict dune erosion.