ABSTRACT

Yuk, J.; Joh, M., and Huh, T., 2020. Simulation of storm wave run-up in the Busan Marine City, South Korea: A case study during typhoon Chaba. In: Malvárez, G. and Navas, F. (eds.), Global Coastal Issues of 2020. Journal of Coastal Research, Special Issue No. 95, pp. 1377–1382. Coconut Creek (Florida), ISSN 0749-0208.

Storm waves can cause severe damage along the Korean coast. In particular, the Busan Marine City in the South Korea often suffers flooding damage due to high storm waves. An accurate and efficient wave prediction system must be constructed to prepare for a coastal disaster. For this study, a wave propagation and run-up prediction system was developed based on a weather model, wave model, and shallow-water equation model with adaptive mesh refinement (AMR) and a wet-dry scheme. Overtopping and flooding are also produced by this prediction system. The weather prediction model (K-MPAS; KISTI Model for Prediction Across Scales) is optimized for better prediction of typhoons in the Western Pacific with a relatively highly-resolved mesh for the target area and model scheme improvements. According to recent analyses for the prediction of typhoons which occurred in the summers, this model has better performance on tracking typhoons compared to operational agencies. The wave model (WAVEWATCH III) consists of three nesting domains to account for accurate wave propagation around the Korean Peninsula. Storm wave characteristics are estimated near the south coast of Korea based on the weather and wave models. Then the obtained wave height and period are used to estimate the wave run-up in the Busan Marine City using the AMR-based model. As a case study, we reproduced the storm wave caused by typhoon Chaba which occurred in 2016 and caused a lot of damage to the city. Wind was predicted fairly well, and wave heights and periods predicted by the wave model were in good agreement with the observations. The difference between the observed and the modeled values for wave run-up height was in the acceptable range. Therefore, the developed prediction system can provide reliable prediction data responding to coastal disaster.

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