• Journal of Korean Society of Coastal and Ocean Engineers
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• v.20 no.5
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• pp.482-490
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• 2008

For a coastal or harbor structure design, one of the most important environmental factors is the appropriate extreme highest tide level condition. Especially, the information of extreme highest tide level distribution is essential for reliability design. In this paper, 23 set of extreme highest tide level data obtained from National Oceanographic Research Institute(NORI) were analyzed for extreme highest tide levels. The probability distributions considered in this research were Generalized Extreme Value(GEV), Gumbel, and Weibull distribution. For each of these distributions, three parameter estimation methods, i.e. the method of moments, maximum likelihood and probability weighted moments, were applied. Chi-square and Kolmogorov-Smirnov goodness-offit tests were performed, and the assumed distribution was accepted at the confidence level 95%. Gumbel distribution which best fits to the 22 tidal station was selected as the most probable parent distribution, and optimally estimated parameters and extreme highest tide level with various return periods were presented. The extreme values of Incheon, Cheju, Yeosu, Pusan, and Mukho, which estimated by Shim et al.(1992) are lower than that of this result.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.31 no.2
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• pp.50-61
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• 2019

The aspects of typhoon-induced surges were classified into three types at the Western coast, and their characteristics were examined. The typhoons OLGA (9907) and KOMPASU (1007) were the representative steep types. As they pass close to the coasts with fast translation velocity, the time of maximum surge is unrelated to tidal phase. However, typhoons PRAPIROON (0012) and BOLAVEN (1215) were the representative mild types, which pass at a long distance to the coasts with slow translation velocity, and were characterized by having maximum surge time is near low tide. Meanwhile, typhoons MUIFA (1109) and WINNIE (9713) can be classified into mild types, but they do not show the characteristics of the mild type. Thus they are classified into propagative type, which are propagated from the outside. Analyzing the annual highest high water level data, the highest water level ever had been recorded when the WINNIE (9713) had attacked. At that time, severe astronomical tide condition overlapped modest surge. Therefore, if severe astronomical tide encounter severe surge in the future, tremendous water level may be formed with very small probability. However, considering that most of the huge typhoons are mild type, time of maximum surge tends to occur at low tide. In case of estimating the extreme water level by a numerical simulation, it is necessary not only to apply various tide conditions and accompanying tide-modulated surge, but also to scrutinize typhoon parameters such as translation velocity and so on.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.5
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• pp.322-330
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• 2020

Modeling for outliers in time series was carried out using the MSL and extreme high, low tide levels (EHL, HLL) data set in the Busan and Mokpo stations. The time-series model is seasonal ARIMA model including the components of the AO (additive outliers) and LS (level shift). The optimal model was selected based on the AIC value and the model parameters were estimated using the 'tso' function (in 'tsoutliers' package of R). The main results by the model application, i.e.. outliers and level shift detections, are as follows. (1) The two AO are detected in the Busan monthly EHL data and the AO magnitudes were estimated to 65.5 cm (by typhoon MAEMI) and 29.5 cm (by typhoon SANBA), respectively. (2) The one level shift in 1983 is detected in Mokpo monthly MSL data, and the LS magnitude was estimated to 21.2 cm by the Youngsan River tidal estuary barrier construction. On the other hand, the RMS errors are computed about 1.95 cm (MSL), 5.11 cm (EHL), and 6.50 cm (ELL) in Busan station, and about 2.10 cm (MSL), 11.80 cm (EHL), and 9.14 cm (ELL) in Mokpo station, respectively.