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.

론 최근 세계적으로 지구 온난화 등의 여러 문제로 인한 이상기 후에 따른 최대급 강도의 재해가 빈번히 발생되어 수많은 인명 및 재산피해가

The coastal area of Japan has been damaged yearly by storm surges and flooding disasters in the past, including those associated with typhoons. In addition, the scale of damage is increasing rapidly due to the changing global climate and environment. As disasters due to storm surges become increasingly unpredictable, more measures should be taken to prevent serious damage and casualties. The Japanese government published a hazard map manual in 2015 and obligates the creation of a hazard map based on a parametric model as a measure to reduce high-scale storm surges. Parametric model (typhoon model) accounting for the topographical influences of the surroundings is essential for calculating the wind field of a typhoon. In particular, it is necessary to calculate the wind field using a parametric model in order to simulate a virtual typhoon (the largest typhoon) and to improve the reproducibility. Therefore, in this study, the aim was to establish a hazard map by assuming storm surges of the largest scale and to propose a parametric model that considers the changing shape of typhoons due to topography. The main objectives of this study were to analyze the characteristics of typhoons due to pass through Japan, to develop a parametric model using a combination of Holland’s and Myers’s models that is appropriate for the largest scale of typhoon, and to analyze the parameters of Holland’s model using grid point values (GPVs). Finally, we aimed to propose a method that considers the changing shape of typhoons due to topography. The modeling outcomes of tide levels and storm surge heights show that the reproduced results obtained by the analysis method proposed in this study are more accurate than those obtained using GPVs. In addition, the reproducibility of the proposed model was evaluated showing the high and excellent reproducibility of storm surge height according to the geographic characteristics.

Yoon, I.J. and Hong, J.-W., 2019. Development of disaster prevention system based on deep neural network using deep learning with dropout. In: Lee, J.L.; Yoon, J.-S.; Cho, W.C.; Muin, M., and Lee, J. (eds.), The 3rd International Water Safety Symposium. Journal of Coastal Research, Special Issue No. 91, pp. 186-190. Coconut Creek (Florida), ISSN 0749-0208.Recently, unprecedented abnormal climates and disasters of the greatest intensity have increased worldwide due to various problems such as global warming. In particular, from the Great East Japan Eartquake in March 2011, Japan has suffered from the highest frequency of disasters (floods, earthquakes, etc.) and the single largest external force (tsunami) that have not been experienced before. For such disasters of the maximum frequency, the hard and soft countermeasures alone have limitations and it is critical to integrate and appropriately harmonize them with various disaster prevention systems.The purpose of this study is to develop a flood risk management information system to support natural disaster mitigation measures. The main function of the disaster prevention support system is to select the most similar one to a typhoon before landing based on past typhoon data and artificial intelligence (AI) technology and to present guidelines for prior disaster prevention activities according to various disaster factors caused by the selected typhoon (e.g., water level and river flow rate). A database was constructed for 189 typhoons that directly or indirectly affected the target area among those that occurred between 1950 and 2017, and a system was developed by applying AI technologies such as Deep Neural Network (DNN) and Dropout. The main parameters of this database are typhoon route, central pressure, moving speed, precipitation, water level, and flow rate. For the grid sizes of the model, 2° and 1° in longitude and in latitude were considered. The system search results showed the highest reliability of the model at the grid size of 1° when only typhoon route, center pressure, and moving speed were considered compared to the results of considering other parameters.