2021 Fiscal Year Final Research Report

Probabilistic projection of future change in mega storm surge risk by storm surge model improvement and multi ensemble experiments

Research Project

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Project/Area Number	19H02253
Research Category	Grant-in-Aid for Scientific Research (B)
Allocation Type	Single-year Grants
Section	一般
Review Section	Basic Section 22040:Hydroengineering-related
Research Institution	Kansai University
Principal Investigator	YASUDA TOMOHIRO 関西大学, 環境都市工学部, 准教授 (60378916)
Co-Investigator(Kenkyū-buntansha)	中條壮大大阪市立大学, 大学院工学研究科, 准教授 (20590871) 金洙列熊本大学, くまもと水循環・減災研究教育センター, 准教授 (60508696) 志村智也京都大学, 防災研究所, 准教授 (70789792) 森信人京都大学, 防災研究所, 教授 (90371476)
Project Period (FY)	2019-04-01 – 2022-03-31
Keywords	高潮 / 気候変動 / アンサンブル予測 / ディープラーニング / 確率台風モデル
Outline of Final Research Achievements	The purpose of this study is to predict future changes in probabilistic major storm surge risk. To achieve this goal, we have improved the storm surge model, stochastic typhoon model, and neural network model, and conducted multiple ensemble experiments to estimate the future changes in storm surge height with a high degree of scientific confidence. The following research projects have been conducted: (1) multiple ensemble storm surge simulations and event attribution for extreme typhoons causing storm surge disasters, (2) improvement and application of a global stochastic typhoon model, (3) development of a deep learning storm surge prediction model, and (4) development of a neural network model for storm surge prediction. (3) development of a deep learning storm surge forecasting model, and (4) introduction of a wave overtopping/wave overflow transition model into a coupled storm surge/wave model.
Free Research Field	海岸工学
Academic Significance and Societal Importance of the Research Achievements	台風を人工的に発生させる確率台風モデルはいくつか開発されているが，台風特性に海面水温分布を考慮して温暖化の影響を反映できるモデルはない．気象データを入力して高潮水位の最大値を予測するニューラルネットワークモデルはいくつかあるが，高潮水位予測にディープラーニング（深層学習）を適用した事例はない．さらに，高潮と波浪の相互作用，越波と越流の遷移過程，高潮の河川遡上を個別にモデル化した事例はあるが，すべてを統合したモデルはない．