Development and Application of Storm Tide and Wave Models

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Ocean Engineering".

Deadline for manuscript submissions: closed (8 January 2021) | Viewed by 3074

Special Issue Editors


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Guest Editor
Department of Civil, Environmental and Ocean Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, USA
Interests: flood hazard assessment; nature-based flood mitigation; hurricane storm surge; wave setup, wave–current interaction; coastal circulation

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Guest Editor
Center for Water Cycle Marine Environment and Disaster Management (CWMD), Department of Civil Environmental Engineering and Architecture, Kumamoto University, 2-39-1 Kurokami, Chuo-ku, Kumamoto-shi, Japan
Interests: fluid dynamics and hydrodynamics; combined numerical modelling for coasts (surges, waves, tides, and sediments); storm surge modelling; wave modelling; coastal flood modelling

Special Issue Information

Dear Colleagues,

Extreme sea levels induced by storm tides and waves are among the most destructive natural hazards worldwide, causing coastal flooding, severe erosion, and damage to coastal and offshore structures. In recent years, record-breaking extreme sea levels have been witnessed due to intensified hurricanes/typhoons/cyclones and winter storms. For an effective mitigation of, response to, and recovery from such hazards, it is essential to improve our modeling capabilities and understanding of storm tides and waves. Despite recent advances in model development, there is still a growing demand for new models that are computationally cost-effective yet efficiently resolve/parameterize complex physical processes. Additionally, studies of past storm tide and wave events are of great interest to coastal managers, decision makers, and researchers, as such studies reveal the level of hazards, vulnerability, and risk in coastal areas.

This Special Issue aims to compile the latest research in storm tide and wave modeling using new or existing dynamic and statistical models and artificial intelligence methods. We welcome articles focused on the development and validation of new models or application of existing models to hindcasts of historical events. Examples of topics include but are not limited to:

  • Artificial intelligence for storm surge, tide, and wave prediction/forecast;
  • Statistical modeling;
  • Improved physics and numerical methods for dynamic models;
  • Computationally fast models;
  • Effects of wave–current interactions on storm tide and wave;
  • Coastal flooding due to storm tide and wave overtopping/runup, and their interactions with river flow;
  • High-resolution and three-dimensional modeling;
  • Model coupling.

We look forward to receiving contributions to this Special Issue in the form of research articles and reviews.

Dr. Reza Marsooli
Dr. Sooyoul Kim
Guest Editors

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Keywords

  • storm surge
  • storm tide
  • wave
  • coastal flooding
  • modeling

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Published Papers (1 paper)

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Research

27 pages, 5051 KiB  
Article
Development of GMDH-Based Storm Surge Forecast Models for Sakaiminato, Tottori, Japan
by Sooyoul Kim, Hajime Mase, Nguyen Ba Thuy, Masahide Takeda, Cao Truong Tran and Vu Hai Dang
J. Mar. Sci. Eng. 2020, 8(10), 797; https://doi.org/10.3390/jmse8100797 - 14 Oct 2020
Cited by 7 | Viewed by 2534
Abstract
The current study developed storm surge hindcast/forecast models with lead times of 5, 12, and 24 h at the Sakaiminato port, Tottori, Japan, using the group method of data handling (GMDH) algorithm. For training, local meteorological and hydrodynamic data observed in Sakaiminato during [...] Read more.
The current study developed storm surge hindcast/forecast models with lead times of 5, 12, and 24 h at the Sakaiminato port, Tottori, Japan, using the group method of data handling (GMDH) algorithm. For training, local meteorological and hydrodynamic data observed in Sakaiminato during Typhoons Maemi (2003), Songda (2004), and Megi (2004) were collected at six stations. In the forecast experiments, the two typhoons, Maemi and Megi, as well as the typhoon Songda, were used for training and testing, respectively. It was found that the essential input parameters varied with the lead time of the forecasts, and many types of input parameters relevant to training were necessary for near–far forecasting time-series of storm surge levels. In addition, it was seen that the inclusion of the storm surge level at the input layer was critical to the accuracy of the forecast model. Full article
(This article belongs to the Special Issue Development and Application of Storm Tide and Wave Models)
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