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Water
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Simulation and Numerical Analysis of Storm Surges
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Simulation and Numerical Analysis of Storm Surges

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Oceans and Coastal Zones".

Deadline for manuscript submissions: closed (31 December 2024) | Viewed by 3307

Special Issue Editors

Dr. Stephen Medeiros

E-Mail Website
Guest Editor
Civil Engineering Department, College of Engineering, Embry-Riddle Aeronautical University, Daytona Beach, FL. USA
Interests: hurricane storm surge; hydrology; surface roughness; remote sensing; lidar; hydrodynamics; machine learning
Special Issues, Collections and Topics in MDPI journals
Dr. Matthew Bilskie

E-Mail Website
Guest Editor
School of Environmental, Civil, Agricultural, and Mechanical Engineering, University of Georgia, Athens, GA, USA
Interests: coastal resiliency; stakeholder engagement; coastal flooding; sea level rise; stormwater

Special Issue Information

Dear Colleagues,

Developing computer models for simulating hurricane storm surges is critical to assessing and improving the resilience of coastal communities. Results such as inundation patterns and wave characteristics produced by these models are used in coastal engineering, evacuation studies, damage assessments, infrastructure planning, and emergency management. This Special Issue offers a platform to publish advances in the development, validation, and computation of numerical hydrodynamic models focused on hurricane storm surge simulations. We welcome manuscripts focused on mesh development, topobathymetric characterization of the domain, nodal attributes and parameters, interpolation methods, the characterization of forcing mechanisms, innovative validation techniques and metrics, sensitivity analyses, and any other topic related to numerical storm surge modeling worldwide. Manuscripts focused on machine learning, artificial intelligence, and remote sensing are welcome but they must explicitly describe how the use of those technologies supports numerical simulations.

Dr. Stephen Medeiros
Dr. Matthew Bilskie
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • hurricane storm surge
  • simulation models
  • coastal communities
  • inundation patterns
  • wave characteristics
  • numerical modelling
  • high-performance computing
  • hydrodynamics
  • tides
  • model validation
  • sea level rise

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Published Papers (2 papers)

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Research

29 pages, 12077 KiB  
Article
Predictability of Hurricane Storm Surge: An Ensemble Forecasting Approach Using Global Atmospheric Model Data
by Rebecca E. Morss, David Ahijevych, Kathryn R. Fossell, Alex M. Kowaleski and Christopher A. Davis
Water 2024, 16(11), 1523; https://doi.org/10.3390/w16111523 - 25 May 2024
Cited by 1 | Viewed by 1505
Abstract
Providing storm surge risk information at multi-day lead times is critical for hurricane evacuation decisions, but predictability of storm surge inundation at these lead times is limited. This study develops a method to parameterize and adjust tropical cyclones derived from global atmospheric model [...] Read more.
Providing storm surge risk information at multi-day lead times is critical for hurricane evacuation decisions, but predictability of storm surge inundation at these lead times is limited. This study develops a method to parameterize and adjust tropical cyclones derived from global atmospheric model data, for use in storm surge research and prediction. We implement the method to generate storm tide (surge + tide) ensemble forecasts for Hurricane Michael (2018) at five initialization times, using archived operational ECMWF ensemble forecasts and the dynamical storm surge model ADCIRC. The results elucidate the potential for extending hurricane storm surge prediction to several-day lead times, along with the challenges of predicting the details of storm surge inundation even 18 h before landfall. They also indicate that accurately predicting Hurricane Michael’s rapid intensification was not needed to predict the storm surge risk. In addition, the analysis illustrates how this approach can help identify situationally and physically realistic scenarios that pose greater storm surge risk. From a practical perspective, the study suggests potential approaches for improving real-time probabilistic storm surge prediction. The method can also be useful for other applications of atmospheric model data in storm surge research, forecasting, and risk analysis, across weather and climate time scales. Full article
(This article belongs to the Special Issue Simulation and Numerical Analysis of Storm Surges)
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16 pages, 5659 KiB  
Article
Improvement in Storm Surge Numerical Forecasting Based on Wave Buoys Data
by Cifu Fu, Honglin Guo, Kaikai Cheng and Tao Li
Water 2024, 16(8), 1079; https://doi.org/10.3390/w16081079 - 10 Apr 2024
Viewed by 1227
Abstract
The maximum wind speed radius of a strong typhoon making landfall is an important factor influencing the numerical forecasting of storm surges. A method for inverting the maximum wind speed radius of typhoons based on wave buoys data was designed to significantly reduce [...] Read more.
The maximum wind speed radius of a strong typhoon making landfall is an important factor influencing the numerical forecasting of storm surges. A method for inverting the maximum wind speed radius of typhoons based on wave buoys data was designed to significantly reduce the error in 24 h storm surge forecasting in this paper, and an operation scheme was proposed to enhance the storm surge numerical forecasting system based on this method. Hangzhou Bay and the Yangtze River Estuary, which have been frequently impacted by typhoons over the past five years, were selected as the research area. Common schemes for the maximum wind speed radius were analyzed, and five ladder schemes (10, 15, 20, 25, and 30 km) were established for wave and storm surge numerical model verification of Typhoon Muifa in 2022. Based on a comparison of the wave hindcast results and wave buoys observation data, the wave hindcast result of the commonly used scheme (30 km) was significantly greater than that of the observation data, and the optimal scheme (15 km) closest to the observation data could be determined during the 48 h warning period. Moreover, it was difficult to identify the optimal scheme during the 48 h warning period based on the storm surge hindcast results. A 24 h storm surge numerical forecasting test was performed with the commonly used scheme (30 km) and the optimal scheme (15 km). The results showed that the root mean square error (RMSE) of the optimal scheme (15 km) was 34% lower than that of the commonly used scheme (30 km), while the maximum storm surge error was also reduced from 47.7% for the commonly adopted scheme (30 km) to 11.8% for the optimal scheme (15 km). The maximum storm surges under the optimal scheme (15 km) along Hangzhou Bay and the Yangtze River Estuary ranged from 1.9 to 2.2 m, which were closer to the observation data, and the maximum storm surge under the commonly used scheme (30 km) was 0.8~1.2 m greater than that under the optimal scheme (15 km). Full article
(This article belongs to the Special Issue Simulation and Numerical Analysis of Storm Surges)
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