Special Issue "Coastal Hazards Related to Water"

Special Issue Editor

Guest Editor
Prof. Rick Luettich

University of North Carolina at Chapel Hill, Institute of Marine Sciences, 3431 Arendell Street, Morehead City, NC 28557, USA
Website 1 | Website 2 | E-Mail
Interests: coastal hazards; storm surge modeling; coastal hydrodynamics; coastal risk assessment, risk reduction and resilience; coupled physical-biological processes.

Special Issue Information

Dear Colleagues,

Water draws us to the coast, yet its destructive and life-threatening power poses the principal hazard to life, property, and economies in much of the world’s coastal zone. 2017 was another year of intense tropical cyclone activity, especially in the Atlantic Basin, with devastating consequences throughout the Caribbean, parts of the US, and even the British Isles. Globally, severe tropical and extra-tropical storms continue to cause deaths, massive destruction, and provide constant reminders of the escalating risk associated with living in the coastal zone. The continued growth in commerce, infrastructure, and population; relative sea level rise; and the impacts of a warming climate on storm characteristics are all contributing to an increase in the risk associated with living at the coast. As we seek to manage this risk and create more resilient coastal communities, it is essential that we continue to improve our understanding of and skill in predicting water-related hazards and the efficacy of all potential mitigating measures.

This Special Issue will build on the very successful JMSE issue "Coastal Hazards Related to Storm Surge", and is envisioned as a forum for documenting advances in the state of the art in water-related coastal hazards associated with severe storms, whether attributable to storm surge, surface waves, or precipitation-based flooding. Contributions are encouraged in topics including:

  • improved understanding of coastal hazards;
  • improved coastal hazard predictive capabilities;
  • hydrologic, surge, and wave models, particularly coupled models;
  • climatic and relative sea level change influences on coastal hazards;
  • coastal hazards statistics;
  • improved solution algorithms for coastal hazard models, particularly for new computer architectures;
  • deterministic or probabilistic event-based forecasting;
  • novel solutions for coastal hazard reduction;
  • quantifying the effectiveness of nature-based coastal hazard reduction;
  • surrogate modeling of coastal hazards, and
  • process-based and applied studies.

Prof. Dr. Rick Luettich
Guest Editor

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 papers will be 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. Journal of Marine Science and Engineering is an international peer-reviewed open access quarterly 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 350 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

  • coastal hazards
  • coastal flooding
  • storm surge
  • waves
  • hydrologic flooding
  • modeling
  • coastal hazard reduction
  • nature-based solutions
  • storm surge barriers
  • tropical cyclones
  • extra-tropical storms
  • hurricanes
  • coastal storms
  • sea level rise
  • climate change

Published Papers (3 papers)

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Research

Open AccessArticle Frequency Analysis of Storm-Surge-Induced Flooding for the Huangpu River in Shanghai, China
J. Mar. Sci. Eng. 2018, 6(2), 70; https://doi.org/10.3390/jmse6020070
Received: 14 May 2018 / Revised: 1 June 2018 / Accepted: 5 June 2018 / Published: 11 June 2018
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Abstract
Shanghai, as a coastal city, is vulnerable to various types of flooding. The floodwalls along the Huangpu River provide protection against typhoon-induced flooding. However, there is limited insight into the actual safety level of the flood defences in Shanghai, and recent failures have
[...] Read more.
Shanghai, as a coastal city, is vulnerable to various types of flooding. The floodwalls along the Huangpu River provide protection against typhoon-induced flooding. However, there is limited insight into the actual safety level of the flood defences in Shanghai, and recent failures have highlighted their vulnerability. Therefore, the aims of this paper are to derive a series of new flood frequency curves for the Huangpu River, and to evaluate the level of protection of the floodwall system. This paper analysed over 100 years (1912–2013) of annual maximum water levels for three stations at near-sea, mid-stream and inland locations along the Huangpu River. Best-fit curves were determined for a number of selected probability distributions using statistical performance indicators. As a result, new flood frequency curves of the water levels for different storm surge return periods were produced. The results showed that generalised extreme value (GEV) was identified as the most suitable probability distribution for the datasets. Analysis showed that the current design water levels correspond to exceedance probabilities of 1/500 per year at the near-sea and mid-stream stations, and no more than 1/50 per year at the inland station of the Huangpu River, whereas the intended safety standard is 1/1000 per year. A comparison of the findings with a dataset of the crest heights of the floodwalls showed that the current protection level of the floodwalls along the Huangpu River is expected to be around 1/50 per year in terms of overtopping for the lowest sections. The results of this study can be utilized to provide future recommendations for flood risk management in Shanghai. Full article
(This article belongs to the Special Issue Coastal Hazards Related to Water)
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Open AccessArticle Simulating Storm Surge Impacts with a Coupled Atmosphere-Inundation Model with Varying Meteorological Forcing
J. Mar. Sci. Eng. 2018, 6(2), 35; https://doi.org/10.3390/jmse6020035
Received: 14 February 2018 / Revised: 8 March 2018 / Accepted: 26 March 2018 / Published: 5 April 2018
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Abstract
Storm surge events have the potential to cause devastating damage to coastal communities. The magnitude of their impacts highlights the need for increased accuracy and real-time forecasting and predictability of storm surge. In this study, we assess two meteorological forcing configurations to hindcast
[...] Read more.
Storm surge events have the potential to cause devastating damage to coastal communities. The magnitude of their impacts highlights the need for increased accuracy and real-time forecasting and predictability of storm surge. In this study, we assess two meteorological forcing configurations to hindcast the storm surge of Hurricane Sandy, and ultimately support the improvement of storm surge forecasts. The Weather Research and Forecasting (WRF) model is coupled to the ADvanced CIRCulation Model (ADCIRC) to determine water elevations. We perform four coupled simulations and compare storm surge estimates resulting from the use of a parametric vortex model and a full-physics atmospheric model. One simulation is forced with track-based meteorological data calculated from WRF, while three simulations are forced with the full wind and pressure field outputs from WRF simulations of varying resolutions. Experiments were compared to an ADCIRC simulation forced by National Hurricane Center best track data, as well as to station observations. Our results indicated that given accurate meteorological best track data, a parametric vortex model can accurately forecast maximum water elevations, improving upon the use of a full-physics coupled atmospheric-surge model. In the absence of a best track, atmospheric forcing in the form of full wind and pressure field from a high-resolution atmospheric model simulation prove reliable for storm surge forecasting. Full article
(This article belongs to the Special Issue Coastal Hazards Related to Water)
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Open AccessArticle Sub-Ensemble Coastal Flood Forecasting: A Case Study of Hurricane Sandy
J. Mar. Sci. Eng. 2017, 5(4), 59; https://doi.org/10.3390/jmse5040059
Received: 15 October 2017 / Revised: 27 November 2017 / Accepted: 28 November 2017 / Published: 15 December 2017
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Abstract
In this paper, it is proposed that coastal flood ensemble forecasts be partitioned into sub-ensemble forecasts using cluster analysis in order to produce representative statistics and to measure forecast uncertainty arising from the presence of clusters. After clustering the ensemble members, the ability
[...] Read more.
In this paper, it is proposed that coastal flood ensemble forecasts be partitioned into sub-ensemble forecasts using cluster analysis in order to produce representative statistics and to measure forecast uncertainty arising from the presence of clusters. After clustering the ensemble members, the ability to predict the cluster into which the observation will fall can be measured using a cluster skill score. Additional sub-ensemble and composite skill scores are proposed for assessing the forecast skill of a clustered ensemble forecast. A recently proposed method for statistically increasing the number of ensemble members is used to improve sub-ensemble probabilistic estimates. Through the application of the proposed methodology to Sandy coastal flood reforecasts, it is demonstrated that statistics computed using only ensemble members belonging to a specific cluster are more representative than those computed using all ensemble members simultaneously. A cluster skill-cluster uncertainty index relationship is identified, which is the cluster analog of the documented spread-skill relationship. Two sub-ensemble skill scores are shown to be positively correlated with cluster forecast skill, suggesting that skillfully forecasting the cluster into which the observation will fall is important to overall forecast skill. The identified relationships also suggest that the number of ensemble members within in each cluster can be used as guidance for assessing the potential for forecast error. The inevitable existence of ensemble member clusters in tidally dominated total water level prediction systems suggests that clustering is a necessary post-processing step for producing representative and skillful total water level forecasts. Full article
(This article belongs to the Special Issue Coastal Hazards Related to Water)
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