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

Deadline for manuscript submissions: 25 March 2025 | Viewed by 19000

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Special Issue Editor

Dr. Deniz Velioglu Sogut

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Guest Editor

Ocean Engineering and Marine Sciences, Florida Institute of Technology, 150 W University Blvd, Melbourne, FL 32901, USA
Interests: nearshore hydrodynamics; coastal hydrodynamics; coastal morphodynamics; wave-induced scour; wave–current–structure interactions; coastal resilience; nature-based solutions (NBS); tsunami; storm surge; wave energy; fluid mechanics; computational fluid dynamics (CFD); high-performance computing (HPC); data analysis and processing

Special Issue Information

Dear Colleagues,

There has been a substantial increase in the intensity, frequency, and duration of extreme natural events (e.g., hurricanes, storms, tsunamis, and landslides) over the past four decades. Given the high population concentration in low-elevation coastal zones, the most pressing challenge for coastal communities is to strengthen their resilience to future coastal disasters. Understanding risk and planning actions ahead of time is critical for improving the ability to adapt to changing conditions and rapidly recovering from disruption caused by these threats. A proper disaster response will reduce disaster-related fatalities, ensure the economic sustainability of coastal communities, and help to maintain coastal ecosystems. This Special Issue aims to address the impact of extreme natural events on coastal communities and promote coastal disaster preparedness. Original research articles and reviews are all welcome. Research areas may include (but are not limited to) pre-field, field, post-field surveys, as well as analytical, numerical, and experimental approaches, to assess coastal disaster impacts and responses.

We look forward to receiving your contributions.

Dr. Deniz Velioglu Sogut
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 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. Journal of Marine Science and Engineering is an international peer-reviewed open access monthly 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
tsunami
scour
flooding
nature-based solutions
vegetation
artificial reef
coastal resilience
field survey

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Published Papers (11 papers)

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Research

Jump to: Review

27 pages, 8065 KiB

Open AccessArticle

Structural Failure Modes of Single-Story Timber Houses Under Tsunami Loads Using ASCE 7’S Energy Grade Line Analysis

by Darko Otey, Juan Carlos Vielma and Patricio Winckler

J. Mar. Sci. Eng. 2025, 13(3), 484; https://doi.org/10.3390/jmse13030484 - 28 Feb 2025

Viewed by 278

Abstract

The structural response of single-story timber houses subjected to the 27 February 2010 Chile tsunami is studied in San Juan Bautista, an island town located nearly 600 km westward from the earthquake’s rupture source, in the Pacific Ocean. The ASCE 7-22 energy grade line analysis (EGLA) is used to calculate flow depths and velocities as functions of the topography and recorded runup. To understand the structural response along the topography, reactions and displacements are computed at six positions every 50 m from the coastline. Houses are modeled using the Robot software, considering dead and live loads cases under the Load and Resistance Factor Design (LRFD) philosophy. The results show that houses located near the coastline experience severe displacements and collapse due to a combination of hydrodynamic forces, drag and buoyancy, which significantly reduces the efficiency of the foundations’ anchorage. Structures far from the coastline are less exposed to reduced velocities, resulting in decreased displacements, structural demand and a tendency to float. Finally, the methodology is validated by applying a nonlinear analysis of the structures subjected to tsunami loads at the different positions considered in this study. Despite their seismic resistance, lightweight timber houses are shown to not be suitable for areas prone to tsunamis. Tsunami-resilient design should therefore consider heavier and more rigid materials in flooding areas and the relocation of lightweight structures in safe zones. Full article

(This article belongs to the Special Issue Coastal Disaster Assessment and Response)

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19 pages, 4376 KiB

Open AccessArticle

Tracing the 2018 Sulawesi Earthquake and Tsunami’s Impact on Palu, Indonesia: A Remote Sensing Analysis

by Youshuang Hu, Aggeliki Barberopoulou and Magaly Koch

J. Mar. Sci. Eng. 2025, 13(1), 178; https://doi.org/10.3390/jmse13010178 - 19 Jan 2025

Viewed by 998

Abstract

The 2018 Sulawesi Earthquake and Tsunami serves as a backdrop for this work, which employs simple and straightforward remote sensing techniques to determine the extent of the destruction and indirectly evaluate the region’s vulnerability to such catastrophic events. Documenting damage from tsunamis is only meaningful shortly after the disaster has occurred because governmental agencies clean up debris and start the recovery process within a few hours after the destruction has occurred, deeming impact estimates unreliable. Sentinel-2 and Maxar WorldView-3 satellite images were used to calculate well-known environmental indices to delineate the tsunami-affected areas in Palu, Indonesia. The use of NDVI, NDSI, and NDWI indices has allowed for a quantifiable measure of the changes in vegetation, soil moisture, and water bodies, providing a clear demarcation of the tsunami’s impact on land cover. The final tsunami inundation map indicates that the areas most affected by the tsunami are found in the urban center, low-lying regions, and along the coast. This work charts the aftermath of one of Indonesia’s recent tsunamis but may also lay the groundwork for an easy, handy, and low-cost approach to quickly identify tsunami-affected zones. While previous studies have used high-resolution remote sensing methods such as LiDAR or SAR, our study emphasizes accessibility and simplicity, making it more feasible for resource-constrained regions or rapid disaster response. The scientific novelty lies in the integration of widely used environmental indices (dNDVI, dNDWI, and dNDSI) with threshold-based Decision Tree classification to delineate tsunami-affected areas. Unlike many studies that rely on advanced or proprietary tools, we demonstrate that comparable results can be achieved with cost-effective open-source data and straightforward methodologies. Additionally, we address the challenge of differentiating tsunami impacts from other phenomena (et, liquefaction) through index-based thresholds and propose a framework that is adaptable to other vulnerable coastal regions. Full article

(This article belongs to the Special Issue Coastal Disaster Assessment and Response)

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16 pages, 10055 KiB

Open AccessArticle

Coastal Protection for Tsunamis

by Angela Santos and Nelson Mileu

J. Mar. Sci. Eng. 2024, 12(12), 2349; https://doi.org/10.3390/jmse12122349 - 21 Dec 2024

Viewed by 621

Abstract

Previous research showed that a tsunami similar to the 1755 event would inundate Caxias’ low-ground areas in Oeiras municipality, Portugal. However, the streets of downtown Caxias were not well reproduced, which is a limitation of the area’s mitigation strategies and evacuation plan. For these reasons, new Lidar data were used for the first time in Portugal. The new local topography data allowed the construction of a more accurate DEM, which was used in the tsunami numerical model to update and improve the inundation results. As a complement, a field survey was conducted in several locations to assess coastal features and protection. The numerical model results show that low-ground areas up to 6 m in height were inundated by the tsunami, including the residential area, the road, and the railway. To stop the tsunami waves from inundating these areas, it is proposed that the construction of more sea walls up to 7 m in height and a third bridge over the Barcarena Stream, only for pedestrians, ranging from 5 to 7 m in height, which will serve as a gate for the incoming tsunami waves. These coastal protections should be part of the strategy to mitigate coastal overtopping (winter storm surges and tsunamis) not only in Caxias but also in other coastal zones. Full article

(This article belongs to the Special Issue Coastal Disaster Assessment and Response)

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19 pages, 7507 KiB

Open AccessArticle

Spatiotemporal Climatology of Georgia Tropical Cyclones and Associated Rainfall

by Reilly Corkran, Jill Trepanier and Vincent Brown

J. Mar. Sci. Eng. 2024, 12(10), 1693; https://doi.org/10.3390/jmse12101693 - 24 Sep 2024

Viewed by 1496

Abstract

Tropical cyclones (TCs), often characterized by high wind speeds and heavy rainfall, cause widespread devastation, affecting millions of people and leading to economic losses worldwide. TC-specific research in Georgia is scarce, likely due to the minimal geographical extent of its coast and the infrequency of direct landfalls. Research on Georgia TCs does not account for storms that make landfall in other southeastern states (e.g., Florida) and continue north, northeast, or northwest into Georgia. This study used the North Atlantic Basin hurricane database (HURDAT2) to quantify the spatiotemporal patterns of direct and indirect landfalling of Georgia tropical cyclones (>16 ms⁻¹) from 1851 to 2021. TC-induced rainfall was also quantified using rainfall data (nClimGrid-Daily and nClimGrid) from 1951 to 2021 to estimate the proportion of Georgia’s total annual and monthly rainfall attributed to TCs. A multi-methodological approach, incorporating statistics and mapping, is employed to assess the trends of Georgia’s tropical cyclones and the associated rainfall. The study analyzed 113 TCs and found that, on average, less than one TC annually (

\bar{x}

= 0.66) traverses the state. September averaged the highest percentage (25%) of TC-induced rainfall, followed by October (14%), and August (13%). This pattern aligns with the TC season, with the highest frequency of TCs occurring in September (n = 35), followed by August (n = 25), and October (n = 18). We found that 10% of tropical storms make landfall on the coastline, while the remaining 91% enter Georgia by making landfall in Florida (92%), Louisiana (7%), or South Carolina (1%) first. A threat of TCs during the peak of the season emphasizes the importance of heightened awareness, increased planning practices, and resource allocation during these periods to protect Georgia’s history and natural beauty, and its residents. Full article

(This article belongs to the Special Issue Coastal Disaster Assessment and Response)

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20 pages, 5149 KiB

Open AccessArticle

Evaluating Vegetation Effects on Wave Attenuation and Dune Erosion during Hurricane

by Mengdi Ma, Wenrui Huang, Sungmoon Jung, Christopher Oslon, Kai Yin and Sudong Xu

J. Mar. Sci. Eng. 2024, 12(8), 1326; https://doi.org/10.3390/jmse12081326 - 6 Aug 2024

Cited by 2 | Viewed by 1705

Abstract

This study employs the XBeach surfbeat model (XBSB) to explore the effects of vegetation on wave attenuation and dune erosion in a case study of Mexico Beach during Hurricane Michael. The XBSB model was validated against laboratory experiments of wave-induced dune erosion and wave attenuation by vegetation. In the case study of vegetation on dunes in Mexico Beach during Hurricane Michael, different vegetation drag coefficients were evaluated to investigate the effects of vegetation on wave attenuation and dune erosion. LiDAR data of dune profiles before and after Hurricane Michael were used for model validation. The findings reveal that vegetation on dunes significantly affects wave attenuation and dune erosion. Under vegetated conditions, as the vegetation drag coefficient value increases, wave attenuation also increases, leading to a reduction of dune erosion. An increase in vegetation density enhances wave attenuation in the vegetated area, including reductions in significant wave height and flow velocity. However, the rate of change in attenuation decreases as the vegetation density increases. Through simulations under regular wave condition on Mexico Beach, an optimal vegetation density was identified as 800 units/m². Beyond this density, additional vegetation does not substantially improve wave attenuation. Furthermore, the position of the dune crest elevation is related to the location where the alongshore flow velocity begins to decrease. The findings highlight the essential role of coastal vegetation in enhancing coastal resilience against hurricanes. Full article

(This article belongs to the Special Issue Coastal Disaster Assessment and Response)

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22 pages, 12698 KiB

Open AccessArticle

Non-Equilibrium Scour Evolution around an Emerged Structure Exposed to a Transient Wave

by Deniz Velioglu Sogut, Erdinc Sogut, Ali Farhadzadeh and Tian-Jian Hsu

J. Mar. Sci. Eng. 2024, 12(6), 946; https://doi.org/10.3390/jmse12060946 - 5 Jun 2024

Cited by 1 | Viewed by 1073

Abstract

The present study evaluates the performance of two numerical approaches in estimating non-equilibrium scour patterns around a non-slender square structure subjected to a transient wave, by comparing numerical findings with experimental data. This study also investigates the impact of the structure’s positioning on bed evolution, analyzing configurations where the structure is either attached to the sidewall or positioned at the centerline of the wave flume. The first numerical method treats sediment particles as a distinct continuum phase, directly solving the continuity and momentum equations for both sediment and fluid phases. The second method estimates sediment transport using the quadratic law of bottom shear stress, yielding robust predictions of bed evolution through meticulous calibration and validation. The findings reveal that both methods underestimate vortex-induced near-bed vertical velocities. Deposits formed along vortex trajectories are overestimated by the first method, while the second method satisfactorily predicts the bed evolution beneath these paths. Scour holes caused by wave impingement tend to backfill as the flow intensity diminishes. The second method cannot sufficiently capture this backfilling, whereas the first method adequately reflects the phenomenon. Overall, this study highlights significant variations in the predictive capabilities of both methods in regard to the evolution of non-equilibrium scour at low Keulegan–Carpenter numbers. Full article

(This article belongs to the Special Issue Coastal Disaster Assessment and Response)

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15 pages, 4659 KiB

Open AccessArticle

Morphological Changes in Storm Hinnamnor and the Numerical Modeling of Overwash

by Bohyeon Hwang, Kideok Do and Sungyeol Chang

J. Mar. Sci. Eng. 2024, 12(1), 196; https://doi.org/10.3390/jmse12010196 - 22 Jan 2024

Cited by 3 | Viewed by 1357

Abstract

Constant changes occur in coastal areas over different timescales, requiring observation and modeling. Specifically, modeling morphological changes resulting from short-term events, such as storms, is of great importance in coastal management. Parameter calibration is necessary to achieve more accurate simulations of process-based models that focus on specific locations and event characteristics. In this study, the XBeach depth-averaged model was adopted to simulate subaerial data pre- and post-storms, and overwash phenomena were observed using the data acquired through unmanned aerial vehicles. The parameters used for the model calibration included those proposed in previous studies. However, an emphasis was placed on calibrating the parameters related to sediment transport that were directly associated with overwash and deposition. Specifically, the parameters corresponding to the waveform parameters, wave skewness, and wave asymmetry were either integrated or separated to enable an adequate representation of the deposition resulting from overwash events. The performance and sensitivity of the model to changes in volume were assessed. Overall, the waveform parameters exhibit significant sensitivity to volume changes, forming the basis for calibrating the deposition effects caused by overwashing. These results are expected to assist in the more effective selection and calibration of parameters for simulating sediment deposition due to overwash events. Full article

(This article belongs to the Special Issue Coastal Disaster Assessment and Response)

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19 pages, 8091 KiB

Open AccessArticle

Applicability Evaluation of the Global Synthetic Tropical Cyclone Hazard Dataset in Coastal China

by Xiaomin Li, Qi Hou, Jie Zhang, Suming Zhang, Xuexue Du and Tangqi Zhao

J. Mar. Sci. Eng. 2024, 12(1), 73; https://doi.org/10.3390/jmse12010073 - 27 Dec 2023

Viewed by 1370

Abstract

A tropical cyclone dataset is an important data source for tropical cyclone disaster research, and the evaluation of its applicability is a necessary prerequisite. The Global Synthetic Tropical Cyclone Hazard (GSTCH) dataset is a dataset of global tropical cyclone activity for 10,000 years from 2018, and has become accepted as a major data source for the study of global tropical cyclone hazards. On the basis of the authoritative Tropical Cyclone Best Track (TCBT) dataset proposed by the China Meteorological Administration, this study evaluated the applicability of the GSTCH dataset in relation to two regions: the Northwest Pacific and China’s coastal provinces. For the Northwest Pacific, the results show no significant differences in the means and standard deviations of landfall wind speed, landfall pressure, and annual occurrence number between the two datasets at the 95% confidence level. They also show the cumulative distributions of central minimum pressure and central maximum wind speed along the track passed the Kolmogorov–Smirnov (K-S) test at the 95% confidence level, thereby verifying that the GSTCH dataset is consistent with the TCBT dataset at sea-area scale. For China’s coastal provinces, the results show that the means or standard deviations of tropical cyclone characteristics between the two datasets were not significantly different in provinces other than Guangdong and Hainan, and further analysis revealed that the cumulative distributions of the tropical cyclone characteristics in Guangdong and Hainan provinces passed the K-S test at the 95% confidence level, thereby verifying that the GSTCH dataset is consistent with the TCBT dataset at province scale. The applicability evaluation revealed that no significant differences exist between most of the tropical cyclone characteristics in the TCBT and GSTCH datasets, and that the GSTCH dataset is an available and reliable data source for tropical cyclone hazard studies in China’s coastal areas. Full article

(This article belongs to the Special Issue Coastal Disaster Assessment and Response)

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15 pages, 21250 KiB

Open AccessArticle

Assessing Coastal Vulnerability to Storms: A Case Study on the Coast of Thrace, Greece

by Iason A. Chalmoukis

J. Mar. Sci. Eng. 2023, 11(8), 1490; https://doi.org/10.3390/jmse11081490 - 26 Jul 2023

Cited by 2 | Viewed by 1261

Abstract

Climate change is expected to increase the risks of coastal hazards (erosion and inundation). To effectively cope with these emerging problems, littoral countries are advised to assess their coastal vulnerabilities. In this study, coastal vulnerability is first assessed by considering two basic storm-induced phenomena, i.e., erosion and inundation. First, the erosion is computed using the numerical model for Storm-induced BEAch CHange (SBEACH), whereas the inundation is estimated using two different empirical equations for comparison. Then, the integration of the vulnerabilities of both storm-induced impacts associated with the same return period permits the identification of the most hazardous regions. The methodology is applied to the coast of Thrace (Greece). The majority of the coastline is not vulnerable to erosion, except for some steep and narrow beaches and the coast along the city of Alexandroupolis. Beaches with very low heights are highly vulnerable to inundation. Half of the studied coastline is considered highly or very highly vulnerable, whereas the other half is relatively safe. The above results will help decision-makers choose how to invest their resources for preventing damage. Full article

(This article belongs to the Special Issue Coastal Disaster Assessment and Response)

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21 pages, 9815 KiB

Open AccessArticle

Evaluation of Reliquefaction Behavior of Coastal Embankment Due to Successive Earthquakes Based on Shaking Table Tests

by Mintaek Yoo and Sun Yong Kwon

J. Mar. Sci. Eng. 2023, 11(5), 1002; https://doi.org/10.3390/jmse11051002 - 8 May 2023

Viewed by 1608

Abstract

Liquefaction caused by long-term cyclic loads in loose saturated soil can lead to ground subsidence and superstructure failures. To address this issue, this study aimed to emulate the liquefaction phenomenon based on a shaking table test while especially focusing on the soil behavior mechanism due to the reliquefaction effect. Liquefaction and reliquefaction behaviors were analyzed by ground conditions where an embankment was located on the coastal ground. Silica sand was used for the experiment for various thickness and liquefiable conditions, and the embankment model was constructed above the model ground. For seismic waves, sine wave excitation was applied, and a total of five excitations (cases) were conducted. When the upper ground layer consisted of a non-liquefiable layer, liquefaction did not occur due to the first excitations but occurred by the third excitation. The results indicated that as the earthquake was applied, the water level in the liquefiable layer increased to the height of the non-liquefiable layer and liquefaction could occur. It was identified that even if liquefaction did not occur for the main earthquake, liquefaction could occur due to aftershocks caused by a rise in the groundwater level due to a series of earthquakes. In a general seismic design code, liquefaction assessment is performed only for soil layers below the groundwater level; however, when successive earthquakes occur, unexpected liquefaction damage could occur. Therefore, to mitigate the earthquake risk of liquefaction for coastal embankments, it is necessary to evaluate the liquefaction by aftershocks even when the groundwater level of the ground layer under an embankment is low. Full article

(This article belongs to the Special Issue Coastal Disaster Assessment and Response)

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Review

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30 pages, 4130 KiB

Open AccessEditor’s ChoiceReview

Ensemble Neural Networks for the Development of Storm Surge Flood Modeling: A Comprehensive Review

by Saeid Khaksari Nezhad, Mohammad Barooni, Deniz Velioglu Sogut and Robert J. Weaver

J. Mar. Sci. Eng. 2023, 11(11), 2154; https://doi.org/10.3390/jmse11112154 - 11 Nov 2023

Cited by 5 | Viewed by 3256

Abstract

This review paper focuses on the use of ensemble neural networks (ENN) in the development of storm surge flood models. Storm surges are a major concern in coastal regions, and accurate flood modeling is essential for effective disaster management. Neural network (NN) ensembles have shown great potential in improving the accuracy and reliability of such models. This paper presents an overview of the latest research on the application of NNs in storm surge flood modeling and covers the principles and concepts of ENNs, various ensemble architectures, the main challenges associated with NN ensemble algorithms, and their potential benefits in improving flood forecasting accuracy. The main part of this paper pertains to the techniques used to combine a mixed set of predictions from multiple NN models. The combination of these models can lead to improved accuracy, robustness, and generalization performance compared to using a single model. However, generating neural network ensembles also requires careful consideration of the trade-offs between model diversity, model complexity, and computational resources. The ensemble must balance these factors to achieve the best performance. The insights presented in this review paper are particularly relevant for researchers and practitioners working in coastal regions where accurate storm surge flood modeling is critical. Full article

(This article belongs to the Special Issue Coastal Disaster Assessment and Response)

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