Tsunami Flow Characteristics on the East Coast of the UAE by One-Dimensional Numerical Analysis and Artificial Neural Networking

The coastal developments in the Middle East put low priority on tsunami risk assessment due to the rare occurrence and absence of genuine tsunami track records on the coastline in the past. Tsunami-vulnerable coasts, including the east coast of the UAE, need to prepare for, and pay attention to, the impact of future tsunamis due to increased earthquake activity in the region. This study investigated the tsunami characteristics of the nearshore from hypothetical tsunami conditions by applications of numerical modeling and Artificial Neural Network (ANN) methods. The modeling results showed that the maximum tsunami depth at the shore was highest in Khor Fakkan and Mirbih for the given tsunami boundary conditions, while the tsunami withdrawal was greater on the southern bathymetry compared to that on the northern bathymetry when the tsunami period increased. ANN results confirmed that the still sea depth and seabed slope were more important than the tsunami period when predicting the maximum tsunami depth at the shore.

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Publication Details

Journal
Sustainability
Published
2025-08-03
DOI
https://doi.org/10.3390/su17157036
Primary Topic
earthquake and tectonic studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Tsunami Flow Characteristics on the East Coast of the UAE by One-Dimensional Numerical Analysis and Artificial Neural Networking

Noura Al-Ahbabi, Fatima Alketbi, Cheng Chen, M. Mohamed Sameer Ali et al.
Sustainability
earthquake and tectonic studies
article

Tsunami Flow Characteristics on the East Coast of the UAE by One-Dimensional Numerical Analysis and Artificial Neural Networking

Noura Al-Ahbabi, Fatima Alketbi, Cheng Chen, M. Mohamed Sameer Ali, N.A.K. Nandasena, Maryam R. Al-Shehhi, Ashraf Hefny, Noura Alblooshi
article en

Abstract

The coastal developments in the Middle East put low priority on tsunami risk assessment due to the rare occurrence and absence of genuine tsunami track records on the coastline in the past. Tsunami-vulnerable coasts, including the east coast of the UAE, need to prepare for, and pay attention to, the impact of future tsunamis due to increased earthquake activity in the region. This study investigated the tsunami characteristics of the nearshore from hypothetical tsunami conditions by applications of numerical modeling and Artificial Neural Network (ANN) methods. The modeling results showed that the maximum tsunami depth at the shore was highest in Khor Fakkan and Mirbih for the given tsunami boundary conditions, while the tsunami withdrawal was greater on the southern bathymetry compared to that on the northern bathymetry when the tsunami period increased. ANN results confirmed that the still sea depth and seabed slope were more important than the tsunami period when predicting the maximum tsunami depth at the shore.

SustainabilityVol. 17(15)
United Arab Emirates University (AE), Fuzhou University (CN)
United Arab Emirates University
Openalex Percentile: Top 79%
earthquake and tectonic studies
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Tsunami Flow Characteristics on the East Coast of the UAE by One-Dimensional Numerical Analysis and Artificial Neural Networking — Noura Al-Ahbabi, Fatima Alketbi, et al. · Sustainability (2025) | TGRS Research Map | TGRS