Articles | Volume 30, issue 5
https://doi.org/10.5194/hess-30-1333-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-30-1333-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
11 Mar 2026
Research article |
| 11 Mar 2026
| 11 Mar 2026
Climate adaptation-aware flood prediction for coastal cities using Deep Learning
Division of Engineering, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
Areg Karapetyan
Division of Engineering, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
Aaron Chung Hin Chow
Division of Engineering, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
Samer Madanat
Division of Engineering, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
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Short summary
In this research, we developed an AI-driven framework that rapidly predicts floods in coastal areas, considering various shoreline protection strategies and a different sea-level rise scenarios. By combining data from two coastal cities, our lightweight model delivers near real-time flood projections under various adaptation strategies. This approach can guide policymakers in designing effective defenses, ultimately promoting safer coastal communities and infrastructure.
In this research, we developed an AI-driven framework that rapidly predicts floods in coastal...
