Deep vision-based framework for coastal flood prediction under sea level rise and shoreline protection.

ABSTRACT: The world's coastal regions are home to billions, yet they are also hotspots for climate change-induced adversities, such as sea level rise (SLR), which exacerbate coastal risks, increasing the likelihood and severity of floods. To assess these risks and inform adaptation measures, coastal engineers require predictive models capable of producing accurate, high-resolution flood maps under the given projected climate change impacts and potential mitigation strategies (e.g., construction of seawalls). While traditional physics-based hydrodynamic simulators can deliver accurate results, their application incurs massive computational burdens. On the other hand, supervised Deep Learning (DL) techniques offer immense potential for creating data-driven surrogates that are orders of magnitude faste

SUBMITTER: Karapetyan A 

PROVIDER: S-EPMC12847901 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature