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PIM-TSUNAMI: A global TSUNAMI hazard amplification model considering site-specific factors and applying Physics-Informed Machine learning

Objective

Project PIM-TSUNAMI aims to develop a model that incorporates the effects of site-specific factors on tsunami heights, using Physics-Informed Machine Learning simulations and offering a user-friendly interface. Megathrust earthquakes in subduction zones, along with their cascading tsunamis, have led to some of the most devastating hazards on Earth, such as the 2004 Indian Ocean tsunami, which claimed more than 220,000 lives, and the 2011 Tohoku tsunami in Japan, resulting in over 20,000 fatalities. Recent understanding has revealed that the tsunami potential of megathrust earthquakes depends on site-specific factors such as slab curvature, bathymetry steepness, and sediment thickness. Despite significant advancements in tsunami hazard analysis over the past 30 years, the critical issue of site-specific factors, which can amplify tsunami hazards two- to threefold, remains a major gap in research and practice. By addressing this critical gap, PIM-TSUNAMI offers significant improvements to global tsunami hazard assessments and contributes to the safety of millions of people worldwide who live at risk of tsunamis.

The objectives of this project are: i) Understand the impacts of site-specific factors on tsunami-genesis, ii) Develop a user-friendly model for tsunami amplification for global subduction zones, and iii) Disseminate the model to relevant stakeholders. The user-friendly interface of the PIM-TSUNAMI model combined with our diverse dissemination strategy and the host supervisor’s active involvement in the tsunami community and his role as Secretary General of the IUGG Joint Tsunami Commission will guarantee its reach to relevant stakeholders and Disaster Risk Reduction (DRR) authorities worldwide and implementation. The automated workflow of PIM-TSUNAMI makes it easily accessible and applicable to researchers and coastal DRR authorities worldwide.

Fields of science (EuroSciVoc)

CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.

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Coordinator

UNIVERSITY OF BATH
Net EU contribution
€ 260 347,92
Address
CLAVERTON DOWN
BA2 7AY Bath
United Kingdom

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Region
South West (England) Gloucestershire, Wiltshire and Bristol/Bath area Bath and North East Somerset, North Somerset and South Gloucestershire
Activity type
Higher or Secondary Education Establishments
Links
Total cost
No data
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