Multi-Source Tsunami Hazard Assessment for Digital Twin Workflows

Recent advancements in the Digital Twin Component for Tsunamis, developed within the EU-funded DT-GEO project, are transforming rapid hazard assessment from static pre-computed databases to dynamic, data-informed workflows.  In this presentation, a novel workflow for Probabilistic Tsunami Forecasting (PTF) due to earthquake-triggered landslides is presented through a site demonstrator for the Mediterranean Sea motived by the 1908 Messina Strait earthquake and tsunami. A key innovation is the integration of earthquake-triggered submarine landslides and the application of AI driven inundation emulators for rapid prediction linked to earthquake workflows and related shakemaps. In addition, we showcase possible use of the workflow for new geophysical settings for a submarine slope in Southwest India. These synergies between digital twin architectures and machine learning provide a robust framework for anticipatory action and disaster risk management at both regional and global scales.  

This work was partially funded by the EU DT-GEO project (A Digital Twin for GEOphysical extremes, https://dtgeo.eu/) through the European Union’s Horizon Europe research and innovation programme under grant agreement nº 101058129 and PCTWIN project, jointly funded by the Natural Environment Research Council (NERC), UKRI and the Ministry of Earth Sciences (MoES), Government of India (Grant: NE/Z503496/1).