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Using artificial intelligence to enable earlier and more reliable tsunami alerts

An early warning system that quickly classifies submarine earthquakes and determines the risk of tsunami events has been developed by scientists at Cardiff University, Wales.

The team, from the University’s School of Mathematics, combined state-of-the-art acoustic technology with artificial intelligence (AI) to monitor tectonic activity in real-time.

Their work, published in Physics of Fluids, used sound recordings captured by underwater microphones, called hydrophones, to measure the acoustic radiation produced by 200 earthquakes that happened in the Pacific and Indian Ocean.

Dr Usama Kadri, a Senior Lecturer in Applied Mathematics at Cardiff University and the study’s co-author, said: "Our study demonstrates how to obtain fast and reliable information about the size and scale of tsunamis by monitoring acoustic-gravity waves, which travel through the water much faster than tsunami waves enabling more time for evacuation of locations before landfall."

Acoustic-gravity waves are naturally occurring sound waves that move through the deep ocean at the speed of sound and can travel thousands of kilometres in the water.

Dr Kadri added: "This acoustic radiation also carries information about the originating source of the tectonic event and its pressure field can be recorded at distant locations, even thousands of kilometres away from the source. This is important because not all underwater earthquakes cause tsunamis."

Current warning systems rely on waves reaching sea buoys before tsunami warnings are triggered, leaving little time for evacuation.

The team’s work predicting tsunami risk is part of a long-running project to enhance natural hazard warning systems across the globe.

The paper, Numerical validation of an effective slender fault source solution for past tsunami scenarios, can be accessed here.



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