Tsunamis are powerful yet devastating natural disasters that can cause significant damage to coastal infrastructure and loss of life. Until now, it has been difficult to provide early warning systems due to the fact that the tsunami risk is highly dependent on the underwater earthquake that triggers it.
However, researchers from the University of California, Los Angeles and Cardiff University in the U.K. have developed an early warning system that combines state-of-the-art acoustic technology with artificial intelligence to efficiently classify underwater earthquakes and predict potential tsunami risk.
The key to this system lies in the measurement of the acoustic radiation generated by the earthquake, which travels quickly enough to provide early warning. This acoustic radiation contains information regarding the tectonic event taking place and is picked up by underwater microphones, referred to as hydrophones. This information is used to provide a triangulation of the earthquake’s source and AI algorithms are used to classify the slip type and magnitude of the underwater earthquake.
The model can then quickly calculate key properties such as effective length and width, uplift speed, and duration to calculate the size of the potential tsunami. When tested on available hydrophone data, this model was found to successfully describe the earthquake parameters with low computational demand.
The application of this system to enhance existing hazard warning systems is potentially life-saving. Improved safety for offshore platforms and ships are the short-term benefits of this technology, while researchers continue to improve the model by including more information to increase its accuracy.
The University of California, Los Angeles (UCLA) is a public research university in Los Angeles, California and is world-renowned for its academics, faculty, and research programs. Founded in 1919, it is the flagship institution of the University of California system and is one of the most selective universities in the world.
Bernabe Gomez is a researcher of Aerospace and Mechanical Engineering at UCLA and one of the authors of the article “An acoustic-based early warning system for underwater earthquakes and tsunamis”. He has contributed to the development of the early warning system for tsunamis and his research focuses on deriving analytical solutions for the pressure field of underwater sound sources. He is currently working to improve the model by including more information to increase its accuracy.
