With the aid of arms control technology and artificial intelligence, a team of scientists at Cardiff University’s School of Mathematics has developed a method that uses underwater microphones to provide early warnings of potentially deadly tsunamis.
The result of earthquakes, volcanoes, underwater landslides, and other causes, tsunamis are among the most deadly of natural disasters, capable of causing widespread destruction across tens of thousands of miles. In 2004, one struck the Indian Ocean, resulting in about 230,000 deaths as huge walls of displaced water struck Indonesia, Sri Lanka, India, Thailand, Somalia, Myanmar, the Maldives, Malaysia, Tanzania, the Seychelles, Bangladesh, South Africa, Yemen, and Kenya.
There are tsunami detection and warning systems, though these leave much to be desired. Based on seismographs and bottom-pressure sensors attached to buoys, these can detect earthquakes, though not all earthquakes result in tsunamis and the buoys can only detect tsunamis when one passes them, which doesn’t leave a lot of time to react.
These warning systems are helpful, though very limited. Tsunamis form and travel because of a very complex interplay of factors. This is why some can devastate whole regions while others might only raise the water level a few feet when they come ashore.
To improve on this, the Cardiff team developed a mathematical model based on data collected from the hydrophone network established to enforce the 1996 Comprehensive Nuclear Test-Ban Treaty by keeping an electronic ear cocked for the distinct ocean sounds of a nuclear explosion. While listening, the underwater microphones were able to detect four earthquakes associated with tsunamis.
Using this data, advanced acoustic technology, and artificial intelligence, the team was able to detect and analyze in real-time sounds radiating from 200 earthquakes in the Pacific and Indian Oceans. They were able to locate the origin of the quakes, describe the pressure field generated, the duration of the wave, and its speed of travel. In this way, the system could classify the earthquake’s type and magnitude, and the size of the tsunami.
Not only can such information save lives, it can also help to avoid false alarms and tailor warnings to suit the predicted danger. Designed to be used alongside existing warning systems, the next step will be to develop user-friendly software that can be installed in national warning centers sometime this year.
“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,” said Dr. Usama Kadri, Senior Lecturer in Applied Mathematics.
The research was published in Physics of Fluids.
Hydrophones and AI improve tsunami early warning systems [New Atlas]