New Method Discovered to Predict a Tsunami

Anna Dutton

Scientists and Mathematicians at Cardiff University have developed a new way of predicting a tsunami based on underwater sound technology.

Tsunamis are caused by an earthquake in the deep ocean, this causes a large volume of water to be displaced. These waves can then travel thousands of miles, affecting regions not near the epicentre. When they reach shallower waters, the waves gather momentum and can have devastating effects on local villages. The largest tsunami to-date was the tsunami in 2004 on Boxing Day affecting those on the coast of the Indian Ocean.

The team in Cardiff hope to allow extra warning times for tsunamis as they intend to measure the fast-moving underwater sound waves. As Dr Usama Kadri explains, the lead author of the study from Cardiff mathematics department, ‘by taking measurements of acoustic gravity waves’ the study has ‘everything it needs’ to predict a tsunami.

The sound waves are more efficient at predicting tsunamis because they can travel ten-times faster than the tsunami, and spread out in all directions, regardless of the tsunami’s trajectory. These vibrations are easy to detect on standard underwater hydrophones so are ideal for detecting these sorts of movements.

The study carried out by Cardiff University, published in the Journal of Fluid Mechanics, goes into further detail, outlining how the key characteristics of an earthquake can be identified. These features include: the duration, dimension, orientation, and speed. Current methods for detecting a tsunami rely on any of the above features reaching a floating buoy and physically touching it; the new method using waves can detect tsunamis far quicker, saving lives.

The buoys are also expensive, and as Dr Kadri notes, ‘the characteristics of the earthquake fault’ allow the team to ‘calculate the characteristics of a tsunami.’ This then results in ‘real-time’ calculations that are more efficient.

In summary, these findings will allow the prediction of tsunamis to be more accurate and precise. This will enable earlier warning and will mean more lives can be saved, hopefully contributing to stop a repeat of the 2004 devastation.

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