New research uncovers major issue with tsunami warning systems: 'It's not a matter of if, but when'

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4 days ago

New research uncovers major issue with tsunami warning systems: 'It's not a matter of if, but when'
Tsunami warning systems have seen significant advancements with the development of new technologies. However, there seem to be limitations in these systems.
Researchers from the University of Western Ontario found that machine learning and advanced decision-making tools could improve how quickly and accurately warnings are issued.
The study, published in the Coastal Engineering Journal, suggests that more advanced artificial intelligence models can improve tsunami warnings — provided they're trained on high-quality, real-world data.
The researchers built tsunami warning models using three different methods: multiple linear regression, random forest, and neural network. The last two methods worked better, but the quality of data used to train the models made a significant difference in the accuracy of their predictions.
If the training data doesn't reflect real-world conditions, the model may not perform accurately even if it ran well during standard tests. And that's the key challenge. Not all tsunami-prone areas have real-world data. For instance, there are only four ocean-bottom sensors on the west coast of Canada.
In Tofino, a popular surfing destination on Vancouver Island, this lack of data poses a huge problem in predicting tsunamis. Although no tsunami has ever hit the town, its topography puts it at a high risk for a huge tsunami.
Beneath the waters near Tofino is a tectonic plate boundary whose movement can produce a magnitude 9.0 earthquake. One big jolt from the Cascadia Subduction Zone could trigger a tsunami up to 30 meters high, capable of reaching the shoreline within 20 minutes.
The researchers still don't know how large the tsunami might be, but they're certain that it will happen. "It's not a matter of if, but when," said Katsu Goda, a University of Western Ontario associate professor and Canada Research Chair in multi-hazard risk assessment, per Phys.org.
Around the globe, researchers are doubling down on technology that can help predict and mitigate the impact of natural disasters.
One team has developed a new model to improve the predictions of tsunamis and help address deadly storm surges. Another is developing a futuristic, self-powered seawall that protects against tsunami waves and transforms tidal water movement into electricity.
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Researchers are also developing artificial intelligence-powered flood vision to predict how flooding from rising seas and severe storms could impact local communities, helping people visualize risks and prepare in advance before the impacts of nature become severe.
There's still too much uncertainty involved in predicting tsunamis, but these developments represent important progress toward more accurate warning systems that can give people more time to evacuate, save lives, and protect infrastructure and ecosystems.
In the meantime, staying informed on critical climate issues can help boost awareness and preparedness for calamities.
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