UC research engineer Dr Alberto Ardid and Associate Professor David Dempsey used machine learning to analyse seismic patterns from 24 volcanoes, including three in New Zealand, leading up to 41 past eruptions.
They found the eruption warning signals follow repeatable patterns that can be transferred to other less studied volcanoes.
"This finding could be a breakthrough for eruption forecasting, allowing us to use data from well-monitored volcanoes to improve monitoring and risk mitigation at under-monitored sites, enhancing volcano safety globally," Ardid said.
Eruptions pose a significant threat to about 29 million people around the world who live within 10km of an active volcano.
"Timely and accurate eruption forecasting can save lives, reduce economic losses, and minimise losses due to disruptions to air travel, agriculture, and global supply chains," Ardid said.
"Our method provides a cost-effective and scalable solution for improving forecasting at under-monitored volcanoes, benefiting communities and disaster management agencies globally."
Ardid recently won the New Zealand Geophysics Prize for this research.
He says it was exciting to develop a tool that can contribute to volcano warning systems and prevent loss of life.
"It will be particularly valuable in developing countries where data is scarce, such as Southeast Asia and Central America, and that is a big motivation behind this project."
The plan is to share the codes with volcano observatories in New Zealand and overseas via an open-access policy.
"The modelling tool we’ve come up with is relatively simple and it’s complementary to existing practices of volcanic observations, but it provides an extra layer of information,” he said.
“It means we can start to think about forecasting eruptions at volcanoes that have never had instrumentally recorded eruptions, such as Mount Taranaki,” he says.
UC School of Earth and Environment volcanologist, Professor Ben Kennedy, also collaborated on the study, which was published in Nature Communications on Wednesday (February 26).
Kennedy said effective warning systems may help save lives when unpredictable and hazardous active volcanoes, such as Whakaari / White Island, Ruapehu and Tongariro in New Zealand, erupt.
“This new research is really exciting because it challenges the current paradigm that eruption precursors, or warning signs, are unique to individual volcanoes.
“This is the first time we’ve had a model that demonstrates how we can use eruption precursor data from a number of volcanoes to help forecast a future eruption at another volcano where there’s very little available data.”
The research project was a collaboration between UC, Auckland University Professor Shane Cronin, and 18 international researchers across nine countries.
