AI flood warning system in the works

Michael Olney

A Cork town has been studied as part of a project aiming to use artificial intelligence and satellite technology to develop an early warning system for communities at risk of severe flooding.

Midleton in county Cork was one of several Irish locations chosen by researchers at CeADAR, Ireland’s centre for applied artificial intelligence (AI), for the project.

Last October, Midleton fell victim to sudden and severe flooding after the Owenacurra River burst its banks during Storm Babet.

CeADAR used data collected by the European Space Agency’s Sentinel-1 satellite to build an AI model capable of accurately predicting the extent of future floods.

The new model can prompt communities to take emergency measures to limit damage from floods, evacuate residents, and protect livestock.

It is hoped the model will soon be available to flood-prone communities across the country.

The AI model forms part of CAMEO, a €9 million project led by UCD to develop an Earth Observations (EO) services sector in Ireland and explore the potential impact of EO data in the areas of climate, agriculture, and the marine.

It comes in response to a period of significant flooding events in recent months, with flooding following Storm Ciarán, Storm Debbie, and Storm Babet badly affecting residents and businesses in the west and south-west of the country in particular.

Experts believe that flooding will worsen in Ireland in the coming years with increasing concentrations of greenhouse gas emissions in the atmosphere leading to more intense precipitation events during winter, and worse floods in historically vulnerable areas, as well as in areas that never flooded previously.

Earlier this year, the Irish Fiscal Advisory Council warned that extreme flooding events resulting from climate change could cost the state around €500 million a year by the end of the decade. However, the report also estimates that a one-in-ten-year flooding event in Dublin could cost the exchequer up to €2.9bn with more than 14,500 properties at risk.