UK scientists develop tool to swiftly assess the impact of sea-level rise on flood risk

It will help improve early-stage decisions in preparation for climate change issues

Scientists have developed a tool to help predict the damage caused by flooding, such as here in Kent. PA
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British scientists have developed a tool which can swiftly assess the impact of sea-level rises on the risks of areas flooding.

Researchers from the University of Cambridge used Hull in eastern England, one of Britain's most vulnerable cities to flooding, as a base to create the digital tool which can now be used around the world.

It will enable towns, cities, regions and countries around the world to make better and earlier decisions to prepare for climate change.

Hull was chosen after devastating floods destroyed thousands of homes and caused £40 million ($49.45 million) of damage in 2007.

The tool assesses the economic impact of tens of thousands of potential scenarios of rising seas and mitigation activities.

It is the first time the full scope of the Intergovernmental Panel on Climate Change (IPCC) sea-level rise projections can be seen in an interactive way.

“It’s vital that places like Hull make informed decisions on how best to reduce risk and increase resilience," said Mike Dobson, who works for Arup, global specialists in the sustainable environment.

"Hull is low lying — it’s similar to New Orleans in many ways due to its low-lying nature on the coast — and there are 100,000 properties potentially at risk from the most-extreme weather events.

“These ‘once-in-a-lifetime’ flooding events will become more frequent as sea levels rise and we experience more storms.

“I’ve been working in flood-risk management for over 20 years trying to help make good decisions.

“It’s often pretty static — lots of modelling, lots of economics presented in a static report with conclusions at the end. We wanted to see what else was possible and bring it to life. Cambridge University managed to unblock the complex modelling, which allowed us to do that.”

He has been working with Prof Tom Spencer, director of the Cambridge Coastal Research Unit, in an attempt to find solutions.

“Fortunately, there’s a wealth of climate data available,” said Prof Spencer.

“Ideally, you’d feed this high-spec climate science modelling into informed decision-making.

“It’s a very complex set of tasks which requires a lot of resource — and most organisations just don’t have that. So what tends to happen is everything is oversimplified and only a small number of possible scenarios are considered — not enough to build in the uncertainties of the climate changes we face.”

Prof Spencer and his colleague Dr Elizabeth Christie started with detailed sea-level rise prediction information from the UK Climate Projections data in 2018 to model the effects of climate change.

They then developed a framework that incorporates sea-level rise uncertainty into coastal flood-risk assessment by streamlining the process of modelling sea levels, wave overtopping and flood spreading on land.

By the end of their research, the team had 10 million data points relating to 21,300 scenarios with 122 increments of sea-level rise and seven extreme water levels.

“Cambridge University did the analytical heavy lifting,” said Steven Downie, a fluid dynamics specialist in Arup’s technology and research team.

“As a result, they could statistically describe a really broad spectrum of scenarios we were able turn into a prototype tool that allows users to delve into the data by toggling variables like time, storms and tides, defences and so on, and then compare outcomes in terms of scale of flooding across a geographical area.

“This work is about the huge decisions that society has to make about adapting for climate change.

“We just don’t know how things are going to play out and we’re only going to get a few chances to get these things right. It’s simply better to make good decisions and this tool will help this by capturing future sea rises in the economic decision process.”

Updated: January 19, 2023, 5:08 PM