;
;
Analysing future climate change impacts on sea level rises
Arup’s new sea-level rise insights tool explores how uncertainty over future sea level rises can be captured in the economic decision process.
The science surrounding climate change is hugely complex and uncertain. To estimate how our climate will change in the future, the Intergovernmental Panel on Climate Change (IPCC) uses a broad range of large scale scientific analyses, which provide a spectrum of possible outcomes. The cost of carrying out detailed engineering assessments for each possible outcome makes it difficult to bring through all the climate science into the economic calculations which guide our actions.
This reduction in the flow of information means that city leaders and decision makers face a difficult challenge to understand the right interventions to make now, to manage the risk of future climate change impacts.
The sea level rise insights tool was developed as part of the EuroSea project, and in partnership with the Environment Agency, Cambridge University, The National Oceanography Centre. This was jointly funded by Arup University’s research programme and the EuroSea project, which receives funding from the European Union's Horizon research and innovation programme under grant agreement No 862626.
Project Summary
122 sea level rise increments modelled
7 extreme water level return periods used
21,300scenarios run in just 2 hours
User led research
To manage coastal flood risk in our cities and towns, decision makers need better data driven modelling and information. Arup worked with the Environment Agency to ensure the sea level insights tool was robust and useful for flood risk mitigation stakeholders.
The tool was developed using data from the urban coastal area of Hull, as it has the second highest number of properties at risk of flooding in the UK, second only to London.
Improving climate impact modelling
Typically, flood risk assessments only consider a limited band of the uncertainty of the sea level rise. The challenge with managing this risk is that as projections get further from the present day, the uncertainty of the prediction increases. In addition, discount rates applied in economic Net Present Value financial calculations also mean that the impacts of worst case scenarios later in the century have limited impact on decisions we are taking now.
Professor Tom Spencer and Dr Elizabeth Christie from the Cambridge Coastal Research Unit, within the Department of Geography at the
University of Cambridge (UCAM) led the climate change impact modelling for this project using detailed sea level rise prediction information from the UK Climate Projections data in 2018 (UKCP18).
The modelling framework developed by UCAM 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. This allows all the uncertainty to be propagated through to the calculation of risk, driven by economic damages.
To quantify the flood hazard, reduced complexity models are used to allow a large number of scenarios to be run and all potential pathways of flooding considered at some level. By the end of the research, UCAM was running 21,300 scenarios in just 2 hours, which gave the Arup team new levels of data and new opportunities to improve insight for decision makers.
Future applications
The sea level rise insight tool is designed to improve decisions on flood risk management and resilience. In the future the tool can potentially be applied to towns, cities and regions around the world so that they can make better decisions to prepare for climate change and, just as important, help explain these decisions to the public.
To discuss how the sea level insights prototype could be applied to your region, or location contact us.
The Arup Journal 2022 Issue 2
Learn more about this project in the Arup Journal. Applying a gender lens to sustainable transport system design, mass timber construction in the USA, and mitigating the impact of climate change on coastal areas – discover more in the Arup Journal.
Download
