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Projects: Projects for Investigator
Reference Number EP/X041093/1
Title UQ4FM: Uncertainty Quantification for Flood Modelling
Status Started
Energy Categories Not Energy Related 90%;
Other Cross-Cutting Technologies or Research(Other Supporting Data) 10%;
Research Types Basic and strategic applied research 100%
Science and Technology Fields PHYSICAL SCIENCES AND MATHEMATICS (Computer Science and Informatics) 10%;
ENVIRONMENTAL SCIENCES (Earth Systems and Environmental Sciences) 90%;
UKERC Cross Cutting Characterisation Not Cross-cutting 100%
Principal Investigator Professor L Beevers

Sch of Engineering and Electronics
University of Edinburgh
Award Type Standard
Funding Source EPSRC
Start Date 01 March 2024
End Date 28 February 2027
Duration 36 months
Total Grant Value £636,121
Industrial Sectors No relevance to Underpinning Sectors
Region Scotland
Programme NC : Engineering
 
Investigators Principal Investigator Professor L Beevers , Sch of Engineering and Electronics, University of Edinburgh (99.999%)
  Other Investigator Dr A Wilson , Sch of Mathematics, University of Edinburgh (0.001%)
  Industrial Collaborator Project Contact , Ove Arup & Partners Ltd (0.000%)
Project Contact , Environmental Agency (0.000%)
Project Contact , Scottish Environmental Protection Agency (0.000%)
Project Contact , Fathom (0.000%)
Project Contact , Kaya Consulting Limited (0.000%)
Web Site
Objectives
Abstract Currently 6.4 million people, as well as critical infrastructure such as road, rail and power networks, are exposed to flood risk across the UK, and this is expected to rise to 10.8 million people and encompass further critical assets by 2080. The 2020 National Risk Register places flooding behind only pandemics and large-scale attacks as the most significant risks to the UK. Despite this, routine flood risk assessments for planning, development and adaptation purposes use deterministic methods to assess flood hazard, using hydro-dynamic process-based models which are computationally heavy (~hours to ~weeks run time). This established process fails to acknowledge, quantify and capture the cascading uncertainties inherent in the process, which manifest from a wide range of sources including climate scenarios, flow gauging, extreme value estimates and hydrological models. Under estimation of current and future flood hazard could lead to what the Government's Climate Change Risk Assessment (CCRA) terms 'lock-in' and under-engineered adaptation measures, whilst over-estimation could lead to financially non-viable schemes and inappropriate development.The flood analytics industry must urgently move towards probabilistic methods which acknowledge and quantify cascading uncertainties; but this requires yet-to-be developed algorithms which capture the critical uncertainties within the process and reduce the computational burden associated with forward Uncertainty Quantification (UQ).This project will deliver the speed up required to robustly assess flood hazard uncertainty through the development of novel and bespoke uncertainty quantification algorithms for inundation modelling; and by demonstrating their applicability to the prediction of current and future flood hazards at a range of scales, incorporating a wide range of uncertainties in the modelling chain. Success will deliver the step change needed by the flood analytics industry to embrace the necessary transition to UQ assessment, thus placing the UK at the forefront of flooding research, and future proofing climate change adaptation.
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Added to Database 20/12/23