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Details of Grant 

EPSRC Reference: EP/X041093/1
Title: UQ4FM: Uncertainty Quantification for Flood Modelling
Principal Investigator: Beevers, Professor L
Other Investigators:
Wilson, Dr A
Researcher Co-Investigators:
Project Partners:
Arup Group Ltd Environment Agency (Grouped) Fathom
Kaya Consulting Limited Scottish Environmental Protection Agency
Department: Sch of Engineering
Organisation: University of Edinburgh
Scheme: Standard Research
Starts: 01 March 2024 Ends: 28 February 2027 Value (£): 636,121
EPSRC Research Topic Classifications:
Coastal & Waterway Engineering
EPSRC Industrial Sector Classifications:
No relevance to Underpinning Sectors
Related Grants:
EP/Y000145/1 EP/X040941/1
Panel History:
Panel DatePanel NameOutcome
12 Jul 2023 Engineering Prioritisation Panel Meeting 12 and 13 July 2023 Announced
Summary on Grant Application Form
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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