FUTURE-FLOOD: New estimates of evolving UK flood risk for improved climate resilience

Lead Research Organisation: University of Bristol


Recent devastating floods across the UK and Europe have highlighted the need to make society more resilient to flooding. This need is even more urgent given that flooding is predicted to become more frequent and destructive with climate change. However, current estimates of future flood risk in the UK and elsewhere are unreliable as they are typically based on coarse resolution climate models, which are unable to capture the short-duration rainfall extremes responsible for flooding. They also do not capture critical changes in the spatial extent and temporal clustering of rainfall events and neglect key physical processes in changing rainfall and river flow patterns.
FUTURE-FLOOD is an ambitious project to advance our understanding of future inland flood risk and provide new flood estimates across the UK that are fit for purpose. It will bring together internationally state-of-the-art high resolution climate projections with advanced flood modelling capability. We will exploit a new set of continuous 100yr climate projections that provide rainfall data hour by hour, for every 2.2km grid box across the UK, for 1981-2080 for twelve ensemble members. This is like starting twelve weather forecasts and running each for 100yrs. These projections (an extension of "UKCP Local" only available for three 20yr periods) are unique in their spatial and temporal coverage. They will be exploited to gain new understanding of changes in rainfall over the coming years and decades, including changes in temporal clustering, antecedent conditions and spatial extent of events. Such changes are not well understood but are likely to be critically important for flood risk.
The 100yr UKCP Local projections will be used to drive hydrological and flood models, providing a complete UK-wide assessment of changes in the frequency and severity of compound pluvial and fluvial flooding for the first time. UKCP Local rainfall data will be used directly such that complex changes to rainfall patterns and intensity distributions are captured in the simulated river flows and flood levels. A recent pilot study (carried out by the project team) showed that using the full UKCP Local space-time varying precipitation fields to drive flood models can lead to radically different estimates of future flood risks to those contained in current guidance based on simplified uplift methods. This pilot study did not capture compound effects and was limited to only one pluvial site (Bristol) and two fluvial catchments (Thet and Dyfi) but demonstrated the need for the national-scale study proposed here.
We will compare results with flooding simulated using standard approaches and coarser resolution climate model data, assessing the reliability of existing flood predictions. Additional flood modelling experiments will allow us to identify the physical controls on flooding and its change through time, including the role of changes in the space-time variability of rainfall and its interactions with the landscape. This understanding will be key to identifying improved uplift approaches commonly used by practitioners for future flood risk assessment.
Providing flood projections continuously over 100yrs is a major step forward and will enable us to interpret individual observed flood events in the context of climate change and translate results to changes for specific policy-relevant global warming levels. We will combine the new flood hazard information with estimates of exposure and vulnerability to estimate flood risk (e.g. properties flooded, damage to critical infrastructure, monetary loss). This estimation will include projections of socio-economic change. We will demonstrate the use of this new information in decision-making at national scale. We will also co-develop a local-scale demonstrator (initially for Bristol) with city decision-makers to take the new flood information through to improving city resilience, assessing the scope for and benefits of adaptive action.


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