Journal
WATER AND ENVIRONMENT JOURNAL
Volume 33, Issue 3, Pages 427-442Publisher
WILEY
DOI: 10.1111/wej.12415
Keywords
cellular automata flood model; decision support; 2D flood modelling; flood risk management; surface water management plan; urban flooding
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Funding
- Cambridgeshire County Council
- UK Engineering & Physical Sciences Research Council through the Water Informatics Science and Engineering Centre for Doctoral Training [EP/L016214/1]
- UK Engineering & Physical Sciences Research Council through Safe & SuRe research fellowship [EP/K006924/1]
- EPSRC [EP/H015736/1, EP/K006924/1] Funding Source: UKRI
- NERC [NE/K008765/1, NE/P011217/1] Funding Source: UKRI
- Natural Environment Research Council [NE/P011217/1] Funding Source: researchfish
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This research evaluates performance of a rapid assessment framework for screening surface water flood risk in urban catchments. Recent advances in modelling have developed fast and computationally efficient cellular automata frameworks which demonstrate promising utility for increasing available evidence to support surface water management, however, questions remain regarding trade-offs between accuracy and speed for practical application. This study evaluates performance of a rapid assessment framework by comparing results with outputs from an industry standard hydrodynamic model using a case study of St Neots in Cambridgeshire, UK. Results from the case study show that the rapid assessment framework is able to identify and prioritise areas of flood risk and outputs flood depths which correlate above 97% with the industry standard approach. In theory, this finding supports a simplified representation of catchments using cellular automata, and in practice presents an opportunity to apply the framework to develop evidence to support detailed modelling.
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