Abstract
AbstractThis 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.
Highlights
Flood management is an established component of UK environmental policy, there is an emerging recognition that a historic focus on fluvial and coastal flooding has left a gap in managing urban surface water (Pitt, 2008)
The utility of the rapid assessment framework is examined through three questions, representing scenarios with increasing levels of detail: Can the framework consistently prioritise areas of flood risk for a no sewer scenario? Can the framework consistently prioritise areas of flood risk for a drainage system scenario? Is the approach suitable for modelling interventions in an urban catchment? These questions are answered through comparing the rapid assessment framework with a published surface water management plan, undertaken by Arcadis, using industry standard hydrodynamic modelling
The degree of utility of the rapid assessment framework to screen catchments in the no sewer scenario is evaluated relative to three questions, each progressing to more nuanced level of application: Firstly, can the framework broadly replicate flood dynamics and identify priority flood spots (PFS) in the urban catchment? Secondly, does the framework correlate flood depths with industry standard techniques? And thirdly, are outcomes from application of the rapid assessment technique comparable to analysis using the industry standard approach?
Summary
Flood management is an established component of UK environmental policy, there is an emerging recognition that a historic focus on fluvial and coastal flooding has left a gap in managing urban surface water (Pitt, 2008). Recent reports estimate annual surface water flood damages in the United Kingdom between 0.25 and 0.5 billion GBP (EWA, 2009; DEFRA, 2012), and predict this to rise to between 0.5 and 1 billion GBP over the 50 years (Committee on Climate Change A.S.C., 2012). Studies estimate that UK surface water flooding constitutes up to 40% of national annual flood damages (Douglas et al, 2010). Managing surface water flooding is of national strategic importance and is amongst the hazards prioritised in the UK Climate Change Risk Assessment, National Risk Register and National Flood Resilience Review (DEFRA, 2012; Committee on Climate Change, 2015; 2017; HM Government, 2016). UK flood policy has identified this risk and legislated towards identifying and managing hazards (Pitt, 2008; DCLG, 2010; HM Government, 2010). A key objective of this process is to identify possible interventions which can be applied to alleviate flood risks
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