Stochastic Approach to Flood Risk Modelling: Maths Foresees

For the UK, increased risk of frequent and severe flooding in the future is one of the most challenging issues. Given that future climate change scenarios indicate that storm and flood frequency will increase, the UK’s susceptibility to storm clusters will also be magnified. Thus, this project combines stakeholder knowledge (Scottish Environment Protection Agency, SEPA) with cross-disciplinary academic expertise (statistical, river process, climate change & flood modelling) to refine mathematical modeling approaches in flood risk to better consider cluster-related uncertainties in light of climate change. Specifically, the impacts of climate change on clustering of extreme river flow events will consider changes to the severity of flood hazard from antecedent events e.g. non-return of river baseflow, antecedent water storage of the floodplains and natural channel morphodynamics.

Objectives

  • Develop a proficient statistical modelling framework for integrating regional climate change projections within synthetic river flow series.
  • Advance our HMM-GP modelling framework to synthesizing flow time series at finer temporal resolutions (1 hour; 15 minute) capable of robustly capturing flashy flow regimes.
  • Generate a robust, viable and constrained methodological approach for representing extreme event clusters in flood model inflow conditions.
  • Quantify the impacts of clustering of extreme events on flood hazard, accounting for future climate change.
  • Promote our methodology to flood risk management stakeholders, e.g. via  Flood Modelling Guidance for Stakeholders.

Contact:  S.Patidar@hw.ac.uk or H.Haynes@hw.ac.uk