Incorporating river bed level changes into flood risk modelling

Douglas Pender, Sandhya Patidar, Gareth Pender, Heather Haynes

Research output: Contribution to conferencePaper

Abstract

Typically, flood risk assessments (FRAs) are conducted for single N year extreme flow events using a single survey ofthe river channel and floodplains. This approach is fundamentally flawed as it does not account for any changes in theconveyance capacity of the channel that will occur due to sediment transport and morphological adjustment. Therefore,to provide a more robust estimate of future flood risk, the uncertainties related to these changes should be incorporatedinto inundation modelling. This paper proposes a modelling methodology that combines: a stochastic model, forestimating streamflow; a 1D sediment transport model (HEC-RAS), to estimate morphological change; and, a 1D/2Dlinked model (TUFLOW) to estimate inundation. This can be considered as the first quantitative modelling methodologyto account for sediment-related uncertainty in FRA and provides valuable insights into the sensitivity of future flood riskto this variable. The methodology is demonstrated through a conceptual implementation that evaluates the change ininundation for eight flood events with Return Periods (RPs) of 1, 2, 5, 10, 25, 50, 100 and 200 years, along an alluvialriver reach (River Caldew, UK) subjected to 50 years of sediment transport. Results show that, whilst all events exhibitan increase in flooded area and volume, these changes are more pronounced at the lower, more frequent, RPs (160%compared to 9% increase in flood extent for 1 and 200 year RPs respectively).
Original languageEnglish
Number of pages9
Publication statusPublished - 28 Jun 2015
Event36th IAHR World Congress - The Hague, Netherlands
Duration: 28 Jun 20153 Jul 2015

Conference

Conference36th IAHR World Congress
CountryNetherlands
CityThe Hague
Period28/06/153/07/15
OtherDeltas of the future and what happens upstream

Fingerprint Dive into the research topics of 'Incorporating river bed level changes into flood risk modelling'. Together they form a unique fingerprint.

Cite this