Incorporating sedimentological data in UK flood frequency estimation

Sean Longfield, Duncan Faulkner, Thomas Kjeldsen, Mark Macklin, Anna Jones, Simon Foulds, Paul Brewer, Hywel Griffiths

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)
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Abstract

This study presents a new analytical framework for combining historical flood data derived from sedimentological records with instrumental river flow data to increase the reliability of flood risk assessments. Historical flood records were established for two catchments through re-analysis of sedimentological records; the Nant Cwm-du, a small, steep upland catchment in the Cambrian Mountains of Wales, and a piedmont reach of the River Severn in mid Wales. The proposed framework is based on maximum likelihood and least-square estimation methods in combination with a Generalised Logistic distribution; this enables the
sedimentological data to be combined effectively with existing instrumental river flow data. The results from this study are compared to results obtained using existing industry standard methods based solely on instrumental data. The comparison shows that inclusion of sedimentological data can have an important impact on flood risk estimates, and that the methods are sensitive to assumptions made in the conversion of the sedimentological records into flood flow data. As current industry standard methods for flood risk analysis are known to be highly uncertain, the ability to include additional evidence of past flood events derived from sedimentological records as demonstrated in this study can have a significant impact on flood risk assessments.
Original languageEnglish
Article numbere12449
Number of pages19
JournalJournal of Flood Risk Management
Early online date20 Apr 2018
DOIs
Publication statusPublished - 31 May 2018

Keywords

  • flood frequency estimation
  • least-square estimation
  • maximum likelihood estimation
  • sedimentological flood data
  • uncertainty

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