Longfield, Sean, Faulkner, Duncan, Kjeldsen, Thomas , Macklin, Mark, Jones, Anna, Foulds, Simon, Brewer, Paul and Griffiths, Hywel (2019) Incorporating sedimentological data in UK flood frequency estimation. Journal of Flood Risk Management . ISSN 1753-318X
Full content URL: https://doi.org/10.1111/jfr3.12449
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Item Type: | Article |
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Item Status: | Live Archive |
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.
Keywords: | sedimentological flood data, flood frequency estimation, maximum likelihood estimation, least-square estimation, uncertainty. |
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Subjects: | F Physical Sciences > F810 Environmental Geography F Physical Sciences > F841 Maritime Geography F Physical Sciences > F840 Physical Geography |
Divisions: | College of Science > School of Geography |
ID Code: | 31967 |
Deposited On: | 29 Oct 2018 09:46 |
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