Using lake sediment archives to improve understanding of flood magnitude and frequency: recent extreme flooding in northwest UK
Using lake sediment archives to improve understanding of flood magnitude and frequency: recent extreme flooding in northwest UK
We present the first quantitative reconstruction of palaeofloods using lake sediments for the UK and show that for a large catchment in NW England the cluster of devastating floods from 1990 to present is without precedent in this 558‐year palaeo‐record. Our approach augments conventional flood magnitude and frequency (FMF) analyses with continuous lake sedimentary data to provide a longer‐term perspective on flood magnitude recurrence probabilities. The 2009 flood, the largest in >558 years, had a recurrence interval larger (1:2,200 year) than revealed by conventional flood estimation using shorter duration gauged single station records (1:1,700 year). Flood‐rich periods are non‐stationary in their correlation with climate indices, but the 1990‐2018 cluster is associated with warmer Northern Hemisphere Temperatures and positive Atlantic Multidecadal Oscillation. Monitored records rarely capture the largest floods and our palaeoflood series shows, for this catchment, such omissions undermine evaluations of future risk. Our approach provides an exemplar of how to derive centennial palaeoflood reconstructions from lakes coupled well with their catchments around the world.
2366-2376
Chiverrell, R.C.
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Sear, D.A.
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Warburton, J.
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Macdonald, N.
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Schillereff, D.N.
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Dearing, J.A.
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Croudace, I.W.
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Brown, J.
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Bradley, J.
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30 September 2019
Chiverrell, R.C.
956c80f7-dc30-4208-b15f-98f04330a49b
Sear, D.A.
ccd892ab-a93d-4073-a11c-b8bca42ecfd3
Warburton, J.
908c4afe-aecc-4061-964f-fe1c14070809
Macdonald, N.
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Schillereff, D.N.
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Dearing, J.A.
dff37300-b8a6-4406-ad84-89aa01de03d7
Croudace, I.W.
24deb068-d096-485e-8a23-a32b7a68afaf
Brown, J.
64c8be68-e3cb-49ff-b5b0-525db5f4bcd0
Bradley, J.
7abc0060-2a06-425b-824b-1612430e7049
Chiverrell, R.C., Sear, D.A., Warburton, J., Macdonald, N., Schillereff, D.N., Dearing, J.A., Croudace, I.W., Brown, J. and Bradley, J.
(2019)
Using lake sediment archives to improve understanding of flood magnitude and frequency: recent extreme flooding in northwest UK.
Earth Surface Processes and Landforms, 44 (12), .
(doi:10.1002/esp.4650).
Abstract
We present the first quantitative reconstruction of palaeofloods using lake sediments for the UK and show that for a large catchment in NW England the cluster of devastating floods from 1990 to present is without precedent in this 558‐year palaeo‐record. Our approach augments conventional flood magnitude and frequency (FMF) analyses with continuous lake sedimentary data to provide a longer‐term perspective on flood magnitude recurrence probabilities. The 2009 flood, the largest in >558 years, had a recurrence interval larger (1:2,200 year) than revealed by conventional flood estimation using shorter duration gauged single station records (1:1,700 year). Flood‐rich periods are non‐stationary in their correlation with climate indices, but the 1990‐2018 cluster is associated with warmer Northern Hemisphere Temperatures and positive Atlantic Multidecadal Oscillation. Monitored records rarely capture the largest floods and our palaeoflood series shows, for this catchment, such omissions undermine evaluations of future risk. Our approach provides an exemplar of how to derive centennial palaeoflood reconstructions from lakes coupled well with their catchments around the world.
Text
Chiverrell et al 2019 Earth Surface Processes and Landforms
- Accepted Manuscript
Text
esp.4650
- Version of Record
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Accepted/In Press date: 9 May 2019
e-pub ahead of print date: 17 May 2019
Published date: 30 September 2019
Identifiers
Local EPrints ID: 431244
URI: http://eprints.soton.ac.uk/id/eprint/431244
ISSN: 0197-9337
PURE UUID: 3231f85b-11d5-4006-bbb8-8f153a8f522c
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Date deposited: 28 May 2019 16:30
Last modified: 16 Mar 2024 03:39
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Author:
R.C. Chiverrell
Author:
J. Warburton
Author:
N. Macdonald
Author:
D.N. Schillereff
Author:
J. Brown
Author:
J. Bradley
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