Articles | Volume 22, issue 3
https://doi.org/10.5194/hess-22-2023-2018
https://doi.org/10.5194/hess-22-2023-2018
Research article
 | 
29 Mar 2018
Research article |  | 29 Mar 2018

Benchmarking ensemble streamflow prediction skill in the UK

Shaun Harrigan, Christel Prudhomme, Simon Parry, Katie Smith, and Maliko Tanguy

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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Publish subject to revisions (further review by editor and referees) (29 Oct 2017) by Q.J. Wang
AR by Shaun Harrigan on behalf of the Authors (08 Dec 2017)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (13 Dec 2017) by Q.J. Wang
RR by Guillaume Thirel (05 Jan 2018)
RR by Anonymous Referee #3 (14 Jan 2018)
ED: Publish as is (29 Jan 2018) by Q.J. Wang
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Short summary
We benchmarked when and where ensemble streamflow prediction (ESP) is skilful in the UK across a diverse set of 314 catchments. We found ESP was skilful in the majority of catchments across all lead times up to a year ahead, but the degree of skill was strongly conditional on lead time, forecast initialization month, and individual catchment location and storage properties. Results have practical implications for current operational use of the ESP method in the UK.