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

Viewed

Total article views: 6,890 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
4,393 2,391 106 6,890 713 113 148
  • HTML: 4,393
  • PDF: 2,391
  • XML: 106
  • Total: 6,890
  • Supplement: 713
  • BibTeX: 113
  • EndNote: 148
Views and downloads (calculated since 28 Jul 2017)
Cumulative views and downloads (calculated since 28 Jul 2017)

Viewed (geographical distribution)

Total article views: 6,890 (including HTML, PDF, and XML) Thereof 6,406 with geography defined and 484 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 20 Nov 2024
Download
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.