Articles | Volume 28, issue 14
https://doi.org/10.5194/hess-28-3133-2024
https://doi.org/10.5194/hess-28-3133-2024
Research article
 | 
19 Jul 2024
Research article |  | 19 Jul 2024

Leveraging a novel hybrid ensemble and optimal interpolation approach for enhanced streamflow and flood prediction

Mohamad El Gharamti, Arezoo Rafieeinasab, and James L. McCreight

Viewed

Total article views: 5,034 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
3,617 1,238 179 5,034 170 211
  • HTML: 3,617
  • PDF: 1,238
  • XML: 179
  • Total: 5,034
  • BibTeX: 170
  • EndNote: 211
Views and downloads (calculated since 25 Jan 2024)
Cumulative views and downloads (calculated since 25 Jan 2024)

Viewed (geographical distribution)

Total article views: 5,034 (including HTML, PDF, and XML) Thereof 4,787 with geography defined and 247 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved (final revised paper)

Latest update: 01 Nov 2026
Download
Short summary
This study introduces a hybrid data assimilation scheme for precise streamflow predictions during intense rainfall and hurricanes. Tested in real events, it outperforms traditional methods by up to 50 %, utilizing ensemble and climatological background covariances. The adaptive algorithm ensures reliability with a small ensemble, offering improved forecasts up to 18 h in advance, marking a significant advancement in flood prediction capabilities.
Share
Altmetrics
Final-revised paper
Preprint