Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 26, issue 21
Articles | Volume 26, issue 21
https://doi.org/10.5194/hess-26-5669-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-26-5669-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 26, issue 21
Research article
 | 
10 Nov 2022
Research article |  | 10 Nov 2022

Seamless streamflow forecasting at daily to monthly scales: MuTHRE lets you have your cake and eat it too

David McInerney, Mark Thyer, Dmitri Kavetski, Richard Laugesen, Fitsum Woldemeskel, Narendra Tuteja, and George Kuczera

Viewed

Total article views: 1,994 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,401 524 69 1,994 49 48
  • HTML: 1,401
  • PDF: 524
  • XML: 69
  • Total: 1,994
  • BibTeX: 49
  • EndNote: 48
Views and downloads (calculated since 26 Jan 2022)
Cumulative views and downloads (calculated since 26 Jan 2022)

Viewed (geographical distribution)

Total article views: 1,994 (including HTML, PDF, and XML) Thereof 1,829 with geography defined and 165 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 23 Nov 2024
Download
Short summary
Streamflow forecasts a day to a month ahead are highly valuable for water resources management. Current practice often develops forecasts for specific lead times and aggregation timescales. In contrast, a single, seamless forecast can serve multiple lead times/timescales. This study shows seamless forecasts can match the performance of forecasts developed specifically at the monthly scale, while maintaining quality at other lead times. Hence, users need not sacrifice capability for performance.
Read more