Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 26, issue 1
Articles | Volume 26, issue 1
https://doi.org/10.5194/hess-26-197-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-26-197-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 26, issue 1
Research article
 | 
14 Jan 2022
Research article |  | 14 Jan 2022

Choosing between post-processing precipitation forecasts or chaining several uncertainty quantification tools in hydrological forecasting systems

Emixi Sthefany Valdez, François Anctil, and Maria-Helena Ramos

Viewed

Total article views: 3,628 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,651 899 78 3,628 108 56 58
  • HTML: 2,651
  • PDF: 899
  • XML: 78
  • Total: 3,628
  • Supplement: 108
  • BibTeX: 56
  • EndNote: 58
Views and downloads (calculated since 16 Aug 2021)
Cumulative views and downloads (calculated since 16 Aug 2021)

Viewed (geographical distribution)

Total article views: 3,628 (including HTML, PDF, and XML) Thereof 3,420 with geography defined and 208 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 13 Dec 2024
Download
Short summary
We investigated how a precipitation post-processor interacts with other tools for uncertainty quantification in a hydrometeorological forecasting chain. Four systems were implemented to generate 7 d ensemble streamflow forecasts, which vary from partial to total uncertainty estimation. Overall analysis showed that post-processing and initial condition estimation ensure the most skill improvements, in some cases even better than a system that considers all sources of uncertainty.
Read more