Articles | Volume 26, issue 10
https://doi.org/10.5194/hess-26-2797-2022
https://doi.org/10.5194/hess-26-2797-2022
Research article
 | 
01 Jun 2022
Research article |  | 01 Jun 2022

Performance-based comparison of regionalization methods to improve the at-site estimates of daily precipitation

Abubakar Haruna, Juliette Blanchet, and Anne-Catherine Favre

Viewed

Total article views: 1,674 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,211 428 35 1,674 26 19
  • HTML: 1,211
  • PDF: 428
  • XML: 35
  • Total: 1,674
  • BibTeX: 26
  • EndNote: 19
Views and downloads (calculated since 30 Nov 2021)
Cumulative views and downloads (calculated since 30 Nov 2021)

Viewed (geographical distribution)

Total article views: 1,674 (including HTML, PDF, and XML) Thereof 1,497 with geography defined and 177 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 26 Apr 2024
Download
Short summary
Reliable prediction of floods depends on the quality of the input data such as precipitation. However, estimation of precipitation from the local measurements is known to be difficult, especially for extremes. Regionalization improves the estimates by increasing the quantity of data available for estimation. Here, we compare three regionalization methods based on their robustness and reliability. We apply the comparison to a dense network of daily stations within and outside Switzerland.