Articles | Volume 25, issue 8
https://doi.org/10.5194/hess-25-4611-2021
https://doi.org/10.5194/hess-25-4611-2021
Research article
 | 
30 Aug 2021
Research article |  | 30 Aug 2021

Combining split-sample testing and hidden Markov modelling to assess the robustness of hydrological models

Etienne Guilpart, Vahid Espanmanesh, Amaury Tilmant, and François Anctil

Viewed

Total article views: 2,800 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,092 639 69 2,800 74 90
  • HTML: 2,092
  • PDF: 639
  • XML: 69
  • Total: 2,800
  • BibTeX: 74
  • EndNote: 90
Views and downloads (calculated since 22 Dec 2020)
Cumulative views and downloads (calculated since 22 Dec 2020)

Viewed (geographical distribution)

Total article views: 2,800 (including HTML, PDF, and XML) Thereof 2,640 with geography defined and 160 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 16 Sep 2025
Download
Short summary
The stationary assumption in hydrology has become obsolete because of climate changes. In that context, it is crucial to assess the performance of a hydrologic model over a wide range of climates and their corresponding hydrologic conditions. In this paper, numerous, contrasted, climate sequences identified by a hidden Markov model (HMM) are used in a differential split-sample testing framework to assess the robustness of a hydrologic model. We illustrate the method on the Senegal River.
Share