Proceedings of IAHS
Proceedings of IAHS
PIAHS
Articles | Volume 385
Articles | Volume 385
https://doi.org/10.5194/piahs-385-65-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/piahs-385-65-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 385
Post-conference publication
 | 
18 Apr 2024
Post-conference publication |  | 18 Apr 2024

Regional multi-objective calibration for distributed hydrological modelling: a decision tree based approach

Matteo Pesce, Alberto Viglione, Jost von Hardenberg, Larisa Tarasova, Stefano Basso, Ralf Merz, Juraj Parajka, and Rui Tong

Viewed

Total article views: 281 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
192 71 18 281 15 12
  • HTML: 192
  • PDF: 71
  • XML: 18
  • Total: 281
  • BibTeX: 15
  • EndNote: 12
Views and downloads (calculated since 18 Apr 2024)
Cumulative views and downloads (calculated since 18 Apr 2024)

Viewed (geographical distribution)

Total article views: 269 (including HTML, PDF, and XML) Thereof 269 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 03 Nov 2024
Download
Short summary
The manuscript describes an application of PArameter Set Shuffling (PASS) approach in the Alpine region. A machine learning decision-tree algorithm is applied for the regional calibration of a conceptual semi-distributed hydrological model. Regional model efficiencies don't decrease significantly when moving in space from catchments used for the regional calibration (training) to catchments used for the procedure validation (test) and, in time, from the calibration to the verification period.
Read more