Articles | Volume 28, issue 17
https://doi.org/10.5194/hess-28-4219-2024
https://doi.org/10.5194/hess-28-4219-2024
Research article
 | Highlight paper
 | 
12 Sep 2024
Research article | Highlight paper |  | 12 Sep 2024

Large-sample hydrology – a few camels or a whole caravan?

Franziska Clerc-Schwarzenbach, Giovanni Selleri, Mattia Neri, Elena Toth, Ilja van Meerveld, and Jan Seibert

Viewed

Total article views: 1,972 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,629 292 51 1,972 27 21
  • HTML: 1,629
  • PDF: 292
  • XML: 51
  • Total: 1,972
  • BibTeX: 27
  • EndNote: 21
Views and downloads (calculated since 02 Apr 2024)
Cumulative views and downloads (calculated since 02 Apr 2024)

Viewed (geographical distribution)

Total article views: 1,972 (including HTML, PDF, and XML) Thereof 1,923 with geography defined and 49 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 19 Oct 2024
Download
Executive editor
Large sample hydrology datasets such as Caravan provides the community with hydrometeorological information and catchment attributes for many catchments in the world and offers the opportunity for hydrological research. However, there are considerable differences between the forcing data of Caravan compared to the CAMELS datasets, especially with potential evaporation. This can lead to wrong conclusions on catchment hydrological drivers and affect regionalization. This papers shows the important of robustness of large sample datasets and the need to keep assessing that.
Short summary
We show that the differences between the forcing data included in three CAMELS datasets (US, BR, GB) and the forcing data included for the same catchments in the Caravan dataset affect model calibration considerably. The model performance dropped when the data from the Caravan dataset were used instead of the original data. Most of the model performance drop could be attributed to the differences in precipitation data. However, differences were largest for the potential evapotranspiration data.