Articles | Volume 28, issue 15
https://doi.org/10.5194/hess-28-3665-2024
https://doi.org/10.5194/hess-28-3665-2024
Technical note
 | 
13 Aug 2024
Technical note |  | 13 Aug 2024

Technical Note: The divide and measure nonconformity – how metrics can mislead when we evaluate on different data partitions

Daniel Klotz, Martin Gauch, Frederik Kratzert, Grey Nearing, and Jakob Zscheischler

Viewed

Total article views: 1,354 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
996 292 66 1,354 21 54 44
  • HTML: 996
  • PDF: 292
  • XML: 66
  • Total: 1,354
  • Supplement: 21
  • BibTeX: 54
  • EndNote: 44
Views and downloads (calculated since 29 Feb 2024)
Cumulative views and downloads (calculated since 29 Feb 2024)

Viewed (geographical distribution)

Total article views: 1,354 (including HTML, PDF, and XML) Thereof 1,332 with geography defined and 22 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 10 Oct 2024
Download
Short summary
The evaluation of model performance is essential for hydrological modeling. Using performance criteria requires a deep understanding of their properties. We focus on a counterintuitive aspect of the Nash–Sutcliffe efficiency (NSE) and show that if we divide the data into multiple parts, the overall performance can be higher than all the evaluations of the subsets. Although this follows from the definition of the NSE, the resulting behavior can have unintended consequences in practice.