Articles | Volume 22, issue 8
https://doi.org/10.5194/hess-22-4145-2018
https://doi.org/10.5194/hess-22-4145-2018
Research article
 | 
03 Aug 2018
Research article |  | 03 Aug 2018

Improvement of model evaluation by incorporating prediction and measurement uncertainty

Lei Chen, Shuang Li, Yucen Zhong, and Zhenyao Shen

Viewed

Total article views: 2,984 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,993 940 51 2,984 305 59 64
  • HTML: 1,993
  • PDF: 940
  • XML: 51
  • Total: 2,984
  • Supplement: 305
  • BibTeX: 59
  • EndNote: 64
Views and downloads (calculated since 23 Aug 2017)
Cumulative views and downloads (calculated since 23 Aug 2017)

Viewed (geographical distribution)

Total article views: 2,984 (including HTML, PDF, and XML) Thereof 2,876 with geography defined and 108 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 16 Apr 2024
Download
Short summary
In this study, the cumulative distribution function approach (CDFA) and the Monte Carlo approach (MCA) were used to develop two new approaches for model evaluation within an uncertainty framework. These proposed methods could be extended to watershed models to provide a substitution for traditional model evaluations within an uncertainty framework.