Articles | Volume 23, issue 11
https://doi.org/10.5194/hess-23-4783-2019
https://doi.org/10.5194/hess-23-4783-2019
Research article
 | 
25 Nov 2019
Research article |  | 25 Nov 2019

A virtual hydrological framework for evaluation of stochastic rainfall models

Bree Bennett, Mark Thyer, Michael Leonard, Martin Lambert, and Bryson Bates

Viewed

Total article views: 2,985 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,837 1,086 62 2,985 140 71 81
  • HTML: 1,837
  • PDF: 1,086
  • XML: 62
  • Total: 2,985
  • Supplement: 140
  • BibTeX: 71
  • EndNote: 81
Views and downloads (calculated since 25 Sep 2018)
Cumulative views and downloads (calculated since 25 Sep 2018)

Viewed (geographical distribution)

Total article views: 2,985 (including HTML, PDF, and XML) Thereof 2,580 with geography defined and 405 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 19 May 2024
Download
Short summary
A new stochastic rainfall model evaluation framework is introduced, with three key features: (1) streamflow-based, to directly evaluate modelled streamflow performance, (2) virtual, to avoid confounding errors in hydrological models or data, and (3) targeted, to isolate errors according to specific sites/months. The framework identified the importance of rainfall in the wetting-up months for providing reliable predictions of streamflow over the entire year despite their low flow volumes.