Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

IF value: 5.153
IF5.153
IF 5-year value: 5.460
IF 5-year
5.460
CiteScore value: 7.8
CiteScore
7.8
SNIP value: 1.623
SNIP1.623
IPP value: 4.91
IPP4.91
SJR value: 2.092
SJR2.092
Scimago H <br class='widget-line-break'>index value: 123
Scimago H
index
123
h5-index value: 65
h5-index65
Volume 23, issue 4
Hydrol. Earth Syst. Sci., 23, 2147–2172, 2019
https://doi.org/10.5194/hess-23-2147-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Hydrol. Earth Syst. Sci., 23, 2147–2172, 2019
https://doi.org/10.5194/hess-23-2147-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 30 Apr 2019

Research article | 30 Apr 2019

A likelihood framework for deterministic hydrological models and the importance of non-stationary autocorrelation

Lorenz Ammann et al.

Viewed

Total article views: 2,053 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,444 574 35 2,053 53 41 41
  • HTML: 1,444
  • PDF: 574
  • XML: 35
  • Total: 2,053
  • Supplement: 53
  • BibTeX: 41
  • EndNote: 41
Views and downloads (calculated since 13 Aug 2018)
Cumulative views and downloads (calculated since 13 Aug 2018)

Viewed (geographical distribution)

Total article views: 1,788 (including HTML, PDF, and XML) Thereof 1,777 with geography defined and 11 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved (final revised paper)

No saved metrics found.

Saved (preprint)

No saved metrics found.

Discussed (final revised paper)

No discussed metrics found.

Discussed (preprint)

No discussed metrics found.
Latest update: 22 Oct 2020
Publications Copernicus
Download
Short summary
The uncertainty of hydrological models can be substantial, and its quantification and realistic description are often difficult. We propose a new flexible probabilistic framework to describe and quantify this uncertainty. It is show that the correlation of the errors can be non-stationary, and that accounting for temporal changes in correlation can lead to strongly improved probabilistic predictions. This is a promising avenue for improving uncertainty estimation in hydrological modelling.
The uncertainty of hydrological models can be substantial, and its quantification and realistic...
Citation