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 20, issue 7
Hydrol. Earth Syst. Sci., 20, 2811–2825, 2016
https://doi.org/10.5194/hess-20-2811-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 20, 2811–2825, 2016
https://doi.org/10.5194/hess-20-2811-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 13 Jul 2016

Research article | 13 Jul 2016

Using dry and wet year hydroclimatic extremes to guide future hydrologic projections

Stephen Oni et al.

Download

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (06 Apr 2016) by Niko Verhoest
AR by Stephen Oni on behalf of the Authors (04 May 2016)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (15 May 2016) by Niko Verhoest
RR by Anonymous Referee #1 (10 Jun 2016)
RR by Patrick Willems (12 Jun 2016)
ED: Publish subject to minor revisions (Editor review) (13 Jun 2016) by Niko Verhoest
AR by Stephen Oni on behalf of the Authors (21 Jun 2016)  Author's response    Manuscript
ED: Publish as is (22 Jun 2016) by Niko Verhoest
Publications Copernicus
Download
Short summary
This paper presents an important framework to improve hydrologic projections in cold regions. Hydrologic modelling/projections are often based on model calibration to long-term data. Here we used dry and wet years as a proxy to quantify uncertainty in projecting hydrologic extremes. We showed that projections based on long-term data could underestimate runoff by up to 35% in boreal regions. We believe the hydrologic modelling community will benefit from new insights derived from this study.
This paper presents an important framework to improve hydrologic projections in cold regions....
Citation