Articles | Volume 22, issue 9
Research article
07 Sep 2018
Research article |  | 07 Sep 2018

Global re-analysis datasets to improve hydrological assessment and snow water equivalent estimation in a sub-Arctic watershed

David R. Casson, Micha Werner, Albrecht Weerts, and Dimitri Solomatine


Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Publish as is (09 Aug 2018) by Gianpaolo Balsamo
AR by David Casson on behalf of the Authors (24 Aug 2018)  Author's response    Manuscript
Short summary
In high-latitude (> 60° N) watersheds, measuring the snowpack and predicting of snowmelt runoff are uncertain due to the lack of data and complex physical processes. This provides challenges for hydrological assessment and operational water management. Global re-analysis datasets have great potential to aid in snowpack representation and snowmelt prediction when combined with a distributed hydrological model, though they still have clear limitations in remote boreal forest and tundra environments.