Articles | Volume 22, issue 4
Research article
11 Apr 2018
Research article |  | 11 Apr 2018

Statistical forecast of seasonal discharge in Central Asia using observational records: development of a generic linear modelling tool for operational water resource management

Heiko Apel, Zharkinay Abdykerimova, Marina Agalhanova, Azamat Baimaganbetov, Nadejda Gavrilenko, Lars Gerlitz, Olga Kalashnikova, Katy Unger-Shayesteh, Sergiy Vorogushyn, and Abror Gafurov


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 subject to revisions (further review by Editor and Referees) (01 Oct 2017) by Ilias Pechlivanidis
AR by Heiko Apel on behalf of the Authors (09 Nov 2017)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (26 Nov 2017) by Ilias Pechlivanidis
RR by Anonymous Referee #2 (12 Dec 2017)
RR by Anonymous Referee #3 (16 Jan 2018)
RR by Anonymous Referee #4 (24 Jan 2018)
ED: Publish subject to minor revisions (review by editor) (04 Feb 2018) by Ilias Pechlivanidis
AR by Heiko Apel on behalf of the Authors (13 Feb 2018)  Author's response    Manuscript
ED: Publish as is (27 Feb 2018) by Ilias Pechlivanidis
Short summary
Central Asia crucially depends on water resources supplied by snow melt in the mountains during summer. To support water resources management we propose a generic tool for statistical forecasts of seasonal discharge based on multiple linear regressions. The predictors are observed precipitation and temperature, snow coverage, and discharge. The automatically derived models for 13 different catchments provided very skilful forecasts in April, and acceptable forecasts in January.