Articles | Volume 19, issue 9
https://doi.org/10.5194/hess-19-3969-2015
https://doi.org/10.5194/hess-19-3969-2015
Research article
 | 
25 Sep 2015
Research article |  | 25 Sep 2015

Performance and robustness of probabilistic river forecasts computed with quantile regression based on multiple independent variables

F. Hoss and P. S. Fischbeck

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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: Reconsider after major revisions (06 Feb 2015) by Albrecht Weerts
AR by Frauke Hoss on behalf of the Authors (12 Feb 2015)  Author's response   Manuscript 
ED: Referee Nomination & Report Request started (13 Feb 2015) by Albrecht Weerts
RR by Satish Regonda (25 Apr 2015)
RR by Anonymous Referee #2 (17 Jun 2015)
ED: Publish subject to minor revisions (Editor review) (26 Jun 2015) by Albrecht Weerts
AR by Frauke Hoss on behalf of the Authors (28 Jul 2015)
ED: Publish as is (27 Aug 2015) by Albrecht Weerts
AR by Frauke Hoss on behalf of the Authors (06 Sep 2015)
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Short summary
This paper further develops the method of quantile regression (QR) to generate probabilistic river stage forecasts. Besides the forecast itself, this study uses the rate of rise of the river stage in the last 24 and 48h and the forecast error 24 and 48h before as predictors in QR configurations. When compared to just using the forecast as an independent variable, adding the latter four predictors significantly improved the forecasts, as measured by the Brier skill score and the CRPS.