Articles | Volume 24, issue 8
https://doi.org/10.5194/hess-24-3967-2020
https://doi.org/10.5194/hess-24-3967-2020
Research article
 | 
12 Aug 2020
Research article |  | 12 Aug 2020

Stochastic simulation of streamflow and spatial extremes: a continuous, wavelet-based approach

Manuela I. Brunner and Eric Gilleland

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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: Reconsider after major revisions (further review by editor and referees) (23 Apr 2020) by Patricia Saco
AR by Manuela Irene Brunner on behalf of the Authors (23 Apr 2020)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (27 May 2020) by Patricia Saco
RR by Anonymous Referee #1 (16 Jun 2020)
ED: Publish subject to minor revisions (review by editor) (16 Jun 2020) by Patricia Saco
AR by Manuela Irene Brunner on behalf of the Authors (18 Jun 2020)  Author's response    Manuscript
ED: Publish as is (07 Jul 2020) by Patricia Saco
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Short summary
Stochastically generated streamflow time series are used for various water management and hazard estimation applications. They provide realizations of plausible but yet unobserved streamflow time series with the same characteristics as the observed data. We propose a stochastic simulation approach in the frequency domain instead of the time domain. Our evaluation results suggest that the flexible, continuous simulation approach is valuable for a diverse range of water management applications.