Articles | Volume 26, issue 21
Hydrol. Earth Syst. Sci., 26, 5685–5695, 2022
https://doi.org/10.5194/hess-26-5685-2022
Hydrol. Earth Syst. Sci., 26, 5685–5695, 2022
https://doi.org/10.5194/hess-26-5685-2022
Technical note
11 Nov 2022
Technical note | 11 Nov 2022

Technical note: Modeling spatial fields of extreme precipitation – a hierarchical Bayesian approach

Bianca Rahill-Marier et al.

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2022-70', Anonymous Referee #1, 18 Apr 2022
    • AC1: 'Reply on RC1', Naresh Devineni, 25 Jul 2022
  • RC2: 'Comment on hess-2022-70', Anonymous Referee #2, 30 May 2022
    • AC2: 'Reply on RC2', Naresh Devineni, 25 Jul 2022
  • RC3: 'Comment on hess-2022-70', Anonymous Referee #3, 13 Jun 2022
    • AC3: 'Reply on RC3', Naresh Devineni, 25 Jul 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Publish subject to revisions (further review by editor and referees) (29 Jul 2022) by Xing Yuan
AR by Naresh Devineni on behalf of the Authors (17 Sep 2022)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (25 Sep 2022) by Xing Yuan
RR by Anonymous Referee #3 (28 Sep 2022)
RR by Xun Sun (20 Oct 2022)
ED: Publish as is (25 Oct 2022) by Xing Yuan
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Short summary
We present a new approach to modeling extreme regional rainfall by considering the spatial structure of extreme events. The developed models allow a probabilistic exploration of how the regional drainage network may respond to extreme rainfall events and provide a foundation for how future risks may be better estimated.