Articles | Volume 28, issue 3
Research article
16 Feb 2024
Research article |  | 16 Feb 2024

Seasonal prediction of end-of-dry-season watershed behavior in a highly interconnected alluvial watershed in northern California

Claire Kouba and Thomas Harter


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2023-41', Anonymous Referee #1, 29 Mar 2023
    • AC1: 'Reply on RC1', Claire Kouba, 24 Jul 2023
  • RC2: 'Comment on hess-2023-41', Rob van Kirk, 04 Apr 2023
    • AC2: 'Reply on RC2', Claire Kouba, 24 Jul 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
ED: Reconsider after major revisions (further review by editor and referees) (21 Aug 2023) by Genevieve Ali
AR by Claire Kouba on behalf of the Authors (30 Sep 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (25 Oct 2023) by Genevieve Ali
RR by Rob van Kirk (30 Oct 2023)
RR by Belize Lane (04 Dec 2023)
ED: Publish subject to technical corrections (18 Dec 2023) by Genevieve Ali
AR by Claire Kouba on behalf of the Authors (30 Dec 2023)  Author's response   Manuscript 

The requested paper has a corresponding corrigendum published. Please read the corrigendum first before downloading the article.

Short summary
In some watersheds, the severity of the dry season has a large impact on aquatic ecosystems. In this study, we design a way to predict, 5–6 months in advance, how severe the dry season will be in a rural watershed in northern California. This early warning can support seasonal adaptive management. To predict these two values, we assess data about snow, rain, groundwater, and river flows. We find that maximum snowpack and total wet season rainfall best predict dry season severity.