Articles | Volume 30, issue 11
https://doi.org/10.5194/hess-30-3647-2026
https://doi.org/10.5194/hess-30-3647-2026
Research article
 | 
16 Jun 2026
Research article |  | 16 Jun 2026

Continental-scale prediction of hydrologic signatures and processes

Ryoko Araki, Anne Holt, John C. Hammond, Admin Husic, Gemma Coxon, and Hilary K. McMillan

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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 egusphere-2025-6156', Anonymous Referee #1, 19 Jan 2026
    • AC1: 'Reply on RC1', Ryoko Araki, 03 Mar 2026
  • RC2: 'Comment on egusphere-2025-6156', Anonymous Referee #2, 22 Jan 2026
    • AC2: 'Reply on RC2', Ryoko Araki, 03 Mar 2026

Peer review completion

AR – Author's response | RR – Referee report | ED – Editor decision | EF – Editorial file upload
ED: Publish subject to revisions (further review by editor and referees) (16 Mar 2026) by Albrecht Weerts
AR by Ryoko Araki on behalf of the Authors (20 Mar 2026)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (22 Mar 2026) by Albrecht Weerts
RR by Anonymous Referee #1 (03 Apr 2026)
RR by Anonymous Referee #2 (14 Apr 2026)
ED: Publish subject to minor revisions (review by editor) (22 Apr 2026) by Albrecht Weerts
AR by Ryoko Araki on behalf of the Authors (28 Apr 2026)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (11 May 2026) by Albrecht Weerts
AR by Ryoko Araki on behalf of the Authors (14 May 2026)  Manuscript 
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Short summary
We mapped dominant hydrologic processes across the United States by analyzing observed streamflow dynamics. Using random forest models and interpretable machine learning techniques, we predicted processes in data-scarce regions and identified key drivers such as climate, soil and geology, land cover, topography, and human influence. The resulting maps of dominant processes and their drivers reveal strong regional patterns that guide hydrologic model selection and water resource management.
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