Articles | Volume 26, issue 14
https://doi.org/10.5194/hess-26-3805-2022
https://doi.org/10.5194/hess-26-3805-2022
Research article
 | 
19 Jul 2022
Research article |  | 19 Jul 2022

On the similarity of hillslope hydrologic function: a clustering approach based on groundwater changes

Fadji Z. Maina, Haruko M. Wainwright, Peter James Dennedy-Frank, and Erica R. Siirila-Woodburn

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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-2021-520', A. D. Parsekian, 05 Feb 2022
    • AC1: 'Reply on RC1', Fadji Zaouna Maina, 09 Mar 2022
  • RC2: 'Comment on hess-2021-520', Anonymous Referee #2, 10 Feb 2022
    • AC2: 'Reply on RC2', Fadji Zaouna Maina, 09 Mar 2022

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) (09 Mar 2022) by Hilary McMillan
AR by Fadji Zaouna Maina on behalf of the Authors (13 Apr 2022)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (15 Apr 2022) by Hilary McMillan
RR by Anonymous Referee #2 (08 May 2022)
RR by A. D. Parsekian (08 Jun 2022)
ED: Publish as is (12 Jun 2022) by Hilary McMillan
AR by Fadji Zaouna Maina on behalf of the Authors (13 Jun 2022)
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Short summary
We propose a hillslope clustering approach based on the seasonal changes in groundwater levels and test its performance by comparing it to several common clustering approaches (aridity index, topographic wetness index, elevation, land cover, and machine-learning clustering). The proposed approach is robust as it reasonably categorizes hillslopes with similar elevation, land cover, hydroclimate, land surface processes, and subsurface hydrodynamics, hence a similar hydrologic function.