Articles | Volume 25, issue 6
https://doi.org/10.5194/hess-25-2997-2021
https://doi.org/10.5194/hess-25-2997-2021
Research article
 | 
03 Jun 2021
Research article |  | 03 Jun 2021

Evaluation of random forests for short-term daily streamflow forecasting in rainfall- and snowmelt-driven watersheds

Leo Triet Pham, Lifeng Luo, and Andrew Finley

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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: Publish subject to revisions (further review by editor and referees) (28 Sep 2020) by Dimitri Solomatine
AR by Leo Pham on behalf of the Authors (04 Nov 2020)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (19 Nov 2020) by Dimitri Solomatine
RR by Francesco Avanzi (21 Nov 2020)
RR by Anonymous Referee #2 (02 Jan 2021)
ED: Publish subject to revisions (further review by editor and referees) (15 Jan 2021) by Dimitri Solomatine
AR by Leo Pham on behalf of the Authors (24 Jan 2021)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (01 Feb 2021) by Dimitri Solomatine
RR by Anonymous Referee #2 (05 Feb 2021)
ED: Publish subject to revisions (further review by editor and referees) (09 Feb 2021) by Dimitri Solomatine
AR by Leo Pham on behalf of the Authors (02 Mar 2021)  Author's response    Author's tracked changes    Manuscript
ED: Publish subject to revisions (further review by editor and referees) (10 Mar 2021) by Dimitri Solomatine
AR by Leo Pham on behalf of the Authors (10 Mar 2021)  Author's response    Author's tracked changes    Manuscript
ED: Publish subject to revisions (further review by editor and referees) (10 Mar 2021) by Dimitri Solomatine
ED: Referee Nomination & Report Request started (11 Mar 2021) by Dimitri Solomatine
RR by Anonymous Referee #2 (15 Mar 2021)
ED: Publish subject to minor revisions (review by editor) (05 Apr 2021) by Dimitri Solomatine
AR by Leo Pham on behalf of the Authors (06 Apr 2021)  Author's response    Author's tracked changes    Manuscript
ED: Publish as is (15 Apr 2021) by Dimitri Solomatine
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Short summary
Model evaluation metrics suggest that RF performs better in snowmelt-driven watersheds. The largest improvements in forecasts compared to benchmark models are found among rainfall-driven watersheds. RF performance deteriorates with increases in catchment slope and soil sandiness. We note disagreement between two popular measures of RF variable importance and recommend jointly considering these measures with the physical processes under study.