Articles | Volume 26, issue 18
https://doi.org/10.5194/hess-26-4603-2022
https://doi.org/10.5194/hess-26-4603-2022
Research article
 | 
16 Sep 2022
Research article |  | 16 Sep 2022

Evaluation of water flux predictive models developed using eddy-covariance observations and machine learning: a meta-analysis

Haiyang Shi, Geping Luo, Olaf Hellwich, Mingjuan Xie, Chen Zhang, Yu Zhang, Yuangang Wang, Xiuliang Yuan, Xiaofei Ma, Wenqiang Zhang, Alishir Kurban, Philippe De Maeyer, and Tim Van de Voorde

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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-2022-90', Anonymous Referee #1, 07 May 2022
  • RC2: 'Comment on hess-2022-90', Anonymous Referee #2, 27 May 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) (12 Jun 2022) by Efrat Morin
AR by Haiyang Shi on behalf of the Authors (20 Jun 2022)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (24 Jun 2022) by Efrat Morin
RR by Anonymous Referee #1 (28 Jun 2022)
RR by Anonymous Referee #2 (01 Aug 2022)
ED: Publish subject to revisions (further review by editor and referees) (01 Aug 2022) by Efrat Morin
AR by Haiyang Shi on behalf of the Authors (03 Aug 2022)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (11 Aug 2022) by Efrat Morin
RR by Anonymous Referee #2 (18 Aug 2022)
ED: Publish subject to minor revisions (review by editor) (28 Aug 2022) by Efrat Morin
AR by Haiyang Shi on behalf of the Authors (28 Aug 2022)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (29 Aug 2022) by Efrat Morin
AR by Haiyang Shi on behalf of the Authors (29 Aug 2022)
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Short summary
There have been many machine learning simulation studies based on eddy-covariance observations for water flux and evapotranspiration. We performed a meta-analysis of such studies to clarify the impact of different algorithms and predictors, etc., on the reported prediction accuracy. It can, to some extent, guide future global water flux modeling studies and help us better understand the terrestrial ecosystem water cycle.