Articles | Volume 25, issue 9
Hydrol. Earth Syst. Sci., 25, 4773–4788, 2021
https://doi.org/10.5194/hess-25-4773-2021
Hydrol. Earth Syst. Sci., 25, 4773–4788, 2021
https://doi.org/10.5194/hess-25-4773-2021

Research article 02 Sep 2021

Research article | 02 Sep 2021

Bias-correcting input variables enhances forecasting of reference crop evapotranspiration

Qichun Yang et al.

Download

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2021-69', Anonymous Referee #1, 24 Feb 2021
    • AC1: 'Reply on RC1', Qichun Yang, 10 Jun 2021
  • RC2: 'Comment on hess-2021-69', Anonymous Referee #2, 24 Feb 2021
    • AC3: 'Reply on RC2', Qichun Yang, 20 Jul 2021
  • RC3: 'Comment on hess-2021-69', Anonymous Referee #3, 04 Mar 2021
    • AC4: 'Reply on RC3', Qichun Yang, 20 Jul 2021

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Publish subject to minor revisions (further review by editor) (21 Jul 2021) by Nadia Ursino
AR by Qichun Yang on behalf of the Authors (28 Jul 2021)  Author's response    Author's tracked changes    Manuscript
ED: Publish as is (05 Aug 2021) by Nadia Ursino
Download
Short summary
Forecasts of water losses from land surface to the air are highly valuable for water resource management and planning. In this study, we aim to fill a critical knowledge gap in the forecasting of evaporative water loss. Model experiments across Australia clearly suggest the necessity of correcting errors in input variables for more reliable water loss forecasting. We anticipate that the strategy developed in our work will benefit future water loss forecasting and lead to more skillful forecasts.