Articles | Volume 27, issue 1
https://doi.org/10.5194/hess-27-289-2023
https://doi.org/10.5194/hess-27-289-2023
Research article
 | 
12 Jan 2023
Research article |  | 12 Jan 2023

The effects of rain and evapotranspiration statistics on groundwater recharge estimations for semi-arid environments

Tuvia Turkeltaub and Golan Bel

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on hess-2022-257', Tongchao Nan, 20 Sep 2022
    • AC1: 'Reply on CC1', Golan Bel, 21 Sep 2022
  • RC1: 'Comment on hess-2022-257', Tongchao Nan, 23 Sep 2022
    • AC2: 'Reply on RC1', Golan Bel, 08 Dec 2022
  • RC2: 'Comment on hess-2022-257', Anonymous Referee #2, 03 Dec 2022
    • AC3: 'Reply on RC2', Golan Bel, 08 Dec 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Publish subject to minor revisions (further review by editor) (09 Dec 2022) by Gerrit H. de Rooij
AR by Golan Bel on behalf of the Authors (09 Dec 2022)  Author's response    Author's tracked changes    Manuscript
ED: Publish subject to technical corrections (09 Dec 2022) by Gerrit H. de Rooij
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Short summary
Groundwater is an essential resource affected by climate conditions and anthropogenic activities. Estimations of groundwater recharge under current and future climate conditions require long-term climate records that are scarce. Different methods to synthesize climate data, based on observations, are used to estimate groundwater recharge. In terms of groundwater recharge estimation, the best synthesis method is based on the daily statistics corrected to match the observed monthly statistics.