Articles | Volume 26, issue 10
Hydrol. Earth Syst. Sci., 26, 2759–2778, 2022
https://doi.org/10.5194/hess-26-2759-2022
Hydrol. Earth Syst. Sci., 26, 2759–2778, 2022
https://doi.org/10.5194/hess-26-2759-2022
Research article
25 May 2022
Research article | 25 May 2022

A framework for irrigation performance assessment using WaPOR data: the case of a sugarcane estate in Mozambique

Abebe D. Chukalla et al.

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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-2021-409', Anonymous Referee #1, 14 Oct 2021
    • AC2: 'Reply on RC1', Abebe Demissie Chukalla, 31 Jan 2022
  • RC2: 'Comment on hess-2021-409', Anonymous Referee #2, 12 Jan 2022
    • AC1: 'Reply on RC2', Abebe Demissie Chukalla, 30 Jan 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Publish subject to minor revisions (further review by editor) (23 Feb 2022) by Dominic Mazvimavi
AR by Abebe Demissie Chukalla on behalf of the Authors (04 Mar 2022)  Author's response    Author's tracked changes    Manuscript
ED: Publish as is (04 May 2022) by Dominic Mazvimavi

Post-review adjustments

AA: Author's adjustment | EA: Editor approval
AA by Abebe Demissie Chukalla on behalf of the Authors (24 May 2022)   Author's adjustment   Manuscript
EA: Adjustments approved (24 May 2022) by Dominic Mazvimavi
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Short summary
New techniques to monitor the performance of irrigation schemes are vital to improve land and water productivity. We developed a framework and applied the remotely sensed FAO WaPOR dataset to assess uniformity, equity, adequacy, and land and water productivity at the Xinavane sugarcane estate, segmented by three irrigation methods. The developed performance assessment framework and the Python script in Jupyter Notebooks can aid in such irrigation performance analysis in other regions.