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

Chukalla, Abebe D.; Mul, Marloes L.; van der Zaag, Pieter; van Halsema, Gerardo; Mubaya, Evaristo; Muchanga, Esperança; den Besten, Nadja; Karimi, Poolad

doi:https://doi.org/10.5194/hess-26-2759-2022

Articles | Volume 26, issue 10

https://doi.org/10.5194/hess-26-2759-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-26-2759-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 26, issue 10

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, Marloes L. Mul, Pieter van der Zaag, Gerardo van Halsema, Evaristo Mubaya, Esperança Muchanga, Nadja den Besten, and Poolad Karimi

Supplement

https://doi.org/10.5194/hess-26-2759-2022-supplement

Data sets

The FAO portal to monitor Water Productivity through Open access of Remotely sensed derived data FAO https://wapor.apps.fao.org/home/WAPOR_2/1

Model code and software

StandarStandardized protocol for land and water productivity analyses using WaPOR (v1.1) A. D. Chukalla, M. Mul, B. Tran, and P. Karimi https://doi.org/10.5281/zenodo.4641360

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.