event 02 sept. 2021

Research article // A scale-based framework to understand the promises, pitfalls and paradoxes of irrigation efficiency to meet major water challenges

By Bruce Lankford, Alvar Closas, James Dalton, Elena López Gunn, Tim Hesse, Jerry W Knox, Saskia van der Kooij, Jonathan Lautze, David Molden, Stuart Orr, Jamie Pittock, Brian Richter, Philip J Riddell, Christopher A Scott, Jean-philippe Venot, Jeroen Vos and Margreet Zwarteveen. In this paper, the authors propose a framework termed an ‘irrigation efficiency matrix’ (IEM) which places IE centrally within contemporary water challenges and purposively addresses the ‘promises’ of IE (referring to expectations of the benefits associated with higher and improving IE) set against its ‘pitfalls’ (hidden risks, biases, omissions and faultlines associated with not fully understanding IE) and ‘paradoxes’ (clear contradictions and/or when outcomes materially go against expectations). The backdrop of this paper is therefore the control of water by people, sensors and machines in the multitudinous evolving fields of the world’s irrigation systems and how that cumulatively shapes and is recursively shaped by weather, climate and water management in irrigation systems and river basins, in turn responding to powerful corporate, national and international interests.

category Research Papers, Publications and Books tag Water tag Irrigation tag Governance tag SDGs
Irrigation and SD Gs

© The authors

Highlights

  • Irrigation efficiency is more than a performance indicator or water-savings panacea.
  • Managing irrigation efficiency supports water, food and energy goals.
  • Insufficient understanding of irrigation efficiency may impede policy goals.
  • The meanings and use of irrigation efficiency depend on spatial scale and viewpoint.
  • A matrix of scales and dimensions is proposed to explore irrigation efficiency.

Abstract

An effective placement of irrigation efficiency in water management will contribute towards meeting the pre-eminent global water challenges of our time such as addressing water scarcity, boosting crop water productivity and reconciling competing water needs between sectors. However, although irrigation efficiency may appear to be a simple measure of performance and imply dramatic positive benefits, it is not straightforward to understand, measure or apply. For example, hydrological understanding that irrigation losses recycle back to surface and groundwater in river basins attempts to account for scale, but this generalisation cannot be readily translated from one location to another or be considered neutral for farmers sharing local irrigation networks. Because irrigation efficiency (IE) motives, measures, effects and technologies play out at different scales for different people, organisations and purposes, and losses differ from place to place and over time, IE is a contested term, highly changeable and subjective. This makes generalisations for science, management and policy difficult. Accordingly, we propose new definitions for IE and irrigation hydrology and introduce a framework, termed an ‘irrigation efficiency matrix’, comprising five spatial scales and ten dimensions to understand and critique the promises, pitfalls and paradoxes of IE and to unlock its utility for addressing contemporary water challenges.

Keywords

Water allocation; Irrigation; Irrigation efficiency; River basins; Scale; SDGs

Published

October 2020

By

Global Environmental Change

Citation

Lankford, B., Closas, A., Dalton, J., López Gunn, E., Hess, T., Knox, J. W., van der Kooij, S., Lautze, J., Molden, D., Orr, S., Pittock, J., Richter, B., Riddell, P. J., Scott, C. A., Venot, J., Vos, J., & Zwarteveen, M. (2020). A scale-based framework to understand the promises, pitfalls and paradoxes of irrigation efficiency to meet major water challenges. Global Environmental Change, 65, 102182. https://doi.org/10.1016/j.gloenvcha.2020.102182

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A scale-based framework to understand the promises, pitfalls and paradoxes of irrigation efficiency to meet major water challenges

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