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A global analysis of irrigation scheme water supplies in relation to requirements

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  • Benavides, Juan
  • Hernández-Plaza, Eva
  • Mateos, Luciano
  • Fereres, Elías

Abstract

The performance of irrigation schemes around the world has been below expectations. The assessment of irrigation performance is an essential step towards improving agricultural water use. One of the primary performance indicators is the relative irrigation supply (RIS, the ratio between the amount of water delivered and the crop net irrigation requirements). This study presents a worldwide analysis of irrigation scheme performance by evaluating key attributes that influence the RIS. The analysis was based on a review of reports and scientific papers that yielded 264 cases belonging to 25 countries in six world regions. The database was subjected to two types of statistical analysis: k-means clustering and analysis of covariance (ANCOVA). The cluster grouped irrigation schemes which were characterized by low RIS and advanced irrigation technology. The ANCOVA showed that the RIS co-varied significantly with the variation in precipitation, delivery schedule, on-farm irrigation systems, distribution network, and region, but not with the crop. The ANCOVA also showed that modern pressurized on-farm irrigation systems and on-demand distribution systems significantly improve RIS. The ANCOVA general linear model had a good capacity to predict RIS with a coefficient of determination of R2 = 0.83.

Suggested Citation

  • Benavides, Juan & Hernández-Plaza, Eva & Mateos, Luciano & Fereres, Elías, 2021. "A global analysis of irrigation scheme water supplies in relation to requirements," Agricultural Water Management, Elsevier, vol. 243(C).
    • Handle: RePEc:eee:agiwat:v:243:y:2021:i:c:s0378377420308362
    DOI: 10.1016/j.agwat.2020.106457
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    2. Wu, Shiang-Jen & Yang, Han-Yuan & Chang, Che-Hao & Hsu, Chih-Tsung, 2023. "Modeling GA-derived optimization analysis for canal-based irrigation water allocation under variations in runoff-related and irrigation-related factors," Agricultural Water Management, Elsevier, vol. 290(C).
    3. Kim, Dong-Hyeon & Her, Younggu & Cheng, Liguang & Jang, Taeil, 2025. "Improving wheat yield and water use efficiency through soil water-guided furrow irrigation and hydraulic simulation," Agricultural Water Management, Elsevier, vol. 318(C).
    4. You, Yongliang & Song, Ping & Yang, Xianlong & Zheng, Yapeng & Dong, Li & Chen, Jing, 2022. "Optimizing irrigation for winter wheat to maximize yield and maintain high-efficient water use in a semi-arid environment," Agricultural Water Management, Elsevier, vol. 273(C).
    5. Duarte, A.C. & Mateos, L., 2022. "How changes in cropping intensity affect water usage in an irrigated Mediterranean catchment," Agricultural Water Management, Elsevier, vol. 260(C).
    6. Gao, Zitian & Guo, Danlu & Ryu, Dongryeol & Western, Andrew W., 2024. "An integrated approach for multi-year irrigation benchmarking using satellites, surveys and on-farm measured data," Agricultural Water Management, Elsevier, vol. 302(C).

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