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Water Use Efficiency and Productivity of the Irrigation Districts in Southern Alberta

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  • Md Ali
  • K. Klein

Abstract

The data envelopment analysis (DEA) model was used to estimate the technical efficiency (TE) scores, the Malmquist total factor productivity (TFP) indices, and their implicit input shadow shares for 12 irrigation districts in Southern Alberta using data for the period 2008–12. The main purpose was to establish benchmarks so that future increases in conservation, efficiency and total factor productivity of water use (major goals of Alberta’s Water for Life strategy) can be assessed. Results of an input-oriented DEA model indicated that the irrigation districts were, on average, 84.3 % technically efficient in their input use, primarily the net water diverted. The output-oriented model indicated that the irrigation districts, alternatively, could expand their total irrigated areas by 58.3 % with the current level of input use. Over the period 2008–12, the year-to-year mean Malmquist TFP for the irrigation districts of Southern Alberta was estimated to be 0.98 %. Net water diverted was identified as the most important contributing input (76 %) to the TFP change. The second and third contributing factors were pivot irrigation technology (6 %) and precipitation (5 %). Copyright Springer Science+Business Media Dordrecht 2014

Suggested Citation

  • Md Ali & K. Klein, 2014. "Water Use Efficiency and Productivity of the Irrigation Districts in Southern Alberta," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(10), pages 2751-2766, August.
    • Handle: RePEc:spr:waterr:v:28:y:2014:i:10:p:2751-2766
    DOI: 10.1007/s11269-014-0634-y
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    Cited by:

    1. Jay Nigam & Totakura Bangar Raju & Ramachandra K. Pavan Kumar Pannala, 2023. "Performance Evaluation of Irrigation Canals Using Data Envelopment Analysis for Efficient and Sustainable Irrigation Management in Jharkhand State, India," Energies, MDPI, vol. 16(14), pages 1-14, July.
    2. Nguyen Bich Hong & Mitsuyasu Yabe, 2017. "Improvement in irrigation water use efficiency: a strategy for climate change adaptation and sustainable development of Vietnamese tea production," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 19(4), pages 1247-1263, August.
    3. Ali, M.K., 2018. "Estimation of irrigation water use efficiency with a stochastic frontier model," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277354, International Association of Agricultural Economists.
    4. Ke-Liang Wang & Jianguo Wang & Jianming Wang & Lili Ding & Mingsong Zhao & Qunwei Wang, 2020. "Investigating the spatiotemporal differences and influencing factors of green water use efficiency of Yangtze River Economic Belt in China," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-24, April.
    5. José Sánchez & Juan Reca & Juan Martínez, 2015. "Water Productivity in a Mediterranean Semi-Arid Greenhouse District," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(14), pages 5395-5411, November.
    6. Xiyue Zhang & Fangcheng Sun & Huaizu Wang & Yi Qu, 2020. "Green Biased Technical Change in Terms of Industrial Water Resources in China’s Yangtze River Economic Belt," IJERPH, MDPI, vol. 17(8), pages 1-20, April.
    7. X. C. Cao & R. Shu & X. P. Guo & W. G. Wang, 2019. "Scarce water resources and priority irrigation schemes from agronomic crops," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 24(3), pages 399-417, March.
    8. Alexandros Maziotis & María Molinos-Senante & Ramon Sala-Garrido, 2017. "Assesing the Impact of Quality of Service on the Productivity of Water Industry: a Malmquist-Luenberger Approach for England and Wales," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(8), pages 2407-2427, June.
    9. Qiang Fu & Ye Liu & Tianxiao Li & Dong Liu & Song Cui, 2017. "Analysis of Irrigation Water Use Efficiency Based on the Chaos Features of a Rainfall Time Series," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(6), pages 1961-1973, April.
    10. Wasi Ul Hassan Shah & Yuting Lu & Gang Hao & Hong Yan & Rizwana Yasmeen, 2022. "Impact of “Three Red Lines” Water Policy (2011) on Water Usage Efficiency, Production Technology Heterogeneity, and Determinant of Water Productivity Change in China," IJERPH, MDPI, vol. 19(24), pages 1-23, December.
    11. María Molinos-Senante & Alexandros Maziotis & Ramon Sala-Garrido, 2017. "Assessment of the Total Factor Productivity Change in the English and Welsh Water Industry: a Färe-Primont Productivity Index Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(8), pages 2389-2405, June.
    12. Changchun Tan & Qinhong Peng & Tao Ding & Zhixiang Zhou, 2021. "Regional Assessment of Land and Water Carrying Capacity and Utilization Efficiency in China," Sustainability, MDPI, vol. 13(16), pages 1-16, August.
    13. Fabrício Gonçalves & Renato Ribeiro & Raimundo Costa & Julien Burte, 2015. "A Management Analysis Tool for Emancipated and Public Irrigation Areas Using Neural Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(7), pages 2393-2406, May.
    14. Chui-Yu Chiu & William Tang, 2022. "Measuring the Operational Efficiency and the Water Resources Management Efficiency for Industrial Parks: Empirical Study of Industrial Parks in Taiwan," Sustainability, MDPI, vol. 14(21), pages 1-22, October.

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    More about this item

    Keywords

    Technical efficiency; Malmquist index; Data envelopment analysis; Linear programming; C61; Q15; Q25;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • Q15 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Land Ownership and Tenure; Land Reform; Land Use; Irrigation; Agriculture and Environment
    • Q25 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Water

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