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Optimization of Water and Energy Spatial Patterns in the Cascade Pump Station Irrigation District

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  • Chen Bai

    (State Key Laboratory of Eco-Hydraulics in Northwest Arid Region, Xi’an University of Technology, Xi’an 710048, China
    Department of Electronics and Information, Xi’an Polytechnic University, Xi’an 710048, China)

  • Lixiao Yao

    (State Key Laboratory of Eco-Hydraulics in Northwest Arid Region, Xi’an University of Technology, Xi’an 710048, China)

  • Cheng Wang

    (State Key Laboratory of Eco-Hydraulics in Northwest Arid Region, Xi’an University of Technology, Xi’an 710048, China
    Key Laboratory of Oasis Town and Mountain-Basin System Ecology of Xinjiang Bingtuan, Shihezi University, Shihezi 832003, China)

  • Yongxuan Zhao

    (Water Resources and Hydroelectric Investigation and Design and Research Institute Corporation Limited, Lanzhou 730000, China)

  • Weien Peng

    (Jingtaichuan Electric Lifting Irrigation Water Resources Utilization Center, Jingtai, Baiyin 730400, China)

Abstract

Cascade pump station irrigation districts (CPSIDs) consume large quantities of water and energy. Water- and energy-saving results and income increases are guaranteed under the sustainable development of the CPSID. The CPSID is divided into several sub-districts based on the elevation difference of topography and pump station distributions. The spatial patterns of crops and irrigation technologies can be changed by adjusting crop planting structures and developing drip irrigation in each sub-district. Its optimization will change the spatial patterns of irrigation water and energy consumption to achieve water- and energy-saving results, increase income, and provide an ecological advantage. To obtain the optimal spatial patterns of water and energy in the CPSID, a multi-objective linear programming model of minimum irrigation water consumption, minimum energy consumption, and highest crop output value was established. This model was applied to the Jingdian Phase I Irrigation District in northwest China, and an optimal scheme of water and energy spatial patterns was obtained. Compared with the present situation, the optimal scheme could save water by 26.18%, save energy by 29.38%, and increase income by 29.55%. The increased investment in the drip irrigation project would lead to reduced irrigation water and energy consumption and increased crop output value. The research results provide a scientific basis for the sustainable development of agriculture and ecological environment protection in the CPSID.

Suggested Citation

  • Chen Bai & Lixiao Yao & Cheng Wang & Yongxuan Zhao & Weien Peng, 2022. "Optimization of Water and Energy Spatial Patterns in the Cascade Pump Station Irrigation District," Sustainability, MDPI, vol. 14(9), pages 1-17, April.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:9:p:4943-:d:797884
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    1. Fan, Xing & Zhang, Wen & Chen, Weiwei & Chen, Bin, 2020. "Land–water–energy nexus in agricultural management for greenhouse gas mitigation," Applied Energy, Elsevier, vol. 265(C).
    2. Soto-García, M. & Martínez-Alvarez, V. & García-Bastida, P.A. & Alcon, F. & Martin-Gorriz, B., 2013. "Effect of water scarcity and modernisation on the performance of irrigation districts in south-eastern Spain," Agricultural Water Management, Elsevier, vol. 124(C), pages 11-19.
    3. Espinosa-Tasón, Jaime & Berbel, Julio & Gutiérrez-Martín, Carlos, 2020. "Energized water: Evolution of water-energy nexus in the Spanish irrigated agriculture, 1950–2017," Agricultural Water Management, Elsevier, vol. 233(C).
    4. Chen Zhang & Edward McBean & Jeanne Huang, 2014. "A Virtual Water Assessment Methodology for Cropping Pattern Investigation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(8), pages 2331-2349, June.
    5. Zhang, Zhidong & Zheng, Yi & Han, Feng & Xiong, Rui & Feng, Lian, 2021. "Recovery of an endorheic lake after a decade of conservation efforts: Mediating the water conflict between agriculture and ecosystems," Agricultural Water Management, Elsevier, vol. 256(C).
    6. Karimov, Akmal Kh. & Smakhtin, Vladimir & Karimov, Aziz A. & Khodjiev, Khalim & Yakubov, Sadyk & Platonov, Alexander & Avliyakulov, Mirzaolim, 2018. "Reducing the energy intensity of lift irrigation schemes of Northern Tajikistan- potential options," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2967-2975.
    7. D. Dutta & Pavan Kumar, 2015. "Application of fuzzy goal programming approach to multi-objective linear fractional inventory model," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(12), pages 2269-2278, September.
    8. Karimov, Akmal Kh & Toshev, Rashid H. & Karshiev, Rustam & Karimov, Aziz A., 2021. "Water–energy nexus in Central Asia's lift irrigation schemes: Multi-level linkages," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
    9. Huang, Qiuqiong & Wang, Jinxia & Li, Yumin, 2017. "Do water saving technologies save water? Empirical evidence from North China," Journal of Environmental Economics and Management, Elsevier, vol. 82(C), pages 1-16.
    10. Jiménez-Aguirre, M.T. & Isidoro, D., 2018. "Hydrosaline Balance in and Nitrogen Loads from an irrigation district before and after modernization," Agricultural Water Management, Elsevier, vol. 208(C), pages 163-175.
    11. Ibrikci, Hayriye & Cetin, Mahmut & Karnez, Ebru & Flügel, Wolfgang Albert & Tilkici, Burak & Bulbul, Yunus & Ryan, John, 2015. "Irrigation-induced nitrate losses assessed in a Mediterranean irrigation district," Agricultural Water Management, Elsevier, vol. 148(C), pages 223-231.
    12. I. Fernández García & P. Montesinos & E. Camacho Poyato & J. A. Rodríguez Díaz, 2017. "Optimal Design of Pressurized Irrigation Networks to Minimize the Operational Cost under Different Management Scenarios," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(6), pages 1995-2010, April.
    13. Inuiguchi, Masahiro & Sakawa, Masatoshi, 1995. "Minimax regret solution to linear programming problems with an interval objective function," European Journal of Operational Research, Elsevier, vol. 86(3), pages 526-536, November.
    14. Hamiden Abd El- Wahed Khalifa & Pavan Kumar, 2022. "A goal programming approach for multi-objective linear fractional programming problem with LR possibilistic variables," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(4), pages 2053-2061, August.
    15. Chang, Ching-Ter, 2007. "Multi-choice goal programming," Omega, Elsevier, vol. 35(4), pages 389-396, August.
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