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Analyzing the Drivers of Agricultural Irrigation Water Demand in Water-Scarce Areas: A Comparative Study of Two Regions with Different Levels of Irrigated Agricultural Development

Author

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  • Mengya Hua

    (State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China)

  • Yuyan Zhou

    (State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China)

  • Cailian Hao

    (Research Center for Strategy of Global Mineral Resources, Chinese Academy of Geological Science, Beijing 100037, China)

  • Qiang Yan

    (Research Center for Strategy of Global Mineral Resources, Chinese Academy of Geological Science, Beijing 100037, China)

Abstract

Both the demand for agricultural irrigation and the level of water-saving technology in water-scarce regions have met food demand with technological progress and economic growth. There are differences in irrigation water demand drivers in regions with different levels of irrigated agricultural development. However, the relationship between related drivers in response to regional irrigation water demand is not fully understood. This study quantified the driving influence of six indicators, including technological progress, planting structure, water conservation management, economic development, planting scale, and consumption intensity, on agricultural irrigation water demand in JC (Jinchang) and WW (Wuwei), two cities in the Shiyang River Basin, from 2011 to 2020. The results shows that economic development is the main driver of the increase in irrigation water demand, with 29% and 43% driving contributions in JC and WW, respectively. Consumption intensity contributes the most to the decrease in irrigation water demand, with 31% and 23% of driving contribution in JC and WW, respectively. Cropping size has a greater positive drive on irrigation water demand in non-agricultural areas relative to agricultural areas. Planting structure has a more pronounced negative drive on irrigation water demand in agricultural areas relative to non-agricultural areas. In particular, relative to irrigated areas, the proportion of water-saving irrigated areas to the sown areas has a greater impact on changes in irrigation water demand, with a significant rebound effect when it exceeds 80%, so that blindly expanding water-saving irrigated areas will drive an increase in irrigation water demand. The results of this study can provide useful suggestions for agricultural water management in water-scarce areas with different levels of water-saving irrigation development, and realize the sustainable development of agriculture in water-scarce areas.

Suggested Citation

  • Mengya Hua & Yuyan Zhou & Cailian Hao & Qiang Yan, 2023. "Analyzing the Drivers of Agricultural Irrigation Water Demand in Water-Scarce Areas: A Comparative Study of Two Regions with Different Levels of Irrigated Agricultural Development," Sustainability, MDPI, vol. 15(20), pages 1-14, October.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:20:p:14951-:d:1261176
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    References listed on IDEAS

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    1. Zhang, Shulin & Su, Xiaoling & Singh, Vijay P & Ayantobo, Olusola Olaitan & Xie, Juan, 2018. "Logarithmic Mean Divisia Index (LMDI) decomposition analysis of changes in agricultural water use: a case study of the middle reaches of the Heihe River basin, China," Agricultural Water Management, Elsevier, vol. 208(C), pages 422-430.
    2. Weijing Ma & Lihong Meng & Feili Wei & Christian Opp & Dewei Yang, 2020. "Sensitive Factors Identification and Scenario Simulation of Water Demand in the Arid Agricultural Area Based on the Socio-Economic-Environment Nexus," Sustainability, MDPI, vol. 12(10), pages 1-19, May.
    3. Zikang Xing & Miaomiao Ma & Yongqiang Wei & Xuejun Zhang & Zhongbo Yu & Peng Yi, 2020. "A new agricultural drought index considering the irrigation water demand and water supply availability," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 104(3), pages 2409-2429, December.
    4. Geng, Qingling & Zhao, Yongkun & Sun, Shikun & He, Xiaohui & Wang, Dong & Wu, Dingrong & Tian, Zhihui, 2023. "Spatio-temporal changes and its driving forces of irrigation water requirements for cotton in Xinjiang, China," Agricultural Water Management, Elsevier, vol. 280(C).
    5. Gajić, Boško & Kresović, Branka & Tapanarova, Angelina & Životić, Ljubomir & Todorović, Mladen, 2018. "Effect of irrigation regime on yield, harvest index and water productivity of soybean grown under different precipitation conditions in a temperate environment," Agricultural Water Management, Elsevier, vol. 210(C), pages 224-231.
    6. Ang, B.W. & Liu, F.L., 2001. "A new energy decomposition method: perfect in decomposition and consistent in aggregation," Energy, Elsevier, vol. 26(6), pages 537-548.
    7. Mohammad Alghassab & Zafar A. Khan & Abdullah Altamimi & Muhammad Imran & Fahad F. Alruwaili, 2022. "Prospects of Hybrid Energy in Saudi Arabia, Exploring Irrigation Application in Shaqra," Sustainability, MDPI, vol. 14(9), pages 1-18, April.
    8. Bin Guo & Weihong Li & Jinyun Guo & Chuanfa Chen, 2015. "Risk Assessment of Regional Irrigation Water Demand and Supply in an Arid Inland River Basin of Northwestern China," Sustainability, MDPI, vol. 7(9), pages 1-16, September.
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