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Spatio-Temporal Dynamics and Contributing Factors of Irrigation Water Use in the Loess Plateau

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  • Jiayu He

    (School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China)

  • Yayun Hu

    (School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China)

  • Luocheng Shi

    (School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China)

  • Haitao Wang

    (School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China)

  • Yan Tong

    (School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China)

  • Wen Dai

    (School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China)

  • Mengmeng Zhang

    (School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China)

Abstract

The “Grain for Green” policy has led to a reduction in cultivated land area in the Loess Plateau, intensifying the conflict between ecological conservation and food security. As a key strategy to mitigate this tension, irrigated farmland has undergone significant changes in both its spatial extent and water consumption, which may further exacerbate the water crisis. Hence, the spatio-temporal dynamics and driving forces behind these changes require greater attention and have not yet been comprehensively explored. This study integrates multi-source datasets and employs piecewise linear regression and the Logarithmic Mean Divisia Index (LMDI) model to analyze the spatio-temporal evolution of cultivated land and irrigation water use. Furthermore, it quantifies the contributions of key factors such as cultivated land area, irrigation intensity, and crop planting structure to irrigation water dynamics. The results show that (1) The total cultivated land area in the Loess Plateau decreased by 12.4% from 1985 to 2020, with increases primarily concentrated along the Yellow River between Hekou and Longmen, while decreases were predominantly observed around major cities such as Xi’an, Taiyuan, and Yuncheng. Conversely, the irrigated area exhibited an overall upward trend, with minor declines occurring between 1977 and 1985. (2) While the total irrigation water use increased overall, piecewise linear regression analysis identified four distinct phases, with the first three phases showing growth, followed by a decline after 2001. (3) The expansion of agricultural irrigation areas emerged as the primary driver of increased irrigation water use, whereas advancements in irrigation efficiency effectively reduced water consumption. This study provides novel insights into the spatio-temporal dynamics of irrigation water use in the Loess Plateau and offers valuable guidance for optimizing water resource management and advancing sustainable development in the region.

Suggested Citation

  • Jiayu He & Yayun Hu & Luocheng Shi & Haitao Wang & Yan Tong & Wen Dai & Mengmeng Zhang, 2025. "Spatio-Temporal Dynamics and Contributing Factors of Irrigation Water Use in the Loess Plateau," Land, MDPI, vol. 14(6), pages 1-15, June.
    • Handle: RePEc:gam:jlands:v:14:y:2025:i:6:p:1286-:d:1680178
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    References listed on IDEAS

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    1. Ang, B. W., 2004. "Decomposition analysis for policymaking in energy:: which is the preferred method?," Energy Policy, Elsevier, vol. 32(9), pages 1131-1139, June.
    2. Ang, B. W., 2005. "The LMDI approach to decomposition analysis: a practical guide," Energy Policy, Elsevier, vol. 33(7), pages 867-871, May.
    3. Chen, Mengting & Luo, Yufeng & Shen, Yingying & Han, Zhenzhong & Cui, Yuanlai, 2020. "Driving force analysis of irrigation water consumption using principal component regression analysis," Agricultural Water Management, Elsevier, vol. 234(C).
    4. Maria Christoforidou & Gerlo Borghuis & Chris Seijger & Gerardo E. Halsema & Petra Hellegers, 2023. "Food security under water scarcity: a comparative analysis of Egypt and Jordan," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 15(1), pages 171-185, February.
    5. Liangang Xiao & Minglei Ding & Chong Wei & Ruiming Zhu & Rongqin Zhao, 2020. "The Impacts of Conservation Agriculture on Water Use and Crop Production on the Loess Plateau: From Know-What to Know-Why," Sustainability, MDPI, vol. 12(18), pages 1-18, September.
    6. 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.
    7. Xiaozhi Xiang & Jesper Svensson & Shaofeng Jia, 2017. "Will the energy industry drain the water used for agricultural irrigation in the Yellow River basin?," International Journal of Water Resources Development, Taylor & Francis Journals, vol. 33(1), pages 69-80, January.
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