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Equitable Allocation of Blue and Green Water Footprints Based on Land-Use Types: A Case Study of the Yangtze River Economic Belt

Author

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  • Gang Liu

    (State Key Laboratory of Hydrology of Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China
    Institute of Management Science, Hohai University, Nanjing 210098, China
    Hohai University Coastal Development and Protection Collaborative Innovation Center, Nanjing 210098, China)

  • Lu Shi

    (Institute of Management Science, Hohai University, Nanjing 210098, China)

  • Kevin W. Li

    (College of Economics and Management, Fuzhou University, Fuzhou, Fujian 350116, China
    Odette School of Business, University of Windsor, Windsor, ON N9B 3P4, Canada)

Abstract

This paper develops a lexicographic optimization model to allocate agricultural and non-agricultural water footprints by using the land area as the influencing factor. An index known as the water-footprint-land density (WFLD) index is then put forward to assess the impact and equity of the resulting allocation scheme. Subsequently, the proposed model is applied to a case study allocating water resources for the 11 provinces and municipalities in the Yangtze River Economic Belt (YREB). The objective is to achieve equitable spatial allocation of water resources from a water footprint perspective. Based on the statistical data in 2013, this approach starts with a proper accounting for water footprints in the 11 YREB provinces. We then determined an optimal allocation of water footprints by using the proposed lexicographic optimization approach from a land area angle. Lastly, we analyzed how different types of land uses contribute to allocation equity and we discuss policy changes to implement the optimal allocation schemes in the YREB. Analytical results show that: (1) the optimized agricultural and non-agricultural water footprints decrease from the current levels for each province across the YREB, but this decrease shows a heterogeneous pattern; (2) the WFLD of 11 YREB provinces all decline after optimization with the largest decline in Shanghai and the smallest decline in Sichuan; and (3) the impact of agricultural land on the allocation of agricultural water footprints is mainly reflected in the land use structure of three land types including arable land, forest land, and grassland. The different land use structures in the upstream, midstream, and downstream regions lead to the spatial heterogeneity of the optimized agricultural water footprints in the three YREB segments; (4) In addition to the non-agricultural land area, different regional industrial structures are the main reason for the spatial heterogeneity of the optimized non-agricultural water footprints. Our water-footprint-based optimal water resources allocation scheme helps alleviate the water resources shortage pressure and achieve coordinated and balanced development in the YREB.

Suggested Citation

  • Gang Liu & Lu Shi & Kevin W. Li, 2018. "Equitable Allocation of Blue and Green Water Footprints Based on Land-Use Types: A Case Study of the Yangtze River Economic Belt," Sustainability, MDPI, vol. 10(10), pages 1-27, October.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:10:p:3556-:d:173734
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    References listed on IDEAS

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    Cited by:

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    2. Gang Liu & Weiqian Wang & Kevin W. Li, 2019. "Water Footprint Allocation under Equity and Efficiency Considerations: A Case Study of the Yangtze River Economic Belt in China," IJERPH, MDPI, vol. 16(5), pages 1-24, March.
    3. Gang Liu & Fan Hu & Yixin Wang & Huimin Wang, 2019. "Assessment of Lexicographic Minimax Allocations of Blue and Green Water Footprints in the Yangtze River Economic Belt Based on Land, Population, and Economy," IJERPH, MDPI, vol. 16(4), pages 1-21, February.
    4. Yaqing Wang & Chaofan Xian & Yaqiong Jiang & Xuelian Pan & Zhiyun Ouyang, 2020. "Anthropogenic reactive nitrogen releases and gray water footprints in urban water pollution evaluation: the case of Shenzhen City, China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(7), pages 6343-6361, October.
    5. Elbeltagi, Ahmed & Deng, Jinsong & Wang, Ke & Hong, Yang, 2020. "Crop Water footprint estimation and modeling using an artificial neural network approach in the Nile Delta, Egypt," Agricultural Water Management, Elsevier, vol. 235(C).

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