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Optimization of Water Consumption Distribution Based on Crop Suitability in the Middle Reaches of Heihe River

Author

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  • Liuyue He

    (Center for Agricultural Water Research in China, China Agricultural University, Beijing 100083, China)

  • Sufen Wang

    (Center for Agricultural Water Research in China, China Agricultural University, Beijing 100083, China)

  • Congcong Peng

    (Center for Agricultural Water Research in China, China Agricultural University, Beijing 100083, China)

  • Qian Tan

    (Center for Agricultural Water Research in China, China Agricultural University, Beijing 100083, China)

Abstract

Optimizing regional crop water consumption is considered to be a significant approach for increasing yields and reducing water consumption. This paper proposes a single-objective linear programming model which couples the distributed water consumption model with crop suitability. The impacts of meteorological, topographic, and soil factors were taken into account in both the distributed water consumption model and the crop suitability. The developed model was applied to a real case study in the middle reaches of Heihe River basin, in the northwest of China. In the optimization model, the net benefit which combined the water consumption with crop suitability was regarded as the objective function, while the limits on available water and planting area were set as the constraints. Optimal results regarding crop distribution and water consumption were generated for dry, normal, and wet hydrological years. Two optimization strategies were analyzed, including one with a fixed area of each crop and the other with a fixed total planting area. Economic analyses showed that net income under both optimization strategies increased by 31% and 33%, respectively. Although water consumption increased slightly in both optimization scenarios, the unit water income and unit area income were much higher than in the pre-optimization conditions. The obtained results are valuable for supporting the adjustment of planting patterns and the identification of desired plans for sustainable irrigation water allocation.

Suggested Citation

  • Liuyue He & Sufen Wang & Congcong Peng & Qian Tan, 2018. "Optimization of Water Consumption Distribution Based on Crop Suitability in the Middle Reaches of Heihe River," Sustainability, MDPI, vol. 10(7), pages 1-17, June.
  • Handle: RePEc:gam:jsusta:v:10:y:2018:i:7:p:2119-:d:153664
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    References listed on IDEAS

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    Cited by:

    1. He, Liuyue & Xu, Zhenci & Wang, Sufen & Bao, Jianxia & Fan, Yunfei & Daccache, Andre, 2022. "Optimal crop planting pattern can be harmful to reach carbon neutrality: Evidence from food-energy-water-carbon nexus perspective," Applied Energy, Elsevier, vol. 308(C).
    2. Hossein Mikhak & Mehdi Rahimian & Saeed Gholamrezai, 2022. "Implications of changing cropping pattern to low water demand plants due to climate change: evidence from Iran," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(8), pages 9833-9850, August.
    3. Zerihun Anbesa Gurmu & Henk Ritzema & Charlotte de Fraiture & Mekonen Ayana, 2019. "Stakeholder Roles and Perspectives on Sedimentation Management in Small-Scale Irrigation Schemes in Ethiopia," Sustainability, MDPI, vol. 11(21), pages 1-18, November.
    4. Harrison W. Smith & Amanda J. Ashworth & Phillip R. Owens, 2022. "GIS-Based Evaluation of Soil Suitability for Optimized Production on U.S. Tribal Lands," Agriculture, MDPI, vol. 12(9), pages 1-10, August.
    5. Fan, Yunfei & He, Liuyue & Liu, Yi & Wang, Sufen, 2022. "Optimal cropping patterns can be conducive to sustainable irrigation: Evidence from the drylands of Northwest China," Agricultural Water Management, Elsevier, vol. 274(C).
    6. Zhang, Fan & Cai, Yanpeng & Tan, Qian & Wang, Xuan, 2021. "Spatial water footprint optimization of crop planting: A fuzzy multiobjective optimal approach based on MOD16 evapotranspiration products," Agricultural Water Management, Elsevier, vol. 256(C).

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