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Multi-Objective Optimization of Hydropower and Agricultural Development at River Basin Scale

Author

Listed:
  • Amir Hatamkhani

    (Shahid Beheshti University)

  • Ali Moridi

    (Shahid Beheshti University)

Abstract

The need for achieving efficient, equitable and sustainable use of water resources to meet water demands of different sectors is necessary, particularly in areas where water resources are decreasing. In the basins where water is required for both energy production and irrigation, allocation of water resources must be planned in such a way that both objectives can be achieved. In this research, a simulation-optimization approach has been used to solve the problem of optimal planning at the watershed scale. The water evaluation and planning system (WEAP) simulation model link with the multi-objective particle swarm optimization (MOPSO) model for optimal long term planning at the basin scale. Therefore, the objective functions of the problem are 1) maximize the cultivation area of agricultural development sectors and 2) maximize the energy produced by the hydropower plant. The developed simulation-optimization model was employed in the problem of optimal water resources planning in the Kashkan river basin in the west of Iran. The Pareto front obtained represents the best trade-off between hydropower and agricultural development in the basin and can be used for water-energy-food nexus planning. For example one of the solutions of Pareto front, in addition to an increase of about 8% of the objective function 2 (generated energy), the value of the objective function 1 (cultivation area) is approximately 5 times higher than the results of previous studies. This demonstrates the proper performance of the simulation-optimization model in the optimal allocation and planning of water resources at the basin scale based on the water-energy-food nexus approach.

Suggested Citation

  • Amir Hatamkhani & Ali Moridi, 2019. "Multi-Objective Optimization of Hydropower and Agricultural Development at River Basin Scale," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(13), pages 4431-4450, October.
    • Handle: RePEc:spr:waterr:v:33:y:2019:i:13:d:10.1007_s11269-019-02365-x
    DOI: 10.1007/s11269-019-02365-x
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    References listed on IDEAS

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    Cited by:

    1. Ahmad Hamidov & Katharina Helming, 2020. "Sustainability Considerations in Water–Energy–Food Nexus Research in Irrigated Agriculture," Sustainability, MDPI, vol. 12(15), pages 1-20, August.
    2. Hatamkhani, Amir & Moridi, Ali & Haghighi, Ali Torabi, 2023. "Incorporating ecosystem services value into the optimal development of hydropower projects," Renewable Energy, Elsevier, vol. 203(C), pages 495-505.
    3. Mirzaie, Nargis & Banihabib, Mohammad Ebrahim & shahdany, S. Mehdy hashemy & Randhir, Timothy O., 2021. "Fuzzy particle swarm optimization for conjunctive use of groundwater and reclaimed wastewater under uncertainty," Agricultural Water Management, Elsevier, vol. 256(C).
    4. Amir Hatamkhani & Mojtaba Shourian & Ali Moridi, 2021. "Optimal Design and Operation of a Hydropower Reservoir Plant Using a WEAP-Based Simulation–Optimization Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(5), pages 1637-1652, March.
    5. Amir Hatamkhani & Ali Moridi, 2021. "Optimal Development of Agricultural Sectors in the Basin Based on Economic Efficiency and Social Equality," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(3), pages 917-932, February.
    6. Sajith, Gouri & Srinivas, Rallapalli & Golberg, Alexander & Magner, Joe, 2022. "Bio-inspired and artificial intelligence enabled hydro-economic model for diversified agricultural management," Agricultural Water Management, Elsevier, vol. 269(C).
    7. Zhang, Zepeng & Wang, Qingzheng & Guan, Qingyu & Xiao, Xiong & Mi, Jimin & Lv, Songjian, 2023. "Research on the optimal allocation of agricultural water and soil resources in the Heihe River Basin based on SWAT and intelligent optimization," Agricultural Water Management, Elsevier, vol. 279(C).

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