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A Simulation–Optimization System to Assess Dam Construction with a Focus on Environmental Degradation at Downstream

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  • Mahdi Sedighkia

    (James Cook University)

  • Asghar Abdoli

    (Environment Science Research Institute)

Abstract

The present study proposes and evaluates an integrated framework to assess dam construction and removal, encompassing the simulation of downstream river habitats and reservoir operation in three distinct statuses: conventional reservoir operation optimization, optimal release considering environmental aspects within the optimization model, and natural flow conditions. Fuzzy physical habitat simulation was employed to assess physical habitats, while an ANFIS-based model was utilized to simulate thermal tension and dissolved oxygen tension at downstream habitats. Particle swarm optimization was applied in the optimization models. To evaluate the effectiveness of the proposed framework, results from the optimization system as well as habitat suitability models in the natural flow and current condition were compared using various measurement indices, including the reliability index, vulnerability index, the Nash–Sutcliffe model efficiency coefficient (NSE), and root mean square error (RMSE). The case study results suggest that the reliability of water supply may be diminished under optimal release for environmental and demand considerations. Additionally, optimal release for the environment may not adequately protect downstream aquatic habitats. Therefore, in cases where the preservation of downstream habitats is a priority, dam removal may be a logical solution. Moreover, it is essential to acknowledge that the main limitation of the proposed method is its high computational complexity.

Suggested Citation

  • Mahdi Sedighkia & Asghar Abdoli, 2024. "A Simulation–Optimization System to Assess Dam Construction with a Focus on Environmental Degradation at Downstream," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 38(7), pages 2489-2509, May.
    • Handle: RePEc:spr:waterr:v:38:y:2024:i:7:d:10.1007_s11269-024-03781-4
    DOI: 10.1007/s11269-024-03781-4
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    References listed on IDEAS

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    1. Behrang Beiranvand & Parisa-Sadat Ashofteh, 2023. "A Systematic Review of Optimization of Dams Reservoir Operation Using the Meta-heuristic Algorithms," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(9), pages 3457-3526, July.
    2. Jia Chen, 2021. "Long-Term Joint Operation of Cascade Reservoirs Using Enhanced Progressive Optimality Algorithm and Dynamic Programming Hybrid Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(7), pages 2265-2279, May.
    3. Jehangir Awan & Deg-Hyo Bae, 2014. "Improving ANFIS Based Model for Long-term Dam Inflow Prediction by Incorporating Monthly Rainfall Forecasts," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(5), pages 1185-1199, March.
    4. Mohammad Ehteram & Hojat Karami & Sayed Farhad Mousavi & Saaed Farzin & Alcigeimes B. Celeste & Ahmad-El Shafie, 2018. "Reservoir Operation by a New Evolutionary Algorithm: Kidney Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(14), pages 4681-4706, November.
    5. Ciobanu Dumitru & Vasilescu Maria, 2013. "Advantages and Disadvantages of Using Neural Networks for Predictions," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(1), pages 444-449, May.
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