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Long-Term Planning of Water Systems in the Context of Climate Non-Stationarity with Deterministic and Stochastic Optimization

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  • Didier Haguma

    (Université de Sherbrooke)

  • Robert Leconte

    (Université de Sherbrooke)

Abstract

Seasonal inflow variability, climate non-stationarity and climate change are matters of concern for water system planning and management. This study presents optimization methods for long-term planning of water systems in the context of a non-stationary climate with two levels of inflow variability: seasonal and inter-annual. Deterministic and stochastic optimization models with either one time-step (intra-annual) or two time-steps (intra-annual and inter-annual) were compared by using three water system optimization models. The first model used one time-step sampling stochastic dynamic programming (SSDP). The other models with two time-steps are long-term deterministic dynamic programming (LT-DDP) and long-term sampling stochastic dynamic programming (LT-SSDP). The study area is the Manicouagan water system located in Quebec, Canada. The results show that there will be an increase of inflow to hydropower plants in the future climate with an increase of inflow uncertainty. The stochastic optimization with two time-steps was the most suitable for handling climate non-stationarity. The LT-DDP performed better in terms of reservoir storage, release and system efficiency but with high uncertainty. The SSDP had the lowest performance. The SSDP was not able to deal with the non-stationary climate and seasonal variability at the same time. The LT-SSDP generated operating policies with smaller uncertainty compared to LT-DDP, and it was therefore a more appropriate approach for water system planning and management in a non-stationary climate characterized by high inflow variability.

Suggested Citation

  • Didier Haguma & Robert Leconte, 2018. "Long-Term Planning of Water Systems in the Context of Climate Non-Stationarity with Deterministic and Stochastic Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(5), pages 1725-1739, March.
    • Handle: RePEc:spr:waterr:v:32:y:2018:i:5:d:10.1007_s11269-017-1900-6
    DOI: 10.1007/s11269-017-1900-6
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    References listed on IDEAS

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    1. Didier Haguma & Robert Leconte & Pascal Côté & Stéphane Krau & François Brissette, 2014. "Optimal Hydropower Generation Under Climate Change Conditions for a Northern Water Resources System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(13), pages 4631-4644, October.
    2. Ludovic Gaudard & Manfred Gilli & Franco Romerio, 2013. "Climate Change Impacts on Hydropower Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(15), pages 5143-5156, December.
    3. B. Fiseha & S. Setegn & A. Melesse & E. Volpi & A. Fiori, 2014. "Impact of Climate Change on the Hydrology of Upper Tiber River Basin Using Bias Corrected Regional Climate Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(5), pages 1327-1343, March.
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    1. Yves Mbeutcha & Michel Gendreau & Gregory Emiel, 2021. "A hybrid dynamic programming - Tabu Search approach for the long-term hydropower scheduling problem," Computational Management Science, Springer, vol. 18(3), pages 385-410, July.
    2. Xinyu Wu & Shuai Yin & Chuntian Cheng & Zhiyong Chen & Huaying Su, 2023. "SSDP Model with Inflow Clustering for Hydropower System Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(3), pages 1109-1123, February.

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