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Reservoir Capacity Planning Using Stochastic Multiobjective Programming Integrated with MCMC Technique

In: Pursuing Sustainability

Author

Listed:
  • Ho Wen Chen

    (Tung-Hai University)

  • Kieu Lan Phuong Nguyen

    (Tung-Hai University
    Nguyen Tat Thanh University)

Abstract

Determining the location and size of new reservoirs requires a risk-informed decision approach. The scope of risk management, which has been increasingly recognized today, should consider the resulting economic benefit and the local unique hydrological conditions while maintaining necessary water quality in the river. Thus, the incorporation of environmental and economic factors into the reservoir capacity planning process is essential. This chapter presents an optimization-based risk analysis framework to size a new reservoir in a river basin with focus on sustainable development. The framework is designed for a multidisciplinary assessment of reservoir sizing, simultaneously addressing natural patterns of stream flows, adequate water supply, and pristine water quality in the river watershed. A set of water quality parameters, that is, dissolved oxygen (DO) and biochemical oxygen demand (BOD), is used as a surrogate index to reflect water quality impacts. A dynamic stochastic optimization is applied to the problems in which the uncertainty is modeled using the Markov Chain Monte Carlo (MCMC) technique. A case study of Hou-Lung River Basin in Taiwan is used to illustrate the capability of the framework.

Suggested Citation

  • Ho Wen Chen & Kieu Lan Phuong Nguyen, 2021. "Reservoir Capacity Planning Using Stochastic Multiobjective Programming Integrated with MCMC Technique," International Series in Operations Research & Management Science, in: Chialin Chen & Yihsu Chen & Vaidyanathan Jayaraman (ed.), Pursuing Sustainability, chapter 0, pages 315-339, Springer.
    • Handle: RePEc:spr:isochp:978-3-030-58023-0_13
    DOI: 10.1007/978-3-030-58023-0_13
    as

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