Reservoir Capacity Planning Using Stochastic Multiobjective Programming Integrated with MCMC Technique

Ho Wen Chen () and Kieu Lan Phuong Nguyen
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Ho Wen Chen: Tung-Hai University
Kieu Lan Phuong Nguyen: Tung-Hai University

Chapter Chapter 13 in Pursuing Sustainability, 2021, pp 315-339 from Springer

Abstract: 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.

Keywords: Reservoir capacity planning; Water quality; Water resources management; Stochastic programming; Markov Chain Monte Carlo technique (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-3-030-58023-0_13

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DOI: 10.1007/978-3-030-58023-0_13

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