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Estimating irrigation water demand using an improved method and optimizing reservoir operation for water supply and hydropower generation: A case study of the Xinfengjiang reservoir in southern China

水力发电 供水 水资源管理 环境科学 水资源 缺水 环境工程 工程类 生态学 生物 电气工程
作者
Yiping Wu,Chen Ji
出处
期刊:Agricultural Water Management [Elsevier BV]
卷期号:116: 110-121 被引量:88
标识
DOI:10.1016/j.agwat.2012.10.016
摘要

The ever-increasing demand for water due to growth of population and socioeconomic development in the past several decades has posed a worldwide threat to water supply security and to the environmental health of rivers. This study aims to derive reservoir operating rules through establishing a multi-objective optimization model for the Xinfengjiang (XFJ) reservoir in the East River Basin in southern China to minimize water supply deficit and maximize hydropower generation. Additionally, to enhance the estimation of irrigation water demand from the downstream agricultural area of the XFJ reservoir, a conventional method for calculating crop water demand is improved using hydrological model simulation results. Although the optimal reservoir operating rules are derived for the XFJ reservoir with three priority scenarios (water supply only, hydropower generation only, and equal priority), the river environmental health is set as the basic demand no matter which scenario is adopted. The results show that the new rules derived under the three scenarios can improve the reservoir operation for both water supply and hydropower generation when comparing to the historical performance. Moreover, these alternative reservoir operating policies provide the flexibility for the reservoir authority to choose the most appropriate one. Although changing the current operating rules may influence its hydropower-oriented functions, the new rules can be significant to cope with the increasingly prominent water shortage and degradation in the aquatic environment. Overall, our results and methods (improved estimation of irrigation water demand and formulation of the reservoir optimization model) can be useful for local watershed managers and valuable for other researchers worldwide.

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