院报 ›› 2021, Vol. 38 ›› Issue (1): 1-7.DOI: 10.11988/ckyyb.20201194

• 专家特约稿 • 上一篇    下一篇

长江流域梯级枢纽泥沙调控关键技术

卢金友1, 赵瑾琼1,2   

  1. 1. 水利部江湖治理与防洪重点实验室,武汉 430010;
    2. 河流研究所,武汉 430010
  • 收稿日期:2020-11-20 修回日期:2020-12-22 出版日期:2021-01-01 发布日期:2021-01-27
  • 通讯作者: 赵瑾琼(1986-),男,山东菏泽人,高级工程师,博士,主要从事水沙运动模拟与调控方面的研究。E-mail: zhaojinqiong@outlook.com
  • 作者简介:卢金友(1963-),男,浙江仙居人,教授级高级工程师,硕士,主要从事水流泥沙运动规律、江湖演变与治理等方面的研究。 E-mail: Lujy@mail.crsri.cn
  • 基金资助:
    国家重点研发计划项目(2016YFC0402309);国家自然科学基金项目(51779014);中央级公益性科研院所基金项目(CKSF2019490)

Key Technologies of Sediment Regulation for Cascade Reservoirs in Yangtze River Basin

LU Jin-you1, ZHAO Jin-qiong1,2   

  1. 1. Key Laboratory of River-Lake Regulation and Flood Control of Ministry of Water Resources,Yangtze River Scientific Research Institute,Wuhan 430010, China;
    2. River Department,Yangtze River Scientific Research Institute, Wuhan 430010, China
  • Received:2020-11-20 Revised:2020-12-22 Online:2021-01-01 Published:2021-01-27

摘要: 通过将水沙动力学与水库调度优化理论相结合,围绕长江流域梯级枢纽泥沙调控关键技术开展研究。在改进恢复饱和系数、非均匀沙挟沙力等关键计算模式的基础上,完善并集成长江上游梯级水库群水沙数学模型、长江中下游复杂江湖河网水沙数学模型和典型河段平面二维水沙数学模型,构建了江河湖库水沙输移模拟模块。基于泥沙对防洪、发电、航运和长期使用4个主要目标的影响,构建了长江泥沙优化调控目标函数,进而集成水沙输移模拟模块构建了长江泥沙优化调度模型,并提出了基于预构泥沙信息库、结合BP神经网络的模型求解方法和非劣解集的改进灰靶评价方法。在此基础上,以三峡水库为例,提出了汛期“蓄清排浑”动态运用方案以及长期分阶段泥沙调控策略。

关键词: 泥沙调控, 梯级枢纽, 泥沙运动, 长期使用, 多目标水沙数学模型, 蓄清排浑, 长江流域

Abstract: Combining flow and sediment dynamics with optimization theory, we developed a technology of sediment control for cascade reservoirs integrating simulation module, dispatching module and decision module.Firstly, we improved the coefficient of saturation recovery and the sediment carrying capacity of non-uniform sediment, and on this basis built the simulation module of water/sediment transport in rivers, lakes, and reservoirs by integrating the water/sediment models for cascade reservoirs in upstream Yangtze River, for complex river-lake network in mid-and downstream Yangtze River and the 2D model for typical reaches. Subsequently, we constructed the objective function of sediment’s optimal regulation in consideration of flood control, power generation, navigation, and long-term use, and further established the optimal sediment-dispatching model. Furthermore we employed the BP neural network in association with the pre-constructed sediment information base to fit the prediction for the sedimentation and scouring, and present an improved grey-target evaluation method based on non-inferior solution set. Taking the Three Gorges Reservoir as an example, we finally put forward the dynamic operation scheme of “storing clear water and discharging muddy water” in flood season and the long-term staged sediment control strategy.

Key words: sediment regulation, cascade reservoirs, sediment movement, long-term use, multi-objective water-sediment mathematical model, storing clear water and discharging muddy water, Yangtze River basin

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