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基于情景的多目标优化泥沙河流水库:以黄河下游为例。

Scenario-based multi-objective optimization of reservoirs in silt-laden rivers: A case study in the Lower Yellow River.

机构信息

Institute of Hydrology and Water Resources, Civil Engineering, Zhejiang University, Hangzhou 310058, China.

Institute of Hydrology and Water Resources, Civil Engineering, Zhejiang University, Hangzhou 310058, China.

出版信息

Sci Total Environ. 2022 Jul 10;829:154565. doi: 10.1016/j.scitotenv.2022.154565. Epub 2022 Mar 17.

Abstract

Severe sedimentation often takes place in the river channel of silt-laden rivers, which is often mitigated through water-sediment regulation of the reservoirs. However, watersediment regulation is often competitive with other objectives of reservoirs, like water supply and hydropower generation; on the other hand, the reduction of channel sedimentation is often achieved at the expense of reservoir sedimentation, which reduces the service life of reservoirs. The Yellow River used to be the river with largest sediment transport over the world, but has experienced significant declination of runoff and sediment in recent years. This study presents a scenario-based multi-objective optimization operation model for the Xiaolangdi reservoir considering hydropower generation, reservoir sedimentation and channel sedimentation, with a generalized linear model coupled to calculate channel sedimentation based on runoff and sediment time series. A stochastic model that can reproduce both spatial correlations and low frequency attributes of the data series is adopted to generate two different scenarios based on different periods of observation and the performance of the multi-objective operation model under different scenarios is tested. The results indicate that: (1) the proposed optimization model can generate different schemes of reservoir operation and enhance operation performance; (2) the generalized linear model can well fit the relationship between daily channel sedimentation and runoff-sediment factors, but tends to overestimate the erosion efficiency after 2005; (3) the reservoir sedimentation and channel sedimentation show linear competitive relation, i.e., an average increase of 1 ton in reservoir sedimentation would result in declination of channel sedimentation from 0.455 to 0.488 tons, while the competitive relationship between hydropower generation and reservoir sedimentation is non-linear and weak; (4) the increase in the proportion of non-flood sediment load to the total sediment load makes it more difficult to prevent the reservoir from silting up.

摘要

严重的泥沙淤积经常发生在多沙河流的河道中,通常可以通过水库的水沙调节来缓解。然而,水沙调节往往与水库的其他目标相竞争,如供水和发电;另一方面,减少河道淤积往往以牺牲水库淤积为代价,从而缩短水库的使用寿命。黄河曾经是世界上输沙量最大的河流,但近年来径流量和泥沙量都有显著减少。本研究提出了一种基于情景的多目标优化调度模型,用于考虑小浪底水库的水力发电、水库淤积和河道淤积,该模型结合广义线性模型来计算基于径流量和泥沙时间序列的河道淤积。采用一种可以再现数据序列空间相关性和低频属性的随机模型,根据不同的观测期生成两种不同的情景,并测试多目标运行模型在不同情景下的性能。结果表明:(1)所提出的优化模型可以生成不同的水库运行方案,提高运行性能;(2)广义线性模型可以很好地拟合日河道淤积与径流量泥沙因子之间的关系,但在 2005 年后往往会高估侵蚀效率;(3)水库淤积和河道淤积呈线性竞争关系,即水库淤积平均增加 1 吨,河道淤积将从 0.455 吨减少到 0.488 吨,而发电与水库淤积之间的竞争关系是非线性和较弱的;(4)非洪水输沙量占总输沙量的比例增加,使得水库淤积的防治更加困难。

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