大朝山电站入库径流变化及预测研究  

Research on Streamflow Analysis and Prediction for Dachaoshan Reservoir

作　　者：欧阳慧[1] 邵骏[2] 李秀峰[3] 

机构地区：[1]昆明冶金高等专科学校,云南昆明650033 [2]四川大学水利水电学院,四川成都610065 [3]云南电力调度中心,云南昆明650011

出　　处：《水电能源科学》2010年第7期6-8,46,共4页Water Resources and Power

摘　　要：采用希尔伯特-黄变换和Mann-Kendall非参数检验法对对澜沦江流域大朝山电站1961～2008年入库径流周期及趋势变化规律进行研究,根据分析结果建立BP神经网络-希尔伯特-黄变换耦合模型预测了未来5 a大朝山电站入库径流.结果表明,大朝山电站入库流量序列主要存在3、7、16 a近似周期成分,1961～2000年入库流量呈减少趋势,在进入21世纪后径流有所增加,未来径流量将继续保持递减趋势,2014年将达到最小值,之后径流有所回升.According to the streamflow series from 1961 to 2008 years of Dachaoshan Reservoir in Lancang River,Hilbert-Huang transform and Mann-Kendall nonparametric test method are used to analyze the streamflow period and trend characteristics.Combination of Hilbert-Huang transform and BP neural network model is applied to predict streamflow of Dachaoshan Reservoir in the five years to come.The results show that the streamflow series exist 3-year,7-year,16-year approximate cycle components,respectively;the streamflow tends to decreased trend from 1961 to 2000 years and increases in the 21st century;the streamflow keeps on decreasing until 2014 years and then rises again.

关 键 词：大朝山 电站 入库流量 径流变化 预测研究 Analysis 希尔伯特 入库径流 黄变换 非参数检验法 澜沦江流域 周期成分 神经网络 模型预测 分析结果 递减趋势 变化规律 最小值 径流量 序列 

分 类 号：TK79[动力工程及工程热物理—流体机械及工程] TV7[水利工程—水利水电工程]