基于水库历史年入库径流序列组分分析和识别,采用线性趋势回归检验法、有序聚类法、方差线谱法等方法,推求出序列趋势项、跳跃项及周期项等确定性成分,提出基于集合经验模态分解法(EEMD方法)的水库年径流自回归随机模拟模型(EEMD-AR),并应用于丹江口水库的年径流随机模拟和预报中.通过EEMD分解,解决了当丹江口水库历史年径流序列为非平稳序列时不能直接应用自回归模型(AR)进行随机模拟和预报的问题.模拟结果表明,EEMD-AR模型能较好地模拟丹江口水库年径流序列并保持原历史序列的统计特性,且模型预报精度符合要求.%Based on the analysis and identification of the annual runoff sequence components of the Danjiangkou Reservoir, deterministic components such as the trend term, the jumping term and the periodic term were derived by using linear trend regression analysis method, sequential cluster method and variance spectrum method, etc. A stochastic auto-regression model of annual runoff based on Ensemble Empirical Mode Decomposition ( EEMD) was proposed ( EEMD-AR) and it was applied to the stochastic simulation and prediction of the annual runoff in the Danjiangkou Reservoir. Through the EEMD decomposition, the problem that stochastic simulation and prediction by auto-regression ( AR) model cannot be directly applied due to the non-stationary historical runoff sequence of the Danjiangkou Reservoir has been solved. The simulation results show that EEMD-AR model can simulate and predict the annual runoff sequence of the Danjiangkou Reservoir in a good forecast accuracy and it maintain the statistical characteristics of the original historical sequence.
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