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流域径流受诸多因素影响,变化复杂,仅凭观测站统计数据难以发现其演变规律。以混沌理论为基础,以鄱阳湖入湖外洲站、李家渡站和渡峰坑站的月径流时间序列为研究对象详细说明了求取时间序列中混沌特征数的方法。首先利用C-C方法选取相空间重构参数即时间延迟τ和嵌入维数m,在此基础上进行相空间重构,采用G-P关联积分法计算关联维数和Rosenstein小数据量法计算最大Lypanuov指数。结果表明鄱阳湖入湖外洲站、李家渡站和渡峰坑站的月径流序列的饱和关联维数非整数,同时最大Lyapunov指数也为正数,这充分说明鄱阳湖入湖外洲站、李家渡站和渡峰坑站的月径流序列均具有明显的混沌特征。而且通过最大Lyapunov指数和关联维数的计算表明鄱阳湖入湖的外洲站月径流复杂程度最大,混沌特性最强,对初值的敏感性最强,李家渡站次之,渡峰坑站最小。
The runoff of a river basin is affected by many factors and the change is complex. It is difficult to find out the evolution law of the runoff based solely on the statistic data of the observatory. Based on the chaos theory, the monthly runoff time series of Wazhou station, Lijiadu station and Fufengkeng station which are located in the Poyang Lake into the lake are described in detail as a method to calculate the number of chaotic features in the time series. Firstly, phase-space reconstruction parameters such as time delay τ and embedding dimension m are selected by C-C method. Phase space reconstruction is performed on this basis. The maximum Lypanuov exponent is calculated by using G-P correlation integral method and Rosenstein small data volume method. The results show that the saturation correlation dimension of monthly runoff series at Wazhou station, Lijiadu station and Fufengkeng station entering Poyang Lake is non-integer, and the maximum Lyapunov exponent is also positive, which fully shows that Poyang Lake locates at Wazhouzhou Station, Lijiadu The monthly runoff series of stations and Shuifengkeng stations all have obvious chaotic characteristics. Moreover, the calculation of maximum Lyapunov exponent and correlation dimension shows that the monthly runoff of Poyang Lake into the lake is the most complex with the highest chaotic characteristic and the highest sensitivity to the initial value, followed by Lijiadu Station and Dufengkeng Station .