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中文摘要：
应用小波分析方法及相关理论,以海河流域黑龙洞泉域47a（1956~2002年）年降雨序列和黄河利津站54a（1950~2003年）年径流序列为例,深入研究并定量描述随序列长度变化时水文时间序列主周期值和复杂特性的变化规律和特征。分析结果显示：不同方法（熵谱分析（MESA）、连续小波变换和小波方差分析）对相同长度序列的周期识别结果一致,不同长度序列的主周期值不同;此外,不同长度序列（包括原序列和消噪序列）的信息量系数（ICF）和分维数（D）也不等。研究结果表明：（1）水文序列特性复杂多变,存在整体变化特性和十分复杂的局部特性;（2）由局部特性发生变化造成序列的复杂程度随序列长度而变化,从而引起序列主周期值及复杂度（ICF和D）随序列长度变化而变化;（3）相比于序列的整体变化特性,局部特性更加复杂多变且更难以进行描述,因此也难以进行准确地模拟预测。对于引起水文序列局部特性变化的物理机制仍需进行深入探讨。
英文摘要：
By applying wavelet analysis（WA） to both the 47a（1956-2002） rainfall series measured at Heilongdong station in the Haihe River basin and the 54a（1950-2003） runoff series measured at Lijin station on the Yellow River,variations dominant period and complexity of hydrologic series with series length were analyzed and described.The results indicate that period identificationresults of certain se ries by MESA,WA and wavelet variance analysis are similar,but they vary with series lengths,moreover,information cost function（ICF） and fractal dimension（D） of observed and de-noised series also vary with series lengths.By comprehensive analysis,it can be concluded that：（1） global and local characteristics of hydrologic series are highly complicated;（2） variations of the dominant period,ICF and D are caused by complex local characteristics of hydrologic series;（3） compared with global characteristics,local characteristics of series data are more complicated and difficult to be described,thus also more difficult to be simulated.Whereas the physical mechanisms should be studied in the future to further understand the local characteristics of hydrologic series.
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