水文序列周期成分和突变特征识别的小波分析法  

Wavelet Analysis for the Diagnosis of Period and Jump in Hydrological Time Series

作　　者：王文圣[1] 丁晶[1] 衡彤[1] 向红莲[1] 

机构地区：[1]四川大学水电学院,四川成都610065

出　　处：《工程勘察》2003年第1期32-35,共4页Geotechnical Investigation & Surveying

基　　金：国家自然科学基金项目 (5 0 2 790 2 3) ;四川大学高速水力学国家重点实验室开放基金 (2 0 0 8)

摘　　要：以三峡宜昌站年最大洪峰序列和金沙江屏山站年平均流量序列为例 ,利用小波变换时频局部化功能 ,将水文序列的频率特征在时间域上展现出来 ,清晰地给出了各种周期的强弱和分布情况以及突变点 ,而且还分析出其主要周期。研究结果表明 ,小波分析法是优越的。Based on the time series of the annual maximum peak discharge at Yichang station in Three Gorges and the annual mean discharge at Pingshan station in Jinsha River,the characteristics of period and jump of hydrological time series have been probed with Morlet wavelet transform.The study shows that wavelet transform can clearly demonstrate all kinds of features of hydrological time series:the strength and distribution of the period and jump as well as the major periods.

关 键 词：水文序列 周期成分 突变 小波分析法 年平均流量 年最大洪峰流量 

分 类 号：P333[天文地球—水文科学]