摘要:
该文基于四川岷江上游桑坪、杂谷脑两个水文站1962—2002年的月径流实测资料,采用小波理论分析杂谷脑河流域径流变化趋势及其周期特征.选用db3小波函数对标准化径流序列进行多分辨分析,其低频重构序列显示该流域径流变化呈递减趋势,并且植被平均状况较差的区域相对植被平均状况较好的区域径流下降趋势明显,变化剧烈,证明了森林植被的水源涵养功能及调节能力,植被恢复与更新有助于改善流域的水文状况.另外,除森林对径流影响较大外,人类活动如灌溉、水电站等也是引起流域径流量递减的重要原因.选用复Morlet小波函数对标准月径流序列进行连续小波变换,根据小波方差图可以确定,杂谷脑站上游径流过程存在6a左右的显著周期,桑坪站上游径流过程存在7~8a的显著周期.研究结果表明,小波变换是分析非平稳随机时间序列的有效工具,在水文水资源领域应用潜力很大.
Abstract:
Based on the monthly flow series of the two gauging stations, Zagunao and Sangping on Zagunao River, upper stream of the Minjiang, the wavelet transform was adopted to analyze the flow trend and periodic variation of the Zagunao Watershed. The standardized time series were decomposed by Multi-Resolution Analysis (MRA) using the db3 wavelet function. The reconstruction of the lowest frequency part shows the descending trends for the two flow series and the trend descends more rapidly in regions with worse vegetation conditions than those with better vegetation conditions, which testifies the equalizing effect of forests on stream flow. Besides the vegetation, human activities such as increasing irrigation and hydroelectric power stations are also important factors on the descending flow. Finally, continuous wavelet transform (CWT) was carried out to identify the periodic variation of the two standardized series using the complex valued Morlet function. And the wavelet variance is employed to identify the dominant period, which results in 6 years for Zagunao and 7-8 years for Sangping approximately. The results indicate that the wavelet transform is an effective tool for nonstationary stochastic series analysis, which has great potential in hydrology and water resources research.
百度学术
下载:
