Abstract
AbstractIn this study, the wavelet transform and the Mann–Kendall test are used to determine possible trends in annual streamflow series. The wavelet analysis provides detailed information about the time‐frequency contents of the data. Using wavelet components of the original data, it was aimed to find which periodicities are mainly responsible for a trend in the original data. Also, the global wavelet spectra and the continuous wavelet transform (CWT) were used for the analysis of the streamflow data, in order to explain its time‐frequency characteristics. Annual streamflow series across Turkey were used for the detection of trends for the original data and the periodic wavelet components (obtained by discrete wavelet transform). It was found that some periodic events clearly affect the trend in the streamflow series. The DW4 component (16‐yearly periodic component) at the stations of the Sakarya basin is the effective periodic component and is responsible for producing a real trend in the data. The effects of regional differences on the wavelet‐trend analysis are studied using records of the stations located in different climate areas. DW2 (4‐yearly component) and DW3 (8‐yearly component) are the dominant periodic components of this data. This study aims to explain the trend structure in the data. Copyright © 2009 John Wiley & Sons, Ltd.
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