Seasonal and spatial variations in the scaling and correlation structure of streamflow data
Article first published online: 11 MAY 2012
Copyright © 2012 John Wiley & Sons, Ltd.
Volume 27, Issue 12, pages 1681–1690, 15 June 2013
How to Cite
Özger, M., Mishra, A. K. and Singh, V. P. (2013), Seasonal and spatial variations in the scaling and correlation structure of streamflow data. Hydrol. Process., 27: 1681–1690. doi: 10.1002/hyp.9314
- Issue published online: 4 JUN 2013
- Article first published online: 11 MAY 2012
- Accepted manuscript online: 23 MAR 2012 03:31PM EST
- Manuscript Accepted: 2 MAR 2012
- Manuscript Received: 13 SEP 2011
- Korean Government (MEST). Grant Number: NRF-2009-220-D00104
- correlation dimension;
Seasonal and spatial variability in scaling, correlation and wavelet variance parameter of daily streamflow data were investigated using 56 gauging stations from five basins located in two different climate zones. Multifractal temporal scaling properties were detected using a multiplicative cascade model. The wavelet variance parameter yielded persistence properties of the streamflow time series. Seasonal variations were found to be significant in that winter and spring seasons where large-scale frontal events are dominant showed higher long-term correlations and less multifractality than did summer and fall seasons. Coherent spatial variations were apparent. The Neches River basin located in a subtropic humid climate zone exhibited high persistence and long-term correlation as well as less multifractality as compared with other basins. It is found that larger drainage areas tend to have smaller multifractality and higher persistence structure, and this tendency becomes apparent in regions that receive large amounts of precipitation and decreases towards arid regions. Copyright © 2012 John Wiley & Sons, Ltd.