HR: 0800h
AN: H51E-0803    [Abstracts]
TI: Understanding the structure of step-pool mountain streams through wavelet analysis
AU: * Burge, L M
EM: lburge@okanagan.bc.ca
AF: Department of Geography and Earth and Environmental Science, Okanagan College, 1000 KLO Road, Kelowna, BC V1Y 4X8, Canada
AU: Corbett, N
EM: ncorbett@okanagan.bc.ca
AF: Department of Mathematics, Okanagan College, 1000 KLO Road, Kelowna, BC V1Y 4X8, Canada
AB: The periodicity of structures, like step-pool spacing, in the long profiles of mountain streams, has been debated in the literature. Some authors claim to have established the existence of periodicity in step-pool sequences through the use of the Fourier transform. Other authors claim that statistical models, based on renewal processes, adequately explain the placement of the steps. In the latter case, the implication is that step placement is random rather than periodic. In fact, the Fourier transform is best suited to the analysis of stationary signals: signals for which the spectral (frequency or wavelength) content does not evolve through time or space. In the context of long profiles, this implies that one or more dominant wavelengths persist down the entire reach. Given the complexity of river systems, it is not unreasonable to assume that spacing of steps varies along the reach. As such, straightforward Fourier analysis may provide an incomplete or misleading picture of the spectral content of long profiles. On the other hand, the wavelet transform has been successfully applied to analysis of non-stationary signals. Unlike the Fourier transform, which supplies spectral information for the entire signal record, the wavelet transform produces a time-scale or space-scale (i.e. space-wavelength) map that preserves the local spectral content of the signal. Consequently, for long profiles, the wavelet transform has the capacity to detect periodic structures, which persist along the entire reach, as well as "transient" structures that occur at isolated locations along the reach. In this paper, we investigate the applicability of the continuous wavelet transform for the analysis of long profiles associated with mountain streams. We begin by demonstrating how the wavelet transform differentiates prototypical signals that cannot easily be differentiated with the Fourier transform. We then show how the transform can be applied to reveal the space-wavelength structure of a number of mountain stream long profiles.
DE: 1815 Erosion
DE: 1825 Geomorphology: fluvial (1625)
DE: 1856 River channels (0483, 0744)
DE: 1861 Sedimentation (4863)
SC: Hydrology [H]
MN: 2007 Fall Meeting