River bed sediment surface characterisation using wavelet transform-based methods.

Abstract

The primary purpose of this work was to study the morphological change of river-bedsediment surfaces over time using wavelet transform analysis techniques. The wavelettransform is a rapidly developing area of applied mathematics in both science andengineering. As it allows for interrogation of the spectral made up of local signalfeatures, it has superior performance compared to the traditionally used Fouriertransform which provides only signal averaged spectral information. The main study ofthis thesis includes the analysis of both synthetically generated sediment surfaces andlaboratory experimental sediment bed-surface data. This was undertaken usingtwo-dimensional wavelet transform techniques based on both the discrete and thestationary wavelet transforms.A comprehensive data-base of surface scans from experimental river-bed sedimentsurfaces topographies were included in the study. A novel wavelet-basedcharacterisation measure - the form size distribution ifsd) - was developed to quantifythe global characteristics of the sediment data. The fsd is based on the distribution ofwavelet-based scale-dependent energies. It is argued that this measure will potentiallybe more useful than the traditionally used particle size distribution (psd), as it is themorphology of the surface rather than the individual particle sizes that affects the nearbed flow regime and hence bed friction characteristics.Amplitude and scale dependent thresholding techniques were then studied. It was foundthat these thresholding techniques could be used to: (1) extract the overall surfacestructure, and (2) enhance dominant grains and formations of dominant grains withinthe surfaces. It is shown that assessment of the surface data-sets post-thresholding mayallow for the detection of structural changes over time