Abstract

Abstract. The accuracy of hydraulic models depends on the quality of the bathymetric data they are based on, whatever the scale at which they are applied. The along-stream (longitudinal) and cross-sectional geometry of natural rivers is known to vary at the scale of the hydrographic network (e.g., generally decreasing slope, increasing width in the downstream direction), allowing parameterizations of main cross-sectional parameters with large-scale proxies such as drainage area or bankfull discharge (an approach coined downstream hydraulic geometry, DHG). However, higher-frequency morphological variability (i.e., at river reach scale) is known to occur for many stream types, associated with varying flow conditions along a given reach, such as the alternate bars or the pool–riffle sequences and meanders. To consider this high-frequency variability of the geometry in the hydraulic models, a first step is to design robust methods to characterize the scales at which it occurs. In this paper, we introduce new wavelet analysis tools in the field of geomorphic analysis (namely, wavelet ridge extraction) to identify the pseudo-periodicity of alternating morphological units from a general point of view (focusing on pool–riffle sequences) for six small French rivers. This analysis can be performed on a single variable (univariate case) but also on multiple variables (multivariate case). In this study, we choose a set of four variables describing the flow degrees of freedom: velocity, hydraulic radius, bed shear stress, and a planform descriptor that quantifies the local deviation of the channel from its mean direction. Finally, this method is compared with the bedform differencing technique (BDT), by computing the mean, median, and standard deviation of their longitudinal spacings. The two methods show agreement in the estimation of the wavelength in all reaches except one. The method aims to extract a pseudo-periodicity of the alternating bedforms that allow objective identification of morphological units in a continuous approach with the maintenance of correlations between variables (i.e., at many station hydraulic geometry, AMHG) without the need to define a prior threshold for each variable to characterize the transition from one unit to another.

Highlights

  • Hydraulic modeling is based on the description of river morphology, and this is the essential input of models despite its scarcity and cost of acquisition

  • We introduce an automatic procedure called wavelet ridge extraction defined by Lilly and Olhede (2011) and used in this study to extract the longitudinal spacing of the alternating morphological units (MUs)

  • We found that the wavelengths extracted by the multivariate wavelet analysis are generally included in the variance intervals of the wavelengths found by the bedform differencing technique (BDT)

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Summary

Introduction

Hydraulic modeling is based on the description of river morphology (cross-sectional geometry), and this is the essential input of models despite its scarcity and cost of acquisition. The most important aspect to know is the river bathymetric data at the local scale, detailed and specific to the site and local conditions (Alfieri et al, 2016) This component is essential for accurate modeling of river hydraulics such as flood modeling (e.g., Neal et al, 2015; Trigg et al, 2009), river restoration (e.g., Wheaton et al, 2004), ecohydraulics (e.g., Pasternack and Brown, 2013), environmental modeling, and fluvial process (e.g., Rodríguez et al, 2013). Longitudinal variability in river geometry may have a greater impact on the simulation of the water level than the cross-sectional shapes (Saleh et al, 2013), and it must be taken into account in the hydraulic models. Mahdade et al.: Automatic identification of alternating morphological units in river channels for many morphological channel types, each type being characterized by typical morphological units (MUs), e.g., pools, riffles, steps, point bars, and meanders

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