Robust methods for the decomposition and interpretation of compound dunes applied to a complex hydromorphological setting

Abstract

Underwater dunes are a morphological feature that are explored by marine scientists and coastal engineers alike. This study presents new methodologies in order to simplify bedform identification and morphodynamic analyses. Specifically, subaqueous compound dunes are decomposed with a simple yet extensive tracking algorithm, which relies on a repeated evaluation of unfiltered bed elevation profiles according to five predefined length classes. In a second step, morphological trends are assessed in the form of bed migration rates, bed slope asymmetries and net sediment changes, in which all parameters are referred to equidistant sections of the examined fairway stretch. This integrated approach not only avoids the challenges in weighting the varying size and abundance of dunes of different scales but also ensures comparability between dune‐specific and areal parameters, which significantly improves the interpretation of the morphological setting as a whole. The developed methods are applied to the Outer Jade fairway, an anthropogenically influenced and regularly maintained waterway in the German Bight, and allow scrutiny of spatio‐temporal trends in this region. Based on a unique data set of 100 sequential high‐quality echo‐sounding surveys, various types of bedforms are identified, comprising large‐scale primary as well as superimposing secondary dunes that are assumed to interfere with each other. Temporal trends show a long‐term rise of the troughs of major bedforms and constant maximum crest elevations near the official maintenance depth, which matches the observed long‐term aggradation of sediments. The spatial distribution of integrated morphodynamic parameters reflects a previously described zone of primary dune convergence and facilitates the precise localization of this geophysical singularity. The presented findings both confirm the robustness of the proposed methodologies and, in return, enhance the understanding of morphological processes in the Outer Jade. © 2020 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd.

Automatic Mapping and Characterisation of Linear Depositional Bedforms: Theory and Application Using Bathymetry from the North West Shelf of Australia

“…On the other hand, automated and semi-automated measurements provide results that are much more scattered and presumably more representative of bedform variability. Interestingly, metrics reported in this study (Figure 16) as well as metrics obtained by various automated methods [20,22,24] all return height/width ratio that appear below the trend reported in Ashley chart. This observation further supports that there is a need to increase the use of automated bedform measurement technics and to update existing classifications.…”

“…It is key to measure metrics perpendicularly to the bedform orientation to ensure that they are not affected by geometrical distortions (e.g., stoss and lee angle measurements made along an oblique cross section will return lower values than reality as well as incorrect width values). In that context, several of the existing methods require user-specified profiles or require rotating the bathymetry [19][20][21][22][23][24]. Here, the script generates perpendicular profiles along crestline polylines to be used as inputs, similar to what was attempted in [28].…”

“…Similarly, ref. [23] analysed longitudinal profiles to identify a change in derivatives signs while [24], also using longitudinal profiles, used the position of local minima and maxima. Other authors have attempted to use spatial classes (e.g., [25][26][27][28][29]), building on concepts such as geomorphons [30], topographic signatures [31] or index [32], that are then converted into individual features.…”

Special issue: Marine and river bedforms dynamics, MARID VI

“…The method presented by Scheiber et al (2021) was developed to analyse compound bedforms in a tidal channel. The developed tracking algorithm relies on repeated evaluation of unfiltered bed elevation profiles according to five predefined length classes.…”

“…The wavelength of interest as well as its orientation can be automatically determined by a series of 2D Fourier analyses. With these, the crests and troughs of each bedform scale can be identified on bedform profiles taken through the bedform main orientation, and the dune wavelength, height and leeside angles can be calculated.The method presented byScheiber et al (2021) was developed to analyse compound bedforms in a tidal channel. The developed tracking algorithm relies on repeated evaluation of unfiltered bed elevation profiles according to five predefined length classes.…”