The superimposition of rhythmic bed forms of different spatial scales is a common and natural phenomenon on sandy seabeds. The dynamics of such seabeds may interfere with different offshore activities and are therefore of interest to both scientists and offshore developers. State-of-the-art echo sounding accuracy allows for the analysis of bed form dynamics on unprecedented spatial and temporal scales. However, the superimposition of bed forms complicates the automated determination of morphodynamic parameters of individual bed form components. In this research we present the extension and comparison of two well-known, automated signal-processing methods for the 1-D and 2-D separation of bathymetric data derived from multibeam echo soundings into different components that each represents a bed form of a particular length scale. One method uses geostatistical filtering, and the other uses a Fourier decomposition of the bathymetric data. The application of both methods in two case studies of the North Sea shows that both methods are successful and that results correspond well. For example, megaripples up to 0.83 m height could be separated from 1.49-2.28 m high sand waves, and regionally averaged lengths and heights of sand waves, as calculated in either method, differ only 0.42-8.2% between methods. The obtained sand wave migration rates differ 7-11% between methods. The resulting morphometric and morphodynamic bed form quantification contributes to studies of empirical behavior and morphodynamic model validation and is valuable in risk assessments of offshore human activities.@en

Extensive seabed sediment mapping is highly relevant to describe marine ecosystems and to quantify the distribution and extent of benthic habitats. Compared to traditional mapping methods, primarily based on bed sampling, multibeam echo sounding (MBES) is a time-efficient tool to acquire high-resolution bathymetric and backscatter data over large areas. We use a Bayesian method for unsupervised acoustic sediment classification (ASC) of MBES backscatter data of the Cleaver Bank, Netherlands Continental Shelf. On these sparsely distributed backscatter datasets, we tested and evaluated different Kriging algorithms, showing that Ordinary Kriging results in a reliable map. We introduce a new approach to classify interpolated MBES backscatter based on the Bayesian method for producing full-coverage sediment maps. Comparison to a traditional sediment map and in situ measurements shows that this approach resolves lateral heterogeneities (kilometers). When evaluating the high-resolution sediment map obtained from the Bayesian method, based on the actual backscatter, mapping laterally heterogeneous sediments significantly improved (meters). In order to create the optimal sediment map, we aimed to integrate ASC into existing maps, which, however, requires quantified spatial uncertainties of both considered maps. Finally, the low discrimination power of MBES backscatter for coarse sediments is highlighted as a shortcoming of current ASC mapping.@en

In natural rivers, flow discharge may fluctuate across a range of time scales – from diurnal to seasonal - but is often most pronounced during hydrographs that may encompass long-duration floods. Under these varying flows, bedforms can be created and modified by the flow without achieving any ‘equilibrium’ state. A lag between changes in flow and the morphological response of the bedforms, termed bedform hysteresis, is commonly present. Importantly for channel management and navigation, since dunes may grow larger during floods, but often experience a lagged decay in size during lowering water levels, critical water depths may be reached for inland shipping. There is also a consensus that dunes possess a more flattened shape, and lower leeside angle, than previously assumed in large rivers and that such dunes do not exhibit a region of permanent flow separation downstream of the dune. This different leeside shape thus questions traditional ideas of flow interactions with dunes, where flow separation in the steep dune lee side leads to energy loss (form drag) that increases flow resistance and energy expenditure within the flow. This paper quantifies dune hysteresis in the River Waal, Netherlands, by investigating how dune morphology changes through flood hydrographs, using high spatial- and temporal- resolution bathymetric data and robust computational analysis methods to produce probability density functions of dune morphology. This quantification aims to provide a better understanding of dune hysteresis in large rivers. The analysis examines several large data sets of river bathymetry from a 13 km reach of the River Waal, Netherlands, in a time series of bi-weekly multibeam echo sounder surveys over the last 12 years. Parameterization includes dune height, wavelength, leeside angle and leeside shape, to assess dune kinematics and hysteresis during different flood hydrographs.@en

In natural rivers, flow discharge may fluctuate across a range of time scales – from diurnal to seasonal - but is often most pronounced during hydrographs that may encompass long-duration floods. Under these varying flows, bedforms can be created and modified by the flow without achieving any ‘equilibrium’ state. A lag between changes in flow and the morphological response of the bedforms, termed bedform hysteresis, is commonly present. Importantly for channel management and navigation, since dunes may grow larger during floods, but often experience a lagged decay in size during lowering water levels, critical water depths may be reached for inland shipping. There is also a consensus that dunes possess a more flattened shape, and lower leeside angle, than previously assumed in large rivers and that such dunes do not exhibit a region of permanent flow separation downstream of the dune. This different leeside shape thus questions traditional ideas of flow interactions with dunes, where flow separation in the steep dune lee side leads to energy loss (form drag) that increases flow resistance and energy expenditure within the flow. This paper quantifies dune hysteresis in the River Waal, Netherlands, by investigating how dune morphology changes through flood hydrographs, using high spatial- and temporal- resolution bathymetric data and robust computational analysis methods to produce probability density functions of dune morphology. This quantification aims to provide a better understanding of dune hysteresis in large rivers. The analysis examines several large data sets of river bathymetry from a 13 km reach of the River Waal, Netherlands, in a time series of bi-weekly multibeam echo sounder surveys over the last 12 years. Parameterization includes dune height, wavelength, leeside angle and leeside shape, to assess dune kinematics and hysteresis during different flood hydrographs.@en