The use of fractals to quantify the morphology of cluster microforms

Papanicolaou, A. N.; Tsakiris, Achilleas G.; Strom, Kyle

doi:10.1016/j.geomorph.2011.10.007

Cited by 25 publications

(9 citation statements)

References 56 publications

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“…How were the clusters related to the surrounding sediment movements? Aspects of the quantification of these characteristics have been conducted in a number of studies to date [ Brayshaw , ; Hendrick et al ., ; Papanicolaou et al ., ; Papanicolaou and Schuyler , ; Reid et al ., ; Strom and Papanicolaou , ; Strom et al ., ; Strom and Papanicolaou , ]. The present study differs from previous investigations either through the experimental setup, where idealized glass beads have been monitored using image analysis, or in relation to the sampling method, where manual surveys of cluster position in natural river bed situations have been conducted.…”

Section: Introductionmentioning

confidence: 99%

Laboratory study of gravel‐bed cluster formation and disintegration

Heays

Friedrich

Melville

2014

Water Resources Research

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Increased knowledge of clusters is essential for the understanding of sediment transport behavior and the monitoring and protection of aquatic life. A physical study using graded river gravels is conducted in a laboratory environment. Using photogrammetry and painted gravels, a cluster identification tool (CIT) is developed based on image subtraction between subsequent frames, allowing identification of any stable areas and groups of particles on the bed. This is combined with digital particle tracking (DPT) to present a novel approach for monitoring the formation and disintegration of clusters. Clusters from graded gravels are formed successfully during the experimental stage, allowing investigation into the complex dynamic behavior of cluster formation and disintegration in a simulated natural environment. Various anchor stone arrangements are used in the experiments. However, only about one fifth of the potential anchor stones on the bed surface enable cluster formation. In general, clusters classified as ''typical'' and ''heap'' are most common. Inspection of temporal cluster coverage of the test-bed surface shows that the proportion of clusters present on the surface tends to grow with time. Maximum cluster surface coverage of between 5% and 34% is observed. In addition, particles entering and departing from clusters are monitored. Most commonly, particles enter from directly upstream of the cluster, however >20% of particles approach from a direction >20 deg from the streamwise direction. Approximately 35% of all particles directly upstream of a cluster bypass the cluster.

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Section: Introductionmentioning

confidence: 99%

Laboratory study of gravel‐bed cluster formation and disintegration

Heays

Friedrich

Melville

2014

Water Resources Research

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“…Lane, ) and parallel need to develop better means of routinely acquiring patch‐scale DEMs or other surface representations, from which suitable roughness parameterizations are extracted. For example, although there are some exciting recent developments (Papanicolaou et al ., ) there is no standard, accepted means of identifying and codifying ‘large roughness elements’ within the microtopographic confusion that characterizes gravel‐bed sediment textures, or of describing their arrangement and distribution. This is despite widespread acknowledgment (Morris, , et seq.)…”

Section: Discussionmentioning

confidence: 99%

Sensitivity of interfacial hydraulics to the microtopographic roughness of water‐lain gravels

Rice

Buffin‐Bélanger

Reid

2013

Earth Surf Processes Landf

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Flow within the interfacial layer of gravel-bed rivers is poorly understood, but this zone is important because the hydraulics here transport sediment, generate flow structures and interact with benthic organisms. We hypothesized that different gravel-bed microtopographies generate measurable differences in hydraulic characteristics within the interfacial layer. This was tested using a high density of spatially and vertically distributed, velocity time series measured in the interfacial layers above three surfaces of contrasting microtopography. These surfaces had natural water-worked textures, captured in the field using a casting procedure. Analysis was repeated for three discharges, with Reynolds numbers between 165000 and 287000, to evaluate whether discharge affected the impact of microtopography on interfacial flows. Relative submergence varied over a small range (3.5 to 8.1) characteristic of upland gravel-bed rivers. Between-surface differences in the median and variance of several time-averaged and turbulent flow parameters were tested using non-parametric statistics. Across all discharges, microtopographic differences did not affect spatially averaged (median) values of streamwise velocity, but were associated with significant differences in its spatial variance, and did affect spatially averaged (median) turbulent kinetic energy. Sweep and ejection events dominated the interfacial region above all surfaces at all flows, but there was a microtopographic effect, with Q2 and Q4 events less dominant and structures less persistent above the surface with the widest relief distribution, especially at the highest Reynolds number flow. Results are broadly consistent with earlier work, although this analysis is unique because of the focus on interfacial hydraulics, spatially averaged 'patch scale' metrics and a statistical approach to data analysis. An important implication is that observable differences in microtopography do not necessarily produce differences in interfacial hydraulics. An important observation is that appropriate roughness parameterizations for gravel-bed rivers remain elusive, partly because the relative contributions to flow resistance of different aspects of bed microtopography are poorly constrained.

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“…The degree of complexity of a polygon is characterized by the fractal dimension (D), for simple Euclidean shapes, D = 1 (the dimension of a line). As the polygons become more complex, the fractal dimension increasingly to 2, Papanicolaou et al, [10] demonstrated four different outlines (perimeters) with increasing degree of convolution, Fig. 2B-D illustrates object outlines with greater degree of convolution than the circle of Fig.…”

Section: Fractal Dimensionmentioning

confidence: 95%

Stream morphometry analysis by airborne laser altimetry

Yang

Liu³

2014

2014 IEEE Geoscience and Remote Sensing Symposium

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The river characteristics have played an important role for hydrological models. Sediments supplied from landslides may affect the river channel morphological changes in different reaches or magnitude; namely, the riverbed morphology can be related to disaster events. Measurements of riverbed morphology are made using high-resolution LiDAR DEM in this study to understand the relationship. Quantifying the morphology along a river channel has been proven difficult; till the airborne laser altimetry technology was implemented in the survey. In this study, the remote sensing techniques are employed to assist the studies on stream roughness distribution and morphological investigation. The results are proven to be valuable for hydrological and engineering applications.

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The use of fractals to quantify the morphology of cluster microforms

Cited by 25 publications

References 56 publications

Laboratory study of gravel‐bed cluster formation and disintegration

Laboratory study of gravel‐bed cluster formation and disintegration

Sensitivity of interfacial hydraulics to the microtopographic roughness of water‐lain gravels

Stream morphometry analysis by airborne laser altimetry

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