Controls of alluvial cover formation, morphology and bedload transport in a sinuous channel with a non‐alluvial boundary

Remote sensing enables us to measure fluvial systems without disrupting their dynamics. Small‐scale physical models of rivers allow us to observe their geomorphic evolution, but we need remote sensing methods to monitor these laboratory landscapes without altering their flow or topography, just as with field‐scale rivers. In this paper, we review how experimental geomorphologists have adapted remote sensing for the laboratory. We consider how remote methods to monitor model topography, flow depth, velocity and planform have been employed, enabling uninterrupted experimental evolution. We also explore the transfer of techniques between field‐scale and experimental remote sensing; the controlled conditions in the lab aided the development of some methods, while others benefited from airborne deployment. We consider recent developments offered by laboratory remote sensing, including through‐water laser scanning and adaptations of structure‐from‐motion photogrammetry; we also consider new challenges associated with these developments, such as computational power. Finally, we discuss new research problems that laboratory remote sensing is opening up to geomorphology. We hope this review will be useful for experimentalists seeking to collect data remotely, continuously and/or cost‐effectively.

Section: Dye-based Planform Trackingmentioning

confidence: 99%

Remote sensing of laboratory rivers

Leenman

Eaton

2023

“…Rivers are most often designed with pool spacing of five to seven times the channel width (Hudson, 2002) These experiments were done previously as part of another research project related to formation of alluvial cover, bed topography and bar formation in channels with differing bed material supply rates (Papangelakis et al, 2021;Peirce et al, 2021) but provided a useful set of data on which to run GFV analysis. The applied feed rates and fixed planform patterns were controlled variables and contributed to systematic morphological differences between channels because of differences in the bar dimensions, amplitude and position (Papangelakis et al, 2021;Peirce et al, 2021). These flume channels were selected for GFV investigation because they provided opportunities for quasi-controlled comparisons of bed topography development and morphology to evaluate the relationship to variety metrics in real physical channels.…”

Section: Generation Of River Synthetic Surfaces and Description Of Fl...mentioning

confidence: 99%

Evaluating river morphology change with a geomorphic form variation approach

Dawson,

Ashmore,

Corry

2023

Geomorphic river design strives for natural resilience by encouraging geomorphic form complexity and morphological processes linked to greater habitat diversity. Increasing availability of high‐resolution topographic data and spatial feature mapping methods provide advantages for morphological analysis and river restoration planning. We propose and evaluate an approach to quantifying topographic variability of geomorphic form and pixel‐level surface roughness resulting from channel planform geometry differences using spatially continuous variety computation applied to component metrics including flow direction, aspect and planform curvature. We define this as the geomorphic form variation (GFV) approach and found it scalable, repeatable and a multi‐stage analytical metric for quantifying physical aspects of river‐bed topographic variability. GFV may complement process‐based morphological feature mapping applications, hydraulic assessment indices and spatial habitat heterogeneity metrics commonly used for ecological quality evaluation and river restoration. The GFV was tested on controlled synthetic channels derived from River Builder software and quasi‐controlled sinuous planform flume experiment channels. Component variety metrics respond independently to specific geometric surface changes and are sensitive to multi‐scaled morphology change, including coarser‐grained sediment distributions of pixel‐level surface roughness. GFV showed systematic patterns of change related to the effects of channel geometry, vertical bed feature (pool‐bar) frequency and amplitude, and bar size, shape and orientation. Hotspot analysis found that bar margins were major components of topographic complexity, whereas grain‐scale variety class maps further supported the multi‐stage analytical capability and scalability of the GFV approach. The GFV can provide an overall variety value that may support river restoration decision‐making and planning, particularly when geomorphic complexity enhancement is a design objective. Analysing metric variety values with statistically significant hotspot cluster maps and complementary process‐based software and mapping applications allows variety correspondence to systematic feature changes to be assessed, providing an analytical approach for river morphology change comparison, channel design and geomorphic process restoration.

“…Consequently, we might expect that had we used a mixed GSD, the alluvial roughness and pivot angles could all have been smaller, potentially reducing the differences between the bedrock and alluvial surfaces. A further complication of a mixed GSD is that the GSD can vary between different areas of the sediment cover (Papangelakis et al, 2021). Consequently, the size of grains at any location on the bed, and hence pivot angle, becomes even harder to predict (Prancevic & Lamb, 2015).…”

Section: Implications Of Our Experimental Designmentioning

confidence: 99%

The influence of bedrock river morphology and alluvial cover on gravel entrainment: Part 1. Pivot angles and surface roughness

Buechel

Hodge

Kenmare

2022

Sediment entrainment in bedrock rivers is a key process for river incision and landscape evolution. Bedrock riverbeds are typically comprised of both exposed bedrock and alluvial patches, meaning grains can be entrained from positions on both surfaces. The critical shear stress needed to entrain a grain will be affected by the topography that the grain is located on, as it determines grain pivot angle and exposure, and impacts the local flow profile. The aim of this pair of articles is to determine how the properties of bedrock surfaces with and without sediment cover affect the grain‐scale geometry of sediment grains, and consequently their critical shear stress. We report experiments using 3D‐printed scaled replicas of fluvial bedrock surfaces, with 0 to 100% additional sediment cover. For each surface, grain pivot angles were measured using a tilt table. In this first article, we report how surface roughness and grain pivot angle vary between surfaces and with different amounts of sediment cover, and we explore the relationship between pivot angles and different metrics for measuring surface roughness. We find that: (1) surface roughness is not necessarily a linear combination of the individual roughness of bedrock and alluvial areas, and the underlying bedrock topography can still influence surface roughness at 100% sediment cover; (2) pivot angles generally, but not always, decrease with increasing grain size relative to surface roughness; (3) changes in pivot angles with increasing sediment cover are best explained by changes in surface roughness at spatial scales comparable to the grain size; and (4) pivot angles are also best explained by roughness metrics that incorporate the direction of roughness with respect to the tilt direction, and the surface inclination. This work provides new insights into the processes behind grain entrainment in bedrock rivers that are critical for determining how landscapes may evolve.