High resolution topographic data are necessary to understand benthic habitat, quantify processes
at the water-sediment interface, and support computational fluid dynamics models for
both surface and hyporheic hydraulics. In riverine systems, these data are typically collected
using traditional surveying methods (total station, DGPS, etc.), airborne or terrestrial laser
scanning, and photogrammetry. Recently, handheld surveying equipment has been rapidly
acquiring popularity in part due to its processing capacity, price, size, and versatility. One
such device is the iPhone LiDAR, which could have a good balance between precision and
ease of use and is a potential replacement for conventional measuring tools. Here, we evaluated
the accuracy of the LiDAR sensor and a Structure from Motion (SfM) method based
on photos collected using the iPhone Cameras. We compared the LiDAR and SfM elevations
to those from a high-precision laser scanner for an experimental rough water-worked gravelbed
channel with boulder-like structures. We observed that both the LiDAR and SfM methods
captured the overall streambed morphology and detected large (Hs 15 cm) and macro
(5cm Hs < 15cm) scales of topographic variations (Hs, roughness). The SfM technique
also captured small scale (Hs <5cm) roughness whereas the LiDAR consistently simplified it
with errors of 3.7 mm.
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Quantifying flow resistance in mountain streams using computational fluid dynamics modeling over structure‐from‐motion photogrammetry‐derived microtopography
Flow resistance in mountain streams is important for assessing flooding hazard and quantifying sediment transport and bedrock incision in upland landscapes. In such settings, flow resistance is sensitive to grain‐scale roughness, which has traditionally been characterized by particle size distributions derived from laborious point counts of streambed sediment. Developing a general framework for rapid quantification of resistance in mountain streams is still a challenge. Here we present a semi‐automated workflow that combines millimeter‐ to centimeter‐scale structure‐from‐motion (SfM) photogrammetry surveys of bed topography and computational fluid dynamics (CFD) simulations to better evaluate surface roughness and rapidly quantify flow resistance in mountain streams. The workflow was applied to three field sites of gravel, cobble, and boulder‐bedded channels with a wide range of grain size, sorting, and shape. Large‐eddy simulations with body‐fitted meshes generated from SfM photogrammetry‐derived surfaces were performed to quantify flow resistance. The analysis of bed microtopography using a second‐order structure function identified three scaling regimes that corresponded to important roughness length scales and surface complexity contributing to flow resistance. The standard deviation
- NSF-PAR ID:
- 10460810
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Earth Surface Processes and Landforms
- Volume:
- 44
- Issue:
- 10
- ISSN:
- 0197-9337
- Page Range / eLocation ID:
- p. 1973-1987
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Salmonids create an egg nest, called a redd, in hyporheic streambed gravel to bury their eggs, characterized by a pit and a hump topography, resembling a dune. Embryos' survival depends on downwelling oxygen‐rich stream water fluxes, influenced by the redd shape, stream hydraulics, and the hydraulic conductivity of the redd sediment,
K . We hypothesize that downwelling fluxes increase with stream discharge and redd aspect ratio (A R =A /L, withA, the redd amplitude andL, its length), and they can be predicted using a set of dimensionless numbers, which include the stream flow Reynolds (Re ) and Froude (Fr ) numbers,A R , and the redd relative submergence (A /Y 0 , withY 0 , the water depth). We address our goal by simulating the surface and subsurface flows with numerical hydraulic models linked through the near‐bed pressure distribution quantified with a two‐phase (air‐water) two‐dimensional surface water computational fluid dynamics model, validated with experiments. We apply the modeling approach to five redd sizes, which span the field observed range (from ∼1 to ∼4 m long), and by increasing discharge from shallow (0.1 m) and slow (0.15 m/s) to deep (8 m) and fast (3.3 m/s). Results confirm that downwelling fluxes increase with discharge and redd aspect ratio due to the increased near‐bed head gradient over the redd. Averaged downwelling fluxes are a function ofRe ,Fr ,A R , and hydraulic conductivity of the redd and not of the undisturbed streambed material. The derived regression equation may help evaluate regulated and unregulated flow impacts on hyporheic flows during embryo incubation. -
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Abstract Stream hydromorphology regulates in‐stream water flow and interstitial flow of water within streambed sediments, the latter known as hyporheic exchange. Whereas hyporheic flow has been studied in sand‐bedded streams with ripples and dunes and in gravel‐bedded streams with pool‐riffle morphology, little is known about its characteristics in plane bed morphology with subdued streambed undulations and sparse macroroughness elements such as boulders and cobbles. Here, we present a proof‐of‐concept investigation on the role of boulder‐induced morphological changes on hyporheic flows based on coupling large‐scale flume sediment transport experiments with computational fluid dynamics. Our results show that placement of boulders on plane beds increase the reach‐scale hyporheic median residence time,
τ 50, by 15% and downwelling flux,q d, by 18% from the plane bed. However, reach‐scale hyporheic exchange changes are stronger withτ 50decreasing by 20% andq dincreasing by 79% once the streambed morphology reached equilibrium (with the imposed upstream sediment and flow inputs on boulders). These results suggest that hyporheic flow is sensitive to the geomorphic response from bed topography and sediment transport in gravel‐bedded streams, a process that has been overlooked in previous work. -
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Abstract Estimates of the onset of sediment motion are integral for flood protection and river management but are often highly inaccurate. The critical shear stress (
τ * c ) for grain entrainment is often assumed constant, but measured values can vary by almost an order of magnitude between rivers. Such variations are typically explained by differences in measurement methodology, grain size distributions, or flow hydraulics, whereas grain resistance to motion is largely assumed to be constant. We demonstrate that grain resistance varies strongly with the bed structure, which is encapsulated by the particle height above surrounding sediment (protrusion,p ) and intergranular friction (ϕ f ). We incorporate these parameters into a novel theory that correctly predicts resisting forces estimated in the laboratory, field, and a numerical model. Our theory challenges existing models, which significantly overestimate bed mobility. In our theory, small changes inp andϕ f can induce large changes inτ * c without needing to invoke variations in measurement methods or grain size. A data compilation also reveals that scatter in empirical values ofτ * c can be partly explained by differences inp between rivers. Therefore, spatial and temporal variations in bed structure can partly explain the deviation ofτ * c from an assumed constant value. Given that bed structure is known to vary with applied shear stresses and upstream sediment supply, we conclude that a constantτ * c is unlikely. Values ofτ * c are not interchangeable between streams, or even through time in a given stream, because they are encoded with the channel history. -
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Synopsis Acquiring accurate 3D biological models efficiently and economically is important for morphological data collection and analysis in organismal biology. In recent years, structure-from-motion (SFM) photogrammetry has become increasingly popular in biological research due to its flexibility and being relatively low cost. SFM photogrammetry registers 2D images for reconstructing camera positions as the basis for 3D modeling and texturing. However, most studies of organismal biology still relied on commercial software to reconstruct the 3D model from photographs, which impeded the adoption of this workflow in our field due the blocking issues such as cost and affordability. Also, prior investigations in photogrammetry did not sufficiently assess the geometric accuracy of the models reconstructed. Consequently, this study has two goals. First, we presented an affordable and highly flexible SFM photogrammetry pipeline based on the open-source package OpenDroneMap (ODM) and its user interface WebODM. Second, we assessed the geometric accuracy of the photogrammetric models acquired from the ODM pipeline by comparing them to the models acquired via microCT scanning, the de facto method to image skeleton. Our sample comprised 15 Aplodontia rufa (mountain beaver) skulls. Using models derived from microCT scans of the samples as reference, our results showed that the geometry of the models derived from ODM was sufficiently accurate for gross metric and morphometric analysis as the measurement errors are usually around or below 2%, and morphometric analysis captured consistent patterns of shape variations in both modalities. However, subtle but distinct differences between the photogrammetric and microCT-derived 3D models could affect the landmark placement, which in return affected the downstream shape analysis, especially when the variance within a sample is relatively small. At the minimum, we strongly advise not combining 3D models derived from these two modalities for geometric morphometric analysis. Our findings can be indictive of similar issues in other SFM photogrammetry tools since the underlying pipelines are similar. We recommend that users run a pilot test of geometric accuracy before using photogrammetric models for morphometric analysis. For the research community, we provide detailed guidance on using our pipeline for building 3D models from photographs.
