Effects of LiDAR-derived, spatially distributed vegetation roughness on two-dimensional hydraulics in a gravel-cobble river at flows of 0.2 to 20 times bankfull

Abu-Aly, T. R.; Pasternack, G. B.; Wyrick, J. R.; Barker, R.; Massa, Derck; Johnson, Thomas R.

doi:10.1016/j.geomorph.2013.10.017

Cited by 72 publications

(83 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…A potential area where the edge-blocking method might be expanded is in the estimation of topographic roughness, which has been a subject of extensive prior research (e.g., Abu-Aly et al, 2014;Casas et al, 2010;Dorn et al, 2014;Forzieri et al, 2011;Straatsma and Baptist, 2008). By defining edge features, a portion of the difference between the grid cell elevation and subgrid features can be removed from the roughness estimation; i.e., we could use, for example, G xx , G yy , H xx , and H yy to remove pixels that have been resolved in to edge features and only consider the remaining pixels in a coarse-grid cell as contributing to roughness.…”

Section: Discussionmentioning

confidence: 99%

Representing hydrodynamically important blocking features in coastal or riverine lidar topography

Hodges

2015

Nat. Hazards Earth Syst. Sci.

View full text Add to dashboard Cite

Abstract. New automated methods are developed for identifying narrow landscape features that cause hydrodynamic blocking and might have critical impacts for management models of river flooding, coastal inundation, climate change, or extreme event analysis. Lidar data processed into a fineresolution raster (1 m × 1 m) can resolve narrow blocking features in topography but typically cannot be directly used for hydrodynamic modeling. For practical applications such data are abstracted to larger scales, which can result in a loss of hydrodynamic blocking effects. The traditional approach to resolving hydrodynamic blocking features is to represent them as cell boundaries within a customized unstructured grid that is tuned to the spatial features. A new automated edge-blocking approach is developed, which allows application of an arbitrarily structured (Cartesian) mesh at coarser scales and provides contiguous representation of blocking features along Cartesian cell boundaries. This approach distorts the shape of a blocking feature (i.e., making it rectilinear along grid cell faces) but retains its critical hydrodynamic blocking height characteristics and spatial continuity within the topographic model.

show abstract

Section: Discussionmentioning

confidence: 99%

Representing hydrodynamically important blocking features in coastal or riverine lidar topography

Hodges

2015

Nat. Hazards Earth Syst. Sci.

View full text Add to dashboard Cite

show abstract

“…Secondly, as a result of shallow depths and large bedforms, calibration would demand simultaneous consideration of topographic data and resistance parameters (e.g., Yan et al, 2015b), and here both are spatially distributed fields leading to a massive number of unknown parameters. In applications that are supported by a spatial classification of land cover (e.g., Schubert et al, 2008;Abu-Aly et al, 2014), the number of calibration parameters can be reduced to the number of landcover classes but such information was not available at this site at an adequate resolution to discern between features such as channels and islands, and even if it were, the issue of calibrating uncertain topography remains. Third, models require lengthy computation times.…”

Section: Flow Simulationmentioning

confidence: 99%

“…But today, it is more common to access a river DTM than cross-sectional data, and popular one-dimensional modeling software such as HEC-RAS (US Army Corps of Engineers, Davis, California) is configured to compute transect data from DEMs using tools such as HEC GeoRAS (US Army Corps of Engineers, Davis, California). The increased availability of river DEMs has also enabled multi-dimensional hydrodynamic river modeling (both 2D and 3D) for numerous applications including studies of morphodynamics (Lane et al, 1999;Abu-Aly et al, 2014), ecology (Crowder and Diplas, 2000;Shen and Diplas, 2008), and flood risk (Sanders, 2007;Bates, 2012;Yan et al, 2015a). Indeed, multi-dimensional hydrodynamic river models offer exciting new opportunities to examine the complexity of river dynamics at fine scale and over spatial extents of practical significance .…”

Section: Introductionmentioning

confidence: 99%

“…High computational costs have generally limited the application of metric resolution models to the mesoscale defined by small multiples of the river width (e.g., Crowder and Diplas, 2000), although there have been a few applications at the macroscale defined by large multiples of the river width (e.g., Abu-Aly et al, 2014;Yan et al, 2015b). Macroscale hydrodynamic modeling is also somewhat common with a grid resolution of tens, hundreds or even thousands of meters, sometimes using sub-grid models to account for channel flows (e.g., Neal et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

“…Dottori et al (2013) caution that the cost of fine-resolution analysis may not be justified for flood inundation modeling, where the main goal is to predict flood stage and flood extent, given other sources of uncertainty. However, a number of researchers have found that a metric resolution is needed to reasonably approximate hydraulic habitat, i.e., local depth and velocity, which is relevant to river ecology and morphology (Crowder and Diplas, 2000;Cook and Merwade, 2009;Clifford et al, 2010;Williams et al, 2013;Abu-Aly et al, 2014). Furthermore, with the aid of analytical models for the vertical velocity distribution including a characterization of bed roughness, metric-resolution 2D models can reconstruct a 3D characterization of flow for a wide range of applications at far less computational expense than 3D models based on the Navier-Stokes equations (Begnudelli et al, 2010;Abu-Aly et al, 2014;Wyrick et al, 2014), although there are many examples of 3D flow phenomena that demand 3D models for an accurate description such as horseshoe vortices around bridge piers and similarly complex turbulent velocity fluctuations occurring around boulders, large bed forms, and other types of flow obstructions (Wu, 2007;Javernick et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Metric-Resolution 2D River Modeling at the Macroscale: Computational Methods and Applications in a Braided River

2015

View full text Add to dashboard Cite

Metric resolution digital terrain models (DTMs) of rivers now make it possible for multi-dimensional fluid mechanics models to be applied to characterize flow at fine scales that are relevant to studies of river hydraulic geometry (HG) and ecological habitat, or microscales. These developments are important for managing rivers because of the potential to better understand system dynamics, anthropogenic impacts, and the consequences of proposed interventions. However, the data volumes and computational demands of microscale river modeling have largely constrained applications to small multiples of the channel width, or the mesoscale. This report presents computational methods to extend a microscale river model beyond the mesoscale to the macroscale, defined as large multiples of the channel width. A method of automated unstructured grid generation is presented that automatically clusters fine resolution cells in areas of curvature (e.g., channel banks), and places relatively coarse cells in areas lacking topographic variability. This overcomes the need to manually generate breaklines to constrain the grid, which is painstaking at the mesoscale and virtually impossible at the macroscale. The method is applied to a braided river (BR) and shown to yield an efficient fine resolution model. The sensitivity of model output to grid design and resistance parameters is also examined based on analysis of hydrology, HG, and river hydraulic habitats and the findings reiterate the importance of model calibration and validation.

show abstract

Modeling complex flow structures and drag around a submerged plant of varied posture

Boothroyd

Hardy

Warburton

et al. 2017

Water Resources Research

View full text Add to dashboard Cite

Although vegetation is present in many rivers, the bulk of past work concerned with modeling the influence of vegetation on flow has considered vegetation to be morphologically simple and has generally neglected the complexity of natural plants. Here we report on a combined flume and numerical model experiment which incorporates time‐averaged plant posture, collected through terrestrial laser scanning, into a computational fluid dynamics model to predict flow around a submerged riparian plant. For three depth‐limited flow conditions (Reynolds number = 65,000–110,000), plant dynamics were recorded through high‐definition video imagery, and the numerical model was validated against flow velocities collected with an acoustic Doppler velocimeter. The plant morphology shows an 18% reduction in plant height and a 14% increase in plant length, compressing and reducing the volumetric canopy morphology as the Reynolds number increases. Plant shear layer turbulence is dominated by Kelvin‐Helmholtz type vortices generated through shear instability, the frequency of which is estimated to be between 0.20 and 0.30 Hz, increasing with Reynolds number. These results demonstrate the significant effect that the complex morphology of natural plants has on in‐stream drag, and allow a physically determined, species‐dependent drag coefficient to be calculated. Given the importance of vegetation in river corridor management, the approach developed here demonstrates the necessity to account for plant motion when calculating vegetative resistance.

show abstract

Effects of LiDAR-derived, spatially distributed vegetation roughness on two-dimensional hydraulics in a gravel-cobble river at flows of 0.2 to 20 times bankfull

Cited by 72 publications

References 36 publications

Representing hydrodynamically important blocking features in coastal or riverine lidar topography

Representing hydrodynamically important blocking features in coastal or riverine lidar topography

Metric-Resolution 2D River Modeling at the Macroscale: Computational Methods and Applications in a Braided River

Modeling complex flow structures and drag around a submerged plant of varied posture

Contact Info

Product

Resources

About