Video observations of bed form morphodynamics in a meander bend

Abstract

A new optical remote sensing technique for estimating water depth from an oblique camera view is described. The water surface and the bed were imaged simultaneously to create time-dependent maps of the water surface velocities and the bed elevations that can be used to validate numerical models at high spatial and temporal resolution. The technique was applied in a sandy meander bend at the University of Minnesota Saint Anthony Falls Laboratory Outdoor StreamLab. The root mean square differences between optical estimates of the bed and in situ observations ranged between 0.01 and 0.03 m. Mean bed form wavelength was 0.73 m and mean crest height was 0.07 m, but both varied with distance around the meander bend. Bed form classification varied with distance downstream, and sinuosity of bed forms varied with local radius of curvature. Bed form roughness scaled similarly to other natural riverine environments although wavelength and height magnitude and variability were larger than predicted by empirical formulations for straight reaches. Bed form translation rate varied between 1 and 5 mm s 21 . Estimates of velocity from particle image velocimetry (PIV) on the water surface were $10% higher than in situ observations collected $0.05 m below the water surface. Using the PIV observations to drive simple equations for bed load sediment flux, we explained up to 72% of the observed variance in downstream sediment flux. The new methodology described here provides nonintrusive, high spatial and temporal resolution measurements of both the bed and the flow.

Medium-term dynamics of a middle Adriatic barred beach

“…Although global reanalysis or numerical modeling may provide a more detailed wave characterization, use of available regional climate models (e.g., The Medatlas Group, 2004) is easier and may represent a valid alternative. Further, the dynamics of the nearshore area before, during and after storm events could also be inspected by means of novel devices like: (i) Lagrangian drifters, capable of measuring both three-dimensional hydrodynamics and seabed depth (e.g., Postacchini et al, 2016a), (ii) videomonitoring systems, like that available at the Senigallia harbor since 2015, to reconstruct the coastline (e.g., Archetti, 2009;Vousdoukas et al, 2011;Archetti et al, 2016), as well as wave field and bed morphology (e.g., Palmsten et al, 2015) and (iii) radar images, like those used for the reconstruction of both wave field and bathymetry, through the depth inversion technique (e.g., Ludeno et al, 2015).…”

Physical complexity to model morphological changes at a natural channel bend

“…These questions are far from being answered in existing studies. Moreover, some studies [e.g., Bohorquez et al ., ; Palmsten et al ., ] reported that bed form as ripples and dunes in river bends can increase the effective roughness height and total shear stress at both lab and field scales. It should be noted that in turn this can further affect hydrodynamics and morphodynamics at the bend.…”

Quantification of bedform dynamics and bedload sediment flux in sandy braided rivers from airborne and satellite imagery

“…The use of UAVs and aerial images has improved our ability to quantify the spatial organisation of river relief and bed roughness (Williams et al, 2014;Dietrich, 2016;James et al, 2017;Carbonneau et al, 2018), to track morphological change over short time periods (Lane et al, 1996(Lane et al, , 2010Palmsten et al, 2015) and to infer sediment transport rates (Lane et al, 1995;Brasington et al, 2003;Vericat et al, 2017). However, a number of outstanding challenges remain.…”