Publication Date:
2015-07-29
Description:
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 bedform wavelength was 0.73 m and mean crest height was 0.07 m, but both varied with distance around the meander bend. Bedform classification varied with distance downstream, and sinuosity of bedforms varied with local radius of curvature. Bedform 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. Bedform translation rate varied between 1 and 5 mm s −1 . 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 bedload sediment flux, we explained up to 72% of the observed variance in downstream sediment flux. The new methodology described here provides non-intrusive, high spatial and temporal resolution measurements of both the bed and the flow. This article is protected by copyright. All rights reserved.
Print ISSN:
0043-1397
Electronic ISSN:
1944-7973
Topics:
Architecture, Civil Engineering, Surveying
,
Geography
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