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Earth Surface Dynamics An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/esurf-2019-38
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esurf-2019-38
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 19 Aug 2019

Submitted as: research article | 19 Aug 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Earth Surface Dynamics (ESurf).

Estimating Sand Bedload in Rivers by Tracking Dunes: a comparison of methods based on bed elevation time-series

Kate C. P. Leary1,2 and Daniel Buscombe3 Kate C. P. Leary and Daniel Buscombe
  • 1Department of Geography, University of California Santa Barbara, Santa Barbara, CA, USA
  • 2Department of Earth and Environment Sciences, New Mexico Tech, Socorro, NM, USA
  • 3Sch. Earth Sciences & Environmental Sustainability, Northern Arizona University, Flagstaff, USA, AZ

Abstract. Quantifying bedload transport is paramount to the effective management of rivers with sand or gravel-dominated bed material. However, a practical and scalable field methodology for reliably estimating bedload remains elusive. A popular approach involves calculating transport from the geometry and celerity of migrating bedforms, extracted from time-series of bed elevation profiles acquired using echosounders. Various echosounder sampling methodologies of how to extract bed elevations profiles exist. Using two sets of repeat multibeam sonar surveys with large spatio-temporal resolution and coverage, we compute bedload using three field techniques (one actual and two simulated) for acquiring bed elevation profiles: repeat multi-, single-, and multiple single-beam sonar. Significant differences in flux arise between repeat multibeam and single beam sonar. Mulitbeam and multiple single beam sonar systems can potentially yield comparable results, but the latter relies on knowledge of bedform geometries and flow that collectively inform optimal beam spacing and sampling rate. These results serve to guide design of optimal sampling, and for comparing transport estimates from different sonar configurations.

Kate C. P. Leary and Daniel Buscombe
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Kate C. P. Leary and Daniel Buscombe
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Diamond Creek Repeat Multibeam Data K. Leary https://doi.org/10.5967/M02J6904

Kate C. P. Leary and Daniel Buscombe
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