Particle Size by Proxy: Decoding the Textural Information in Scattered Sound and Light

Particle Size by Proxy: Decoding the Textural Information in Scattered Sound and Light

Utah State University Water Hydraulics Lab Seminar, 3/14/2017

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Daniel Buscombe

March 14, 2017
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  1. 14 March 2017 Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17

    1/28 1/28
  2. Measuring Particle Size • Traditional particle size analysis by direct

    means (from physical samples) at relatively few discrete locations. Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 2/28 2/28
  3. Measuring Particle Size • Traditional particle size analysis by direct

    means (from physical samples) at relatively few discrete locations. • Accurate, high resolution Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 2/28 2/28
  4. Measuring Particle Size • Traditional particle size analysis by direct

    means (from physical samples) at relatively few discrete locations. • Accurate, high resolution • Costly, slow Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 2/28 2/28
  5. Measuring Particle Size • Traditional particle size analysis by direct

    means (from physical samples) at relatively few discrete locations. • Accurate, high resolution • Costly, slow • Intrusive/Destructive Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 2/28 2/28
  6. Measuring Particle Size • Traditional particle size analysis by direct

    means (from physical samples) at relatively few discrete locations. • Accurate, high resolution • Costly, slow • Intrusive/Destructive • Impossible? Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 2/28 2/28
  7. Measuring Particle Size • Traditional particle size analysis by direct

    means (from physical samples) at relatively few discrete locations. • Accurate, high resolution • Costly, slow • Intrusive/Destructive • Impossible? • Unachievable resolution? Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 2/28 2/28
  8. Bottom-Up • Particle size → settling velocity • Particle size

    → flow velocity at deposition • Particle size → hydraulic roughness • Particle size → habitat suitability • Particle size → moisture retention • → = model (bottom-up, apply to > grain scale) Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 3/28 3/28
  9. Bottom-Up: Particle size → settling velocity • Cuttler, Buscombe et

    al. (2016), Sedimentology • Depending on particle size analysis method, might mispredict transport mode Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 4/28 4/28
  10. Top-Down • Inferring particle size from remotely sensed signals •

    Monitoring continuously over space and/or time with lower accuracy • Tracking big sedimentary changes at unprecedented scales and resolutions • Track changes in particle size as landforms evolve Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 5/28 5/28
  11. Measuring Particle Size ‘by Proxy’ • Particle size analysis from

    by indirect means (usually remotely sensed). • Continuous in space/time Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 6/28 6/28
  12. Measuring Particle Size ‘by Proxy’ • Particle size analysis from

    by indirect means (usually remotely sensed). • Continuous in space/time • Less costly, fast Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 6/28 6/28
  13. Measuring Particle Size ‘by Proxy’ • Particle size analysis from

    by indirect means (usually remotely sensed). • Continuous in space/time • Less costly, fast • Non-intrusive/destructive Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 6/28 6/28
  14. Measuring Particle Size ‘by Proxy’ • Particle size analysis from

    by indirect means (usually remotely sensed). • Continuous in space/time • Less costly, fast • Non-intrusive/destructive • Develop proxies Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 6/28 6/28
  15. Measuring Particle Size ‘by Proxy’ • Particle size analysis from

    by indirect means (usually remotely sensed). • Continuous in space/time • Less costly, fast • Non-intrusive/destructive • Develop proxies • Requisite resolution? Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 6/28 6/28
  16. Today’s Talk • Substrate particle size through scattering of sound

    ◦ using high-frequency sound to classify riverbed substrates continuously in space ◦ 165 km Colorado River in Grand Canyon at 25 cm resolution Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 7/28 7/28
  17. Today’s Talk • Substrate particle size through scattering of sound

    ◦ using high-frequency sound to classify riverbed substrates continuously in space ◦ 165 km Colorado River in Grand Canyon at 25 cm resolution • Suspended particle size through scattering of light and sound ◦ using holography to classify surf zone suspensions continuously in time ◦ using this to better understand acoustics of complicated suspensions Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 7/28 7/28
  18. Particle Size By Sound Scattering Buscombe et al. (2014a,b) JGR

    - Earth Surface Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 8/28 8/28
  19. Particle Size By Sound Scattering Buscombe et al. (2014a,b) JGR

    - Earth Surface Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 8/28 8/28
  20. Particle Size By Sound Scattering Buscombe et al. (2014a,b) JGR

    - Earth Surface Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 9/28 9/28
  21. Particle Size By Sound Scattering Daniel Buscombe. dbuscombe@nau.edu Utah State

    University, 3/14/17 9/28 9/28
  22. LOBOS Video System Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17

    10/28 10/28
  23. ‘Morphological’ & ‘Compositional’ Backscatter I Daniel Buscombe. dbuscombe@nau.edu Utah State

    University, 3/14/17 11/28 11/28
  24. ‘Morphological’ & ‘Compositional’ Backscatter I Daniel Buscombe. dbuscombe@nau.edu Utah State

    University, 3/14/17 11/28 11/28
  25. ‘Morphological’ & ‘Compositional’ Backscatter II Daniel Buscombe. dbuscombe@nau.edu Utah State

    University, 3/14/17 12/28 12/28
  26. ‘Morphological’ & ‘Compositional’ Backscatter II Daniel Buscombe. dbuscombe@nau.edu Utah State

    University, 3/14/17 12/28 12/28
  27. Unvegetated Sand-Gravel-Cobble-Boulders Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 13/28

    13/28
  28. Application to Sediment Studies in Grand Canyon 1. Hydraulic and

    sediment transport models (sediment routing model, rating curves) Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 14/28 14/28
  29. Application to Sediment Studies in Grand Canyon 1. Hydraulic and

    sediment transport models (sediment routing model, rating curves) 2. HFE evaluation Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 14/28 14/28
  30. Application to Sediment Studies in Grand Canyon 1. Hydraulic and

    sediment transport models (sediment routing model, rating curves) 2. HFE evaluation 3. Sediment budgeting Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 14/28 14/28
  31. Application to Sediment Studies in Grand Canyon 1. Hydraulic and

    sediment transport models (sediment routing model, rating curves) 2. HFE evaluation 3. Sediment budgeting 4. Physical habitats Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 14/28 14/28
  32. Marble and Grand Canyon Substrate Classification Daniel Buscombe. dbuscombe@nau.edu Utah

    State University, 3/14/17 15/28 15/28
  33. Marble and Grand Canyon Substrate Classification Daniel Buscombe. dbuscombe@nau.edu Utah

    State University, 3/14/17 15/28 15/28
  34. Time-series of bed composition Daniel Buscombe. dbuscombe@nau.edu Utah State University,

    3/14/17 16/28 16/28
  35. Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 17/28 17/28

  36. Vegetated Gravel-Cobble-Boulders Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 18/28

    18/28
  37. Vegetated Gravel-Cobble-Boulders Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 18/28

    18/28
  38. Application to Ecological Studies in Glen Canyon 1. Submerged (nuisance)

    aquatic vegetation Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 19/28 19/28
  39. Application to Ecological Studies in Glen Canyon 1. Submerged (nuisance)

    aquatic vegetation 2. Hydraulic models Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 19/28 19/28
  40. Application to Ecological Studies in Glen Canyon 1. Submerged (nuisance)

    aquatic vegetation 2. Hydraulic models 3. Physical habitats, foodbase, ecological drivers Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 19/28 19/28
  41. Glen Canyon Substrate Classification Daniel Buscombe. dbuscombe@nau.edu Utah State University,

    3/14/17 20/28 20/28
  42. Glen Canyon Substrate Classification Daniel Buscombe. dbuscombe@nau.edu Utah State University,

    3/14/17 20/28 20/28
  43. Glen Canyon Substrate Classification Daniel Buscombe. dbuscombe@nau.edu Utah State University,

    3/14/17 20/28 20/28
  44. Glen Canyon Substrate Classification Daniel Buscombe. dbuscombe@nau.edu Utah State University,

    3/14/17 20/28 20/28
  45. The Future of Substrate Acoustics Daniel Buscombe. dbuscombe@nau.edu Utah State

    University, 3/14/17 21/28 21/28
  46. The Future of Substrate Acoustics Daniel Buscombe. dbuscombe@nau.edu Utah State

    University, 3/14/17 21/28 21/28
  47. The Future of Substrate Acoustics Daniel Buscombe. dbuscombe@nau.edu Utah State

    University, 3/14/17 21/28 21/28
  48. Suspended Particle Characterization By Sound Scattering Daniel Buscombe. dbuscombe@nau.edu Utah

    State University, 3/14/17 22/28 22/28
  49. Suspended Particle Characterization By Sound Scattering • Viable means for

    continuous monitoring of suspensions • Decades of research for simple sediment • How well dœs it work in the ‘real world’? (flocs, bubbles, organisms) Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 22/28 22/28
  50. 2. Particle Size By Light Scattering Davies, Buscombe et al

    (2014) J. Atmos. & Oceanographic Tech. Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 23/28 23/28
  51. 2. Particle Size By Light Scattering Davies, Buscombe et al

    (2014) J. Atmos. & Oceanographic Tech. Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 23/28 23/28
  52. Particle Holography Davies, Buscombe et al (2014) J. Atmos. &

    Oceanographic Tech. Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 24/28 24/28
  53. Particle Holography Davies, Buscombe et al (2014) J. Atmos. &

    Oceanographic Tech. Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 24/28 24/28
  54. Particle Size: Light vs. Sound Scattering Buscombe et al. (in

    prep) JGR - Oceans Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 25/28 25/28
  55. The Future of Suspended ‘Particle’ Characterization Daniel Buscombe. dbuscombe@nau.edu Utah

    State University, 3/14/17 26/28 26/28
  56. Concluding Remarks 1. We can continue to make advances in

    measuring particle size of submerged sediment by studying the interactions of particles with sound and light Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 27/28 27/28
  57. Concluding Remarks 2. By trading accuracy/precision for coverage (space &

    time), we can tease out the two-way feedbacks between particle size and fluids as landforms evolve Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 27/28 27/28
  58. Concluding Remarks 3. Biological-physical benthic interactions in rivers, lakes and

    seas Daniel Buscombe. dbuscombe@nau.edu Utah State University, 3/14/17 27/28 27/28
  59. Thanks for Listening dbuscombe dbuscombe-usgs Daniel Buscombe. dbuscombe@nau.edu Utah State

    University, 3/14/17 28/28 28/28