Characterization of Bed Morphodynamics Using Multibeam Echo Sounding (MBES) and Wavelet Transform (WT) Analysis

Abstract

The overall objectives of this project are as follows: Application of the Wavelet Transform (WT) technique in the spatial domain to characterize the spatial distribution of co-existing bedforms of multiple dimensions generated under different flow field scenarios (waves, unidirectional flows and combined flows). Demonstrate the applicability of WT analysis for the description of bedforms frequently found in coastal and river environments. An improved description of bed features and their interactions will certainly contribute to a more complete understanding of theories describing bedform formation and evolution. Improve overall understanding of small and large scale features, which is especially important because of their strong implications for the associated patterns of bed roughness characteristics, flow resistance and sediment transport. Describe the hydrodynamic interaction of multiple sized bedforms and, conversely, the bed morphology given averaged hydrodynamic parameters; this approach could be used to develop and validate numerical approaches that will allow detailed examination of associated hydrodynamic and morphological conditions at inlets and river mouths.

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Document Details

Document Type
Technical Report
Publication Date
Sep 30, 2013
Accession Number
ADA597709

Entities

People

  • James L. Best
  • Marcelo H. García

Organizations

  • University of Illinois Urbana–Champaign

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Acoustic Measurement
  • Boundary Layer
  • Civil Engineering
  • Coastal Engineering
  • Data Sets
  • Engineering
  • Engineers
  • Environmental Engineering
  • Flow Fields
  • Fluid Dynamics
  • Great Lakes
  • Missouri River
  • Sedimentation
  • Sonar
  • Spatial Distribution
  • Standing Waves
  • Wavelet Transforms

Fields of Study

  • Environmental science

Readers

  • Coastal Oceanography
  • Computer Vision.