
A two‐dimensional discrete particle model of gravel bed river systems
Author(s) -
MacVicar B. J.,
Parrott L.,
Roy A. G.
Publication year - 2006
Publication title -
journal of geophysical research: earth surface
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.67
H-Index - 298
eISSN - 2156-2202
pISSN - 0148-0227
DOI - 10.1029/2005jf000316
Subject(s) - bed load , bedform , geology , imbrication , turbulence , sediment , sediment transport , entrainment (biomusicology) , flow (mathematics) , geomorphology , hydraulics , geotechnical engineering , mechanics , hydrology (agriculture) , physics , paleontology , rhythm , acoustics , tectonics , thermodynamics
The formation of bed forms in gravel bed rivers acts as a control on stream ecology and the response of rivers to floods. Available models do not reproduce the range of observed bed forms and do not consider interactions between the bed and flow hydraulics. The model presented here considers a gravel bed river as a complex system in which sediment clasts are represented as discrete elements. Simple and local rules describe the sediment and flow dynamics. Using a trimodal sediment distribution, irregular forms that scale with particle diameter develop without explicit feedback mechanisms because of the tendency of large particles to roll along the bed surface and collect into chains. Feedback mechanisms such as imbrication increase the effective entrainment threshold of groups of large particles and increase the stability of these imbricate forms. A second type of bed form is associated with saltating grains and emerges where particles are transported at a preferred distance. The development and maintenance of larger‐scale bed forms require feedback between the bed and flow properties. By allowing mean velocity to adjust to bed morphology and considering the effect of acceleration on turbulence generation and mean velocity profiles we demonstrate the emergence of forms similar in morphology to gravel sheets, dunes, and riffle pools. The model is best used to complement field‐based studies and is suitable for testing hypotheses of streambed behavior.