10. The Potential of Using High-Resolution Process Models to Inform Parameterizations of Morphodynamic Models

  1. Michael Church2,
  2. Pascale M. Biron3 and
  3. André G. Roy4
  1. Richard J. Hardy

Published Online: 17 FEB 2012

DOI: 10.1002/9781119952497.ch10

Gravel-Bed Rivers: Processes, Tools, Environments

Gravel-Bed Rivers: Processes, Tools, Environments

How to Cite

Hardy, R. J. (2012) The Potential of Using High-Resolution Process Models to Inform Parameterizations of Morphodynamic Models, in Gravel-Bed Rivers: Processes, Tools, Environments (eds M. Church, P. M. Biron and A. G. Roy), John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9781119952497.ch10

Editor Information

  1. 2

    Department of Geography, The University of British Columbia, Vancouver, British Columbia, Canada

  2. 3

    Department of Geography, Planning and Environment, Concordia University, Montreal, Quebec, Canada

  3. 4

    Département de géographie, Université de Montréal, Montréal, Québec, Canada

Author Information

  1. Department of Geography, Durham University, Durham, UK

Publication History

  1. Published Online: 17 FEB 2012
  2. Published Print: 20 JAN 2012

ISBN Information

Print ISBN: 9780470688908

Online ISBN: 9781119952497

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Keywords:

  • Computational fluid dynamics;
  • discrete particle models;
  • Exner equation

Summary

In many current morphodynamic models there is considerable process simplification and averaging. Such models are highly dependent on arbitrary parameterization and such limitations prevent both the complexity of the system and the feedback between processes being accurately represented. It is suggested here that an improvement in the empirical transport relations used in the morphodynamic modelling of gravel-bed rivers can potentially be derived from a combined computational fluid dynamics approach linked with a discrete particle model. It is proposed that this form of model, used under different hydraulic conditions and sediment particle characteristics, could provide process informed ranges of particle size-specific entrainment, transport and deposition characteristics which can be encapsulated in a probability distribution. Such process information could then be used to improve spatial and/or temporal parameterizations of reach-length morphodynamic models.