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Use of a genetic algorithm to improve predictions of alternate bar dynamics

Record type: Article

Alternate bars may form in sandy beds of straight rivers and channels. These bars are characterized by the alternation of crests, all moving downstream at a speed of several meters per day. The aim of this paper is to predict the dynamics of alternate bars. To that end, we tested predictions of measured alternate bars in flume experiments, as derived from an amplitude evolution model. Weakly nonlinear stability analysis underlies this amplitude evolution model, so that it applies to situations in which the width-to-depth ratio is close to the critical ratio, above which alternate bars occur. The experiments have a width-to-depth ratio far above the critical value, well outside the range of formal validity of the model. While wavelengths and heights of the alternate bars are still well predicted, we found that the migration rate is not: the amplitude evolution model produces an underestimation of close to a factor of two. Therefore we took a slightly different approach. We tested the predictive capability for this amplitude evolution model by using a genetic algorithm to tune the model to bathymetric data. After tuning, the model is indeed able to predict the migration rate of the bars over periods that exceed the tuning period by far. Limits to the prediction time, i.e., failure of this method, could not be derived for the data sets used in this work.

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Citation

Knaapen, M.A.F. and Hulscher, S.J.M.H. (2003) Use of a genetic algorithm to improve predictions of alternate bar dynamics Water Resources Research, 39, (9), Art.1231. (doi:10.1029/2002WR001793).

More information

Published date: 2003
Keywords: morphology, alternate bars, data assimilation, genetic, algorithm, optimization, modeling, irregular bed forms, rough channels, circulation, sediment, river
Organisations: Ocean and Earth Science, Civil Engineering & the Environment

Identifiers

Local EPrints ID: 27820
URI: http://eprints.soton.ac.uk/id/eprint/27820
ISSN: 0043-1397
PURE UUID: 8bfebd32-bfcd-4d8e-8ade-c3bef4f43e91

Catalogue record

Date deposited: 28 Apr 2006
Last modified: 17 Jul 2017 16:03

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