Characterization of alluvial formation by stochastic modelling of paleo-fluvial processes: The concept and method
Data(s) |
01/05/2015
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Resumo |
Modelling fluvial processes is an effective way to reproduce basin evolution and to recreate riverbed morphology. However, due to the complexity of alluvial environments, deterministic modelling of fluvial processes is often impossible. To address the related uncertainties, we derive a stochastic fluvial process model on the basis of the convective Exner equation that uses the statistics (mean and variance) of river velocity as input parameters. These statistics allow for quantifying the uncertainty in riverbed topography, river discharge and position of the river channel. In order to couple the velocity statistics and the fluvial process model, the perturbation method is employed with a non-stationary spectral approach to develop the Exner equation as two separate equations: the first one is the mean equation, which yields the mean sediment thickness, and the second one is the perturbation equation, which yields the variance of sediment thickness. The resulting solutions offer an effective tool to characterize alluvial aquifers resulting from fluvial processes, which allows incorporating the stochasticity of the paleoflow velocity. |
Formato |
application/pdf |
Identificador | |
Publicador |
Elsevier BV |
Relação |
http://eprints.qut.edu.au/86568/1/Draft%20copy.pdf DOI:10.1016/j.jhydrol.2015.03.007 Jiang, Zhenjiao, Mariethoz, Gregoire, Farrell, Troy, Schrank, Christoph, & Cox, Malcolm (2015) Characterization of alluvial formation by stochastic modelling of paleo-fluvial processes: The concept and method. Journal of Hydrology, 524, pp. 367-377. |
Direitos |
Copyright 2015 Elsevier B.V. |
Fonte |
School of Earth, Environmental & Biological Sciences; School of Mathematical Sciences; Science & Engineering Faculty |
Palavras-Chave | #010299 Applied Mathematics not elsewhere classified #040310 Sedimentology #process-based model #alluvial reservoir #perturbation theory #spectral methods |
Tipo |
Journal Article |