Literature DB >> 22474678

Modelling river history and evolution.

T J Coulthard1, M J Van de Wiel.   

Abstract

Over the last few decades, a suite of numerical models has been developed for studying river history and evolution that is almost as diverse as the subject of river history itself. A distinction can be made between landscape evolution models (LEMs), alluvial architecture models, meander models, cellular models and computational fluid dynamics models. Although these models share some similarities, there also are notable differences between them, which make them more or less suitable for simulating particular aspects of river history and evolution. LEMs embrace entire drainage basins at the price of detail; alluvial architecture models simulate sedimentary facies but oversimplify flow characteristics; and computational fluid dynamics models have to assume a fixed channel form. While all these models have helped us to predict erosion and depositional processes as well as fluvial landscape evolution, some areas of prediction are likely to remain limited and short-term owing to the often nonlinear response of fluvial systems. Nevertheless, progress in model algorithms, computing and field data capture will lead to greater integration between these approaches and thus the ability to interpret river history more comprehensively. This journal is
© 2012 The Royal Society

Year:  2012        PMID: 22474678     DOI: 10.1098/rsta.2011.0597

Source DB:  PubMed          Journal:  Philos Trans A Math Phys Eng Sci        ISSN: 1364-503X            Impact factor:   4.226


  2 in total

1.  Mega riverbed-patterns: linear and weakly nonlinear perspectives.

Authors:  Sk Zeeshan Ali; Subhasish Dey; Rajesh K Mahato
Journal:  Proc Math Phys Eng Sci       Date:  2021-08-11       Impact factor: 2.704

2.  The third dimension in river restoration: how anthropogenic disturbance changes boundary conditions for ecological mitigation.

Authors:  Martin Guzelj; Christoph Hauer; Gregory Egger
Journal:  Sci Rep       Date:  2020-08-04       Impact factor: 4.379

  2 in total

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