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dc.contributor.authorWilliams, RDen_US
dc.contributor.authorBrasington, Jen_US
dc.contributor.authorHicks, DMen_US
dc.description.abstract© 2016 The Author(s) Geography Compass © 2016 John Wiley & Sons Ltd Numerical morphological modelling of braided rivers is increasingly used to explore controls on river pattern and for applied environmental management. This article reviews and presents a taxonomy of braided river morphodynamic models and discusses the challenges facing model development and use, illustrating these challenges with a case example. The taxonomy is contextualised by an initial discussion of the physical mechanisms of braiding. The taxonomy differentiates between reach-scale and catchment-scale models. Reach-scale models are usually physics-based, which are further divided based upon the mathematical approach used to solve equations (analytical or numerical) and their dimensionality (1D, 2D or 3D). Cellular automata models are one type of numerical model that replace at least some physical processes with expedient rules. A 2D physics-based approach encapsulates sufficient process complexity to provide behavioural predictions. Predictions from catchment-scale landscape evolution models have potential for providing boundary conditions. Future progress in physics-based modelling needs to address three challenges: (i) representation of flow and sediment transport; (ii) temporal and spatial scaling; and (iii) model calibration, sensitivity, uncertainty and validation. The key problem for addressing these is the dearth of laboratory or natural experiment datasets. To show that progress can be made by comparing reach-scale predictions to high-resolution observations, a case study of monitoring and modelling, conducted in the Rees River, New Zealand, is presented. Hydraulic predictions of cellular automata and shallow water equation (Delft3d) models are compared to observed inundation extent. The efficacy of high-resolution, multi-temporal morphological data for assessing 2D physics-based morphodynamic model predictions is also demonstrated.en_US
dc.format.extent102 - 127en_US
dc.relation.ispartofGeography Compassen_US
dc.titleNumerical Modelling of Braided River Morphodynamics: Review and Future Challengesen_US
dc.rights.holder2016. The authors
pubs.notesNot knownen_US
qmul.funderFrom Point Clouds to Processes: multidimensional models of river forms and flows::Leverhulme Trusten_US

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