The last half a century has seen more and more developments and applications of mathematical models for fluvial flow, sediment transport and morphological evolution. However, the quality of this modelling practice has emerged as a crucial issue for concern, which is widely viewed as the key that could unlock the full potential of computational fluvial hydraulics. The major factors affecting the modelling quality comprise: (a) poor assumptions in model formulations; (b) simplified numerical solution procedure; (c) the implementation of sediment relationships of questionable validity; and (d) the problematic use of model calibration and verification as assertions of model veracity. An overview of mathematical models for alluvial rivers is provided in this and the companion paper ‘Part 1: General review’. This paper is the second part, dealing with three special issues of mathematical river models. First, turbulence closure models are highlighted, particularly with respect to the role of sediment in modulating turbulence and its implications for adapting turbulence closure models for fluvial sediment-laden flows. Second, the bottom boundary conditions are discussed in detail as one of the main sources of model uncertainty. And third, the commonly used calibration and verification/validation methodology in mathematical river modelling is addressed. It is argued that model calibration can be subjective, verification is impossible because models are not closed systems, and validation does not necessarily establish model truth. Confirmation of observations by models only supports model probability, rather than demonstrating model veracity. It is vital for model developers and end-users to keep aware of what mathematical river models can realistically reflect, and therefore avoid misleading decision-making. Additionally, some strategies are proposed which can improve the practice of mathematical river modelling.
Article navigation
December 2002
Research Article|
December 01 2002
Mathematical modelling of alluvial rivers: reality and myth. Part 2: Special issues
Z. Cao;
Z. Cao
Professor and Director
Institute of Hydraulic Research, Tianjin University, China; presently Department of Geography, University of Southampton
Search for other works by this author on:
P. A. Carling
P. A. Carling
Professor
Department of Geography, University of Southampton
Search for other works by this author on:
Publisher: Emerald Publishing
Received:
November 12 2001
Accepted:
December 07 2001
Online ISSN: 1753-7800
Print ISSN: 1472-4561
© 2002 Thomas Telford Ltd
2002
Proceedings of the Institution of Civil Engineers - Water and Maritime Engineering (2002) 154 (4): 297–307.
Article history
Received:
November 12 2001
Accepted:
December 07 2001
Citation
Cao Z, Carling PA (2002), "Mathematical modelling of alluvial rivers: reality and myth. Part 2: Special issues". Proceedings of the Institution of Civil Engineers - Water and Maritime Engineering, Vol. 154 No. 4 pp. 297–307, doi: https://doi.org/10.1680/wame.2002.154.4.297
Download citation file:
Suggested Reading
Large-scale morphodynamic modelling of the Gironde estuary, France
Maritime Engineering (June,2013)
Predicting flow rate and sediment in bifurcated river branches
Proceedings of the Institution of Civil Engineers - Water Management (July,2015)
Variable input parameter influence on river corridor prediction
Proceedings of the Institution of Civil Engineers - Water Management (December,2014)
Method for assessing discharge in meandering compound channels
Proceedings of the Institution of Civil Engineers - Water Management (March,2015)
Effects of a diversion dyke on river flow: a case study
Proceedings of the Institution of Civil Engineers - Water Management (December,2014)
Related Chapters
Steady uniform flow in open channels
ICE Core Concepts: Hydraulics for Civil Engineers
Open-channel flow with varying conditions
ICE Core Concepts: Hydraulics for Civil Engineers
Building a resilient system of defence against flooding from the Rhône
ICE Themes Flood Resilience
Recommended for you
These recommendations are informed by your reading behaviors and indicated interests.
