MODELLING LONG-TERM MORPHODYNAMICS IN PRACTICE: UNCERTAINTIES AND COMPROMISES

Authors: Williams, J.J., Conduche, T. and Esteves, L.S.

Editors: Wang, P., Rosati, J. and Cheng, J.

Conference: Coastal Sediments 2015

Dates: 11-15 May 2015

Journal: The Proceedings of the Coastal Sediments 2015

Publisher: World Scientific

ISBN: 978-981-4689-98-4

DOI: 10.1142/9789814689977_0216

Abstract:

Two problems limit the ability of morphological models to reproduce the real-world behaviour of geomorphological systems: (a) the dominance of short-term observations which fail to capture the full character of morphological evolution and cannot quantify fully the primary phenomena and mechanisms of change; and (b) incomplete understanding of processes at all relevant scales. Present efforts to reduce uncertainty in morphological models assume that: (a) observations are the key to locate, quantify and reduce uncertainty; and (b) means used to quantify, minimise and control uncertainty will improve model performance. This paper first outlines the principles underpinning morphological model development concerning coastal sandy environments. Then it discusses the use of morphological models and considers approaches that improve predictions through reduced uncertainty. The discussion is supported by two examples that illustrate the compromises that must be reached between what a morphological model is required to predict and what the model can deliver in practice.

https://eprints.bournemouth.ac.uk/22544/

http://www.worldscientific.com/doi/abs/10.1142/9789814689977_0216

Source: Manual

Modelling long-term morphodynamics in practice: uncertainties and compromises

Authors: Williams, J.J., Conduche, T. and Esteves, L.S.

Editors: Wang, P., Rosati, J. and Cheng, J.

Conference: Coastal Sediments 2015

Publisher: World Scientific

ISBN: 978-981-4689-98-4

Abstract:

Two problems limit the ability of morphological models to reproduce the real-world behaviour of geomorphological systems: (a) the dominance of short-term observations which fail to capture the full character of morphological evolution and cannot quantify fully the primary phenomena and mechanisms of change; and (b) incomplete understanding of processes at all relevant scales. Present efforts to reduce uncertainty in morphological models assume that: (a) observations are the key to locate, quantify and reduce uncertainty; and (b) means used to quantify, minimise and control uncertainty will improve model performance. This paper first outlines the principles underpinning morphological model development concerning coastal sandy environments. Then it discusses the use of morphological models and considers approaches that improve predictions through reduced uncertainty. The discussion is supported by two examples that illustrate the compromises that must be reached between what a morphological model is required to predict and what the model can deliver in practice.

https://eprints.bournemouth.ac.uk/22544/

http://www.worldscientific.com/doi/abs/10.1142/9789814689977_0216

Source: BURO EPrints