4.6 Article

Morphodynamic modelling of intertidal sediment transport in Morecambe Bay

Journal

ESTUARINE COASTAL AND SHELF SCIENCE
Volume 53, Issue 1, Pages 79-92

Publisher

ACADEMIC PRESS LTD
DOI: 10.1006/ecss.2000.0618

Keywords

models; morphology; computer simulation; sediment movement; bottom topography; waterline; remote sensing; Morecambe Bay

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The construction of a morphodynamic model for the intertidal region of Morecambe Bay, England, and its calibration and validation using extensive sediment volume change data measured by remote sensing, is described. A properly validated sediment transport model of the bay would be of interest for coastal defence, management and economic purposes. The morphodynamic model consisted of a set of linked modules for predicting 2D depth-averaged tidal currents, waves, sediment transport rates and sediment budgets. The intertidal bathymetry was updated at regular intervals and the currents, waves and sediment transport patterns recomputed using the new bathymetry. Tidal input filtering using representative spring and neap tidal cycles was used to reduce computational requirements. Sediment volume changes during the period 1992-1997 were measured over the intertidal zone at a resolution of 240 in using the waterline method employing remote sensing and hydrodynamic modelling. The total volume of sediment eroded was - 102 +/- 16 x 10(6) m(3), and the total volume accreted was 107 +/- 15 x 10(6) m(3). Tidal asymmetry is shown to be the dominant agent of sediment transport in the intertidal zone, with waves being of secondary importance. A close correlation was found between the computed directions of tidal asymmetry and observed sediment transport paths. It was necessary to use the remotely sensed data for calibration of the sediment transport model as well as for validation. The model showed some limited capability for predicting gross changes in bathymetry, but there were substantial differences between the predicted and observed patterns of sediment movement. The possibility of improvement by a further incorporation of the spatially and temporally extensive field data into the modelling process is discussed. (C) 2001 Academic Press.

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