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An understanding of the geomorphological evolution of the coastal and inner continental shelf environments, in response to natural and/or anthropogenic forcings, depends upon a comprehensive knowledge of the prevailing sediment dynamics. In this contribution, selected methods/tools that can be used to study seabed mobility/transport patterns, are described and these all reviewed in relation to their inherent limitations.The geological, morphological, hydrodynamic and sedimentary information (the environmental framework) necessary to develop a general understanding of the areas investigated are identified. This preliminary information prescribes the investigative tools to be utilized subsequently, i.e. the collection/analysis of data; these can define geomorphological and sedimentological indicators of sediment transport, hydrodynamic/sediment transport field observations and numerical simulations.The results derived from the various methods can be used then independently or, preferably in combination, to establish conceptual models of seabed sediment dynamics over the investigated area. The coherence between the outputs of the different methods/tools controls the confidence level (high, medium or low) of the models. This approach is illustrated in relation to case studies from the southern UK inner continental shelf.

Incorporating a temporal function (i.e. to analyse data over time) into the spatial environment of GIS has been developed and applied in the assessment of the evolution of Nash Bank, South Wales. A stringent programme of monitoring, including annual bathymetric surveys of the bank, is carried out as part of the requirements of aggregate dredging and provides suitable data to analyse changes in bank levels over time. Traditionally GIS has been used to assess the evolution of such coastal landforms by creating a digital terrain model (DTM) for each of the bathymetric datasets and then performing a simple calculation whereby one DTM is subtracted from an earlier one. However, a simple difference in levels between any two snapshots in time can be misleading when trying to evaluate long-term rates of change. The new GIS tool has been developed that calculates such rates (i.e. the time trend) by incorporating a linear regression formula. The results are then plotted out by the tool into GIS as a DTM, in which each individual data cell represents a rate of change (time trend) at that particular location, allowing a clear temporal analysis to be presented for the whole area.