Published on: Thu, 17/03/2011 - 06:04
The following variables and data sets would/could be of value to the agencies and industries most concerned with the management of coastal erosion, coastal protection, beach conservation etc:
- Very high resolution wind-wave mapping and data and climatology, and model outputs providing seasonal variability, inter-annual variability, extreme values, and long term trends.
- Sea level variability, tidal data, accurate high resolution tidal models giving sea level and tidal heights between observing tide gauges; seasonal and annual variability of sea level; long term trend of sea level, taking into account local tectonics, subsidence or uplift of the coast.
- Meteorological forcing of sea level, data and model outputs; wind-wave set-up; barometric forcing; storm surge data and model outputs.
- High resolution coastal geology; integrated maps of the coastal strip, a few km wide onshore and offshore, presenting key topographic and geological data on the same co-ordinates, and using consistent symbols and vertical references, so that processes can be understood and monitored continuously and consistently from the land into the ocean.
- Very high resolution bathymetry in the coastal zone; indication of features which are not stable, such as sand waves, bars, spits and seabed dunes, which may move seasonally or progressively.
- Basin-scale high resolution bathymetry so as to model the propagation of currents, tides, surges, and waves in an accurate way through numerical models.
- Suspended sediments, seasonal variability, bedload transport.
- Vegetation in the coastal zone, both underwater and onshore, which can stabilise the seabed and coastal dunes.
- Deltas, lagoons, vegetation, marshes, etc…?
- River discharges, and seasonal river-borne sediment load.
Some of these are variables already highlighted in the EMODNET plans, but one of the key aspects of the coastal geomorphology requirement is the need for spatial resolution of a few metres to a few tens of metres, and probably detailed seasonal cycles of change.