WORKSTREAM 3 Sediment Dynamics (Lead Glasgow and Strathclyde)
The ‘near-field’ effects on suspended and seabed sediment material in the vicinity of developments are likely to include localised scour, with associated deposition of re-suspended sediment elsewhere, most of this being caused by the physical presence of devices on or near the seabed, rather than to energy extraction per se. This is likely to be highly sensitive to aspects of device and array design and placement, including moorings and associated structures. Large scale (at least 50 km) changes in morphodynamics would also be expected as a result of altered wave and tidal environment, affecting sediment transport rates, seabed topography and littoral zone processes (Miller et al., 2007). Thus changes in erosion, deposition and suspension of sediment due to the placement of energy extraction systems can be expected at a wide range of scales (Couch and Bryden, 2005).
Task WS3.1 Modelling seabed sediment transport and geomorphology
In order to determine changes to the seabed sediment transport rates and sea bottom bathymetry at selected sites, MIKE21 with the ST transport module will be applied. The initial sea bottom bathymetry for these simulations will be derived by the high resolution bathymetry maps available at the selected sites. The impact of energy extraction on the flow and hence bottom sediment transport is governed by the efficiency of the devices, number of devices in an array, array geometry and orientation. Therefore, local and far-field sediment transport vectors will be determined for a range of turbine array scenarios which will be decided in WS1.2. Prior to the application of the model to determine sediment transport rates associated with energy generation, the model will be applied to ‘no energy generation’ scenario at each selected site, existing sediment transport rates and pathways will be modelled and the results will be validated against data available on sediment transport, wherever possible. The near-bed sediment transport vectors provide changes to sediment pathways and transport rates associated with the deployments. The outputs will then be combined with a sea bed updating module where effects on sea bottom morphology at short term time scales such as bed scouring around moorings and, erosion and deposition of sea bottom as a result of sediment redistribution will be determined.
Task WS3.2 Modelling changes in accretion/erosion of the coastline
Extraction of wave energy alters the incident wave field and wave breaking characteristics in the littoral zone (Venugopal and Smith, 2007), which will in turn alter near-bed orbital velocities and near-shore wave induced currents in the littoral zone. This will impact the littoral transport regime changing the adjacent shorelines. Littoral zone transport and sea bottom change at the shorelines adjacent to the selected sites will be modelled using MIKE21, for a range of wave climate scenarios which would cover monthly/yearly maximum and average wave conditions, and extreme wave conditions with various return levels, which will be determined in WS2.4. This will allow investigation of the impact of wave energy devices on the littoral zone and shoreline under extreme conditions for comparison. Task WS3.3 Modelling large scale suspended sediment distributions
Shelf-wide simulation models of suspended particulate mineral material (SPM) are generally considered to have a low skill level due to the complexity of representing the sources and properties of material and the processes involved in settlement, re-suspension and transport (Allen et al., 2007). Here we will take a statistical modeling approach, blending turbidity data from monitoring maintained by MSS (off Stonehaven), with high spatial resolution data from satellite remote sensing. Stage 1 will generate a one dimensional (vertical) statistical model for the temporal dynamics of SPM at given altitudes above the seabed at the monitoring site with explanatory variables being seabed depth and time series of salinity (as a surrogate of river discharge), daily maximum tidal velocity and wave characteristics (see Heath et al., 2002 for approach). Stage 2 will link a self-wide matrix of one-dimensional (vertical) models to 2-dimensional (horizontal) modelled or gridded observational data on the explanatory variables and seabed sediment characteristics (British Geological Survey DigSBS), and assess the skill of the system by comparing with sea surface SPM loads derived from satellite
remote sensing data (McKee et al., 2009). Stage 3 will evaluate consequences for SPM vertical and horizontal distributions, with altered tidal flows and wave energy patterns emerging from the hydrodynamic simulations in the project in which device arrays are represented.
WS3 Deliverables
DW3.1. Spatial distribution of local net sediment transport pathways predicted for energy extraction scenarios
DW3.2. Spatial distribution of net bedload sediment transport rates at tide-averaged scale DW3.3. Spatial distribution maps of bathymetry and coastline change
DW3.4. Fully parameterised statistical model to predict SPM profiles
DW3.5. Spatial distribution maps of the predicted impact of energy extraction scenarios in SPM concentrations for use in WS4
The ‘near-field’ effects on suspended and seabed sediment material in the vicinity of developments are likely to include localised scour, with associated deposition of re-suspended sediment elsewhere, most of this being caused by the physical presence of devices on or near the seabed, rather than to energy extraction per se. This is likely to be highly sensitive to aspects of device and array design and placement, including moorings and associated structures. Large scale (at least 50 km) changes in morphodynamics would also be expected as a result of altered wave and tidal environment, affecting sediment transport rates, seabed topography and littoral zone processes (Miller et al., 2007). Thus changes in erosion, deposition and suspension of sediment due to the placement of energy extraction systems can be expected at a wide range of scales (Couch and Bryden, 2005).
Task WS3.1 Modelling seabed sediment transport and geomorphology
In order to determine changes to the seabed sediment transport rates and sea bottom bathymetry at selected sites, MIKE21 with the ST transport module will be applied. The initial sea bottom bathymetry for these simulations will be derived by the high resolution bathymetry maps available at the selected sites. The impact of energy extraction on the flow and hence bottom sediment transport is governed by the efficiency of the devices, number of devices in an array, array geometry and orientation. Therefore, local and far-field sediment transport vectors will be determined for a range of turbine array scenarios which will be decided in WS1.2. Prior to the application of the model to determine sediment transport rates associated with energy generation, the model will be applied to ‘no energy generation’ scenario at each selected site, existing sediment transport rates and pathways will be modelled and the results will be validated against data available on sediment transport, wherever possible. The near-bed sediment transport vectors provide changes to sediment pathways and transport rates associated with the deployments. The outputs will then be combined with a sea bed updating module where effects on sea bottom morphology at short term time scales such as bed scouring around moorings and, erosion and deposition of sea bottom as a result of sediment redistribution will be determined.
Task WS3.2 Modelling changes in accretion/erosion of the coastline
Extraction of wave energy alters the incident wave field and wave breaking characteristics in the littoral zone (Venugopal and Smith, 2007), which will in turn alter near-bed orbital velocities and near-shore wave induced currents in the littoral zone. This will impact the littoral transport regime changing the adjacent shorelines. Littoral zone transport and sea bottom change at the shorelines adjacent to the selected sites will be modelled using MIKE21, for a range of wave climate scenarios which would cover monthly/yearly maximum and average wave conditions, and extreme wave conditions with various return levels, which will be determined in WS2.4. This will allow investigation of the impact of wave energy devices on the littoral zone and shoreline under extreme conditions for comparison. Task WS3.3 Modelling large scale suspended sediment distributions
Shelf-wide simulation models of suspended particulate mineral material (SPM) are generally considered to have a low skill level due to the complexity of representing the sources and properties of material and the processes involved in settlement, re-suspension and transport (Allen et al., 2007). Here we will take a statistical modeling approach, blending turbidity data from monitoring maintained by MSS (off Stonehaven), with high spatial resolution data from satellite remote sensing. Stage 1 will generate a one dimensional (vertical) statistical model for the temporal dynamics of SPM at given altitudes above the seabed at the monitoring site with explanatory variables being seabed depth and time series of salinity (as a surrogate of river discharge), daily maximum tidal velocity and wave characteristics (see Heath et al., 2002 for approach). Stage 2 will link a self-wide matrix of one-dimensional (vertical) models to 2-dimensional (horizontal) modelled or gridded observational data on the explanatory variables and seabed sediment characteristics (British Geological Survey DigSBS), and assess the skill of the system by comparing with sea surface SPM loads derived from satellite
remote sensing data (McKee et al., 2009). Stage 3 will evaluate consequences for SPM vertical and horizontal distributions, with altered tidal flows and wave energy patterns emerging from the hydrodynamic simulations in the project in which device arrays are represented.
WS3 Deliverables
DW3.1. Spatial distribution of local net sediment transport pathways predicted for energy extraction scenarios
DW3.2. Spatial distribution of net bedload sediment transport rates at tide-averaged scale DW3.3. Spatial distribution maps of bathymetry and coastline change
DW3.4. Fully parameterised statistical model to predict SPM profiles
DW3.5. Spatial distribution maps of the predicted impact of energy extraction scenarios in SPM concentrations for use in WS4