• agreement on risk metrics (including weighting);
• evaluation of the benefits of changes in beach morphology;
• the use of risk attribution as a means of assessment of the contribution to risk of an existing asset;
• how to build flexibility (possibility for upgrading or removal) into design to allow for future changes;
• how to optimise (and support optimisation of) interventions;
• representation of ‘do nothing’ consequences (for erosion particularly);
• accounting for costs and benefits associated with multiple uses of assets (e.g. recreation, conservation, etc.);
• guidance on appropriate use of tools/models.
7.1.3 Systems analysis
The challenge
Flood and erosion risk systems often exhibit significant spatial and temporal complexity with many different sources and pathways (and receptors). System-based thinking enables the complexity to be broken down without losing the behavioural
characteristics of the system as a whole.
The main challenge here is to determine the major influences and changes in these systems that change flood and coastal erosion risk (i.e. how does the system function). As with most things, ‘the devil is in the detail’, requiring in-depth knowledge and
understanding of the system processes and the effects on receptors. Some areas and processes are better understood than others. Although the recent project,
‘Characterisation and Prediction of Large-scale, Long-term Change of Coastal Geomorphological Behaviours’ (SC060074), and others have improved our
understanding and capability greatly with respect to coastal morphological change and sediment transport, further research is required to better understand certain aspects (e.g. cross-shore change).
Recent work in the PAMS project has demonstrated the challenge faced by a pilot conducted on a frontage in West Bay in Dorset. Uncertainty associated with the performance of the West Beach was addressed by refining the fragility curve for the defence and re-running the model to ascertain a revised risk attribution. However, no attempt was made to model long-term changes in beach volume as these could not be replicated and demonstrated.
Scoping the future approach
Current research and consultation with practitioners and industry consultants has identified other issues with, and gaps in, understanding of coastal flood and erosion systems. These are listed in Table 7.1.
When it comes to the analysis and modelling of coastal asset related risks, there are two performance parameters that are very important but which have not attracted sufficient focus and study to date. These performance parameters are beach sediment volume and beach depth at the sea wall (or other defence type).
Beach volume is important because this is what coastal mangers need to maintain by means of recycling/renourishment to maintain the integrity of the defence line over time.
Beach depth at the sea wall (or cliff) is important because sufficient sediment is required to prevent undermining of the structure (or landform) and to limit wave
overtopping in the case of sea defences (i.e. maintain desired hydraulic performance). Proper characterisation of beach performance and that of associated beach control structures is required to characterise the fragility of the defence line properly, bearing in mind that in some cases the beach is the defence line. This issue requires addressing of both long-term shoreline evolution and local fluctuations in beach levels. Future work will need to tackle:
• the issues of assessment of these parameters;
• the provision of tools to enable managers to investigate options and scenarios given changes in these measures.
Natural beach systems provide significant proportion of our defences in the UK. Unlike fixed structures such as sea walls, natural beaches (barrier beaches and dunes, etc.) respond naturally to the forcing wave and water levels, changing dynamically during the storm and then recovering during calmer periods. This process of recovery is poorly understood and needs to be captured within the systems analysis and the performance models used to underpin asset management.
One of the problems is to understand and predict how the wider sediment transport processes impact on beach volume/area. Another is how this, combined with wave processes, impacts on beach height at the defence. Furthermore, control structures such as groynes are often used to control the movement of beach sediment;
understanding and modelling how such management measures perform is a yet further complication.
Thus, risks are realised through the way in which the system behaves. Existing system models are now relatively well-developed for flood risk but they remain more basic in terms of analysis of coastal shoreline systems – as illustrated in Figures 7.2 and 7.3.
Figure 7.2 Outline of a simplified performance analysis framework for flood and coastal erosion asset management.
Figure 7.2 is a stepwise ‘fragility’ framework; the difficult aspects are in linking the ‘coastal whole system’ models efficiently but robustly for processes happening at different temporal (hours, seasons to years) and spatial (single groyne to groyne or beach system) scales. Figure 7.3 is a simplified flow diagram for coastal erosion. There are complex interactions (temporal and spatial) running through the processes at work which need to be captured and described in more detail.
Another issue is risk attribution; the attribution of risk to assets is a key and powerful output from a risk analysis. Embedding systems analysis within software tools (as for flood risk in NCERM, PAMS or MDSF2) enables relatively complex computational calculations to be completed without unnecessary or onerous user inputs. A major challenge will be facilitating a robust system risk analysis (incorporating sequencing issues and probabilistic failure scenarios – groynes, toe defences, cliffs, etc.) in an efficient and transparent manner. Another challenge will be to extend the current RASP type models to enable risk attribution and hence the identification of investment
priorities at a regional scale. Hierarchical planning tools
Hierarchical planning is well established at the coast. However, the use and reuse of data throughout the tools that support these plans is not. For example, data on beach performance, fragility, etc. should be reused in a coherent/consistent manner from a national RACE analysis to local asset management plan. This scoping study has started this rationalisation, but significant further progress is required.
Table 7.1 reflects the uncertainty with which existing datasets, science knowledge and analysis tools can fully represent coastal system behaviour at all such hierarchical levels. One task should be to complete such a gap analysis as thoroughly as possible (see also the discussion in Section 7.1.5 and Appendix 4).
Table 7.1 Coverage and gap analysis of data collection, research and analysis of the coastal S-P-R system for asset management1.
Description Tools/data Data holdings, monitoring, research or developments* Outstanding*
Joint probability (waves and water levels)
WaveNet, BODC, coastal observatories and strategic coastal monitoring programmes
GTI-SEAMaT (?) SANDS (?) Source
Rainfall/groundwater MET Office (?)
Coastal defences PAMS, FLOODsite (T4), EUROtop, NFCDD, SANDS *Longshore connectivity sediment flux effects on performance
Shore platforms Lowering of beaches in front of coastal defence structures (FD1927) (?) Characterisation and prediction of large-scale, long-term change of coastal geomorphological behaviours (SC060074) (?)
Beaches Dunes Saltmarshes
Lowering of beaches in front of coastal defence structures (FD1927) Characterisation and prediction of large-scale, long-term change of coastal geo-morphological behaviours (SC060074)
SANDS GTI-SEAMaT
Coastal observatories and ABMS
*Assessment of condition and performance of beaches and control structures
*Performance analysis and condition assessment of dune systems and saltmarshes
Cliffs RACE, CliffSCAPE *Cliff failure probability related to rainfall
return period events and wave/water level joint probability (JP) return period events. Pathway
Floodplain (topography) RFSM, MDSF, EUROTAS
People Risks to People, EUROtop, Social Deprivation Index (see Section 4) Property NPD, council tax evaluations, Ancient Monuments Record (see Section 4) Receptor
Environment Environmental designation datasets [EBM tools (USA)]
(see Section 5) Notes 1 Those developments that would benefit or be supported well by case studies are marked by an asterisk.