Conventionally flood mapping typically includes only a static water level (e.g. peak of a storm tide) in coastal flood inundation events. Additional factors become increasingly important when increased water-level thresholds are met during the combination of a storm tide and increased mean sea level. This research incorporates factors such as wave overtopping and river flow in a range of flood inundation scenarios of future sea-level projections for a UK case study of Fleetwood, northwest England. With increasing mean sea level it is shown that wave overtopping and river forcing have an important bearing on the cost of coastal flood events. The method presented converts inundation maps into monetary cost. This research demonstrates that under scenarios of joint extreme surge-wave-river events the cost of flooding can be increased by up to a factor of 8 compared with an increase in extent of up to a factor of 3 relative to “surge alone” event. This is due to different areas being exposed to different flood hazards and areas with common hazard where flood waters combine non-linearly. This shows that relying simply on flood extent and volume can under-predict the actual economic impact felt by a coastal community. Additionally, the scenario inundation depths have been presented as “brick course” maps, which represent a new way of interpreting flood maps. This is primarily aimed at stakeholders to increase levels of engagement within the coastal community.
Abstract.A pressing problem facing coastal decision makers is the conversion of "high-level" but plausible climate change assessments into an effective basis for climate change adaptation at the local scale. Here, we describe a web-based, geospatial decision support tool (DST) that provides an assessment of the potential flood risk for populated coastal lowlands arising from future sea-level rise, coastal storms, and high river flows. This DST has been developed to support operational and strategic decision making by enabling the user to explore the flood hazard from extreme events, changes in the extent of the flood-prone areas with sea-level rise, and thresholds of sea-level rise where current policy and resource options are no longer viable. The DST is built in an open-source GIS that uses freely available geospatial data. Flood risk assessments from a combination of LISFLOOD-FP and SWAB (Shallow Water And Boussinesq) models are embedded within the tool; the user interface enables interrogation of different combinations of coastal and river events under rising-sea-level scenarios. Users can readily vary the input parameters (sea level, storms, wave height and river flow) relative to the present-day topography and infrastructure to identify combinations where significant regime shifts or "tipping points" occur. Two case studies demonstrate the attributes of the DST with respect to the wider coastal community and the UK energy sector. Examples report on the assets at risk and illustrate the extent of flooding in relation to infrastructure access. This informs an economic assessment of potential losses due to climate change and thus provides local authorities and energy operators with essential information on the feasibility of investment for building resilience into vulnerable components of their area of responsibility.
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