Probabilistic Approaches to Coastal Risk Decision-Making Under Future Sea Level Projections

Coastal communities are increasingly threatened by flooding from climate change-induced sea level rise and potential increases in storminess. Informed decisions on risk and resilience related to flood risk need to be made, but the assessment process is complex. It is difficult to bring all of the climate science and sea level rise projections to decision-making, and as a result, decisions are made without a real understanding of the uncertainties involved, a problem magnified the further projections go into the future (Figure 1).

Probabilistic Approaches to Coastal Risk Decision-Making Under Future Sea Level Projections By Tom Spencer, Mike Dobson, Elizabeth Christie, Richard Eyres, Sue Manson, Steve Downie, and Angela Hibbert Coastal communities are increasingly threatened by flooding from climate change-induced sea level rise and potential increases in storminess.Informed decisions on risk and resilience related to flood risk need to be made, but the assessment process is complex.It is difficult to bring all of the climate science and sea level rise projections to decision-making, and as a result, decisions are made without a real understanding of the uncertainties involved, a problem magnified the further projections go into the future (Figure 1).
Comprehensive modeling approaches (see ideal option in Figure 2) that allow the impact of a range of potential future conditions to be assessed are not resource efficient.
Therefore, the conventional approach (see current option in Figure 2) involves selecting a narrow range of future sea level rise scenarios for further interrogation-typically the median estimate (solid lines in Figure 1).In addition, the uncertainties implicit in future climate scenarios are rarely taken through the hazard-to-impact framework, resulting in poorly defined predictions and likely limited trust in outputs and low levels of uptake.The research described here (proposed option in Figure 2) uses a source-pathwayreceptor model of flood risk for the city of Hull, Humber Estuary, eastern England to address these problems and develops a new streamlined approach to modeling the interactions between sea level hazards, economic activity, and risk.The purpose of this research was to examine the boundaries of the full range of climate predictions to inform judgment on where to focus attention for detailed study of and planning for future urban flood risk at the large scale and over the long term.Modeling results are not intended for more detailed design or planning activities for Hull at present (where model accuracy would become much more critical).
Situated on the northern bank of the Humber estuary, with a population of 258,000, Hull has the highest number of UK properties at risk of flooding (140,000) in a single urban area outside of London (Figure 3).England's Environment Agency has warned that, with changing climate, water levels in the Humber Estuary could rise by FIGURE 1. Sea level rise projections for the River Humber for a low (RCP2.6)and high emission scenario (RCP8.5),showing 5 th , 50 th (solid line), and 95 th percentiles.Underlying data are from UKCP18 (Palmer et al., 2018).The RCP numbers refer to the projected radiative forcing at 2100 under different climate change scenarios , for example, 2.6 W m -2 and 8.5 W m -2

.FIGURE 2 .
FIGURE 1. Sea level rise projections for the River Humber for a low (RCP2.6)and high emission scenario (RCP8.5),showing 5 th , 50 th (solid line), and 95 th percentiles.Underlying data are from UKCP18(Palmer et al., 2018).The RCP numbers refer to the projected radiative forcing at 2100 under different climate change scenarios, for example, 2.6 W m -2 and 8.5 W m -2 .

FIGURE 3 .
FIGURE 3. Study area location.(left) Humber estuary, Hull, UK.Content licensed under the CC BY-SA 3.0.Contains Ordnance Survey data © Crown copyright and database right.(right) Outer Humber estuary areas at risk of flooding-nearly 90% of the city of Hull lies below the high-tide level.Contains public sector information licensed under the Open Government License v2.0, https://flood-warning-information.service.gov.uk/long-term-flood-risk/map.

FIGURE 5 .
FIGURE 5. A screenshot of the visualization prototype for a single scenario, in this case sea level model RCP4.5 at the 90 th percentile with the best estimate (50%) storm and tide flood depth confidence at a 100-year return period in 2050.(a) The user sets the scenario.(b) A map of the region provides a visual representation of the data for the selected scenario.The user can choose to show flood depth, economic damage, elevation, and population density.In addition, the cursor hover-over functionality provides further information, including: number of buildings affected (residential and non-residential) and socioeconomic descriptor for the region.(c) A summary table shows key metrics for the whole region and (if selected) sub-region.(d) A contour plot indicates the effect of the sea level rise and storm-tide uncertainties on resulting total damage across the region for the chosen scenario.(e) A contour plot shows the effect of the sea level rise and storm-tide uncertainties on the net present value (NPV) of the average annual risk across the region for the chosen scenario.