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While there is high certainty that chronic coastal hazards like floodingand erosion, are increasing due to climate change induced sea-levelrise, there is high uncertainty surrounding the timing, intensity, andlocation of future hazard impacts. Assessments that quantify theseaspects of future hazards are critical for adaptation planning under achanging climate and can reveal new insights into the drivers of coastalhazards. In particular, probabilistic simulations of future hazardimpacts can improve these assessments by explicitly quantifyinguncertainty and by better simulating dependence structures between thecomplex multivariate drivers of hazards. In this study, a regional-scaleprobabilistic assessment of climate change induced coastal hazards isconducted for the Cascadia region, USA during the 21st century. Threeco-produced hazard proxies for beach safety, erosion, and flooding arequantified to identify areas of high hazard impacts and determine hazarduncertainty under three sea-level rise scenarios. A novel chroniccoastal hazard hotspot indicator is introduced that identifies areasthat may experience significant increases in hazard impacts compared topresent day conditions. We find that Southern Cascadia and NorthernWashington have larger hazard impacts and hazard uncertainty due totheir morphologic setting. Erosional hazards, relative to beach safetyand coastal flooding, will increase the most in Cascadia during the 21stcentury under all sea-level rise scenarios. Finally, we find that hazarduncertainty associated with wave and water level variability exceeds theuncertainty associated with sea-level-rise until the end of the century.
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Sea Level and Socioeconomic Uncertainty Drives High‐End Coastal Adaptation Costs
Abstract Sea‐level rise and associated flood hazards pose severe risks to the millions of people globally living in coastal zones. Models representing coastal adaptation and impacts are important tools to inform the design of strategies to manage these risks. Representing the often deep uncertainties influencing these risks poses nontrivial challenges. A common uncertainty characterization approach is to use a few benchmark cases to represent the range and relative probabilities of the set of possible outcomes. This has been done in coastal adaptation studies, for example, by using low, moderate, and high percentiles of an input of interest, like sea‐level changes. A key consideration is how this simplified characterization of uncertainty influences the distributions of estimated coastal impacts. Here, we show that using only a few benchmark percentiles to represent uncertainty in future sea‐level change can lead to overconfident projections and underestimate high‐end risks as compared to using full ensembles for sea‐level change and socioeconomic parametric uncertainties. When uncertainty in future sea level is characterized by low, moderate, and high percentiles of global mean sea‐level rise, estimates of high‐end (95th percentile) damages are underestimated by between 18% (SSP1‐2.6) and 46% (SSP5‐8.5). Additionally, using the 5th and 95th percentiles of sea‐level scenarios underestimates the 5%–95% width of the distribution of adaptation costs by a factor ranging from about two to four, depending on SSP‐RCP pathway. The resulting underestimation of the uncertainty range in adaptation costs can bias adaptation and mitigation decision‐making.
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- Award ID(s):
- 2213432
- PAR ID:
- 10386712
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Earth's Future
- Volume:
- 10
- Issue:
- 12
- ISSN:
- 2328-4277
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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