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Documented trends in rising sea levels, storminess, and extreme wave heights have the potential to increase the frequency and magnitude of coastal change hazards, increasing risks to coastal infrastructure and environmental resources. Coastal planners and decision makers need information about the impacts of future hazards in order to apply mitigation and adaptation strategies. However, making quantitative predictions of beach and dune erosion is complicated by uncertainties surrounding the drivers and impacts of climate change as well as our understanding of climate controls on coastal change hazards. Furthermore, these changes are occurring in a dynamic environment where beach geomorphology evolves over a variety of spatial and temporal scales. Here a new, probabilistic approach for quantifying future coastal change hazards that incorporates the uncertainty associated with both climate change and morphological variability is presented.
First, a suite of synthetic time series of total water levels (TWLs) through 2100 are produced by applying various climate change scenarios, composed of projections of sea-level rise, wave climate, and the frequency of major El Niños, to historical datasets of waves and measured tidal elevations. These time series allow extreme design events to be computed for any time period in the future (e.g., 100-year TWL event in 2030). Using simple coastal change models that require TWLs and various beach morphometrics as input, future coastal change is quantified over a wide range of possible climate futures for sandy, dune-backed coastlines.
The new methodology has been applied to the Tillamook County coast in northwestern Oregon to develop coastal change hazard zones of arbitrary confidence levels for both the 100% and 1% annual chance TWL events at present (2009) and for years 2030, 2050, and 2100. The nature of the probabilistic approach, however, allows for coastal decision makers to determine the desired level of confidence (or exceedance probability), extremity of the event, and planning horizon to consider. The hazard zones are then integrated with various socioeconomic datasets (e.g., structures, roads) to evaluate the exposure of coastal communities to the predicted coastal change hazards at various levels of confidence. When paired with community vulnerability assessments, the hazard map products developed will provide coastal planners with the tools and information to allow for science-based decisions that will increase the adaptive capacity of coastal communities as they prepare for the uncertainties of future climate change.
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