Incorporating climate change and morphological uncertainty into coastal change hazard assessments

Abstract

Documented and forecasted trends in rising sea levels and changes in storminess patterns have the potential to increase the frequency, magnitude, and spatial extent of coastal change hazards. To develop realistic adaptation strategies, coastal planners need information about coastal change hazards that recognizes the dynamic temporal and spatial scales of beach morphology, the climate controls on coastal change hazards, and the uncertainties surrounding the drivers and impacts of climate change. We present a probabilistic approach for quantifying and mapping coastal change hazards that incorporates the uncertainty associated with both climate change and morphological variability. To demonstrate the approach, coastal change hazard zones of arbitrary confidence levels are developed for the Tillamook County (State of Oregon, USA) coastline using a suite of simple models and a range of possible climate futures related to wave climate, sea-level rise projections, and the frequency of major El Niño events. Extreme total water levels are 123Nat Hazards (2015) 75:2081-2102 DOI 10.1007/s11069-014-1417 more influenced by wave height variability, whereas the magnitude of erosion is more influenced by sea-level rise scenarios. Morphological variability has a stronger influence on the width of coastal hazard zones than the uncertainty associated with the range of climate change scenarios.

Projections of Future Beach Loss in Japan Due to Sea-Level Rise and Uncertainties in Projected Beach Loss

“…Although several studies have projected shoreline retreat in consideration of future changes in wave height (e.g. Baron et al [2015] assumed that wave heights will continue to increase at their present rate), we did not consider the change in wave height because its future projection still includes significant uncertainties [IPCC, 2013]. The SLR and wave data at each coastal zone were taken as the data closest to the mid-point of the beach shoreline in each zone.…”

Improving Adaptation Planning for Future Sea-Level Rise

“…Recently, probabilistic methods have gained momentum in the beach management sphere to incorporate the temporal-spatial variability of shoreline change (Callaghan, Roshanka, and Andrew 2009;Ranasinghe, Callaghan, and Stive 2011). Baron et al (2014) incorporates the uncertainty associated with both SLR and changing beach dynamics using a probabilistic approach to map shoreline change hazards with varying confidence levels. Lentz et al (2015) used a Bayesian network to assign probabilities to sea-level rise, elevation, and land cover that take into account a static response (inundation) and a dynamic response to SLR (e.g., sediment transport dynamics and ecosystem migration).…”

Global distribution of nearshore slopes with implications for coastal retreat

“…The nearshore area is here defined as the part of the P. Athanasiou et al: Global distribution of nearshore slopes cross-shore profile between the depth of closure d c (i.e., the depth seaward of which there is no significant change in bottom elevation) and the shoreline (MSL). The nearshore slope (the ratio of the d c over the horizontal distance between the d c and the shoreline) modulates the wave transformation (Battjes, 1974) and the total water levels (Serafin et al, 2019), while it is associated with geomorphological processes at various temporal scales (Bruun, 1962;Wright and Short, 1984;Dean, 1991). Therefore, a global assumption of uniform slope likely hides the spatial variability of coastal hydro-and morphodynamics.…”