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Abstract (from http://www.bioone.org/doi/abs/10.2112/JCOASTRES-D-13-00202.1): Traditional long-term (decadal) and large-scale (hundreds of kilometers) shoreline change modeling techniques, known as single transect, or ST, often overfit the data because they calculate shoreline statistics at closely spaced intervals along the shore. To reduce overfitting, recent work has used spatial basis functions such as polynomials, B splines, and principal components. Here, we explore an alternative to such basis functions by using regularization to reduce the dimension of the ST model space. In our regularized-ST method, traditional ST is an end member of a continuous spectrum of models. We use an evidence information criterion...
Abstract (from http://journals.sagepub.com/doi/abs/10.1177/0739456X16657160): Sea-level rise (SLR) presents risks to communities and ecosystems because of hazards like coastal erosion. In order to adapt, planners and the public seek estimates of shoreline change with high confidence and accuracy. The complexity of shorelines produces considerable uncertainty in the timing, location and magnitude of change. We present and discuss a probabilistic shoreline model for SLR planning. Using the coast of Maui as an illustrative case, we compare this model to a common deterministic model. We discuss the advantages of a probability-based model for SLR adaptation, including for prioritizing actions, phasing, visualizing risk...
Abstract (from http://link.springer.com/article/10.1007%2Fs11069-015-1698-6): Chronic erosion in Hawaiʻi causes beach loss, damages homes and infrastructure, and endangers critical habitat. These problems will likely worsen with increased sea level rise (SLR). We forecast future coastal change by combining historical shoreline trends with projected accelerations in SLR ( IPCC RCP8.5) using the Davidson-Arnott profile model. The resulting erosion hazard zones are overlain on aerial photos and other GIS layers to provide a tool for identifying assets exposed to future coastal erosion. We estimate rates and distances of shoreline change for ten study sites across the Hawaiian Islands. Excluding one beach (Kailua) historically...
Planning community resilience to sea level rise (SLR) requires information about where, when, and how SLR hazards will impact the coastal zone. We augment passive flood mapping (the so-called “bathtub” approach) by simulating physical processes posing recurrent threats to coastal infrastructure, communities, and ecosystems in Hawai‘i (including tidally-forced direct marine and groundwater flooding, seasonal wave inundation, and chronic coastal erosion). We find that the “bathtub” approach, alone, ignores 35–54 percent of the total land area exposed to one or more of these hazards, depending on location and SLR scenario. We conclude that modeling dynamic processes, including waves and erosion, is essential to robust...