Improving Adaptation Planning for Future Sea-Level Rise: Understanding Uncertainty and Risks Using a Probability-Based Shoreline Model. (September 2016)

• Record Type: Journal Article
• Authors: Spirandelli, Daniele J.; Anderson, Tiffany R.; Porro, Roberto; Fletcher, Charles H.
• Is Part Of: Journal of planning education and research. Volume 36:Number 3(2016:Autumn)
• Page Start: 290
• Page End: 303
• Publication Date: 2016-09
• Subjects: climate change adaptation -- sea-level rise -- probability models -- shoreline change; Regional planning -- Study and teaching -- United States -- Periodicals; City planning -- Study and teaching -- United States -- Periodicals; 307.12
• DOI: 10.1177/0739456X16657160
• Languages: English
• ISSNs: 0739-456X

Abstract

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 and uncertainty, and improving adaptive management.