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      Deep Uncertainties in Sea-Level Rise and Storm Surge Projections: Implications for Coastal Flood Risk Management : Deep Uncertainties in Coastal Flood Risk Management

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          Abstract

          Sea levels are rising in many areas around the world, posing risks to coastal communities and infrastructures. Strategies for managing these flood risks present decision challenges that require a combination of geophysical, economic, and infrastructure models. Previous studies have broken important new ground on the considerable tensions between the costs of upgrading infrastructure and the damages that could result from extreme flood events. However, many risk-based adaptation strategies remain silent on certain potentially important uncertainties, as well as the tradeoffs between competing objectives. Here, we implement and improve on a classic decision-analytical model (Van Dantzig 1956) to: (i) capture tradeoffs across conflicting stakeholder objectives, (ii) demonstrate the consequences of structural uncertainties in the sea-level rise and storm surge models, and (iii) identify the parametric uncertainties that most strongly influence each objective using global sensitivity analysis. We find that the flood adaptation model produces potentially myopic solutions when formulated using traditional mean-centric decision theory. Moving from a single-objective problem formulation to one with multiobjective tradeoffs dramatically expands the decision space, and highlights the need for compromise solutions to address stakeholder preferences. We find deep structural uncertainties that have large effects on the model outcome, with the storm surge parameters accounting for the greatest impacts. Global sensitivity analysis effectively identifies important parameter interactions that local methods overlook, and that could have critical implications for flood adaptation strategies.

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          Author and article information

          Journal
          Risk Analysis
          Risk Analysis
          Wiley
          02724332
          September 05 2017
          Affiliations
          [1 ]Department of Geosciences, The Pennsylvania State University; University Park; PA USA
          [2 ]Department of Statistics, The Pennsylvania State University; University Park; PA USA
          [3 ]Woodrow Wilson School of Public and International Affairs; Princeton University; NJ USA
          [4 ]Department of Energy and Mineral Engineering, The Pennsylvania State University; University Park; PA USA
          [5 ]School of Civil and Environmental Engineering; Cornell University; Ithaca NY USA
          [6 ]Department of Meteorology and Atmospheric Science, The Pennsylvania State University; University Park; PA USA
          [7 ]Earth and Environmental Systems Institute, The Pennsylvania State University; University Park; PA USA
          [8 ]Department of Engineering and Public Policy; Carnegie Mellon University; Pittsburgh PA USA
          Article
          10.1111/risa.12888
          28873257
          7c205332-3f1b-4018-bcbb-d9bbbdcc8f12
          © 2017

          http://doi.wiley.com/10.1002/tdm_license_1.1

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