Design of flood-risk management strategies in New Orleans

Wednesday 31 May, 2017
Climate Change Research Centre Seminar Room, Level 4 Mathews Building, Kensington Campus, Sydney

Despite recent advances projecting global mean sea-level rise, large uncertainties remain surrounding the potential disintegration of the West Antarctic Ice Sheet (WAIS) and the overall fast dynamics of ice sheets. Recent studies have shown that the West Antarctic Ice Sheet may be less stable than previously thought, with the potential to raise sea level by up to 3.3 meters. However, a set of probabilistic sea-level rise projections is still needed that includes the Antarctic fast dynamics. These rising sea levels pose significant risks for coastal communities, and damage and mitigation policies rely on such probabilistic projections. Building flood protection infrastructure to withstand higher sea levels reduces expected total costs through decreased losses when storms occur, but increases costs through construction investments. This study uses a common cost-benefit analysis method to determine optimal levels of flood protection. As an example, this study evaluates the optimal strategy for the northcentral dike ring in New Orleans, assuming the strategy either neglects or includes the contributions to future sea-level rise brought on by the Antarctic fast dynamics. 

This project demonstrated the power of transboundary analysis central to the program centered here at Penn State.  Leveraging and expanding on previous stakeholder engagements, the New Orleans project has developed, tested, applied, and documented a new method to characterize the value informed mental models (ViMM) of stakeholders and model developers. The insights derived from the ViMM analyses then inform the design of scientific, economic, and decision-analytical models as well as guide the development of decision support tools. The insights from the decision analyses further triggered the design of research in the areas of Earth science and statistics, e.g., about the ability to detect warning signs or signposts. This research also highlights the need to refine the decision-analytical approach and to develop new tools, e.g., on how to identify dynamic adaptive pathways in the face of potential threshold responses.

Chris E. Forest is Associate Professor of Climate Dynamics in the Department of Meteorology and Atmospheric Science at The Pennsylvania State University. He is also affiliated wth the Department of Geosciences, an associate in the Earth and Environmental Systems Institute, and associate director for the Network for Sustainable Climate Risk Management. He served as a lead author on the report of the Intergovernmental Panel on Climate Change for the chapter on the evaluation of climate models and on a report for the U.S. Climate Change Science Program examining the estimates of temperature trends in the atmospheric and surface climate data. He was elected to serve on the Electorate Nominating Committee for the Atmospheric and Hydrospheric Sciences Section of the American Association for the Advancement of Science. His research focuses on quantifying uncertainty in climate predictions and their implications for assessing climate risks. He has a B.S. in applied mathematics, engineering, and physics from the University of Wisconsin-Madison and a Ph.D. in meteorology from the Massachusetts Institute of Technology.