Understanding and quantifying storm surge risk and developing robust risk mitigation strategies
Open Access
- Author:
- Ceres, Robert L
- Graduate Program:
- Meteorology
- Degree:
- Doctor of Philosophy
- Document Type:
- Dissertation
- Date of Defense:
- August 02, 2018
- Committee Members:
- Chris Eliot Forest, Dissertation Advisor/Co-Advisor
Chris Eliot Forest, Committee Chair/Co-Chair
Klaus Keller, Committee Member
David W Titley, Committee Member
Murali Haran, Outside Member - Keywords:
- storm surge risk mitigation
hurricane
tropical cyclone
island city on a wedge
New York City
NYC
Manhattan
bias
Generalized Extreme Value distribution
GEV - Abstract:
- Cities around the globe are contemplating costly strategies for managing storm surge risk. The overall effectiveness and success of these major infrastructure investments depends upon understanding at least three interrelated areas. First, stakeholders must identify and assess the future risk of storm surges and society's vulnerability to the full spectrum of those risks. Second, stakeholders need to evaluate a wide variety of storm surge risk mitigation strategies against this full spectrum of future risk. Third, policymakers must balance the benefits of risk mitigation against the large investments needed to implements them, as well as numerous other conflicting objectives and concerns of other stakeholders. Research described in this dissertation directly addresses each of these areas. First we use an Observation System Simulation Experiment and ask the simple and decision-relevant question: How fast can we learn from past and potential future storm surge observations about changes in future statistics? We quantify the time required to detect changes in the probability of extreme storm surge events and estimate low probabilities of detection when substantial but gradual changes to the 100-year storm surge occur. As a result, policy makers may underestimate considerable increases in storm surge risk over the typically long lifespans of major infrastructure projects. Second, we develop a storm surge risk modeling framework, the Island City On a Wedge, to fill the niche between simple storm surge risk models incapable of simulating common characteristics of many coastal cities and complex modeling frameworks that are too computationally expensive to examine and optimize multiple combinations risk mitigation strategies. Using the Island City On a Wedge, we demonstrate that optimal risk mitigation solutions can change if the number of future states of the world, or time span over which the analysis is conducted changes. We couple the Island City On a Wedge to multiple objective evolutionary optimization algorithms and demonstrate the ability to assess storm surge risk and optimize complex risk mitigation strategies. We find that incorporating combinations of various defensive strategies can improve the financial effectiveness of risk mitigation investments. Lastly, we demonstrate the ability of the Island City On a Wedge to model storm surge risk in Manhattan and find Pareto optimal solutions balancing multiple stakeholder objectives and demonstrate the ability to effectively visualize the compromises inherent in any such trade off analysis.