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Improving Storm Surge Hazard Characterization Using "Pseudo-surge" to Augment Hydrodynamic Simulation Outputs

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posted on 15.05.2019 by Matthew P. Shisler
Joint probability methods for assessing storm surge flood risk involve the use of a collection of hydrodynamic storm simulations to fit a response surface model describing the functional relationship between storm surge and storm parameters like central pressure deficit and the radius of maximum wind speed. However, in areas with a sufficiently low probability of flooding, few storms in the simulated storm suite may produce surge, with most storms leaving the location dry with zero flooding. Analysts could treat these zero-depth, “non-wetting” storms as either truncated or censored data. If non-wetting storms are excluded from the training set used to fit the storm surge response surface, the resulting suite of wetting storms may have too few observations to produce a good fit; in the worst case, the model may no longer be identifiable. If non-wetting storms are censored using a constant value, this could skew the response surface fit. The problem is that non-wetting storms are indistinguishable, but some storms may have been closer to wetting than others for a given location. To address these issues, this thesis proposes the concept of a negative surge, or “pseudo-surge”, value with the intent to describe how close a storm came to causing surge at a location. Optimal pseudo-surge values are determined by their ability to improve the predictive performance of the response surface via minimization of a modified least squares error function. We compare flood depth exceedance estimates generated with and without pseudo-surge to determine the value of perfect information. Though not uniformly reducing flood depth exceedance estimate bias, pseudo-surge values do make improvements for some regions where <40% of simulated storms produced wetting. Furthermore, pseudo-surge values show potential to replace a post-processing heuristic implemented in the state-of-the-art response surface methodology that corrects flood depth exceedance estimates for locations where very few storms cause wetting.

History

Degree Type

Master of Science in Industrial Engineering

Department

Industrial Engineering

Campus location

West Lafayette

Advisor/Supervisor/Committee Chair

David R. Johnson

Additional Committee Member 2

Susan R. Hunter

Additional Committee Member 3

Venkatesh M. Merwade

Licence

Exports