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.
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/7754486 |
| Date | 15 May 2019 |
| Creators | Matthew P. Shisler (5930855) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/Improving_Storm_Surge_Hazard_Characterization_Using_Pseudo-surge_to_Augment_Hydrodynamic_Simulation_Outputs/7754486 |
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