Show simple item record

dc.contributor.advisorDyer, Jamie L.
dc.contributor.authorSchlotzhauer, David Scott
dc.date2012
dc.date.accessioned2020-09-18T13:53:31Z
dc.date.available2020-09-18T13:53:31Z
dc.identifier.urihttps://hdl.handle.net/11668/20527
dc.description.abstractOne of the greatest hazards from hurricanes is the flooding due to storm surge. Emergency managers traditionally plan for storm surge by looking at the worst possible impact and design their plans accordingly. This is a safe course of action, but can also be a wasted expense if the worst case does not occur. Risk-based planning is a way to incorporate the likelihood or probability of an impact occurring into emergency planning. With respect to storm surge, though, there is very little information regarding probability of occurrence. This research uses data from a commonly accepted storm surge model, SLOSH from the National Weather Service, to develop probabilities of impact. The process and products are prototypes utilizing data from the 2007 SLOSH model run for the New Orleans basin. Products developed include a map of probability, probabilities of exceedance, and a list of model storms that generate surge at given locations.
dc.publisherMississippi State University
dc.subject.lcshStorm surges--Southern States--Forecasting--Mathematical models.
dc.subject.lcshEmergency management--Southern States--Mathematical models.
dc.subject.lcshHurricane protection--Southern States--Mathematical models.
dc.subject.otherclimatology
dc.subject.otherrisk
dc.subject.otheremergency management
dc.titleQuantification of Storm Surge Probability using Ensemble Slosh Model Data
dc.typeThesis
dc.publisher.departmentDepartment of Geosciences
dc.publisher.collegeCollege of Arts and Sciences
dc.date.authorbirth1963
dc.subject.degreeMaster of Science
dc.subject.majorGeosciences
dc.contributor.committeeMercer, Andrew E.
dc.contributor.committeeCooke, William H.


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record