A multiplex network approach to road flooding prediction

dc.contributor.advisorPassalacqua, Paola
dc.creatorDeo, Isha Padmakar
dc.creator.orcid0000-0002-3233-5863
dc.date.accessioned2021-04-23T20:55:19Z
dc.date.available2021-04-23T20:55:19Z
dc.date.created2019-05
dc.date.issued2019-07-08
dc.date.submittedMay 2019
dc.date.updated2021-04-23T20:55:20Z
dc.description.abstractUrban flooding poses risks to life, property, and health every year in the United States. Although accurate models of road, channel, and storm sewer dynamics exist, they are often not deployable at a short time scale suitable for prediction and emergency response. Using a multiplex network model of the road, channel, and storm sewer networks and the Height Above Nearest Drainage (HAND) method, urban flood prediction can be addressed with a network interaction perspective. By redefining the nodal activity during a storm event, critical nodes of the network can be identified using the network betweenness centrality on a larger scale. Here, the multiplex network is constructed on the University of Texas campus, and modeled through the severe Memorial Day 2015 storms. Critical areas of roadway flooding are identified throughout the UT Campus, corresponding to hotspots of high active betweenness centrality throughout the storm. The multiplex network approach serves as an emergency-response-oriented prediction tool for urban flooding.
dc.description.departmentCivil, Architectural, and Environmental Engineering
dc.format.mimetypeapplication/pdf
dc.identifier.urihttps://hdl.handle.net/2152/85432
dc.identifier.urihttp://dx.doi.org/10.26153/tsw/12396
dc.language.isoen
dc.subjectUrban flooding
dc.subjectMultiplex networks
dc.subjectHAND
dc.titleA multiplex network approach to road flooding prediction
dc.typeThesis
dc.type.materialtext
local.embargo.lift2021-05-01
local.embargo.terms2021-05-01
thesis.degree.departmentCivil, Architectural, and Environmental Engineering
thesis.degree.disciplineEnvironmental and Water Resources Engineering
thesis.degree.grantorThe University of Texas at Austin
thesis.degree.levelMasters
thesis.degree.nameMaster of Science in Engineering

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