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\begin{document}

\title{A Multiplex approach to integrate social vulnerability into urban flood
mapping}



\author[1]{Matthew Preisser}%
\author[1]{Paola Passalacqua}%
\author[2]{R. Patrick Bixler}%
\affil[1]{University of Texas at Austin}%
\affil[2]{University of Texas}%


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  \date{June 03, 2024}


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\begin{abstract}
Depressions are topographic areas that have no outward flow and occur in
portions of landscapes with little to no elevation change, or areas with
negative relief in relation to surrounding areas. While these
depressions are an important part of the hydrological system, they have
historically been filled in or ignored during flow routing and other
hydrological processing calculations. With the increased prevalence of
high-resolution topography data, understanding and evaluating how
topographic depressions can impact overland flow is vital for improving
hydrological analyses, specifically in the context of flood inundation
mapping. Flooding caused from the filling of depressions (pluvial
flooding) can have compounding effects when simultaneously occurring
with river (fluvial) or coastal flooding. Our goal is to consider both
pluvial and fluvial flooding in flat urban environments to identify
areas that are significantly more vulnerable to inundation as compared
to flood mapping from only one particular source. Our approach relies on
a multiplex network that utilizes the Height Above Nearest Drainage
(HAND) method as well as a hydraulic head equalization algorithm to
estimate inundation patterns. Social vulnerability data are integrated
in this framework to identify urban hot spots, defined as areas with a
lower relative socioeconomic status in conjunction with a higher
probability of inundation. Combining technical and social information
leads to the identification of communities that are more vulnerable to
the physical, economical, and social components of floods. This approach
can help urban flood planners associate social disparities in
relationship to flood preparedness and response.%
\end{abstract}%



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