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\begin{document}

\title{Assessing Contributions of Hydrometeorological Drivers to Socioeconomic
Impacts of Compound Extreme Events}



\author[1,2]{Javed Ali}%
\author[1,2]{Thomas Wahl}%
\author[1,2,3]{Alejandra R. Enríquez}%
\author[4]{Md. Mamunur Rashid}%
\author[2,5]{Christopher Emrich}%
\affil[1]{Department of Civil, Environmental and Construction Engineering, University of Central Florida, Orlando, FL 32816, USA}%
\affil[2]{National Center for Integrated Coastal Research, University of Central Florida, Orlando, FL 32816, USA}%
\affil[3]{Institute for Environmental Studies (IVM), Vrije Universiteit Amsterdam, 1081 HV Amsterdam, the Netherlands}%
\affil[4]{Division of Coastal Sciences, School of Ocean Science and Engineering, University of Southern Mississippi, Ocean Springs, MS, 39564 USA}%
\affil[5]{School of Public Administration, University of Central Florida, Orlando, FL 32816, USA}%


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  \date{May 08, 2024}


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\begin{abstract}
Natural hazards such as floods, hurricanes, heatwaves, and wildfires
cause significant economic losses (e.g., agricultural and property
damage) as well as a high number of fatalities. Natural hazards are
often driven by univariate or multivariate hydrometeorological drivers.
Therefore, it is crucial to understand how and which hydrometeorological
variables (i.e., drivers) combine to contribute to the impacts of these
hazards. Additionally, when multiple drivers are associated with a
hazard, traditional univariate risk assessment approaches are
insufficient to cover the full spectrum of impact-relevant conditions
originating from different combinations of multiple drivers. Based on
historical socioeconomic loss data, we develop an impact-based approach
to assess the influence of different hydrometeorological drivers on the
impacts caused by different hazard event types. We use the Spatial
Hazard Events and Losses Database for the United States (SHELDUS) to
identify the historical hazard events that caused socioeconomic impacts
(property and crop damage, injuries, and fatalities) in our case study
area, Miami-Dade County, in south Florida. For 9 different hazard types,
we obtained data for 13 hydrometeorological drivers from historical
in-situ observations and reanalysis products corresponding to the timing
and locations of the hazard events found in the SHELDUS database. The
relative importance of each hazard driver in generating impacts and the
frequency of multiple drivers was then assessed. We found that many
high-impact events were caused by multiple hydrometeorological drivers
(i.e., compound events). For example, 61\% of the recorded flooding
events were compound events rather than univariate hazards and these
contributed 99\% of total property damage and 98.2\% of total crop
damage in Miami-Dade County. For several hazards, such as
hurricanes/tropical storms and wildfires, all the events that caused
damage are classified as compound events in our framework. Our findings
emphasize the benefit of including socioeconomic impact information when
analyzing hazard events, as well as the importance of analyzing all
relevant hydrometeorological drivers to identify compound events.%
\end{abstract}%



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