Rachel Davidson
Professor, Civil and Environmental Engineering; Core Faculty, Disaster Research Center | University of Delaware
Newark, DE, UNITED STATES
Prof. Davidson conducts research on natural disaster risk modeling and civil infrastructure systems.
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Biography
Rachel Davidson is a Professor in the Department of Civil and Environmental Engineering and a core faculty member in the Disaster Research Center at the University of Delaware. After completing her B.S.E. from Princeton University and M.S. and Ph.D. from Stanford University, she spent two years at the University of North Carolina at Charlotte, then six years at Cornell University, both as an Assistant Professor of Civil Engineering. Following a year as a Visiting Assistant Professor at Columbia University, she joined the faculty at the University of Delaware and the Disaster Research Center in 2007. She was a Visiting Professor and Erskine Fellow at the University of Canterbury in Christchurch, New Zealand for the 2013-14 academic year.
Davidson conducts research on natural disaster risk modeling and civil infrastructure systems. Her work involves developing new engineering models to better characterize the impact of future natural disasters, and use that understanding to support decisions to help reduce future losses. It focuses particularly on lifelines (e.g., electric power, water supply) and risk from a regional perspective; on earthquakes and hurricanes. Problems in this field typically involve a great deal of uncertainty, a long time horizon, multiple and competing objectives, and sometimes numerous and conflicting constituencies. They are often spatial and dynamic, and the technical aspects must be understood in the social, economic, political, and cultural contexts in which they exist.
She is a Fellow and Past-President of the Society for Risk Analysis, winner of the 2019 ASCE Charles Martin Duke Lifeline Earthquake Engineering Award, and past-Chair of the Executive Committee of the ASCE Technical Council on Lifeline Earthquake Engineering (TCLEE). Davidson is a 2016 Fellow of the Executive Leadership in Academic Technology and Engineering (ELATE at Drexel ) program. She has been a mentor for the NSF-funded Career Enhancement of Academic Women in Earthquake Engineering (ENHANCE) program and the NSF-funded “Enabling the Next Generation of Hazards and Disaster Researchers” program.
Industry Expertise (1)
Public Safety
Areas of Expertise (4)
Disaster Research
Natural Disaster Risk Modeling
Civil Infrastructure Systems
Lifelines
Media Appearances (2)
COE associate dean for diversity | UDaily
University of Delaware online
2016-09-16
“We’re at a good starting point,” Davidson says. “Our main two tasks right now are to look at the data we have to see where we are in terms of recruitment and retention and then to inventory what we’ve already done to see what has worked and what hasn’t. Once we see where our real challenges are, we can be more strategic moving forward.”
UD professor studies post-quake fires in Japan
University of Delaware online
2011-08-22
“We try to learn as much as possible from every real-life event that happens. Post-earthquake fires, in particular, are understudied despite the fact that they can dominate the losses in an event,” says Davidson.
Articles (5)
Effects of Roof Shape and Roof Pitch on Extreme Wind Fragility for Roof Sheathing
Journal of Structural Engineering2023 Wind fragility curves for roof sheathing were developed for single-family building models to investigate the effects of roof shape and roof pitch on the wind performance of roof sheathing. For gable roofs, it was found that more complex roof shapes are more likely to suffer roof sheathing damage when subjected to high winds. The probability of no roof sheathing failure can be up to 36% higher for a simple gable roof than for a complex gable roof. For hip roofs with different configurations, variation in roof shape has minimal effect on roof sheathing fragility. Roof pitch effects were also evaluated for 10 pitch angles, ranging from 14° to 45°. Results suggest that for roof pitches smaller than 27°, the effects of this angle are more substantial on the performance of gable roofs than on hip roofs. For gable roofs, the probability of no roof sheathing failure can be up to 23% higher for a 23° roof pitch than that for an 18° roof pitch. Furthermore, the inclusion of complex roof shapes in a regional hurricane loss model for New Hanover County, North Carolina, accounted for a 44% increase in estimated annual expected losses from roof sheathing damages compared to a scenario in which all roofs are assumed to have rectangular roof shapes. Therefore, to avoid an underestimation of roof damages due to high-wind impact, the inclusion of complex roof geometries in hurricane loss modeling is strongly recommended.
Searching for signal and borrowing wi-fi: Understanding disaster-related adaptations to telecommunications disruptions through social media
International Journal of Disaster Risk Reduction2023 Disaster events can expose the vulnerability of telecommunications infrastructure to service disruptions. During these traumatic events, when connectivity is most needed, it sometimes takes days, or even weeks or months, for normal service to return. Affected people and communities attempt to adapt to these disruptions in creative ways, but this can lead to changing demands on other parts of the infrastructure. To understand the societal impacts of disasters and inform disaster preparation and response, it can be valuable to understand these behavior changes. In this research, we look to social media (Twitter) to provide insight into how people in Puerto Rico adapted to extended telecommunications disruptions after Hurricane Maria in September 2017. First, to address the challenge of limited signal within the noise of online discourse, we articulate an approach for using machine learning to detect adaptations to telecommunication disruptions in a massive Twitter dataset. Next, using a grounded approach, we developed and applied a qualitative coding scheme that revealed the different ways that people adapted to disruptions in cell service, Wi-Fi access, and electricity for their communication devices. Some of these adaptations demonstrate affected people's willingness to go to great lengths to access telecommunication services, and shifts in how people relied in new ways upon existing infrastructure — e.g. as schools become a place to charge devices. These findings offer empirical insights about how people adapt to telecommunications disruptions as well as methodological contributions around using social media as a signal for informing disaster research and response.
Household impacts of interruption to electric power and water services
Natural Hazards2023 Critical infrastructure systems derive their importance from the societal needs they help meet. Yet the relationship between infrastructure system functioning and societal functioning is not well-understood, nor are the impacts of infrastructure system disruptions on consumers. We develop two empirical measures of societal impacts—willingness to pay (WTP) to avoid service interruptions and a constructed scale of unhappiness, compare them to each other and others from the literature, and use them to examine household impacts of service interruptions. Focusing on household-level societal impacts of electric power and water service interruptions, we use survey-based data from Los Angeles County, USA, to fit a random effects within-between model of WTP and an ordinal logit with mixed effects to predict unhappiness, both as a function of infrastructure type, outage duration, and household attributes. Results suggest household impact increases nonlinearly with outage duration, and the impact of electric power disruptions is greater than water supply disruptions. Unhappiness is better able to distinguish the effects of shorter-duration outages than WTP is. Some people experience at least some duration of outage without negative impact. Increased household impact was also associated with using electricity for medical devices or water for work or business, perceived likelihood of an emergency, worry about an emergency, past negative experiences with emergencies, lower level of preparation, less connection to the neighborhood, higher income, being married, being younger, having pets, and having someone with a medical condition in the house. Financial, time/effort, health, and stress concerns all substantially influence the stated level of unhappiness.
Mitigation insights from emergency managers on working with stakeholders
Journal of Emergency Management2023 Emergency managers have the important responsibility of planning and implementing mitigation policies and programs to reduce losses to life and property. To accomplish these goals, they must use limited time and resources to ensure the communities they serve have adequately mitigated against potential disasters. As a result, it is common to collaborate and coordinate with a wide variety of partner agencies and community organizations. While it is well established that strengthening relationships and increasing familiarity improve coordination, this article advances that narrative by providing direct insights on the ways a select group of local, state, and federal emergency managers view relationships with other mitigation stakeholders. Using insights from a 1-day workshop hosted at the University of Delaware to gather information from mitigation stakeholders, this article provides a discussion of commonalities and challenges workshop participants identified with other stakeholder groups. These insights can inform other emergency managers about potential collaborators and coordination opportunities with similar stakeholders in their own communities.
Household adaptations to infrastructure system service interruptions
Journal of Infrastructure Systems2022 When critical infrastructure system services are disrupted, households typically respond by reducing, delaying, or relocating their demand (e.g., delaying laundry), or augmenting supply (e.g., using a generator). While this phenomenon is well known, there has been little systematic empirical investigation of it. Focusing on electric power and water service interruptions and using revealed and stated preference survey data from Los Angeles County, California, we develop 24 mixed logit models, one each to predict the probability an individual undertakes a specified adaptation as a function of outage duration and characteristics of the individual. The analysis aims to determine: (1) how common different household adaptations are; (2) how adaptation implementation varies with infrastructure type, outage duration, and uses of the service; (3) what household characteristics are associated with implementation of different adaptations; and (4) how adaptations tend to occur together. The percentage of individuals who report doing an adaptation varies greatly across adaptations and outage durations, from 2% to 88%. In general, adaptations that require moving out of the home are the least common of those investigated. For electric power outages, adaptations that could be done at home are less likely as the outage duration increases, while those that require going somewhere are more likely as the duration increases. For water outages, all adaptations (except delaying consumption) are more likely as an outage lasts longer. Using electric power or water for medical devices and/or work and business has a large effect on the likelihood of implementing many adaptations. Preevent conservation habits are also associated with an increased likelihood of implementing adaptations. The influence of household characteristics varies greatly across adaptations. There is evidence that some adaptations tend to occur together (e.g., using water from lakes and the government) and others tend not to (e.g., delaying electricity use and going to a hotel).
Accomplishments (5)
ASCE Charles Martin Duke Lifeline Earthquake Engineering Award (professional)
2019
Fellow of the Executive Leadership in Academic Technology and Engineering (ELATE at Drexel ) (professional)
2016
Visiting Erskine Fellow, Department of Civil and Natural Resources Engineering, University of Canterbury (professional)
2014
Fellow, Society for Risk Analysis (professional)
2011
Best Paper Award, Society for Risk Analysis, Risk Analysis Journal (professional)
2007
Education (3)
Stanford University: PhD, Civil Engineering 1997
Stanford University: MS., Civil Engineering 1994
Princeton University: BSE, Civil Engineering 1993
Links (4)
Languages (1)
- English
Event Appearances (5)
Probabilistic framework for modeling spatially distributed infrastructure
(2018) QuakeCORE Annual Meeting Taupo, New Zealand
An Integrated Scenario-based Evacuation (ISE) Framework for Hurricane Evacuation Modeling
(2016) Society for Risk Analysis Annual Meeting
Post-earthquake fires in the March 2011 Japan earthquake and tsunami. Japan and New Zealand RAPIDs and Research Needs Workshop
(2012) National Science Foundation Arlington, VA
Risk-based regional hurricane evacuation planning
(2011) Society for Risk Analysis Annual Meeting Charleston, SC
Evolving regional natural disaster risk in the international development context
(2011) Society for Risk Analysis Annual Meeting Charleston, SC
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