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Gina Tonn
Researcher at Delaware Department of Natural Resources and Environmental Control
Publications - 13
Citations - 179
Gina Tonn is an academic researcher from Delaware Department of Natural Resources and Environmental Control. The author has contributed to research in topics: Flood myth & Flooding (psychology). The author has an hindex of 7, co-authored 10 publications receiving 106 citations. Previous affiliations of Gina Tonn include Johns Hopkins University & University of Pennsylvania.
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Journal ArticleDOI
An Agent-Based Model of Evolving Community Flood Risk
Gina Tonn,Seth D. Guikema +1 more
TL;DR: This study lends insight into priorities for future work, including the development of more in-depth behavioral and decision rules at the individual and community level, as well as a new modeling approach for integrating behavior, policy, flood hazards, and engineering interventions.
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Cyber risk and insurance for transportation infrastructure
TL;DR: Results indicate that the annual number of transport-related companies affected by cyber incidents and the associated costs are on the rise, and insurance purchase can be an important risk management strategy to allow transportation infrastructure systems to recover from cyber incidents.
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U.S. transportation infrastructure resilience: Influences of insurance, incentives, and public assistance
TL;DR: In this paper, the authors identify barriers to and opportunities for lowering transportation-related disaster losses and for improving infrastructure risk management including the need for better data and metrics to support resilience.
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Hurricanes and Power System Reliability-The Effects of Individual Decisions and System-Level Hardening
TL;DR: A validated power-outage forecasting model is used in conjunction with an agent-based model to characterize how a community’s likelihood of losing power in repeated hurricanes is affected by the complex interactions among individuals’ behavioral responses in whether to engage in personal or collective action.
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Hurricane Isaac: A Longitudinal Analysis of Storm Characteristics and Power Outage Risk.
TL;DR: This analysis provided insight on how rainfall and storm surge, along with wind, contribute to power outages in hurricanes and indicates that inclusion of other covariates, particularly precipitation, may improve model accuracy and robustness across a range of storm conditions and geography.