Abstract
Emergency managers (EMs) need nuanced data that contextualize the local-scale risks and impacts posed by major storm events (e.g. hurricanes and nor’easters). Traditional tools available to EMs, such as weather forecasts or storm surge predictions, do not provide actionable data regarding specific local concerns, such as access by emergency vehicles and potential communication disruptions. However, new storm models now have sufficient resolution to make informed emergency management at the local scale. This paper presents a Participatory Action Research (PAR) approach to capture critical infrastructure managers concerns about hurricanes and nor’easters in Providence, Rhode Island (USA). Using these data collection approach, concerns can be integrated into numerical storm models and used in emergency management to flag potential consequences in real time during the advance of a storm. This paper presents the methodology and results from a pilot project conducted for emergency managers and highlights implications for practice and future academic research.
Highlights
A Participatory Action Research approach is used to capture subject matter expert concerns from major storm events that can be integrated into numerical storm models for emergency management.
This paper presents a standardized approach for capturing facility manager concerns that contains rich, actionable information that is relevant to the emergency management community.
This paper describes a process for working with facility and emergency managers across sectors and organizations to collaborate in the emergency management process for a major city.
The results of this study can be used to enhance emergency management and response by providing emergency managers with actionable information for local scale planning and response during a major storm event.
Funding source: Science and Technology Directorate
Award Identifier / Grant number: 15STCRC00001-06-01
Funding source: U.S. Department of Homeland Security
Award Identifier / Grant number: 2015-ST-061-ND0001-01
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Research Funding: This material is based upon work supported by the U.S. Department of Homeland Security under Grant Award Number 2015-ST-061-ND0001-01. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied, of the U.S Department of Homeland Security.
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