Ocean state rising: Storm simulation and vulnerability mapping to predict hurricane impacts for Rhode Island’s critical infrastructure

Samuel Adams; Austin Becker; Kyle McElroy; Noah Hallisey; Peter Stempel; Isaac Ginis; Deborah Crowley

doi:10.5055/jem.0801

Authors

Samuel Adams, MPA
Austin Becker, PhD https://orcid.org/0000-0001-9224-7913
Kyle McElroy, PE
Noah Hallisey, MS
Peter Stempel, PhD https://orcid.org/0000-0002-0000-4154
Isaac Ginis, PhD https://orcid.org/0000-0002-1074-4308
Deborah Crowley, MS

DOI:

https://doi.org/10.5055/jem.0801

Keywords:

hazard impacts, storm consequences, coastal hazards, vulnerability assessment, risk management, decision support tools, participatory action research, implementation research

Abstract

Predicting the consequences of a major coastal storm is increasingly difficult as the result of global climate change and growing societal dependence on critical infrastructure (CI). Past storms are no longer a reliable predictor of future weather events, and the traditional approach to vulnerability assessment presents accumulated loss in largely quantitative terms that lack the specificity local emergency managers need to develop effective plans and mitigation strategies. The Rhode Island Coastal Hazards Modeling and Prediction (RI-CHAMP) system is a geographic information system (GIS)-based modeling tool that combines high-resolution storm simulations with geolocated vulnerability data to predict specific consequences based on local concerns about impacts to CI. This case study discusses implementing RI-CHAMP for the State of Rhode Island to predict impacts of wind and inundation on its CI during a hurricane, tropical storm, or nor’easter. This paper addresses the collection and field verification of vulnerability data, along with RI-CHAMP’s process for integrating those data with storm models. The project deeply engaged end-users (emergency managers, facility managers, and other stakeholders) in developing RI-CHAMP’s ArcGIS Online dashboard to ensure it provides specific, actionable data. The results of real and synthetic storm models are presented along with discussion of how the data in these simulations are being used by state and local emergency managers, facility owners, and others.

Author Biographies

Samuel Adams, MPA

University of Rhode Island, Department of Marine Affairs, Kingston, Rhode Island

Austin Becker, PhD

Associate Professor and Chair of Marine Affairs, University of Rhode Island, Department of Marine Affairs, Kingston, Rhode Island

Kyle McElroy, PE

University of Rhode Island, Department of Marine Affairs, Kingston, Rhode Island

Noah Hallisey, MS

University of Rhode Island, Department of Marine Affairs, Kingston, Rhode Island

Peter Stempel, PhD

Penn State University, College Station, Pennsylvania

Isaac Ginis, PhD

University of Rhode Island, Graduate School of Oceanography, Narragansett, Rhode Island

Deborah Crowley, MS

University of Rhode Island, Graduate School of Oceanography, Narragansett, Rhode Island

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