Pam Rubinoff, right, and Dr. Austin Becker, second from right, instruct participants in a June training on preparation for “Hurricane Rhody.” Photo via the University of Rhode Island.

Coastal Hazards Analysis, Modeling, and Prediction System for Emergency Planning, Management, and Response

Pam Rubinoff, right, and Dr. Austin Becker, second from right, instruct participants in a June training on preparation for “Hurricane Rhody.” Photo via the University of Rhode Island.

Community

Coastal Hazards Analysis, Modeling, and Prediction System for Emergency Planning, Management, and Response

Expansion to USCG and State of CT

Summary

This Year 10 Project will scale and develop the Coastal Hazards Analysis, Modeling, and Prediction (CHAMP) system, developed in Years 1-9, for two new end user groups:

  1. Emergency management decision-makers and planners in Connecticut through a partnership with the Connecticut Department of Environmental and Energy Protection (CT DEEP)
  2. United States Coast Guard (USCG) for assessment of risk to their facilities in Connecticut, Rhode Island, and Massachusetts including USCG Sector Southeastern New England and portions of Sector Long Island Sound.

CHAMP Overview

Emergency managers need access to relevant, local-scale information about potential storm consequences of extreme storm events in advance of a storm’s landfall. This project leverages advancements in ADvanced CIRCulation (ADCIRC) storm modeling developed concurrently by the Isaac Ginis project. The Coastal Hazards Analysis, Modeling, and Prediction (CHAMP) system integrates critical infrastructure facility managers’ expertise of storm impacts in the same way that “damage functions” are traditionally used to model the structural or economic impact of storm events. By identifying wind/surge/wave/flooding thresholds for asset failure, concerns are linked to storm model predictions for near real-time or planning applications. The system can be applied in both real-time emergency management and for planning exercises. End-user participation in data collection makes outputs directly relevant to emergency managers as they allocate resources and anticipate the impacts of an imminent storm.

Investigators

Dr. Austin Becker
Dr. Austin Becker
University of Rhode Island
Pam Rubinoff
Pam Rubinoff
University of Rhode Island

Other Research Participants/Partners

  • Christopher Damon, Research Associate IV, URI Environmental Data Center
  • Aimee Mandeville, Research Associate IV, URI Environmental Data Center
  • Gregory Bonynge, Research Associate IV, URI Environmental Data Center
  • Isaac Ginis, Prof., URI Graduate School of Oceanography
  • Peter Stempel, Assoc. Prof., Penn State University
  • Sam Adams, PhD Candidate Marine Affairs & URI Director of Emergency Management
  • Kyle McElroy, PhD Candidate, URI Marine Affairs
  • Noah Hallisey, PhD Candidate, URI Marine Affairs