Coastal Hazards Analysis Modeling and Prediction: Collaborative Model-Driven Multi-hazard Forecasting and Planning

  • Peter Stempel
  • , Austin Becker
  • , Isaac Ginis
  • , Samual Adams
  • , Greg Bonynge
  • , Deborah Crowley
  • , Chris Damon
  • , Noah Hallisey
  • , Olivia Krum
  • , Aimee Mandeville
  • , Kyle McElroy

Research output: Contribution to journalArticlepeer-review

Abstract

The Coastal Hazards Modeling and Prediction System (CHAMP) provides real-time hazard impact forecasts for wind, waves, storm surge and flooding in advance of landfalling tropical cyclones (hurricanes) and winter storms (nor’easters) and also functions as a scenario planning tool. We developed CHAMP in collaboration with emergency and facility managers and other diverse end users to meet their needs in the face of increasingly variable extreme storm conditions, where past storms do not necessarily provide a model for future impacts. We describe CHAMP’s functioning, focusing on how the system works as a co-produced "boundary object", a shared point of interaction around which diverse interest holders shape their perceptions uncertainty and the underlying analysis. We argue that this characteristic of the system makes it a model for interactive planning tools that allow end users to manipulate model parameters and outcomes to facilitate environmental planning. While beneficial, and essential to CHAMPs functioning, we also recognize that this degree of engagement also presents challenges to scaling the system.

Original languageEnglish (US)
Pages (from-to)268-277
Number of pages10
JournalJournal of Digital Landscape Architecture
Volume2025
Issue number10
DOIs
StatePublished - 2025

All Science Journal Classification (ASJC) codes

  • Geography, Planning and Development
  • Architecture
  • Computer Science Applications
  • Nature and Landscape Conservation

Fingerprint

Dive into the research topics of 'Coastal Hazards Analysis Modeling and Prediction: Collaborative Model-Driven Multi-hazard Forecasting and Planning'. Together they form a unique fingerprint.

Cite this