Mapping Resilience in Vermont’s 2023 Flood-Response Networks
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In July 2023 Vermont’s Green Mountains were soaked by days of rain, leading to seepage, undercutting, and saturation in what’s now called The Great Floods of 2023. Though Vermont’s communities are accustomed to smaller scale flooding, this flood has rapidly become a key marker of change and danger in collective memory.
This project collaborates with community members, formal responders, and mutual aid volunteers in the Black River Valley to gather ethnographic and geographic data on flooding impacts and responses.
One of our team members collaborated with local mutual aid groups in summer 2023 during the aftermath of the Great Floods and noted a gap:
community members and formal responders do not have easy ways to communicate and collaborate across scales of experience, data, and insight.
Our project begins in this gap. We frame floods as simultaneously social, technical, and natural events which require diverse data for understanding and response. We combine ethnographic and geographic research with engineering and physical sciences data to improve understanding of flood impacts and community resilience.
We hope to use this data to develop a pilot version of a community-driven, accessible mapping tool, designed for communication and collaboration before, during and after inland flooding events. The map will serve as a site through which communication about risk, response, and recovery can more easily pass “up and down scale” among diverse responders, addressing the observed gap in communications and response capacities among different groups of responders and improving resilience.
The impact of these gaps is most evident in tools for communications about risk and recovery—who has access, who really uses them, what is represented in them, and how they are updated them are specific concerns. Our team conducts basic social scientific and geographic research to revise critical understanding of floods as social, technical, and natural phenomena that must be addressed at multiple simultaneous levels.