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NSFDirectorate for Geosciences

Collaborative Research: FIRE-MODEL: Impacts of rapid shifts of moisture availability on regional landscapes, forest hydrology and flammability

Active
Institution
North Carolina State University, NC
Principal investigator
Katherine Martin
Funding
$1.5M
Duration
2026–2029
Open portfolio

Moonbase score

Still being scored

Abstract

This project will investigate the impacts of rapid shifts between extreme wet to extreme dry weather on fuel loading and consequent wildfire risk. Throughout the project, stakeholders look to co-develop and test fire-adaptive management policies against established forest management, with the ultimate goal of reducing wildfire risk and improving safety in rural and WUI communities. Additional broader impacts of the project include the training of two graduate students and one postdoctoral fellow to address these complex challenges and to continue advancing the science of wildfires in the Southeast United States and other humid forest regions. Wildfire dynamics in humid forests, including the Southern Appalachian Mountains are complex and not well understood. Fuel flammability and loading are likely the key drivers of fire ignition and spread, which are dependent on factors including forest disturbances and ecosystem-atmospheric moisture dynamics. This project focuses on the fire risk posed by rapid oscillations between moisture extremes occurring in a short period of time (weeks to months). The central hypothesis is that hydroclimatic rapid oscillations increase fire risk by first causing forest disturbances (such as downed trees and debris accumulation) during extreme wet and stormy events that will rapidly become fuel in subsequent drought conditions. Thus, the objectives include a characterization of these hydroclimatic events and their large-scale drivers, as well as their relationship with observed fires. Field experiments will simulate fuel drying following disturbances, which will be complemented with fuel moisture mapping and modeling using remote Earth observation data and geocomputational approaches. Lastly, the LANDIS-II forest dynamics model will be used to produce scenarios of fire spread and severity under different hydroclimatic conditions determined in collaboration with stakeholders. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Research team

  • Katherine MartinPI
  • Robert SchellerCo-PI
  • Andrew C OishiCo-PI
  • Katia FernandesCo-PI
  • Joshua M GrayCo-PI

LOADING MOONBASE SCORE

Directorate for GeosciencesArtificial Intelligence (AI)INTERDISCIPLINARY PROPOSALSFIRE-Wildland FireFire Science InnovationsSEA LEVEL CHANGESforestwildfireextremeoscillationsmoisturefueldisturbanceswet

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