Modeling of Physically-Based Predictive Fire Events in A Virtual Environment from Geospecific Data
Abstract
Climate change and corresponding extreme weather events, such as wildfires, present significant threats to personnel and critical infrastructure on military installations and the communities in which they live. The inherent dynamic and unpredictable nature of wildfires makes it imperative to develop robust frameworks for understanding and managing wildfire risk. This thesis addresses this urgency by developing a computational technique to simulate wildfire impacts through virtual modeling using geospatial data.Using a fast-running fire modeling software, HFIRE, surface fire spreads are simulated on the fictional continent of Dystopia. A Monte Carlo simulation is conducted to analyze wildfire events, assess fire spread,and evaluate direct and indirect impacts to a designated military installation. Model excursions consider how potential climate change consequences affect these impacts.The findings underscore that drier conditions invariably result in increased fire severity and more frequent impacts to the military installation. Furthermore, it enables the identification of high-risk areas subject to wildfires. These results can facilitate enhanced preventive measures and more effective emergency responses, thereby minimizing the vulnerability of military installations to wildfires in an era of climate change.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 01, 2023
- Accession Number
- AD1224692
Entities
People
- Nicholas E Hardesty
Organizations
- Naval Postgraduate School