Calculating Distributions of 3D Litter Layers with Numerical Simulations
Abstract
Wildfires have increased in size and severity over the past 20 years. All modeling tools to predict fire behavior require characterizing vegetation according to properties that affect combustion. Many wildfire models parameterize the fuel litter in terms of depth and fuel load at the stand scale, but fuel properties vary significantly at much finer scales that drive fire spread along the flanks and back of the fires. Because of challenges with measuring the fine-scale details of the litter, its heterogeneity is typically ignored at these finer scales. This impacts the application of high resolution coupled fire-atmospheric spread models. To address this challenge, we used Blender, a 3D modeling software, to construct physically consistent litter layers by simulating needles falling to the forest floor. The resulting complex litter is then voxelized to compute values for the net surface area to volume ratio, fuel height, bulk density, and porosity within each cell. The goal is to construct distributions of realistic fuel maps that can be used to better understand fire propagation on the forest floor. Such synthetic fuel models show significant promise to bridge scales from submeter to stand level that drive variation in fire behavior.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2019
- Bibcode:
- 2019AGUFMNH23C1024R
- Keywords:
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- 0305 Aerosols and particles;
- ATMOSPHERIC COMPOSITION AND STRUCTURE;
- 3322 Land/atmosphere interactions;
- ATMOSPHERIC PROCESSES;
- 0468 Natural hazards;
- BIOGEOSCIENCES;
- 0485 Science policy;
- BIOGEOSCIENCES;
- 1630 Impacts of global change;
- GLOBAL CHANGE;
- 4337 Remote sensing and disasters;
- NATURAL HAZARDS