Representing 3-dimensional fuels for physics-based fire behavior models: A general framework and case study in a type-converted post-fire shrubfield

Abstract

Background Physics-based three-dimensional (3D) fire behavior models improve planning for prescribed fire application and wildfire mitigation, but require high spatial resolution 3D fuel models as inputs. While multiple methods and data sources for realistically representing 3D, heterogeneous fuels are available, no unifying framework exists to guide the use of these tools to create 3D fuel models across gradients of vegetation characteristics and data availability. Existing data and methods are most uncertain for mid-level fuels (e.g., shrubs and small trees), due to canopy obstruction of remotely sensed data and a relative lack of modeling efforts. Yet, mid-level fuels are especially important as potential ladder fuels and increasingly common as the dominant fuel in type-converted, post-fire, shrub-dominated landscapes. Results Here we introduce the Framework for Representing 3D Fuels (FR3D), a general framework for combining multiple data sources and methods to construct 3D fuel models for forested and unforested landscapes. We then demonstrate FR3D in a case study to build a 3D fuelbed model in a post-fire, shrub-dominated landscape using three new methods for deriving mid-level shrub fuels from: (1) Airborne Laser Scanning (ALS), (2) imputation of Terrestrial Laser Scanning (TLS), and (3) generative modeling of TLS. We compare the resulting fuel models and examine how they affected simulated 3D fire behavior using QUIC-Fire. While each method represented the broad landscape patterning of shrubs, differences in shrub loading, height, and cover highlighted advantages and drawbacks of the different methods. Modeled fire behavior was realistic for all fuel representation methods, but rate of spread and fine fuel consumption was sensitive to the different arrangements of shrubs. Conclusions The sensitivity of fire behavior to shrub modeling methods emphasizes the need for fuel models that faithfully represent local fuelbed characteristics and conditions, and highlights the value in testing a range of modeled fuels to understand the potential range of prescribed fire outcomes. FR3D and novel methods of modeling mid-level fuel provide a foundation for tool integration efforts and increased site-specificity of fuel representation for physics-based fire models.