The overall goal of this project is to improve the representation of combustion processes in coupled fire-atmosphere models operating at the landscape level. Models intended to be used for landscape-scale fires (hundreds of meters to 10s of kilometers), typically divide the simulation domain up into a mesh of grid cells and these grid cells typically range in size from 1 to 30 meters on a side. As the processes governing combustion occur on considerably smaller scales, models require a means of describing these processes that is both capable of dealing with heterogeneity within a cell and scalable if the cell size is changed. A detailed examination of these combustion processes will improve our understanding of fine-fuel heat exchange, ignition, and fire spread and how fire behavior may be affected by fuel conditions. The specific objectives of the project are to:
This project consists of a combination of field experiments and model simulations. The field experiments will focus on intensive measurements of small 4- by 4-meter blocks. Fuels will be sampled using a combination of standard destructive sampling of representative plots outside of the 4- by 4-meter plots and non-destructive sampling and photogrammetry techniques to characterize within plot fuel structure and variability. Fuel moisture and consumption measurements will use remote sensing techniques. For fuel moisture a technique developed for satellites will be used to estimate surface moisture content for use in numerical weather prediction models. This technique will involve using an infrared camera to track changes in fuel temperature, which along with measurements of incoming solar radiation, air temperature, and sensible heat flux will enable solving the surface energy budget for the latent heat flux. This will allow an estimation of surface moisture content. Additional infrared remote sensing techniques developed in the laboratory to estimate fire radiative power and fuel consumption will be adapted to measuring natural fuels.
These two techniques combined will track sub-meter scale changes in fuel moisture and consumption. A critical part of these techniques is estimating the flow field through the plot, as this is important for calculating the sensible heat flux as well as determining the influence of wind on combustion rates. The small plot size will facilitate locating three-dimensional sonic anemometers close to the plot edge. Sonic anemometers will be used to provide turbulence characteristics important to the coupled fire-atmosphere model. These wind measurements will be augmented with flow estimates obtained through image analysis of both visible and infrared imagery.
The modeling component of the study examines the parametric sensitivity of the subgrid-scale models used to represent combustion processes in coupled fire-atmosphere models. Probability density functions are often used to represent subgrid variability, which is not typically know in detail from the field or explicitly resolved because of computational constraints. Such subgrid models have long been acknowledged as a key to model versatility and their refinement is critical to enable the use of these models in a wider range of scenarios and fire scales; however, field observations of adequate resolution or completeness have not been available to accomplish this refinement. The sub-meter scale measurements of the field experiments will provide essential data for examining these functions.
The majority of fire model validation studies focus on comparing simulated fire perimeters to what was observed. Although this may serve as a first cut at validation, it raises the question of whether the model is getting the right answer for the right reason. Only by looking at the small-scale processes can we gain confidence in the model. This study seeks to examine fuel moisture dynamics and consumption at the sub-meter scale to facilitate improved representations of combustion in fire-spread models operating at the landscape scale. This project will benefit Department of Defense managers by: (1) improving our understanding of fuel moisture dynamics, (2) improving our understanding of how fuel heterogeneity impacts fire behavior, and (3) improving the representation of combustion processes in coupled fire-atmosphere models.