Abstract

Recent technological advances have yielded several high-complexity models for fire behavior. Low-intensity burns present difficulties in modeling due to a strong sensitivity to wind and fuels. This dissertation explores support research to improve representation of low-intensity fire in these high-complexity fire simulations. We focus on three areas: (i) data-driven modeling with a Spatially Extended Radiant heat Fire model (SERF), (ii) fuel heterogeneity with our model Distribution of Understory using Elliptical Transport (DUET), and (iii) research on whole system dynamics using chaos theory. To increase simulated resolution of low-intensity fire behavior, we employ an observational data set to develop SERF with spatial resolution on the order of ⇡ 0.05 m2, in contrast to the 1–2 m2 typical of the process-based models. SERF uses probability distributions to calculate radiant heat levels through a coupled map lattice which then inform a cellular automata model. In response to the need for more detailed surface vegetation maps, we develop a mechanistic model for estimating variation in surface vegetation called the Distribution of Understory using Elliptical Transport (DUET). DUET connects the canopy structure to the litter dispersal using ellipses based on tree species characteristics, wind data, and location-specific features, and then calculates grass growth and decomposition in the years since the last burn of the area. Finally, we investigate the sensitivity of a high complexity wildfire model, FIRETEC, using chaos theory. We develop 3900 one-dimensional time series from a FIRETEC simulation designed to represent low-intensity burning conditions. We test them using the Chaos 0-1 Test and an artificial neural network designed to distinguish between stochastic and deterministic series. By focusing on datadriven modeling, vegetation mapping, and broad-scale dynamics, our work adds essential support models and research to process-based fire models when representing low-intensity burns.

Publication Date

7-27-2024

Document Type

Dissertation

Student Type

Graduate

Degree Name

Mathematical Modeling (Ph.D)

Department, Program, or Center

Mathematical Sciences, School of

College

College of Science

Advisor

Anthony Vodacek

Advisor/Committee Member

Nishant Malik

Advisor/Committee Member

Niels Otani

Campus

RIT – Main Campus

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