MTTfireCAL Package for R—An Innovative, Comprehensive, and Fast Procedure to Calibrate the MTT Fire Spread Modelling System

Abstract

Fire spread behavior models are used to estimate fire behavior metrics, fire hazard, exposure, and risk across the landscape. One of the most widely used fire spread models is the minimum travel time (MTT), which requires a very time-consuming, interactive, trial-and-error calibration process to reproduce observed fire regimens. This study presents the MTTfireCAL package for R, a tool that enables fast calibration of the MTT fire spread models by testing and combining multiple settings and then ranking them based on the model’s capacity to reproduce historical fire patterns, such as fire size distribution and fire frequency. Here, we explain the main methodological steps and validate the package by comparing it against the typical calibration procedures in two study areas. In addition, we estimate the minimum number of fire runs required to ensure a reliable calibration. Overall, the use of MTTfireCAL R package and the optimization of the number of ignitions used allowed for a faster calibration of the MTT modeling system than the typical trial-and-error calibration. The MTT modeling system calibrated using MTTfireCAL was also able to better reproduce the historical fire patterns. This tool has the potential to support the academic and operational community working with MTT.

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“…The exposure estimation is dependent on reliable flame length (or fireline intensity) predictions. The recent calibration package developed by Aparício et al (2023) ensures that the model is well calibrated based on the spatial pattern of fire occurrrence and fire size distribution. However, due to the lack of observed fire behavior data it does not guarantee accurate estimates of rate-of-spread nor flame length.…”

“…The simulation system was calibrated for each study area considering the 2001-2022 period and performance was evaluated by comparing (i) the historical vs. estimated fire size distribution, and (ii) the spatial distribution of observed fire frequency vs. simulated burn probability. The recently developed MTTfireCAL Package for R (Aparício et al, 2023) was used to calibrate FConstMTT for each study area. Overall, FConstMTT was able to reproduce the observed historical fire patterns in all the study areas.…”