Meteorology Commons^™

Multifidelity Prediction In Wildfire Spread Simulation: Modeling, Uncertainty Quantification And Sensitivity Analysis, Mario Miguel Valero, Lluís Jofre, Ricardo Torres

Faculty Research, Scholarly, and Creative Activity

Wildfire behavior predictions typically suffer from significant uncertainty. However, wildfire modeling uncertainties remain largely unquantified in the literature, mainly due to computing constraints. New multifidelity techniques provide a promising opportunity to overcome these limitations. Therefore, this paper explores the applicability of multifidelity approaches to wildland fire spread prediction problems. Using a canonical simulation scenario, we assessed the performance of control variates Monte-Carlo (MC) and multilevel MC strategies, achieving speedups of up to 100x in comparison to a standard MC method. This improvement was leveraged to quantify aleatoric uncertainties and analyze the sensitivity of the fire rate of spread (RoS) to …