Deciphering the impact of uncertainty on the accuracy of large wildfire spread simulations

Abstract

Predicting wildfire spread is a challenging task fraught with uncertainties. 'Perfect' predictions are unfeasible since uncertainties will always be present. Improving fire spread predictions is important to reduce its negative environmental impacts. Here, we propose to understand, characterize, and quantify the impact of uncertainty in the accuracy of fire spread predictions for very large wildfires. We frame this work from the perspective of the major problems commonly faced by fire model users, namely the necessity of accounting for uncertainty in input data to produce reliable and useful fire spread predictions. Uncertainty in input variables was propagated throughout the modeling framework and its impact was evaluated by estimating the spatial discrepancy between simulated and satellite-observed fire progression data, for eight very large wildfires in Portugal. Results showed that uncertainties in wind speed and direction, fuel model assignment and typology, location and timing of ignitions, had a major impact on prediction accuracy. We argue that uncertainties in these variables should be integrated in future fire spread simulation approaches, and provide the necessary data for any fire model user to do so.

Revisiting Wildland Fire Fuel Quantification Methods: The Challenge of Understanding a Dynamic, Biotic Entity

“…The capture of such variation necessitates a large number of sampling plots, resulting in trade-offs between the level of detail measured at a sampling unit and the number of sampling units that can be collected. To resolve this requires an understanding of the sensitivities of fire models to the relevant inputs (e.g., [89,90]), although ideally this would be driven by fundamental fire theory [91].…”

Determining Fire Dates and Locating Ignition Points With Satellite Data

“…The impact of ignition location uncertainty has been shown to significantly affect simulated fire patterns [16]. Benali, et al [59] used satellite-derived ignitions to model fire growth and found that the uncertainty associated with ignition location had a large impact on the accuracy of simulations, while the impact of the uncertainty associated with ignition date/hour was relatively low.…”

Assessment of crown fire initiation and spread models in Mediterranean conifer forests by using data from field and laboratory experiments

“…Arca et al, 2007;Duguy et al, 2007;González-Olabarría et al, 2012;Jiménez et al, 2016;Oliveira et al, 2016;Madrigal et al, 2017). Nevertheless, crown fire models have not been tested by experimental burns in Mediterranean conditions and the predictions may therefore be misleading (Cruz & Alexander, 2010;Benali et al, 2016), leading to the application of inappropriate forest and fire management activities.…”