Leveraging national forestry data repositories to advocate wildfire modeling towards simulation-driven risk assessment

Abstract

Los incendios forestales son más disruptivos año tras año. El incremento de su impacto es acompañado de un desarrollo paralelo en los recursos computacionales y el acceso público a bases de datos forestales masivas. En este estudio se propone una metodología de "enjambre de modelos" para estudiar los incendios haciendo hincapié en los datos existentes en España. Como contribución, se ha desarrollado un Autómata Celular que modela la evolución espacio temporal de un incendio real (GIF Cocentaina, 2012), del que se derivan intervalos de confianza de la superficie quemada empleando para el modelado de la incertidumbre los datos del Mapa Forestal Español, la cobertura LiDAR del Proyecto Nacional de Ortofotografía Aérea y el Inventariado Forestal Nacional.

Modeling wildfire dynamics is complex and challenging due to the multiple scales involved in fire propagation, from physical–chemical processes to the interaction with topography and meteorological conditions. To provide reliable indicators of the risk of an ongoing wildfire, models aimed at informing policy-making should quantify the primary sources of uncertainty in their predictions. In this paper, we introduce a novel methodology built on top of Cellular Automata to assess the impact of uncertainty by implementing wildfire ensemble modeling using data from the Spanish National Forestry Data Repositories. Uncertainty is embedded in the model considering the ±2σ deviations from the medians of linear regressions of the canopy stratum with LiDAR metrics as explainable variables. The relevance of dynamic meteorological conditions in contrast to static environment conditions is analyzed. Our results suggest that an accurate account of the fuel model, including time-dependent wind and moisture maps, is mandatory to provide reliable predictions. Using a real case study (Concentaina’s extreme wildfire), we also illustrate the importance of assessing the impact of the firefighters’ mitigation efforts.