Wildfire spread, hazard and exposure metric raster grids for central Catalonia

We provide 40 m resolution wildfire spread, hazard and exposure metric raster grids for the 0.13 million ha fire-prone Bages County in central Catalonia (northeastern Spain) corresponding to node influence grid (NIG), crown fraction burned (CFB) and fire transmission to residential houses (TR). Fire spread and behavior data (NIG, CFB and fire perimeters) were generated with fire simulation modeling considering wildfire season extreme fire weather conditions (97th percentile). Moreover, CFB was also generated for prescribed fire (Rx) mild weather conditions. The TR smoothed grid was obtained with a geospatial analysis considering large fire perimeters and individual residential structures located within the study area. We made these raster grids available to assist in the optimization of wildfire risk management plans within the study area and to help mitigate potential losses from catastrophic events. (C) 2018 The Authors. Published by Elsevier Inc

Planning for Future Fire: Scenario Analysis of an Accelerated Fuel Reduction Plan for the Western United States

Recent fire seasons brought a new fire reality to the western US, and motivated federal agencies to explore scenarios for augmenting current fuel management and forest restoration in areas where fires might threaten critical resources and developed areas. To support this effort, we modeled the scheduling of an accelerated forest and fuel management scenario on 76 western US national forests. Specifically, we modeled a 10-year ramp up of current forest and fuel management that targeted the source of wildfire exposure to developed areas and simulated treatment in areas that accounted for 77% of the predicted exposure. We used a sample of 30 future fire seasons to understand how the plan might be impacted by wildfires and treatment. We found that once fully implemented more than 20% of simulated fires on national forests overlapped fuel treatments, and that roughly 20% of the projects were burned prior to their implementation, suggesting that any plan will undergo significant revision during implementation. Treated areas intersected by wildfire accounted for twice the exposure than nontreated areas that also burned. The study demonstrates the use of scenario planning to design a fuel treatment program that targets wildfire exposure to developed areas, and the methods pave the way for expanded use of scenario planning science to analyze and communicate large scale expansion of current forest and fuel management initiatives

Predicting Paradise: Modeling Future Wildfire Disasters in the Western US.

The 2018 Camp fire destroyed the town of Paradise, California and resulted in 82 fatalities, the worst wildfire disaster in the US to date. Future disasters of similar or greater magnitude are inevitable given predicted climate change but remain highly uncertain in terms of location and timing. As with other natural disasters, simulation models are one of the primary tools to map risk and design prevention strategies. However, risk assessments have focused on estimation of mean values rather than predicting extreme events that are increasingly becoming a reality in many parts of the globe. Using the western US as a study area, we synthesized newer wildfire simulation and building location data (54 million fires, 25 million building locations) and compared the outputs to several sources of observed exposure data. The simulations used synchronized weather among spatial simulation subunits, thereby providing estimates of extreme fire seasons, fire events within them, and exceedance probabilities at multiple scales. We found that annual area burned was accurately replicated by simulations but building exposure was substantially overestimated, although the relatively small historical sample size might have influenced the comparison. We identified extreme fire seasons in the simulation record (10,000 fire years) that exceeded historical fire seasons by 278% in terms of area burned, and 1255% in terms of buildings exposed, under contemporary climate. Simulated building exposure peaked in specific regions along gradients of building density and burnable fuels. The study is the first to explore large scale extreme wildfire exposure in terms of both annual variability and magnitude, providing a broad foundation of methods to advance wildfire disaster prediction