We used spatial optimization to allocate and prioritize prescribed fire treatments in the fire-prone Bages County, central Catalonia (northeastern Spain). The goal of this study was to identify ...suitable strategic locations on forest lands for fuel treatments in order to: 1) disrupt major fire movements, 2) reduce ember emissions, and 3) reduce the likelihood of large fires burning into residential communities. We first modeled fire spread, hazard and exposure metrics under historical extreme fire weather conditions, including node influence grid for surface fire pathways, crown fraction burned and fire transmission to residential structures. Then, we performed an optimization analysis on individual planning areas to identify production possibility frontiers for addressing fire exposure and explore alternative prescribed fire treatment configurations. The results revealed strong trade-offs among different fire exposure metrics, showed treatment mosaics that optimize the allocation of prescribed fire, and identified specific opportunities to achieve multiple objectives. Our methods can contribute to improving the efficiency of prescribed fire treatment investments and wildfire management programs aimed at creating fire resilient ecosystems, facilitating safe and efficient fire suppression, and safeguarding rural communities from catastrophic wildfires. The analysis framework can be used to optimally allocate prescribed fire in other fire-prone areas within the Mediterranean region and elsewhere.
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•Prescribed fire treatment optimization for reducing wildfire risk is challenging.•We designed a multi-objective treatment mosaic for a fire-prone Mediterranean area.•We used an optimization program to explore trade-offs among competing objectives.•Results can be used to evaluate ongoing projects and improve long-term efficiency.•Spatial optimization can guide investments on large landscape management projects.
Southern European countries rely largely on fire suppression and ignition prevention to manage a growing wildfire problem. We explored a more wholistic, long-term approach based on priority maps for ...the implementation of diverse management options aimed at creating fire resilient landscapes, restoring cultural fire regimes, facilitating safe and efficient fire response, and creating fire-adapted communities. To illustrate this new comprehensive strategy for fire-prone Mediterranean areas, we developed and implemented the framework in Catalonia (northeastern Spain). We first used advanced simulation modeling methods to assess various wildfire exposure metrics across spatially changing fire-regime conditions, and these outputs were then combined with land use maps and historical fire occurrence data to prioritize different fuel and fire management options at the municipality level. Priority sites for fuel management programs concentrated in the central and northeastern high-hazard forestlands. The suitable areas for reintroducing fires in natural ecosystems located in scattered municipalities with ample lightning ignitions and minimal human presence. Priority areas for ignition prevention programs were mapped to populated coastal municipalities and main transportation corridors. Landscapes where fire suppression is the principal long-term strategy concentrated in agricultural plains with a high density of ignitions. Localized programs to build defensible space and improve self-protection on communities could be emphasized in the coastal wildland-urban interface and inner intermix areas from Barcelona and Gerona. We discuss how the results of this study can facilitate collaborative landscape planning and identify the constraints that prevent a longer term and more effective solution to better coexist with fire in southern European regions.
•We used modeled wildfire exposure to prioritize management alternatives in Catalonia.•Fuels treatments in forestlands were prioritized to create fire-resilient landscapes.•Lightning and pastoral fires were projected to restore cultural fire regimes.•We identified best municipalities for a safe and efficient wildfire response.•Promoting fire-adapted communities in highly exposed populated areas is a priority.
We assessed potential economic losses and transmission to residential houses from wildland fires in a rural area of central Navarra (Spain). Expected losses were quantified at the individual ...structure level (n = 306) in 14 rural communities by combining fire model predictions of burn probability and fire intensity with susceptibility functions derived from expert judgement. Fire exposure was estimated by simulating 50,000 fire events that replicated extreme (97th percentile) historical fire weather conditions. Spatial ignition probabilities were used in the simulations to account for non-random ignitions, and were estimated from a fire occurrence model generated with an artificial neural network. The results showed that ignition probability explained most of spatial variation in risk, with economic value of structures having only a minor effect. Average expected loss to residential houses from a single wildfire event in the study area was 7955€, and ranged from a low of 740 to the high of 28,725€. Major fire flow-paths were analyzed to understand fire transmission from surrounding municipalities and showed that incoming fires from the north exhibited strong pathways into the core of the study area, and fires spreading from the south had the highest likelihood of reaching target residential structures from the longest distances (>5 km). Community firesheds revealed the scale of risk to communities and extended well beyond administrative boundaries. The results provided a quantitative risk assessment that can be used by insurance companies and local landscape managers to prioritize and allocate investments to treat wildland fuels and identify clusters of high expected loss within communities. The methodological framework can be extended to other fire-prone southern European Union countries where communities are threatened by large wildland fires.
•Lightning efficiency in the triggering of wildfires is of one in ∼ 840 lightning.•Lightning-ignited fire distribution is not related to flash density but to land-use.•Most lightning fires flare up ...in the short term, latent fires above 24 h are rare.•The Ångström Index is an effective means to predict potential lightning fires.•Low-intensity lightning fires should be considered as a tool to reduce forest fuels.
In the present work, we analysed fuel moisture conditions during ignition, holdover, and detection of flaming combustion of lightning-ignited wildfires in Catalonia (north-eastern Spain) between 2003 and 2018. First, we identified the most probable lightning candidate for each wildfire, implementing a matching algorithm between historical lightning-caused fire data and cloud-to-ground lightning records. The bulk of lightning-fire ignitions (80%) occurred between June and September during the warm season. Conifer forests concentrate almost half of the lightning-ignited wildfires. Then, we spatially interpolated air temperature and relative humidity data from automatic weather stations to calculate a weather index describing the evolution of fuel moisture content at the specific wildfire location, from the time of the lightning-caused ignition to the time of the fire detection. Results showed that fuel moisture content drives lightning-ignited wildfires since most ignitions around midday turn into flaming combustion almost immediately, when fuel moisture content reaches the minimum of the day. The holdover duration increased in late afternoon lightning-ignited fires, which remain smouldering overnight and evolve to flaming combustion in the next solar cycle. We found that latent fires above 24 h were rare (15%), and only 3% of the fires had a holdover period above three days. Only 1 in ∼840 cloud-to-ground flashes started a wildland fire. Our outcomes provide valuable insight to improve the modeling and management of natural wildfires in the Mediterranean areas.
We provide the wildland urban interface (WUI) map of the autonomous community of Catalonia (Northeastern Spain). The map encompasses an area of some 3.21 million ha and is presented as a 150-m ...resolution raster dataset. Individual housing location, structure density and vegetation cover data were used to spatially assess in detail the interface, intermix and dispersed rural WUI communities with a geographical information system. Most WUI areas concentrate in the coastal belt where suburban sprawl has occurred nearby or within unmanaged forests. This geospatial information data provides an approximation of residential housing potential for loss given a wildfire, and represents a valuable contribution to assist landscape and urban planning in the region.
We used a fire simulation modeling approach to assess landscape scale wildfire exposure for highly valued resources and assets (HVR) on a fire-prone area of 680 km²located in central Sardinia, Italy. ...The study area was affected by several wildfires in the last half century: some large and intense fire events threatened wildland urban interfaces as well as other socioeconomic and cultural values. Historical wildfire and weather data were used to inform wildfire simulations, which were based on the minimum travel time algorithm as implemented in FlamMap. We simulated 90,000 fires that replicated recent large fire events in the area spreading under severe weather conditions to generate detailed maps of wildfire likelihood and intensity. Then, we linked fire modeling outputs to a geospatial risk assessment framework focusing on buffer areas around HVR. The results highlighted a large variation in burn probability and fire intensity in the vicinity of HVRs, and allowed us to identify the areas most exposed to wildfires and thus to a higher potential damage. Fire intensity in the HVR buffers was mainly related to fuel types, while wind direction, topographic features, and historically based ignition pattern were the key factors affecting fire likelihood. The methodology presented in this work can have numerous applications, in the study area and elsewhere, particularly to address and inform fire risk management, landscape planning and people safety on the vicinity of HVRs.
We implemented a fire risk assessment framework that combines spatially-explicit burn probabilities, post-fire mortality models and public auction timber prices, to estimate expected economic losses ...from wildfires in 155 black pine stands covering about 450ha in the Juslapeña Valley of central Navarra, northern Spain. A logit fire occurrence model was generated from observed historic fires to provide required fire ignition input data. Wildfire likelihood and intensity were estimated by modeling 50,000 fires with the minimum travel time algorithm (MTT) at 30m resolution under 97th percentile fire weather conditions. Post-fire tree mortality due to burning fire intensity at different successional stages ranged from 0.67% in the latest stages to 9.22% in the earliest. Stands showed a wide range of potential economic losses, and intermediate successional stage stands presented the highest values, with about 124€ha−1 on average. A fire risk map of the target areas was provided for forest management and risk mitigation purposes at the individual stand level. The approach proposed in this work has a wide potential for decision support, policy making and risk mitigation in southern European commercial conifer forests where large wildfires are the main natural hazard.
•We quantify economic losses from wildfires in black pine afforestation.•A fire modeling approach accounting for historic ignition probability and extreme fire weather was used to assess wildfire exposure at fine resolution.•We used successional stage specific response functions and timber prices.•Wildfire exposure and potential losses showed stand specific complex spatial patterns.•Results can help policy making and managing wildfire risk at individual stand level.
Wildfires are a growing threat to socioeconomic and natural resources in the wildland–rural–urban intermix in central Navarra (Spain), where recent fast-spreading and spotting short fire events have ...overwhelmed suppression capabilities. A fire simulation modeling approach based on the minimum travel time algorithm was used to analyze the wildfire exposure of highly valued resources and assets (HVRAs) in a 28,000 ha area. We replicated 30,000 fires at fine resolution (20 m), based on wildfire season and recent fire weather and moisture conditions, historical ignition patterns and spatially explicit canopy fuels derived from low-density airborne light detection and ranging (LiDAR). Detailed maps of simulated fire likelihood, fire intensity and fire size were used to assess spatial patterns of HVRA exposure to fire and to analyze large fire initiation and spread through source-sink ratio and fire potential index. Crown fire activity was estimated and used to identify potential spotting-emission hazardous stands. The results revealed considerable variation in fire risk causative factors among and within HVRAs. Exposure levels across HVRAs were mainly related to the combined effects of anthropic ignition locations, fuels, topography and weather conditions. We discuss the potential of fire management strategies such as prioritizing mitigation treatment and fire ignition prevention monitoring, informed by fine-scale geospatial quantitative risk assessment outcomes.
We provide 40m 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.
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.
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•We used wildfire simulation data to predict building exposure in the western US.•We examined the relative effect of building versus fuel density on exposure.•Maximum exposure was observed at building densities between 1400 and 1500 per km2.•Building-fuels density gradients into developed areas affected maximum exposure.•Annual building exposure in extreme fire seasons exceeded historical by 1255%.
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