Coupling the Biophysical and Social Dimensions of Wildfire Risk to Improve Wildfire Mitigation Planning

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/113114/1/risa12373.pd

Social Vulnerability to Large Wildfires in the Western USA

Federal land managers in the US can be informed with quantitative assessments of the social conditions of the populations affected by wildfires originating on their administered lands in order to incorporate and adapt their management strategy to achieve a more targeted prioritization of community wildfire protection investments. In addition, these assessments are valuable to socially vulnerable communities for quantifying their exposure to wildfires originating on adjacent land tenures. We assessed fire transmission patterns using fire behavior simulations to understand spatial variations across three diverse study areas (North-central Washington; Central California; and Northern New Mexico) to understand how different land tenures affect highly socially vulnerable populated places. Transboundary wildfire structure exposure was related to populations with limited adaptive capacity to absorb, recover and modify exposure to wildfires, estimated with the Social Vulnerability Index using US Census unit data (block groups). We found geographic heterogeneity in terms of land tenure composition and estimated fire exposure. Although high social vulnerability block groups covered small areas, they had high population and structure density and were disproportionately exposed per area burned by fire. Structure exposure originated primarily from three key land tenures (wildland-urban interface, private lands and national forests). Federal lands proportionately exposed, on an area basis, populated places with high social vulnerability, with fires ignited on Forest Service administered lands mostly affecting north-central Washington and northern New Mexico communities

Archetypes of Community Wildfire Exposure from National Forests of the Western US

Risk management typologies and their resulting archetypes can structure the many social and biophysical drivers of community wildfire risk into a set number of strategies to build community resilience. Existing typologies omit key factors that determine the scale and mechanism by which exposure from large wildfires occur. These factors are particularly important for land managing agencies like the US Forest Service, which must weigh community wildfire exposure against other management priorities. We analyze community wildfire exposure from national forests by associating conditions that affect exposure in the areas where wildfires ignite to conditions where exposure likely occurs. Linking source and exposure areas defines the scale at which crossboundary exposure from large wildfires occurs and the scale at which mitigation actions need to be planned. We find that the vast majority of wildfire exposure from national forests is concentrated among a fraction of communities that are geographically clustered in discrete pockets. Among these communities, exposure varies primarily based on development patterns and vegetation gradients and secondarily based on social and ecological management constraints. We describe five community exposure archetypes along with their associated risk mitigation strategies. Only some archetypes have conditions that support hazardous fuels programs. Others have conditions where managing community exposure through vegetation management is unlikely to suffice. These archetypes reflect the diversity of development patterns, vegetation types, associated fuels, and management constraints that exist in the western US and provide a framework to guide public investments that improve management of wildfire risk within threatened communities and on the public lands that transmit fires to them

Managing Wildfire Risks: Effects on Water Resources With and Without Fuel Treatment

We work down through various scales to provide an overview of risk assessment tools that use landscape characteristics, fire behavior, and values at risk that help identify fuel treatment priority areas

Assessing wildland fire risk transmission to communities in northern Spain

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.This work was funded by a University of Lleida Research training fellowship to Fermín J. Alcasena Urdíroz

Exploring and Testing Wildfire Risk Decision-Making in the Face of Deep Uncertainty

We integrated a mechanistic wildfire simulation system with an agent-based landscape change model to investigate the feedbacks among climate change, population growth, development, landowner decision-making, vegetative succession, and wildfire. Our goal was to develop an adaptable simulation platform for anticipating risk-mitigation tradeoffs in a fire-prone wildland– urban interface (WUI) facing conditions outside the bounds of experience. We describe how five social and ecological system (SES) submodels interact over time and space to generate highly variable alternative futures even within the same scenario as stochastic elements in simulated wildfire, succession, and landowner decisions create large sets of unique, path-dependent futures for analysis. We applied the modeling system to an 815 km2 study area in western Oregon at a sub-taxlot parcel grain and annual timestep, generating hundreds of alternative futures for 2007–2056 (50 years) to explore how WUI communities facing compound risks from increasing wildfire and expanding periurban development can situate and assess alternative risk management approaches in their localized SES context. The ability to link trends and uncertainties across many futures to processes and events that unfold in individual futures is central to the modeling system. By contrasting selected alternative futures, we illustrate how assessing simulated feedbacks between wildfire and other SES processes can identify tradeoffs and leverage points in fire-prone WUI landscapes. Assessments include a detailed “post-mortem” of a rare, extreme wildfire event, and uncovered, unexpected stabilizing feedbacks from treatment costs that reduced the effectiveness of agent responses to signs of increasing risk

Objective and perceived wildfire risk and its influence on private forest landowners’ fuel reduction activities in Oregon’s (USA) ponderosa pine ecoregion

Policymakers seek ways to encourage fuel reduction among private forest landowners to augment similar efforts on federal and state lands. Motivating landowners to contribute to landscape-level wildfire protection requires an understanding of factors that underlie landowner behaviour regarding wildfire. We developed a conceptual framework describing landowners’ propensity to conduct fuel reduction as a function of objective and subjective factors relating to wildfire risk. We tested our conceptual framework using probit analysis of empirical data from a survey of non-industrial private forest landowners in the ponderosa pine (Pinus ponderosa) region of eastern Oregon (USA). Our empirical results confirm the conceptual framework and suggest that landowners’ perceptions of wildfire risk and propensity to conduct fuel treatments are correlated with hazardous fuel conditions on or near their parcels, whether they have housing or timber assets at risk, and their past experience with wildfire, financial capacity for conducting treatments and membership in forestry and fire protection organisations. Our results suggest that policies that increase awareness of hazardous fuel conditions on their property and potential for losses in residential and timber assets, and that enhance social networks through which awareness and risk perception are formed, could help to encourage fuel reduction among private forest landowners.Keywords: wildland–urban interface, landscape models, non-industrial private forest landowners, wildfire risk, fuel treatment

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