Wildfire Hazard and Risk Assessment

Wildfire risk can be perceived as the combination of wildfire hazards (often described by likelihood and intensity) with the susceptibility of people, property, or other valued resources to that hazard. Reflecting the seriousness of wildfire risk to communities around the world, substantial resources are devoted to assessing wildfire hazards and risks. Wildfire hazard and risk assessments are conducted at a wide range of scales, from localized to nationwide, and are often intended to communicate and support decision making about risks, including the prioritization of scarce resources. Improvements in the underlying science of wildfire hazard and risk assessment and in the development, communication, and application of these assessments support effective decisions made on all aspects of societal adaptations to wildfire, including decisions about the prevention, mitigation, and suppression of wildfire risks. To support such efforts, this Special Issue of the journal Fire compiles articles on the understanding, modeling, and addressing of wildfire risks to homes, water resources, firefighters, and landscapes

A user-centred design framework for disaster risk visualisation

Visualisations are powerful communication tools that have the potential to help societies assess and manage natural hazard and disaster risks. However, the diversity of risk management contexts and user characteristics is a challenge to develop understandable and useable visualisations. We conducted a systematic literature review to understand the current state developing disaster risk visualisations following design best practices and accounting for the heterogeneity between end-users and disaster risk contexts. We find that, despite being widely recommended, tailoring visualisations to users through the process of user-centred design remains a relatively unexplored topic within disaster risk. To address this, we present a unifying user-centred design framework for disaster risk visualisation, based on existing visualisation frameworks. The framework contains three phases: the Define phase, which aims to define and characterise the disaster risk management context and end-user group who will benefit from a visualisation; the Design phase, which is highly iterative and presents an opportunity to test how users interpret different design elements; and the Refine phase, which focuses on evaluating how users understand, respond to, and make decisions based on the visualisation. The framework is sufficiently flexible to be applied to any disaster risk management and natural hazard context to identify challenges and design effective disaster risk visualisations that are understandable and useable

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

Integrating geospatial wildfire models to delineate landscape management zones and inform decision-making in Mediterranean areas

Despite the abundant firefighting resources deployed to reinforce the fire exclusion policy, extreme events continue to cause substantial losses in Mediterranean regions. These catastrophic wildfires question the merely-reactive response, while science-based decision-making advocates for a paradigm shift towards a long-term solution to coexist with fire. Comprehensive management solutions integrate multiple efforts to minimize the number of escaped wildfires in fire ignition hotspots, restrict large fire spread across the landscape, and prevent losses to valued resources and assets. This study develops a wildfire management zone (WMZ) delineation framework to inform decision-making in fire-prone Mediterranean landscapes. First, we combined modeling outcomes of wildfire occurrence, initial attack success, and wildfire transmission to communities to segment the landscape in WMZ blocks. We assumed the worst-case scenario in terms of fire simultaneity and weather conditions to implement the models. The geospatial outcomes were assembled and classified into four primary archetypes, and we then designated the most suitable risk mitigation strategies for each management unit. The WMZs included (1) comprehensive management, (2) human ignition prevention, (3) intensive fuel management, and (4) fire reintroduction areas. Finally, we downscaled within zones to assign specific management prescriptions to the different areas. The results were presented in a set of cross-scale maps to assist in designing risk management plans and raise social awareness. The methodological framework developed in this study may be valuable to help mitigate risk in fire-prone Mediterranean areas, but also in other regions in which similar total suppression policies fail to reduce catastrophic wildfire losses.This work has been financed by the Spanish Ministry of Economy and Competitiveness, postdoctoral ‘Juan de la Cierva Formación’ research grant (FJCI-2016-31090) awarded by Marcos Rodrigues. The work was partially funded by the projects FirEUrisk “DEVELOPING A HOLISTIC, RISK-WISE STRATEGY FOR EUROPEAN WILDFIRE MANAGEMENT”. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101003890; and CLIMARK “Forest management promotion for climate mitigation through the design of a local market of climatic credits” (LIFE16 CCM/ES/000065)

GIS-based methodology for prioritization of preparedness interventions on road transport under wildfire events

Climate change is leading to a rise in the occurrence and intensity of wildfires, exacerbated by the growing encroachment of communities into the natural environment, posing challenges to our global capacity to respond to wildfires. During wildfire events, road transport infrastructure becomes crucial for the evacuation of people and accessibility to an emergency by first responders. Nevertheless, resilience management of transportation infrastructure affected by wildfires is poorly considered, despite its relevant role and high exposure to wildfires. Therefore, this study proposes a new methodology to estimate the priority level for wildfire preparation by combining exposure and criticality of road transportation infrastructure to wildfire hazards with consideration of different wildfire categories. The analysis is conducted at the system level considering interdependencies and redundancies among infrastructure components and using a geographic information system (GIS) to automate the modelling process and visualization of results. The proposed methodology is applied to a case study in the Leiria region of Portugal, demonstrating its utility in prioritizing economic resources and decision-making for areas requiring preparation. This approach can serve as a resilience-based tool for decision-making, supporting the implementation of effective adaptation strategies to enhance wildfire resilience.This work was partly financed by FCT/MCTES through national funds (PIDDAC) under the R&D Unit Institute for Sustainability and Innovation in Structural Engineering (ISISE), under reference UIDB/04029/2020, and under the Associate Laboratory Advanced Production and Intelligent Systems ARISE under reference LA/P/0112/2020. This work is financed by national funds through the Foundation for Science and Technology (Fundaç˜ao para a ciˆencia e tecnologia, FCT, Portugal), under grant agreement 2020.05755.BD attributed to the first author

Enhancing infrastructure resilience in wildfire management to face extreme events: Insights from the Iberian Peninsula

Factors such as human activity and climate change are contributing to an increase in the frequency and intensity of wildfires. This problem has challenged society’s knowledge, response capacity, and resilience, revealing its inadequacy to cope with the new wildfire regime characterized by extreme wildfire events (EWE). Policies on wildfire management mainly focus on suppression and managing emergencies, which may be insufficient to reduce EWE’s incidence and cope with its impact. Consequently, there is a lack of tools to support decision-making in wildfire management in other important aspects, such as prevention and protection. This study examines global wildfire policies specifically in the Iberian Peninsula (Portugal and Spain), including cross-border policies. A GIS-based tool to evaluate different normal and extreme wildfire management policies is applied to a cross-border case study, paying attention to the impact on critical land-based transport systems. A relevant outcome of the tool application is that suppression must be complemented with other wildfire management strategies in the analyzed area. The gained insights can help stakeholders to improve decision-making in wildfire management to successfully address EWE.This work was partly financed by FCT/ MCTES through national funds (PIDDAC) under the R&D Unit Institute for Sustainability and Innovation in Structural Engineering (ISISE), under reference UIDB/ 04029/2020 (doi.org/10.54499/UIDB/04029/2020), and under the Associate Laboratory Advanced Production and Intelligent Systems ARISE under reference LA/P/0112/2020

Developing a quick guide on presenting data and uncertainty

This paper describes the rationale, development and testing of a quick guide leaflet on the presentation of data and uncertainty. While tools for capturing, analysing and presenting data become more advanced, the fundamentals of presenting data with adequate context and clarity remain unchanged. The leaflet, aimed at scientists generating and presenting data, was created as part of an interdisciplinary collaboration (meteorologists, information designers, psychologists) working within the PURE Network project RACER, funded by the UK Natural Environment Research Council. A copy of the leaflet is included in this article

Does Updating Natural Hazard Maps to Reflect Best Practices Increase Viewer Comprehension of Risk?

In this study, we examine whether updating an interactive hazard map using recommendations from the literature improves user map comprehension. Analyses of experimental data collected from 75 university students revealed that map comprehension scores were not significantly better for those who viewed a “best practices” map compared to those who viewed an existing version. This may be because the existing map was itself better than most other interactive maps. Additionally, we found map comprehension levels to have significant positive relationships with objective tests, but not self-reported measures of spatial ability. Moreover, self-reported spatial ability had statistically significant, but only moderately strong, correlations with objective tests. These results indicate that spatial ability should be measured objectively rather than through self-reported methods in research on map comprehension. Further research is needed to examine the cognitive processes involved in hazard map comprehension, especially using a broader range of map characteristics and population segments with more diverse cognitive abilities

SIMULATING AND ASSESSING THE SOUTHERN PINE BEETLE SPOT GROWTH ON MANAGEMENT SCENARIOS USING GIS-BASED MODEL AND 3-D LANDSCAPE VISUALIZATION

Models for simulating southern pine beetle (SPB), Dendroctonus frontalis Zimm., population dynamics and infestation risk are quite well developed. However, most of them are not spatially explicit models. In this study, a GIS-based model, SPBSPOT, is developed for simulating SPB spot growth using ArcGIS software with ArcObject and Visual Basic for Application. SPBSPOT is built by five subroutines. Individual interfaces are developed for each of them to allow users the flexibility to specify stand situations and design management scenarios based on their individual needs. Although integrated pest management systems are currently adopted, SPB management is still challenging because of diverse land ownership, dynamic forest landscapes, and uncertainty of management strategy effects. We incorporate SPBSPOT into a three-dimensional (3-D) visualization by using the visual simulator Visual Nature Studio. 3-D landscape visualization is comprised of multi-spatial, multi-temporal, and multi-expression elements. Supplemented with geographic information system (GIS) databases, remote sensing images, and simulation models, this technique can provide a comprehensive communication medium for decision makers, scientists, and the public with diverse backgrounds on the SPB management. In chapters three and four, we generate GIS maps of possible infestations as the basis of 3-D visualizations to simulate spatial patterns of spot growth under a variety of management scenarios (i.e., thinning, stand restoration, and stand species mixture). In chapter five, SPBSPOT is used to evaluate the ecological and economic effects of salvage operations under four levels of damage severity. In chapter six, an integrated technique of GIS, historic remote sensing images, and 3-D visualization is used to construct a variety of realistic animations depicting effects following SPB infestations on different restoration scenarios (i.e., thinning and prescribed burning). The results indicate that 1) different silvicultural treatments are able to reduce the number of infested trees, but the overall impact on the affected area may not necessarily be changed, 2) thinning treatment responded best (i.e., least damage) to SPB infestation on forest restoration stands, while the thinning + burning treatment may have resulted in too much stress to increase the stand\u27s susceptibility, 3) salvage operation is not necessary for the light severity infestation, but it has critical effects for the higher severity ones. In conclusion, this well-organized GIS-based 3-D visualization can be used in the combination of complex information to enhance alternative management strategy evaluation

Understanding and Managing Wildfire Risks to Residential Communities and Supply Chain Networks

Wildfire has become an increasing threat to humans, the built environment, and ecosystems in the United States. Several factors contribute to such an increase in wildfire risk, including climate change, rapid population growth and infrastructure development at the wildland-urban interface, and accumulated fuels from past wildfire management practices. Increases in wildfire activity have resulted in substantial human and economic losses in the past decade. For example, the 2023 Hawaii wildfires razed more than 2,200 homes and businesses while tragically claiming the lives of at least 115 individuals. A series of California wildfires in 2015, 2017, and 2018 resulted in direct economic losses of $4.8 billion,$18 billion, and $26.3 billion, respectively. In addition to the direct economic losses, the 2018 California wildfires disrupted many supply chain systems, which propagated across the regional economy and induced$88.6 billion in direct losses. These recent wildfires have underscored the urgent need for understanding, assessing, and managing wildfire risks to residential communities and supply chains. To this end, this dissertation aims at understanding and managing wildfire risks to humans, properties, and the regional economy, with a particular focus on residential communities and supply chain networks. To advance our understanding of various proactive and emergency activities, this dissertation begins by examining homeowners’ decisions on wildfire-related proactive actions, such as home hardening, vegetation treatment, and homeowners insurance, through an online survey and subsequently assesses the effect of these actions on the process of housing recovery. Next, this dissertation shifts its focus towards individual behaviors during wildfire events, encompassing their preferences and decisions made during wildfire evacuations. This entails the study of factors like evacuation triggers and timing, as well as a series of en-route decisions made by residents in wildfire-prone areas, all gathered through an online survey. Based on the survey results, data-driven models are developed for predicting evacuees’ behaviors during wildfires. Furthermore, this dissertation integrates these data-driven predictive models with wildfire simulations, vulnerability assessment, and traffic simulation to construct a comprehensive agent-based modeling (ABM) framework for wildfire evacuations under damaged transportation settings. The framework is designed to simulate traffic conditions during a wildfire evacuation and identifies the critical parts of the transportation network for pre-fire risk mitigation actions aimed at improving mobility during a wildfire evacuation.To assess wildfire risk to a supply chain network, this dissertation also proposes a probabilistic wildfire risk assessment framework. It provides rigorous probabilistic descriptions of wildfire ignition likelihood and growth, interaction between supply chain components and wildfire, consequent component damage, and network-level performance reduction. Then, a hypothetical forest-residuals-to-sustainable-aviation-fuel supply chain network is utilized as an illustrative example to demonstrate the capability and applicability of the proposed framework. The proposed framework can be used as a planning tool to evaluate network performance subject to a set of what-if scenarios and the effect of pre- and post-wildfire risk mitigation measures.Overall, this dissertation provides valuable insights for understanding the inherent drivers of individual’s preference on both wildfire proactive actions and evacuation decisions. This information can serve as a foundation for increasing community resilience by helping policymakers and stakeholders to increase participation rates in proactive actions and the responsiveness to evacuation orders. Moreover, the simulation tools and quantitative frameworks developed in this dissertation provide valuable support for stakeholders and policymakers in forecasting post-wildfire performance and implementing more effective pre-event mitigation strategies. These adaptable tools and frameworks show potential for broader applications across various domains, including water distribution networks, transportation systems, and electric power grids, making them valuable assets in addressing the complex challenges posed by dynamic and interconnected systems