Japan has a long history of multiple urban fires but far fewer wildland fires. Recently, Japan experienced several small wildland-urban interface (WUI) fires. Given the situation, the number may increase in the near future. When wildland fires reach communities, structure-to-structure fire spread, the same phenomena to both urban fires and WUI fires, will occur. Urban planning in Japan aimed to prevent large urban fire spread for decades, using strategies as wide roads, parks or non-flammable vegetation as fuel breaks. It is not clear these approaches are effective for the future WUI fire prevention in Japan. In this presentation, Japan’s approach to urban fire mitigation will be introduced in detail and how these approaches may or may not be applicable to WUI fire mitigation will be discussed.
How to cite: Suzuki, S. and Manzello, S. L.: Applying Urban Fire Mitigation Strategies to Wildland-Urban Interface Fires, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4032, https://doi.org/10.5194/egusphere-egu25-4032, 2025.
As wildfires increase both in frequency and intensity due to climate change, there is a pressing need to address the complex interactions between urban expansion and natural ecosystems. The paper explores the development of a novel framework aimed at enhancing resilience against wildfires, particularly focusing on the Wildland-Urban Interface (WUI) and associated infrastructures. The approach proposes an integration of forest, spatial, and physical resilience strategies, leveraging advanced simulation modeling and real-time data to optimize wildfire preparedness and response. While traditional wildfire management has often treated these elements in isolation, the proposed framework emphasizes a holistic strategy that encompasses not just the immediate but also the extended socio-ecological impacts of wildfires. By utilizing cutting-edge technologies including geospatial analysis and artificial intelligence, the framework aims to enhance predictive capabilities and streamline evacuation processes, thus safeguarding both human and environmental health. The implementation of this integrated system is designed to support the infrastructure's inherent resilience features, promoting sustainable urban planning and development. This contribution to wildfire resilience research underscores the critical need for comprehensive planning and collaborative efforts across disciplines, aiming to create a robust buffer against the evolving threat of wildfires in susceptible regions.
How to cite: Sakellariou, S., Mitoulis, S., Flannigan, M., Taylor, S., Tampekis, S., and Argyroudis, S.: Enhancing Wildfire Resilience: A Comprehensive Approach for the Wildland-Urban Interface and Infrastructure, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20461, https://doi.org/10.5194/egusphere-egu25-20461, 2025.
Wildfires are growing in intensity due to land-use changes and climate change impacts. 2023 ranked as the most destructive year for wildfires in the European Union since 2000, with over 500,000 hectares burned. As wildfire hazard increases, so does the need to prevent and mitigate wildfire risk, especially in interface areas where communities and the built environment are adjacent to or intermixed with wildlands. An emerging field of research focus is the Wildland-Industrial Interface (WII), where industrial buildings and infrastructures are at risk of potential wildfire exposure and damage.
In an effort to implement practical wildfire risk-reduction measures in Europe, the DG-ECHO-funded project FIREPRIME is working to deploy wildfire risk-reduction guidelines in three European interface pilot sites: in Austria, Sweden, and Spain. Each pilot site includes a critical infrastructure (an electrical substation, train rail network, and chemical storage facility, respectively) to consider in the risk-reduction guidance. Critical infrastructures, defined as facilities that provide essential services to society, are expected to face a tenfold increase in damages due to climate change by the end of the century, highlighting the urgent need for tailored risk reduction measures against natural hazards. The power grid has had numerous hazardous interactions with wildfires, both through igniting highly destructive wildfires and by experiencing significant damage and subsequent power supply disruptions. Recent examples include the highly destructive 2023 Maui wildfire, ignited by fallen power lines, and the largest wildfire in Texas history, which occurred in 2024, when a damaged utility pole caused power lines to ignite vegetation.
The Austrian critical infrastructure analyzed in this project is an electrical substation operated by the Austrian Power Grid, located in Haiming and nearly completely surrounded by an Alpine forest. Risk-reduction guidance and risk assessments methodologies for the electric power grid are reviewed to identify the most significant wildfire exposure mechanisms and damage modalities. The FireSmart Guidelines for Oil and Gas Industry from Canada are adapted and applied as an initial vulnerability assessment considering the local wildfire threat conditions, defensible space conditions, and location of vulnerable equipment. Available vulnerability assessments methodologies and preventative guidance are outlined to inform further risk-reduction measures.
The FIREPRIME project focuses on implementing already-developed mitigation measures for wildfire risk, by adapting them to European realities; this work is a contribution to increase the European power grid resilience against increasing wildfire threats in future years.
How to cite: Dossi, S., Papathoma-Köhle, M., Fuchs, S., Planas, E., and Pastor, E.: Wildfire Risk-Reduction Guidance for European Critical Infrastructure: Case Study of an Electrical Substation in Austria, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10265, https://doi.org/10.5194/egusphere-egu25-10265, 2025.
Global warming and land-use/land-cover changes, together with the expansion of the wildland-urban interface (WUI), have increased wildfire risk and exposure within Euro-Mediterranean countries. From a landscape-scale perspective, the scientific community has highlighted the interest of recovering the historical agro-forest mosaics to reduce wildfire risk within WUI areas by increasing land-cover discontinuity and fuel structure heterogeneity. Yet, up to date current and forecasted land-use change scenarios point out to the reverse pattern: i.e. an increasing abandonment of rural activities and forest encroachment. Furthermore, an increase in drought-driven tree mortality episodes is also occurring, potentially leading to changes in forest cover and in the amount of highly available fuels. However, it is unknown how the effects of drought events may interact with active landscape planning to reduce wildfire risk in the long-term.
Here, we analyze current and future fire connectivity patterns within the Barcelona Metropolitan Region (NE Spain), one of the most populated Mediterranean WUI areas. First, we assess the effect of different levels of drought-driven tree mortality episodes over fire connectivity in the long-term. Then, we analyze to which extent these disturbances combined with active landscape management strategies (LMS) can contribute to reduce fire connectivity.
We used a process-based model (MEDFATELAND) to simulate forest dynamics until 2050 under two climatic scenarios (low- vs high-drought). Next, we applied a circuit-based algorithm (OMNISCAPE) to model current (2020-2024) and future (2040-2050) fire connectivity (i.e. the spatial arrangement of areas with similar fuel properties that could facilitate contiguous fire spread). We analyzed drought effects over fire connectivity by comparing the results of both low- and high-drought climatic scenarios. Then, we analyze the effects on fire connectivity of drought impacts combined with three active LMS: (i) recovery of former agricultural lands recently abandoned, (ii) increase of current wood extraction rates under a bioeconomy-oriented strategy, and (iii) limited salvage-logging of drought-affected forest stands.
Overall, we observed a fire connectivity reduction in the long-term (2040-2050), passively mediated by high-drought climate effects (tree mortality) which ultimately diminish forests fine fuel loads. Regarding the active LMSs, we observed the greatest fire connectivity decrease by increasing land-cover discontinuity through the recovery of former agricultural areas. However, this LMS also produced fire connectivity increases in some areas that remained as fuel corridors between croplands. In contrast, a limited salvage-logging strategy in drought affected forest areas reduced wildfire connectivity through the whole study area by diminishing the amount of highly available fuels. Interestingly, we did not observe significant effects from an increased wood harvesting LMS, probably due to departing from extremely low current extraction rates within the study area. In conclusion, in this presentation we will explore through an innovative methodology to which extent passive (i.e. drought-driven tree mortality episodes) combined with active landscape management strategies can contribute to improve the prevention of large wildfire events in WUI areas.
How to cite: Balaguer-Romano, R., Espelta, J. M., Brotons, L., Aquilué, N., and De Cáceres, M.: Fire connectivity across the WUI: the interplay between increased drought events and active landscape management strategies, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4285, https://doi.org/10.5194/egusphere-egu25-4285, 2025.
The frequency of extreme wildfires has increased significantly, often exceeding the response capacity of civil protection systems. This trend is particularly worrying in the wildland-urban interface, where fires cause dramatic economic, social, and cultural losses, sometimes resulting in injuries and fatalities. One of the primary reasons for such devastating impacts is the widespread non-compliance with vegetation management regulations around buildings, which allows fires to spread easily to them. Also, large-scale wildfires concentrate impacts in specific regions, leading to their profound disruptions in both rural areas and particularly the wildland urban interface. The destruction of critical infrastructures and residential properties poses immense challenges for local authorities, who must address the needs of displaced citizens while managing complex and often inexistent or inefficient compensation mechanisms.
The current public processes for loss compensation, when established, are marked by significant inefficiencies and inequalities. Many citizens lack the knowledge or capacity to access available aid funds, while others exploit the system by claiming compensation beyond their actual losses. This imbalance often disadvantages those most in need, particularly individuals with lower education levels or limited access to information, thus increasing the impact on vulnerable persons and communities.
The insurance sector offers a potential solution to address these challenges. By tying insurance payments to wildfire risk – understood as the probability of damage multiplied by the potential loss value – citizens would have a financial incentive to adopt risk mitigation practices, such as vegetation management and fire-resistant construction methods and materials. Additionally, insured properties would shift the financial burden of recovery from governments to insurance companies, which are better prepared to manage compensation processes efficiently and equitably. This approach could reduce socio-economic disparities by ensuring fair compensation, regardless of an individual’s ability to navigate bureaucratic procedures. However, such policies must avoid disproportionately burdening rural communities or high-risk areas, as this could lead to depopulation and further vulnerability.
Considering these challenges, this study, with the cooperation of the Portuguese Insurers Association (APS), investigated the position of the insurance sector regarding wildfire risk in Portugal. A survey covering 93% of the dwelling insurance market explored the conditions under which insurers accept wildfire risk, the tools used to assess it, the factors influencing risk rejection, and the potential for adopting more inclusive wildfire risk coverage policies. The results indicated that most insurers tend to accept wildfire risk for strategically significant clients, excluding the general population. However, insurers expressed openness to revising their policies if supported by enhanced scientific tools and standardized risk mitigation frameworks with quantifiable results.
Policy and legal interventions are critical to ensure that financial burdens are distributed equitably, considering socio-economic factors and property usage. Adjustments could include favouring primary residences in rural areas over secondary homes in high-risk zones. While integrating insurance into wildfire risk management is promising, it requires coordinated efforts, including scientific advancements, robust risk mitigation strategies, and progressive policy development. Addressing these challenges will require a multifaceted approach to build more resilient communities and mitigate the growing impacts of wildfires.
How to cite: Almeida, M., Ribeiro, L. M., Lopes, D., and Oliveira Martins, I.: Enhancing wildfire risk management: the potential role of insurance policies in mitigating impacts , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19861, https://doi.org/10.5194/egusphere-egu25-19861, 2025.
Wildfire risks are projected to increase in the future due to climate change, coupled with increased exposure along the wildland-urban interface (WUI) due to population growth and growing cities.
This research presents a modelling framework for simulating potential risks posed by wildland fires to urban areas across the WUI via a multi-stage, loosely coupled approach:
Stage 1 - Wildfire: Using Spark, user-defined equations determine fire spread behaviour (Miller et al. 2015). To calculate Rate of Spread (RoS) and Fireline intensities for New Zealand vegetation types, equations from Pearce (2005) are applied. These, along with localised climate data for current and future conditions, create wildfire scenarios. Flame heights and radiant heat flux (RHF) are spatially analysed at each time-step to assess risks to transport networks, critical infrastructure, and buildings near or outside urban areas along the WUI.
Stage 2 – Building-to-building fire: With ignition points at urban boundaries defined, the second stage of the modelling framework uses a physics-based building-to-building fire spread model like that outlined in Himoto (2022) to simulate urban fire propagation over time. This, combined with wildfire model outputs, informs the risk assessment and micro-scale evacuation model.
Stage 3 – Ensemble risk assessment: Fire exposure from previous stages is used to assess risks to infrastructure and transportation networks. A method, adapted from Butler and Cohen (1998), defines RHF values and maps it to the transport network. This data informs the evacuation model, defining safe zones and low-risk evacuation corridors.
Stage 4 – Evacuation modelling: Building on work by Evans et al. (2020), the evacuation model integrates hazard outputs with micro-scale transport models to simulate evacuee movement under extreme scenarios. By incorporating movement restrictions and evacuee behaviours, it assesses risks to evacuees navigating the network.
Together, these four stages provide a comprehensive risk assessment of wildfires and key insights for refining evacuation planning strategies.
Acknowledgement
This project has received funding from the European Union's Horizon Europe research and innovation programme under the grant agreement number 101147385. Views and opinions expressed are however those of the authors only and do not necessarily reflect those of the European Union or CINEA. Neither the European Union nor the granting authority can be held responsible for them.
References
Butler, W, B., Cohen, D, J. (1998). Firefighter Safety Zones: A Theoretical Model Based on Radiative Heating International Journal of Wildland Fire 8(2) 73 – 77. https://doi.org/10.1071/WF9980073
Evans, B., Chen, A.S., Djordjevic, S., Webber, J., Gómez, A.G., and Stevens, J. (2020). Investigating the 421 effects of pluvial flooding and climate change on traffic flows in Barcelona and Bristol. Sustainability, 422 12(6), 2330. https://doi.org/10.3390/su12062330
Himoto, K. (2022). Large Outdoor Fire Dynamics – Fire Spread Simulation (pp 333 – 367). 1st Edition. CRC Press. http://dx.doi.org/10.1201/9781003096689-10
Miller, C., Hilton, J., Sullivan, A., Prakash, M. (2015). SPARK – A Bushfire Spread Prediction Tool. In: Denzer, R., Argent, R.M., Schimak, G., Hřebíček, J. (eds) Environmental Software Systems. Infrastructures, Services and Applications. ISESS 2015. IFIP Advances in Information and Communication Technology, vol 448. Springer, Cham. https://doi.org/10.1007/978-3-319-15994-2_26
Pearce, G. H. (2025). Appendix 3: Sub-contracted Report: Fuel Load and Fire Behaviour Assessments for Vegetation within LCDB2
How to cite: Evans, B., Valencia-Corea, A., Matthews, R., and Thompson, P.: A Holistic Modelling Framework for Assessing Risks of Wildfires Along the Wildland Urban Interface within New Zealand, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13937, https://doi.org/10.5194/egusphere-egu25-13937, 2025.
Wildfires in the Wildland-Urban Interface (WUI) are a rising problem in Europe, driven by lengthening hot, dry seasons in southern regions and the emergence of fire-prone zones in central and northern countries unprepared for large-scale wildfires. Climate change intensifies these challenges, underscoring the urgent need to enhance resilience and self-protection capabilities of WUI communities.
Although several EU initiatives have focused on improving community resilience to wildfires, their practical implementation and impact remain limited. These efforts are often isolated and localized, lacking integration into a cohesive, harmonized European strategy. This gap has left Europe without a unified framework for fostering fire-adapted communities capable of coexisting with wildfires. In contrast, international programs like FireSmart Canada and Firewise USA provide successful examples of global, community-centered approaches that could inspire European efforts.
The FIREPRIME project aims to address this gap by establishing the foundations for an EU-wide program to promote a culture of wildfire resilience among WUI communities, with a focus on civil protection. FIREPRIME is designing at pilot level the program architecture and governance, and is developing a comprehensive toolkit of resources that includes a smartphone app, guidelines, checklists, and educational materials aimed at enhancing wildfire resilience in three critical targets: households, communities, and infrastructure.
These tools are being piloted in three diverse European regions, each representing unique fire regimes, ecosystems, and population profiles: Collserola-Barcelona, Spain (Mediterranean Europe); Tyrol, Austria (Central Europe); and Gothenburg, Sweden (Northern Europe). This presentation will showcase the rationale behind FIREPRIME, its key tools, and initial results from pilot region collaborations, emphasizing the project's inclusive and regionally sensitive approach, which fosters active engagement with local stakeholders and WUI communities.
How to cite: Planas, E., Rodríguez, I., Cifre, M., Canaleta, G., Papathoma-Köhle, M., Fuchs, S., Sjöström, J., Vermina Plathner, F., Vacca, P., and Pastor, E.: On the need of a European program for wildfire-prepared communities – the FIREPRIME project, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6609, https://doi.org/10.5194/egusphere-egu25-6609, 2025.
This presentation will explore the development of a national approach to Wildfire Community Impact Research (WCIR) in Canada, emphasizing the need for a comprehensive framework to understand and address the evolving relationship between communities and wildfire events. The research proposes a structured methodology for evaluating the consequences of wildfires on communities, focusing on long-term resilience, recovery, and adaptation strategies. By synthesizing diverse datasets and experiences from various regions, the presentation advocates for a global framework that allows for consistent, comparative learning from wildfire-community interactions. This framework aims to facilitate cross-border collaboration, enabling policymakers, researchers, and communities to share knowledge, best practices, and lessons learned. The ultimate goal is to prepare societies for a future where wildfires are an inevitable and recurring challenge, fostering a more adaptive, fire-resilient global community.
How to cite: Winter, K., MacKinnon, B., and Baxter, G.: Fires of the Future: Building a Global Framework for Wildfire-Community Resilience, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4560, https://doi.org/10.5194/egusphere-egu25-4560, 2025.
With California facing ever-increasing losses due to wildfires, there is a need to examine all policy options in order to reduce risks and keep homes insurable. One recent action taken by the insurance commission has been to reward communities that engage in risk reduction activities through the Firewise USA program. While the state mandates insurers to give discounts to residents of participating communities, the effectiveness of this program has not been studied, and insurers cite this lack of study to provide very low and widely varying discounts. Here, we compare Firewise USA communities to similar communities that do not participate in a differences-in-differences design. We find that the probability that a community experiences a fire after becoming a Firewise USA site decreases by 12.5 percentage points, implying that insurance premiums should be reduced by about 6% in participating areas, compared to an average reduction of just 2.4%. Wealthier areas and those more exposed to fire risk are found to be more likely to join the Firewise USA program. The findings suggest that community risk reduction activities could play a key role in reducing losses for wildfires, but more could be done to increase the access to the program for poorer communities.
How to cite: Foreman, T.: Community Programs Support Wildfire Risk Reduction, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15881, https://doi.org/10.5194/egusphere-egu25-15881, 2025.
Forest fires play a crucial role in shaping the Mediterranean biome while posing a significant threat to highly fire-prone Southern European countries. Factors such as prolonged dry periods and fuel accumulation increase the frequency and intensity of wildfires. Fire risk in the Mediterranean Basin is exacerbated by climate change and future climate projections highlight the need for advanced fire risk mapping, monitoring, and management strategies.
The EU-funded FirEUrisk project addresses these challenges through an integrated approach to wildfire risk monitoring, leveraging Earth Observation (EO) data and remote sensing techniques. EO data, particularly from satellites, can effectively monitor fire risk parameters over extensive areas in a resource-efficient manner. Fuel type and model mapping are essential for wildland fire risk monitoring and emergency management, yet existing global and continental-scale thematic maps lack sufficient spatial detail, particularly in regions with heterogeneous vegetation.
This study focuses on developing a methodology to classify fuel types in Sardinia, Italy, a fire-prone pilot site for the FirEUrisk project. Sardinia, the second-largest island in the Mediterranean Basin, experiences prolonged wildfire seasons triggered by human activities and sustained by intense droughts.
Fuel type classification was achieved using machine learning (ML) models trained on Sentinel-2 time series. Input datasets included digital terrain models, vegetation indices, and canopy height estimates. Training and testing samples were collected via an on purpose developed web application, enabling experts to label 10 m x 10 m pixels using orthophotos, Google Street View, and vegetation indices time series. The ML models were trained with 80% of the dataset and tested with 20% and performance metrics such as precision, recall, and F1-score were computed.
This study demonstrated the feasibility of producing high-resolution (10m) fuel type maps for Sardinia using Sentinel-2 time series. However, the classification task remains challenging due to the structural complexity of vegetation in Mediterranean regions, leading to diverse fire behaviours and impacts. Future improvements include additional training samples collection, validation of the resulting classification, and the integration of vertical vegetation structure data, such as RADAR or LiDAR.
How to cite: Voltolina, D., Rajabi, F., Bordogna, G., Salis, M., and Stroppiana, D.: A machine learning approach for high-resolution fuel type mapping in Sardinia, Italy, using Sentinel-2 time series, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16811, https://doi.org/10.5194/egusphere-egu25-16811, 2025.
Aiming at addressing the uncertainty and socio-economic dimensions inherent in wildfire management, and to minimize the impact of wildfires through timely and informed decision-making, our research introduces an architectural framework for a software platform for Detection of Emerging Fire-related Situations and Response Process Management.
The event-driven architecture processes real-time, heterogeneous data from sources like satellite fire detection, meteorological stations, environmental sensors, and AI-enhanced UAV imagery. Events such as temperature anomalies or fire detections trigger dynamic response workflows. Modular, scalable components facilitate seamless ingestion, processing, and analysis of multi-source data. Algorithms model and predict fire behaviour, optimize resource allocation, and guide emergency response strategies. System outputs, including analytics, risk assessments, and situational hazards (e.g., endangered wildlife), are shared via dashboards, mobile apps, AR devices, and text messaging, ensuring broad accessibility.
The most prominent example of said interfaces is an OSM-based mapping tool that emphasizes intuitive navigation, interactive controls, and customizable data visualizations. It incorporates modular components that support real-time data visualization, fire risk assessment, and geospatial analysis. Key features include a user-defined data module enabling seamless integration of custom geospatial data, a non-fuel areas module designed to identify non-fuel zones, and a monitoring module offering comprehensive real-time wildfire surveillance.
The design of both the platform components and the user experience have been co-developed with domain experts, ensuring alignment with operational needs. These experts, including firefighters, environmental engineers, local authorities, and wildlife administrators, contributed to defining event patterns, scenarios, response workflows and feedback on usability, ensuring the system is tailored to real-world wildfire management challenges.
The architectural framework was validated within the TREEADS project, funded by the European Commission’s Horizon 2020 Programme. In particular, two field trials with distinct scenarios took place in Samaria Gorge, Crete, Greece, and the Sorrento Peninsula, Italy, aiming at demonstrating the system’s ability to improve established practices.
Keywords: software architecture; event-driven architectures; decision support system; response process management; remote sensing; data visualisation; mapping tools; real-time data processing; analytics; wildfire management system; real-time risk assessment; OpenStreetMap (OSM); real-time analytics; data stream processing; context-aware wildfire detection; situational awareness
This research has been carried out in the scope of the TREEADS project, which has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 101036926. The authors acknowledge valuable help and contributions from all partners of the TREEADS project.
How to cite: Zapounidis, K., Bantsos, A., Koidis, C., Aptalidis, I., Papadopoulos, K., Despotopoulou, A.-M., Christidis, K., Magoutas, B., Grillakis, E., Arampatzis, G., Phillis, A., Manoudakis, S., Pascale, C., Pacifico, A., Achillas, C., Aidonis, D., and Voulgarakis, A.: Leveraging Mapping Tools and Analytics for Advanced Wildfire Detection and Crisis Management, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1115, https://doi.org/10.5194/egusphere-egu25-1115, 2025.
Extreme Wildfire Events (EWE) exceeding control capacity are becoming a major environmental, economic and social threat, not only in fire-prone regions in Southern Europe, America and Oceania, but also in new areas such as Central and Northern Europe. The EU H2020 FIRE-RES project (https://fire-res.eu/) aims to provide Europe with the necessary capacity to avoid collapse in the face of EWE, which are projected to increase as the result of a harsher climate.
FIRE-RES is a 4-year project (2021–2025) whose scope is to effectively promote the implementation of a holistic fire management approach and support the transition towards more resilient landscapes and communities to EWE in Europe. FIRE-RES brings together a transdisciplinary, multi-actor consortium of 35 partners, formed by researchers, wildfire agencies, technological companies, industry and civil society from 13 countries, linking to broader networks in science and disaster reduction management. The project is implementing a total of 34 Innovation Actions across a set of eleven living labs representing different environments in Europe and Chile. These Innovation Actions are framed within 5 topics: Ecosystem Conservation and Landscape design; Emergency, Risk Mapping and Sustainable Fire Management Models; Economic drivers, Incentives and Insurance Solutions; Governance, Society, Communication and Risk Awareness; and Advanced Technology Solutions - Support Tools for Integrated Fire Management. Its final mission is to boost the socio-ecological transition of the European Union towards a fire-resilient continent by developing a stream of innovative actions.
In its last year, the FIRE-RES consortium is already having results from the implementation of its 34 Innovation Actions. In this talk, selected results related to disaster risk reduction, climate change adaptation, innovations in disaster management, and critical infrastructure protection will be presented.
How to cite: Brunet-Navarro, P., Garcia-Gonzalo, J., and Trasobares, A.: Innovative solutions for fire resilient territories in Europe. Preliminary results from FIRE-RES project, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11257, https://doi.org/10.5194/egusphere-egu25-11257, 2025.
In this study, we present a map of 84 landscape fuel classes for Ukraine, parameterized according to the widely used Fuel Characteristic Classification System (FCCS). The developed fuel map has a resolution of approximately 30 meters and is relevant for 2021. Two-step methodology for the classification and mapping of landscape fuel was applied. Initially, general fuel types were defined using data on land use/land cover, canopy height, and forest/shrub percent cover. These fuel types were then divided into the final number of classes. To this end, we processed catalogues with descriptions of biotopes and species diversity for each ecoregion of Ukraine, and involved Digital Elevation Model data, hydrological basins data and geospatial information on settlements. FCCS includes a large amount of input parameters, enabling the calculation of fire potential and a number of important fire behaviour parameters. Unfortunately, there are no sufficient measurements to parameterize all of input characteristics for the created fuel classes, or fuelbeds according to the FCCS. However, most parameters were managed to reproduce using various information sources, including field surveys, catalogues of biotopes, ecological literature, digital photo series etc. Other parameters (mainly surface woody fuels and duff) were extracted from the corresponding fuelbeds existing in the Fuel Fire Tools (FFT, fire management application that integrates several modules, including FCCS) database. General description and climate type specification along with previously defined parameters were matched to select most appropriate fuelbeds.
To validate the developed fuel data, above-ground biomass (AGB) and total available fuel loading were calculated through FFT software and compared to the ESA CCI (European Space Agency, Climate Change Initiative) global forest AGB dataset for 2021 and 300-meter global fuel map for 2015 developed by Pettinari and Chuvieco. In overall, the created fuelbeds were found to underestimate mean living woody biomass for the sampled pixels (53.95 t/ha against 67.46 t/ha). At the same time, correlation coefficients are equal to 0.89 and 0.86 for Pearson and Spearman correlation, respectively. Upon closer examination, biomass in shrubs, tree scrub and young forests was underpredicted to a greater extent, while better accordance was achieved for mature forests, particularly for open ones. The created fuel dataset also showed a good agreement with the global fuel map for both above-ground biomass and fuel loading.
The gridded landscape fuel data in such a high resolution, developed in this study, are extremely important for a wide range of scientific and applied tasks, including fire management, evaluation of emission rates and modelling of smoke effects from wildfires. It should be noted that this data can be reclassified to ensure compatibility with the FireEUrisk fuel map for Europe.
How to cite: Oshurok, D., Grabovets, D., Petrosian, A., Boldyriev, D., Maremukha, T., Molodets, B., Morhulova, V., and Skrynyk, O.: Fine-resolution gridded landscape fuel data in Ukraine, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8537, https://doi.org/10.5194/egusphere-egu25-8537, 2025.
Forest fires are a recurring issue in many parts of the world, including India. These fires can have various causes, including human activities (such as agricultural burning, campfires, or discarded cigarettes) and natural factors (such as lightning). This study presents a comprehensive and advanced methodology for assessing wildfire susceptibility by integrating diverse environmental variables and leveraging cutting-edge machine learning techniques across Rajasthan, India. The primary goal of the study is to utilize Google Earth Engine to compare locations in Sariska National Park, Rajasthan (India) before and after forest fires. High-resolution satellite data were used to assess the amount and types of changes caused by forest fires. The present study meticulously analyzes various environmental variables, i.e., slope orientation, elevation, normalized difference vegetation index (NDVI), drainage density, precipitation, and temperature to understand landscape characteristics and assess wildfire susceptibility. In addition, a sophisticated random forest regression model is used to predict land surface temperature based on a set of environmental parameters.
How to cite: Sinha, A. and Sharma, L. K.: Application of machine learning on Google Earth Engine for Forest Fire Severity, burned area mapping and Land Surface Temperature Analysis: Rajasthan, India, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8892, https://doi.org/10.5194/egusphere-egu25-8892, 2025.
Wildfire risk assessment has evolved significantly over decades of research, enhancing both the accuracy and practical application of methods to evaluate wildfire occurrences and impacts. However, global changes and climate variability present challenges to quantitative assessments due to the diversity of future scenarios. In this context, we introduce SCENFIRE, a specialized selection algorithm designed to align simulated fire perimeters with specific fire size distribution scenarios.
The foundation of this approach lies in generating a vast collection of plausible simulated fires across a wide range of conditions, assuming a random pattern of ignition. The algorithm then assembles individual fire perimeters based on their specific probabilities of occurrence, determined by (i) the likelihood of ignition and (ii) the probability of particular fire-weather scenarios, including wind speed and direction.
This method offers several significant advantages. First, it eliminates the need for fine-tuning simulation parameters by creating an extensive pool of scenarios, which can be automated using scripting tools such as FConstMTT batch processing. Second, it allows for easy adaptation to various fire size distributions without necessitating recalibration of the simulation process.
The approach is exemplified in the eastern Mediterranean coast of Spain, a region prone to wildfires due to natural conditions and land abandonment. This area has experienced recurring large fire events over recent decades, making it an ideal setting to demonstrate the method's effectiveness.
How to cite: Rodrigues, M.: Introducing SCENFIRE, a Post-Processing of Scenario-Based for the integration of Wildfire simulations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8974, https://doi.org/10.5194/egusphere-egu25-8974, 2025.
As the world grapples with the range of environmental challenges such as climate change, loss of biodiversity and forest degradation, the contribution and consequence of extreme wildfires is placed at the heart of enhancing ecological resilience and protect the forest against the loss of biodiversity. The complexity in developing solutions in response to the challenge results from the interdependency that plays between the different factors and actors being involved in the environmental protection. As the world moves towards a unified goal of global protection of forest, it is vital to ensure research and technological innovations being developed are being presented to the relevant stakeholders that yield lasting impact resulting in the protection of forests. To this end, the goal of the paper is to present the notion of Integrated Fire Management (IFM), a systemic framework developed with technology interventions drawing up on the experiences of firefighters, civil protection authority, citizens and researchers composing of expertise in landscape management, forest and environmental protection. The origins of term IFM could be traced to refer a series of actions implemented through reduction, readiness, response and recovery planning and management of forests natural habitat[1]. While the notion of IFM has been published in the literature dating back to 2006, there has been several interpretations and adoptions of the IFM that has been experimented with since then. At the heart of the IFM strategy, is the interdependency of actions and activities that should be carried out in (i) prevention and preparedness; (ii) fire detection, suppression, and response coordination; and (iii) rehabilitation and restoration of activities. The continuous combination of these activities has been identified to lead a sustainable effort on protecting forest against fire. The use of IFM strategy as a framework has been identified to be instrumental in the planning and operational systems designed to not only reduce the impact of fires but also to optimize the benefits derived from them.
Thus, addressing the need for the adoption of IFM for the protection of forest and environment, the SILVANUS project has identified a strategy for the implementation of the IFM. The different phases of the project activities will extend from the prevention and preparedness stages to the end of restoration activities. The platform has been designed to deliver direct interaction to four (4) stakeholders namely who will actively engage in fire management and forest protection. The project innovations can be summarized as follows:
- Development of an integrated citizen engagement campaign for raising awareness on the threat and positive benefits of fire
- Advanced use of UAVs and UGVs for the collection of situational awareness from the fire fronts
- Installation of IoT and camera devices for in the forest for the early-stage detection and alerts on fire incidents
- AI algorithms for the modelling and forecast of fire spread projected from the fire incident origin
- Use of forward command centers and cloud command center for response coordination
- Use of Earth Observation (EO) datasets for the monitoring of post rehabilitation strategy of the region.
How to cite: Chandramouli, K.: A Systemic Framework for the adoption of Integrated Fire Management, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17691, https://doi.org/10.5194/egusphere-egu25-17691, 2025.
Wildfires are increasing in intensity globally, causing death, displacement, elevated health risks due to smoke inhalation, and billions of dollars in damages. In Canada, wildfires are the costliest disaster by event occurrence and recent fires have had international impacts, including on air quality in the United States. These direct consequences of intense wildfires, in addition to the impacts on financial and insurance markets, necessitates a comprehensive and science-based understanding of wildfire risk. This presentation will provide an overview of the wildfire risk in Canada and discuss the innovative scientific approach to risk modelling. In Canada, single wildfire events have caused billions of dollars of losses to residents, governments, and insurers along with considerable social and health impacts, including community displacement and smoke inhalation. The record-breaking 2023 fire season demonstrated that all of Canada can be affected by wildfires, and the intensity of recent wildfires internationally, including in the United States, illustrate the urgent need to better understand intense wildfires.
In Canada, Public Safety Canada’s (PS’s) mandate is to “keep Canada safe from a range of risks such as natural disasters”. The Data Science and Engineering Team at Public Safety connects data, analysis, and engineering to policy development, to work towards meeting this ambitious mandate and to support effective adaptation. The team is imbedded in a policy directorate and provides data analysis and technical policy input for programs including a federally-backed Insurance Program, Disaster Financial Assistance modernization, and creating and sharing Canada-wide risk ratings for natural hazards, including wildfires.
Canada has significant wildfire risk across much of the country. Many small and medium settlement areas are directly exposed to wildfire risk, and the past few years have seen unprecedented destruction throughout the country. Canada’s extensive forests as well as our dispersed and often remote settlement patterns create a unique and problematic landscape of wildfire risk that will be discussed in the presentation. Several recent wildfire events have led to insurer losses well beyond the historical maximum of losses for any year over the last 50 years. In Canada and across the world, insurers have begun to reduce their risk exposure for high risk properties by refusing policy renewals, reducing capacity to write policies, and raising premiums.
PS is responsible for building a holistic understanding of natural hazards across Canada. In this presentation, we will share our team’s and scientific collaborator’s novel efforts across three federal departments to fill knowledge gaps and perform a ‘first of its kind’ wildfire impact assessment and quantification for residential structures in Canada. This includes progress developing and validating novel approaches for characterizing and communicating probabilistic wildfire hazard, developing a Canada-wide wildfire risk assessment, quantifying house loss to structures, and providing wildfire risk information for Canada-wide financial risk analysis. We will highlight our efforts towards data-informed, aligned and effective adaptation policy in addition to how we are bridging the gap between data, science, and policy to keep Canadians safe.
How to cite: Sandison, J.: A Probabilistic Wildfire Risk Model for Canada: Insights for Data, Science and Policy, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11763, https://doi.org/10.5194/egusphere-egu25-11763, 2025.
Preventing forest fires is crucial to mitigate the significant economic and human losses caused by wildfire outbreaks, which are expected to worsen due to climatic changes. Identifying regions at high risk for forest fires is essential for both preventing wildfire occurrences and optimizing resource management during wildfire season. We have developed an operational pipeline for estimating the daily Fire Danger Index (FDI) using a data-driven approach and machine-learning techniques. This presentation will provide an overview of the pipeline’s architectural framework, detail the machine-learning model utilized, and showcase FDI maps generated for multiple European test sites where the pipeline has been successfully deployed.
How to cite: Alvi, S., Epicoco, I., and Accarino, G.: SILVANUS: Operational ML-based Fire Danger Index, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18829, https://doi.org/10.5194/egusphere-egu25-18829, 2025.
Wildfires play a transformative role in the Mediterranean basin, affecting forest composition and structure. Accurate fuel mapping is essential for advancing fire risk assessments and refining fire behavior models. Wildfires typically begin in surface fuels and can escalate to canopy fuels if there is sufficient continuity in the canopy. This study addresses the need for a comprehensive approach to mapping overstory and understory fuels within an integrated classification system, incorporating forest structure and phenology in central Portugal. Fuel types were classified based on the FirEUrisk hierarchical fuel classification system (FHFCS) through a three-step approach: 1) overstory mapping using multispectral and radar data from Sentinel-1 and Sentinel-2, combined with topographic variables; 2) estimation of shrubland and grassland heights using biophysical models based on precipitation and the Normalized Difference Vegetation Index (NDVI); and 3) understory mapping using spaceborne LiDAR data from the Global Ecosystem Dynamics Investigation (GEDI), employing decision-based rules and spatial interpolation of GEDI footprints. This methodology offers a simple and efficient approach for large-scale mapping of both overstory and understory using multispectral, radar, and LiDAR data in the absence of airborne LiDAR, which could enhance fire simulation models for both surface and crown fires.
How to cite: Mohammadpour, P., Xavier Viegas, D., Pereira, A., and Chuvieco, E.: Overstory and Understory Fuel Type Mapping Using GEDI and Sentinel Data Fusion, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19991, https://doi.org/10.5194/egusphere-egu25-19991, 2025.
In line with the respective demands for more public participation, transparency and fairness in wildfire risk management institutions and procedures, Firelogue as an EU Coordination and Support Action aims to connect, coordinate and support three Innovation Actions (TREEADS, FIRE-RES, SILVANUS) granted under the H2020-LC-GD-1-1-2020 "Prevention and management of extreme forest fires through the integration and demonstration of innovative means" as well as the precursor project “FirEUrisk” by integrating their results across stakeholder groups and Wildfire Risk Management phases (WFRM).
In order to achieve the aformentioned objectives, and with a view to create an online WFRM community, Firelogue has developed a platform called "Lessons on Fire powered by Firelogue" (LoF by Firelogue platform), which disseminates the knowledge of the entire WFRM community as well as technologies and measures developed by the IAs. “LoF by Firelogue” platform built upon the Lessons on Fire platform established by the Pau Costa Foundation (PCF) in 2015, thereby leveraging the valuable insights and experiences gained from their prior endeavors. Upon the completion of the project, Firelogue's platform will be entrusted to PCF to undertake the responsibility of its continuous maintenance and updates.
The LoF by Firelogue platform serves as a highly valuable resource for the WFRM community. It functions as a centralised hub for sharing of knowledge, dissemination of news and events, promotion of EU platforms dedicated to dissemination of activities, as well as access to various existing platforms related to WFRM. One of the notable features of the platform is its ability to facilitate connections between professionals within the field. It ensures that users remain informed about the latest fire-related events and news, while also granting them access to technical publications, best practices in WFRM, case studies, and a range of fire-related documents. The platform along with its associated context, remains open to all, enabling registered users to contribute their own content. Registered users are given the opportunity to upload their own fire-related content through uploading their results, documents, events and news. This collaborative effort enhances and empowers the WFRM sector.
Overall, Firelogue and its LoF powered by Firelogue Platform’s are critical resources for the WFRM community, policy makers and civil society to address current and future wildfire challenges. By creating dialogue and empowering the community, Firelogue makes a significant contribution to mitigating the impacts of wildfire.
Acknowledgement: "This work has been supported by the research project FIRELOGUE. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 101036534. This article reflects only the authors’ views and the Research Executive Agency and the European Commission are not responsible for any use that may be made of the information it contains."
How to cite: Kaskara, M., Kontoes, C., and Oikonomou, S.: Fire up the transdisciplinary dialogue for wildfire risk management, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-963, https://doi.org/10.5194/egusphere-egu25-963, 2025.
This poster presents the use of the PhyFire simulation tool within the framework of the TREEADS project. PhyFire is built on three simplified physical models that work together to simulate various aspects of wildfires. The core fire propagation model, PhyFire, is coupled with HDWind, a high-resolution wind field model that provides localized wind dynamics, and PhyNx, an atmospheric dispersion model used to simulate the dispersion of the smoke generated by the fire. Through various use cases, we demonstrate how this integrated approach enhances fire modelling, prediction, and management. The showcased applications include real-world scenarios where the tool has provided valuable insights and supported decision-making processes for fire prevention and response. Key results highlight the accuracy and versatility of PhyFire in addressing diverse challenges related to wildfire dynamics and mitigation strategies. The selected use cases correspond to three TREEADS pilot areas: the Tiétar valley in the province of Ávila (Spain), the Sorrento peninsula (Italy) and the Samaria Gorge on the island of Crete (Greece). Incorporating the unique characteristics of each pilot area has presented distinct challenges to the simulation model, offering valuable opportunities for refinement and enhancement.
The simulation tool was developed by the Numerical Simulation and Scientific Computing research group at the University of Salamanca and integrated into the TREEADS project's WebGIS platform in collaboration with the Information Technologies for the Intelligent Digitization of Objects and Processes research group from the same university. The integrated tool facilitates its use over the project's pilot areas through a simple and user-friendly interface, enabling the visualization of results within a GIS environment.
How to cite: Asensio, M. I., Cascón, J. M., Iglesias, J. M., Herrero, L., Santos Martín, M. T., Grillakis, E., and Pascale, C.: Fire Simulation with PhyFire: Applications and Results in the TREEADS Project, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1558, https://doi.org/10.5194/egusphere-egu25-1558, 2025.
Residential and non-residential buildings may react differently to a wildfire due to several factors, including differences in architectural design, construction materials, and the location of combustible or hazardous materials. These differences can significantly influence the level of vulnerability to wildfire impacts, with each type of building presenting unique challenges and risks. While residential structures often prioritise factors such as comfort and aesthetic design, non-residential buildings, such as commercial or industrial facilities, may have additional concerns, such as the storage of large quantities of hazardous materials or the need for specific industrial processes, which introduce further wildfire vulnerabilities.
In this study, we present a comprehensive and detailed set of wildfire vulnerability indicators specifically tailored to assess the risks posed to both residential and non-residential buildings located within the Wildland-Urban Interface (WUI). These indicators are designed to evaluate various characteristics of the buildings themselves, including their construction materials, roof types, and storage of flammable or hazardous materials. In addition to the physical characteristics of the structures, the study also considers the immediate surroundings, such as fences, perimeter walls and the type of vegetation present in the area. Ground cover, which can include grass, shrubs or other combustible materials, is also considered a key factor influencing the vulnerability of buildings to wildfire.
By combining these various building and environmental characteristics, the set of vulnerability indicators provides a holistic approach to assessing the physical risks faced by properties in the WUI. This methodology makes it possible to identify specific hotspots where the risk of wildfire damage may be higher, thus allowing for the prioritisation of prevention measures. For example, buildings with highly flammable roofing materials or those located near dense vegetation may be more susceptible to ignition and therefore require more immediate attention in terms of mitigation strategies.
The practical application of these indicators is demonstrated by their use in assessing the vulnerability of an industrial area located in the WUI in the European Alps. This case study illustrates how the indicators can be used to assess real-world scenarios and highlights areas where improvements can be made to enhance the resilience of both residential and non-residential buildings to wildfire. The study also highlights the importance of a localised, context-specific approach to wildfire risk assessment, as factors such as local climate, terrain and vegetation play a significant role in shaping vulnerability in the WUI. By incorporating these elements, the proposed set of indicators aims to contribute to more effective risk assessment and targeted prevention efforts, ultimately enhancing wildfire resilience in areas where human development intersects with wildlands.
How to cite: Fuchs, S., Echtler, P., Wilimek, L., Müller, M., Vacik, H., and Papathoma-Köhle, M.: Comprehensive wildfire vulnerability indicators for residential and non-residential buildings in the WUI, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3462, https://doi.org/10.5194/egusphere-egu25-3462, 2025.
This research examines the complex interactions between natural vegetation and urban infrastructure within the Wildland-Urban Interface (WUI), focusing on the region of Attica, Greece. Human-built environments and wild vegetation converge in areas where conditions favor the propagation of wildfires. The presence of diverse fuel sources, both natural and artificial, fosters the development of conditions conducive to the rapid spread of wildfires. Consequently, these areas are particularly vulnerable to natural hazards. The Attica region is among the most densely populated in Greece, with a population density of over 3.8 million inhabitants. The region is characterized by extensive and unregulated buildings, which renders it a suitable subject for studying WUI. The study addresses the relationship between the increasing frequency of wildfires and the impact of urban sprawl concerning future fire risk, highlighting the critical need for effective risk management strategies. To achieve its objectives, freely available advanced geospatial data from digital and satellite sources was utilised, such as data on urban structures (UCR-Star building footprints from 2014–2021) and vegetation (Corine Land Cover 2018, forest maps from 2022, and high-resolution vegetation data from the Copernicus Database) to map the WUI areas. Historical fire records (Fire frequency) were derived from Landsat satellite imagery (1983–2023), while topographic maps (1988–1994) were processed to create Digital Elevation Models (DEMs) and slope maps, and climatic data modified the Fire Weather Index (FWI) at the 90th percentile for RCP 4.5 projections. The methodology employed a three-stage process to map the WUI, integrating fuel type mapping, dwelling characterisation, and classification of WUI types. The wildfire risk was assessed through a Geographic Information System (GIS)-based model combining hazard (fire history, weather, topography, and fuel types) and susceptibility (land cover and WUI categories) to identify high-risk areas in Attica. The spatial analysis performed the spatial extent of the WUI in Attica, which was estimated to be 26% of the whole region. Furthermore, 37% of the study area was classified as high or very high risk, underscoring the region’s vulnerability. Temporal fire mapping from 1983 to 2023 provided a comprehensive understanding of fire dynamics over four decades, allowing detailed analysis of the relationship between WUI expansion and fire occurrence. Overall, more than 102,000 hectares in Attica have been affected by wildfires, covering over one-third of the region. The findings outline a strong correlation between urban development and wildfire risk, thus offering valuable insights into the factors contributing to fire vulnerability in WUI areas. These findings contribute to the scientific discourse and a solid foundation for developing evidence-based policies to improve fire prevention, response, and resilience in areas where urban and natural landscapes intersect.
How to cite: Psomiadis, E., Oikonomou, A., and Avramidou, M.: Coupling Remote Sensing data and GIS analysis to delineate Wildland-Urban Interfaces and their possible correlation to wildfires in a densely populated area in Greece, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9223, https://doi.org/10.5194/egusphere-egu25-9223, 2025.
Wildfire risk management has gained importance as wildfires increase in their frequency and intensity, with potentially devastating impacts on communities and ecosystems, contributing to climate change, biodiversity loss and ultimately increasing societal vulnerability to multi-hazards. As a result of historical processes influenced by socioeconomic factors, political decisions and changes in human-nature interactions, wildfire risk management has become more complex involving multiple stakeholders often holding competing views. Different views exist, for example, concerning the respective roles of fire suppression, which employs ever more sophisticated technologies, and fire prevention involving land use planning, fuel treatments and Nature-based Solutions. Perceptions of the problem and the potential solutions vary among different stakeholders, which can result in conflicts impeding effective wildfire risk management. Thus, a multifaceted stakeholder approach is needed to address the wildfire challenge.
We conducted a qualitative analysis of stakeholder discourses on wildfire risk management, especially in the Mediterranean context. The analysis focuses on narratives of how experts frame the wildfire risk problem, the potential solutions and interventions they propose for its management, and their corresponding views on Nature-based Solutions. It is mainly based on data collected from two cross-sectoral wildfire workshops and expert interviews, as part of the Horizon 2020 project Firelogue (Cross-sector dialogue for Wildfire Risk Management). The stakeholders and workshop participants come from five relevant working groups within the wildfire risk management community, namely, civil protection, environment, infrastructure, insurance and society. Reports and notes from the workshops, as well as transcripts from the semi-structured interviews were coded manually with the qualitative data analysis software ‘NVivo’ to identify a plurality of views.
The dual role of fire as a natural element and integral part of ecosystems with regenerative functions on the one hand, and as a destructive disturbance to socio-ecological systems on the other, further contributes to the complexity of the nexus between fire, nature and people. Increased land abandonment, forest protection and restoration projects emerged with growing support for allowing forests to be shaped more naturally. Special attention is placed on Nature-based Solutions in the context of wildfires. We classified the expert discourses along the three axiological categories of the Nature Futures Framework (NFF): 1) the instrumental values of nature to society (Nature for Society); 2) the intrinsic values of nature (Nature for Nature) and 3) the relational values weaving human-nature relationships together (Nature as Culture). The discourses differ from each other in the regard of whether impacts and benefits are being foremost quantified and considered in trade-offs, ways to restore natural ecosystems to be self-reinforcing and self-balancing, and how to establish a reciprocal relationship seeing nature and society as interconnected entities.
Understanding the social constructions, worldviews and values of the wildfire community, analyzed and documented with qualitative methods, can help identify compromise solutions and a robust policy space. In this way, this study aims to facilitate a holistic understanding of complex wildfire risks with an interdisciplinary approach and contribute to improving decision-making processes across diverse sectors and scales.
How to cite: Dong, X., Scolobig, A., Linnerooth-Bayer, J., Sendzimir, J., Fresolone, A., and Schinko, T.: Understanding Stakeholder Discourses for improved Wildfire Risk Management, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9292, https://doi.org/10.5194/egusphere-egu25-9292, 2025.
Counterfactual analysis is the study of what might have happened, if a particular circumstance had been different. This type of analysis is being increasingly applied to the field of disaster risk reduction, to estimate how much the effects of a disaster were prevented or amplified by the presence (or absence) of certain factors. The findings of such analyses can then be used as lessons learned from unrealized alternative events, to help inform policies and plans for a more disaster-resilient future.
This study conducts a counterfactual analysis for the 2023 Lahaina wildfires in Hawaii, which caused over $6 billion in losses and more than 100 fatalities. Using a qualitative approach inspired by previously proposed counterfactual analysis frameworks, we investigate a variety of plausible shifts related to the disaster (e.g., in terms of its geographical location and timing) that could have led to an even worse outcome. We find that the casualty number could have been notably increased if the most significant wildfire occurred at night, near a much larger town in the north of Maui, and/or coincided with a volcanic eruption, for instance. The results of this investigation are translated into a series of recommendations for strengthening disaster risk reduction measures (e.g., related to improving early warning systems, community-led evacuations, and consolidating public partnerships with transportation companies) that could significantly reduce wildfire-related losses from any future similar events in the region or elsewhere.
How to cite: Ahmed, H. and Cremen, G.: Learning important risk mitigation lessons through counterfactual analysis of the 2023 Lahaina Wildfires, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9525, https://doi.org/10.5194/egusphere-egu25-9525, 2025.
As the climate changes, wildfires pose a growing threat to infrastructure. Wildfires can adversely impact reliability across a wide range of infrastructure sectors: the heat can directly damage electricity distribution network and communication equipment; smoke can disrupt transport and solar power production; and ash can contaminate water supplies. While some regions of the world have extensive experience with wildfire driven infrastructure outages, changes in climate and land use mean that infrastructure owners around the world are now facing these challenges, including those in Great Britain. Therefore, it is essential to understand the impacts that wildfires could have on infrastructure owners’ ability to provide essential services to society.
We present a methodology to use landcover, vegetation properties, weather, and topography to inform the behaviour and likelihood of wildfires in proximity to critical infrastructure. Simulations across 249 distinct scenarios for Great Britain allowed us to examine the expected behaviour of wildfires, and how this behaviour may change seasonally, under different fuel management scenarios and under extreme heatwave events. This culminated in 316,479-point simulations of fire behaviour. Accounting for local landcover, windspeed, and topography have enabled us to spatially map these scenarios to critical infrastructure assets (power and transportation), enabling visualisation of the changes and impact. Finally, we used a machine-learning based methodology (using landcover, vegetation properties, weather, and topography) to inform the likelihood of wildfires occurring in proximity to critical infrastructure. Simulation using historical recorded wildfire incident data enables model validation and provides insight for climate adaptation planning and resilience enhancement strategies.
How to cite: Donaldson, D. L., Preece, J., Little, K., Ferranti, E., and Kettridge, N.: Spatio-temporal Assessment of Wildfire Risks to Critical Infrastructure: Predicting Wildfires with Machine Learning, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13045, https://doi.org/10.5194/egusphere-egu25-13045, 2025.
Wildfires have a significant impact on the human health of populations on the path of the generated smoke plumes. They emit high amounts of air-pollutants resulting in abnormally high concentrations of harmful particles and gases. These lead to increased diseases associated with bad air quality that are clearly perceived in hospital admissions. Wildfire smoke also impacts society on other levels, such as tourism and airplane routes or the firefighting operations themselves.
The focus of this work is on the forecasting of wildfire smoke. Such forecasts serve essentially two purposes. First the ability to quickly assess potential impacts of wildfires on air quality. Second, to decide on actions that mitigate those impacts. Examples of their usefulness are the FireSmoke platform used in North America, or the European CAMS air quality forecast.
This work presents a new methodology for forecasting wildfire smoke at local-scale. Firstly, the emissions of wildfires are estimated using a fire-progression model. Then the dispersion of smoke at local-scale is estimated using a computationally efficient lagrangean model.
The implementation of this methodology was carried out for the region of Sardinia, Italy. Disperfire was used as the dispersion model, while the Sardinian Wildfire Simulator (SWS) was used in the estimation of fire-progression. A case-study of a past wildfire in the region was chosen to evaluate the developed methodology.
The SWS is a fire-growth model that, based on vegetation characteristics and state, topography and meteorology, is able to estimate how the fire-front will change over time. This type of models have been widely used to support firefighting operations.
Disperfire is a lagrangean dispersion model that works with a numerical grid at resolutions of hundreds of meters. In a first step the emissions at each grid-cell are calculated based on emission-factors and the intensity of the fire, previously estimated by SWS. Then, smoke is modelled as particles, each representing a given mass of smoke, that are advected along the wind velocity vectors. The diffusion phenomena are modelled by moving those particles according to a random normal distribution.
Several runs were carried out using different levels of discretization, by varying the time-step, the grid-resolution and the number of particles used in Disperfire. The influence of the different levels of discretization was assessed.
The newly developed methodology fills a gap by explicitly modelling phenomena such as local-scale dispersion and fire-progression which are often simplified or absent in mesoscale wildfire-smoke forecast systems. This approach provides a foundation for improving the accuracy of mesoscale smoke dispersion models in the future.
How to cite: Osswald, T., Casula, M., Salis, M., Arca, B., Gama, C., and Miranda, A. I.: Wildfire-Smoke Forecasting: A Methodology for Local-Scale Dynamics from Wildfire-Spread to Atmospheric Dispersion, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19604, https://doi.org/10.5194/egusphere-egu25-19604, 2025.
