The combination of natural hazards, along with their frequency and intensity, defines local disturbance regimes that fundamentally shape ecosystems and human societies. We propose 'hazomes,' a novel classification system of the earth based on these specific hazard profiles. Unlike other classification systems such as climatic zones that categorize the earth according to average conditions, 'hazomes' are defined by distinct profiles of extreme natural hazards. We integrate data from multiple open sources and develop methodologies to systematically identify and categorize 'hazomes' across the globe, based on two return periods and two intensities for each hazard type (among others earthquakes, floods, wildfires, and tropical cyclones). This approach reveals thousands of distinct 'hazomes,' reflecting a diverse range of natural disturbance regimes. Our analysis shows that 'hazomes' provide insights that complement traditional classifications such as Köppen–Geiger climatic zones, biomes, and ecoregions.
For enhanced usability and broader application, we also develop two streamlined versions of the classification. The reduced version classifies geographic points based solely on the binary presence or absence of each hazard type. The simplified version distills the framework into less than a hundred principal categories by focusing on the most significant hazard characteristics. These versions balance the richness of detailed data with practical applicability in risk management and planning. This framework aims to deepen insights into ecosystem and societal resilience by highlighting how both ecological and human systems may adapt to or depend upon specific natural disturbance regimes. Among its various potential applications, this approach is particularly useful for facilitating multi-hazard risk assessments and supporting the development of adaptive strategies by transferring knowledge between areas with similar disturbance profiles.
How to cite: Kropf, C. M., Stalhandske, Z., Steinmann, C. B., Hülsen, S., and Bresch, D. N.: Hazomes: A Classification of Earth’s Regions by Hazard Profiles, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9301, https://doi.org/10.5194/egusphere-egu25-9301, 2025.
There is underlying uncertainty in every model, and understanding how this affects decision-making is crucial. Individual hazard models involve numerous assumptions, and quantifying uncertainties becomes even more challenging when these models are integrated to assess multi-hazard events. While these uncertainties are inescapable, it is vital that stakeholders have a good understanding of hazard-model limitations, whether they are involved in long-term policymaking (planning including early-warning systems, infrastructure, and risk management) or short-term decision-making (such as anticipatory action and disaster response).
With this in mind, the project explores the practical applications of environmental multi-hazard models currently in use, looking firstly at models of flooding and related hazards. Taking a multi-level approach, we use qualitative interview evidence and quantitative model evaluation metrics to assess whether these models provide the insights policy-makers need and explore potential improvements to enhance their effectiveness. The feedback from stakeholders is used to make recommendations for model selection, evaluation, and development to prioritise actionable outputs.
As it is important for all sectors to be involved in disaster risk management, it is equally important to examine all hazards to which population and infrastructure assets can be exposed to in a given location, who is vulnerable to such exposure, as well as how this exposure varies with the use of different underlying assumptions. We compare the exposure of assets based on two flood models and consider the effectiveness of this information for long-term decision support, such as prioritising infrastructure investments.
In an era where accessing data globally has simplified, the quality of this data can still vary significantly across different countries and regions. By understanding how scenario-based multi-hazard models are utilised - or could be utilised - to mitigate risks to human lives and livelihoods, we can help nations better prepare for both long- and short-term effects of extreme weather and climate change, while taking into account the underlying uncertainty.
How to cite: Leonova, N. and Thompson, E.: Defining a framework for integrating stakeholder-feedback, taking into account uncertainty, in multi-hazard model evaluation and development., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1706, https://doi.org/10.5194/egusphere-egu25-1706, 2025.
The Fens is the UK’s largest coastal lowland, strategically important for national food production and home to a growing population and economy. A natural floodplain and wetland, the Fens have evolved over four centuries into an engineered landscape dependent on continuous maintenance of drainage channels, flood and coastal defences, tidal barriers and extensive pumping. The region is highly vulnerable to a wide range of climate hazards, such as coastal, pluvial and fluvial flooding, drought, heatwaves and storms. Understanding how related risks may develop over time is crucial in developing a future vision for the region that responds and builds resilience to both current and future challenges.
The presentation will firstly describe the rationale and method that has underpinned the first in-depth place-based multi-hazard risk assessment for the UK Fens. This assessment builds on a flexible model framework developed via a UK project, OpenCLIM (Open CLimate Impacts Modelling framework). Spatially detailed data was extracted for the Fens region, with risk-assessment models consistently considering drought and water resources, agriculture, multiple sources of flooding, sea-level rise, terrestrial biodiversity and heat stress for the present day and with global average warming of 2 and 4°C.
The presentation will then highlight how the integrated assessment supports the analysis of climate risks through a system-lens. The assessment is innovative in highlighting how multi-hazard risks could interact across risks and sectors, identifying potential trade-offs and opportunities across sectors and ways in which this information could support strategic decision making and climate change adaptation. For example, investment in flood resilience assets may protect high grade agricultural land but if drought, water quantity and quality issues and critical short-term challenges to insect pollinators are not addressed in parallel then this investment may be short-sighted.
The analysis emphasises that the Fens cannot respond to the climate crisis with isolated measures targeted to one risk or sector. The challenges are interconnected, necessitating the same for the solutions. Furthermore, it highlights the need for urgent action with a short window of opportunity to make decisions and establish a resilient future for the Fens. One approach to doing so is to explore new visions for the future, which move away from the current status quo, such as defending some areas whilst accepting more flooding in other regions and working to exploit benefits this vision could create for other sectors/stakeholders.
Strong stakeholder engagement and co-production have been crucial in communicating key messages from the multi-hazard climate risk assessment, with the scientific evidence being used as a call to action and guiding roadmap to bring together stakeholders and decision-makers working to envision and safeguard the region’s future. Furthermore, the method and approach demonstrated for the Fens is transferable to other regions, to provide tailored regional multi-hazard climate risk and adaptation assessments that consider local contexts.
How to cite: Jenkins, K., Nicholls, R., Sayers, P., Redhead, J., Price, J., He, Y., Minns, A., and Pywell, R.: An innovative multi-hazard climate change risk assessment framework: Evidence from a place-based assessment of challenges and solutions in the UK Fens, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18584, https://doi.org/10.5194/egusphere-egu25-18584, 2025.
Cultural heritage monuments are invaluable assets that embody the history, culture, and identity of civilizations, making their preservation a global priority. Understanding the multi-hazard risks they face, and particularly earthquakes and floods, is essential to developing effective strategies for their protection in seismic regions and ensuring their resilience for future generations.
This study presents a comprehensive multi-hazard assessment of a significant archaeological site in Greece: the Temple of Apollo at Aegina (Kolona), which was conducted as part of a the Horizon Europe project TRIQUETRA. Detailed and accurate geometric documentation of the archaeological site was done, using UAV imagery (DJI Mavic 3 Enterprise) and GNSS measurements of ground control points, acquiring more nearly 6000 images. Using multi-image photogrammetric techniques a 3D texture model of the site and monuments, with an RMS error of 4 cm, a digital surface model with a resolution of 1 cm and a high-resolution orthophoto with a pixel size of 1 cm (groudel) were produced.
Based on these digital replicas, advanced three-dimensional Finite Element (FEA) models were developed using solid elements to evaluate the structural response and vulnerability of these heritage structures under single hazards and combined earthquake and flood scenarios. The methodology integrates site-specific geotechnical data, historical structural modifications, and current preservation states to create realistic simulation models. The numerical analysis incorporates both seismic loading conditions based on regional hazard data and flood impact forces derived from hydraulic assessment. The multi-hazard approach considers various combinations of seismic and flood events, providing insights into potential failure mechanisms and structural vulnerabilities. Results highlight critical areas requiring preservation attention and demonstrate the varying resilience levels of different structural components under combined loading conditions.
This research contributes to the field of heritage structure preservation by establishing a novel framework for multi-hazard assessment of archaeological sites. The findings provide valuable insights for developing targeted conservation strategies and disaster risk reduction plans for these irreplaceable cultural heritage sites.
Acknowledgments: This work is based on procedures and tasks implemented within the project “Toolbox for assessing and mitigating Climate Change risks and natural hazards threatening cultural heritage—TRIQUETRA”, which is a Project funded by the EU HE research and innovation program under GA No. 101094818.
How to cite: Mode, P., Istrati, D., Spryakos, C., Soile, S., Verykokou, S., and Ioannidis, C.: Towards multi-hazard earthquake-flood impact assessment on ancient monuments based on UAVs, photogrammetry and high-fidelity computational models, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20892, https://doi.org/10.5194/egusphere-egu25-20892, 2025.
Multi-hazards pose increasing risks due to complex interconnections and amplified impacts, needing a thorough understanding of their dynamics. Modeling such interactions on a regional scale is difficult, with few frameworks providing simple yet efficient approaches. The present study proposes a novel regional-scale framework for multi-hazard assessment focusing on cascading interactions due to flood and landslide hazards.
The first step involves a detailed assessment of flood hazards in the study area for a rainfall event. Separately, landslide hazards are evaluated to identify and highlight landslide initiation points. The cascading hazard model uses reach angle to translate landslide hazards into sediment transport within the river network. The sediment transport from the rainfall event is then compared with reference sediment transport corresponding to a specific return period to classify cascading hazards into four levels. The outputs of the flood and cascading models are combined to classify multi-hazard into four levels across the river network. These hazard levels are further aggregated into mapping units such as sub-basins, forming combined hazards. Finally, a hazard matrix merges landslide and combined hazards to produce the overall multi-hazard assessment.
An initial version of this proposed framework is tested on Saint Vincent Island, focusing on a significant event that resulted in widespread flooding and landslides. Preliminary results from applying the multi-hazard framework highlight its effectiveness in identifying zones of heightened risk, particularly in areas where landslides and sediment transport significantly affect the river network and surrounding regions. These findings offer critical insights into the interactions and dynamics of rainfall-induced multi-hazards, demonstrating the framework's potential to inform proactive risk management. The initial outcomes highlight the framework's applicability as a practical tool for hazard mitigation planning while contributing to the broader advancement of multi-hazard research and assessment methodologies.
How to cite: Yeditha, P. K., Hürlimann, M., Abancó, C., and van Westen, C.: A rainfall-induced multi-hazard framework integrating flood, landslide, and their cascading effects: Application to Saint Vincent Island, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9856, https://doi.org/10.5194/egusphere-egu25-9856, 2025.
Current flood hazard mapping and risk management practices typically address pluvial and fluvial flooding separately. In many regions, however, compound pluvial and fluvial flooding (CPFF) are a significant challenge. We develop a methodological approach to explore the relevance of CPFFs for the reconstruction processes and flood risk management in the Ahr valley in western Germany, devastated by the July 2021 flood. A non-stationary regional weather generator is applied to generate 100 realizations of synthetic precipitation and air temperature daily time series over a 72-year historical period (1950-2021). The method of fragments is used to disaggregate daily precipitation into hourly scale. The mHM hydrological model is used for rainfall-runoff simulation, producing the hourly discharge at the gauge Altenahr as fluvial boundary conditions for the downstream area. A total of 208 CPFF events are identified from 100 model realizations. The inundation depth and extent of these CPFF events are subsequently simulated using the RIM2D hydrodynamic model. We present a comparison of resulting CPFF flooding versus fluvial flooding alone. Our analysis reveals that fluvial flooding dominates maximum inundation depths, while pluvial rainfall expands the flood extent. Furthermore, CPFF events demonstrate substantially more severe hazards compared to fluvial flooding alone, which is typically the baseline for flood protection practices. These findings underscore the urgency of integrating CPFF into risk assessments and planning, offering policymakers critical insights to improve resilience against compound flood hazards.
How to cite: Guan, X., Merz, B., Nguyen, V. D., Han, L., Apel, H., Khosh Bin Ghomash, S., and Vorogushyn, S.: Hazard assessment of compound pluvial and fluvial (CPFF) flooding: a case study in the Ahr valley, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8386, https://doi.org/10.5194/egusphere-egu25-8386, 2025.
Abstract
Amidst the escalating impacts of climate change and the growing frequency of natural disasters, the urgent need for robust multi-risk assessment and proactive mitigation strategies has become increasingly apparent. The Garrotxa region, characterized by its diverse array of weather-related hazards (such as torrential rains, floods, debris flows, lahars, tornadoes) and geological hazards (including landslides, rockfalls, earthquakes, and volcanic eruptions), presents an example of the challenges faced by communities globally, necessitating a shift towards anticipatory disaster management. Departing from conventional simulation models, we recognize the fundamental role of past experiences in shaping future risk assessments and mitigation strategies. This paper introduces a methodology for the creation of a multi-hazard database tailored to the Garrotxa region, serving as a foundational step towards subsequent multi-risk analysis. By meticulously documenting the region's historical hazards for the last 123 years, our approach aims to equip stakeholders with a nuanced comprehension of multiple natural processes. This comprehensive strategy, which combines modern monitoring techniques with historical context, forms a synergistic approach crucial for effective, long-term disaster risk mitigation. Our work not only sheds light on the unique challenges faced by the Garrotxa but also provides a scalable model for regions grappling with diverse natural phenomena worldwide. This contribution aims to enhance disaster resilience in regions confronting similar potential multi-hazard scenarios.
The database mentioned in this abstract is part of: the GarMultiRisk Project, funded by the Biodiversity Foundation of the Spanish Ministry for the Ecological Transition and the Demographic Challenge, through the Call for Grants for the implementation of projects contributing to the Spanish National Plan for Adaptation to Climate Change (2021-2030); and of the SIRRN Project (Intelligent System for Natural Risk Reduction) funded by the Spanish National Research Council (CSIC) Artificial Intelligence-SOMMa Grant.
Keywords
Multi-hazard, natural hazards, database, multi-risk, risk management, hazard assessment, decision-making, climate change, resilience.
How to cite: Schneider-Pérez, I., Lagresa, A., López-Saavedra, M., Jiménez, M., Martí, J., Martínez, M., Ocaña, A., and Planagumà, L.: Methodological approach to multi-hazard analysis: the case of the Garrotxa region (Catalonia, Spain), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3544, https://doi.org/10.5194/egusphere-egu25-3544, 2025.
Climate change significantly impacts both the natural and the built environment, necessitating a comprehensive understanding of the risk due to current and future climate-related threats. This study presents a multi-hazard risk assessment framework for buildings in Ireland, serving as an essential first step in developing effective climate adaptation strategies.
The framework is constructed based on three typical components of disaster risk assessment: hazard, vulnerability, and exposure analysis. It provides a comprehensive evaluation of climate-related hazards, including heatwaves, wildfires, heavy precipitation, extreme temperatures, landslides, and strong winds. By incorporating various datasets, the methodology employs a systematic and standardized indicator-based approach to evaluate multiple hazards, offering a holistic risk profile.
The study demonstrates the framework's application through a case study of Dublin, Ireland. This practical implementation illustrates how the methodology can be used to identify potential climate change risk hotspots in urban environments. The approach allows for a high-level risk assessment, which is crucial before commencing any detailed analysis.
By providing a clear and replicable methodology, this research contributes to the global effort to safeguard the built environment against climate change impacts. The framework serves as a valuable tool for policymakers and urban planners, enabling them to prioritize areas for intervention and develop targeted adaptation strategies. This study underscores the importance of proactive risk assessment in enhancing urban resilience to climate change.
How to cite: Rahul, A., Clarke, J., and Nolan, P.: A multi-hazard risk assessment for buildings in Ireland due to climate change impacts, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19583, https://doi.org/10.5194/egusphere-egu25-19583, 2025.
Natural hazard-related disasters result in tens of thousands of deaths and billions in economic losses annually, with their frequency and intensity projected to increase due to climate change. These hazards, such as floods, landslides, and volcanic eruptions, often interact in ways that amplify their impacts, creating cascading or compounding risks. Despite these complexities, most hazard databases focus on single-hazard events, failing to capture critical interactions. To address this gap, we are developing a relational disaster database designed to systematically document and analyse multihazard interactions.
The database is designed to capture both individual hazard events and their interrelations, including causal, temporal, spatial, and amplifying interactions. It consists of two modules: a hazard characteristics and impacts module, which records essential details such as location, magnitude, and consequences, and a hazard linkages module, which documents relationships between hazards with attributes such as time lags, interaction intensity, and confidence levels. This scalable design is interoperable with existing databases like DesInventar and EM-DAT, enabling integration of existing data and automated processing and data analysis. We aim for flexibility, open access, and good metadata to ensure utility for both academic and operational (e.g,. disaster risk managers) end-users.
Complementing the database, we are developing tools for the automated generation of process-linked and coinciding multihazard groups, cumulative impact analysis, and the creation of associated visualizations. Initial database entries include case studies such as the 2023 Lhonak glacial lake outburst flood (GLOF), involving rainfall, landslides, and dam failure, and Hurricane Helene, highlighting meteorological, marine, and geological interactions. The database is currently at a prototype stage, and we welcome community input and collaboration to refine its design, expand its coverage, and ensure its long-term relevance and usability.
Figure: Concept diagram for the structure of the relational multihazard database.
How to cite: Van Wyk de Vries, M., Nava, L., Chen, Y., Augustina, L., Bell, L., Nicholas, J., Clarke, B., Ungar, R., Hill, A., Sharma, K., Morin, J., and Hussain, E.: A relational disaster database to document and resolve multihazard interactions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12887, https://doi.org/10.5194/egusphere-egu25-12887, 2025.
In 2023 and 2024 and in partnership with Sage on Earth Consulting, BGC Engineering undertook a province-wide hazard exposure assessment for the provincial government of British Columbia, Canada. British Columbia spans approximately 940,000 square kilometers, stretching from the Pacific Ocean in the west to the Rocky Mountains in the east and from the Yukon border in the north to Washington State in the south. This expansive region faces a wide array of natural hazards, including flooding from mountain streams, tsunamis and shoreline erosion in coastal communities; earthquakes; landslides; debris flows; wildfires; drought; extreme heat and, increasingly, cascading hazards intensified by climate change. The goal of this project was to design and implement a geospatial workflow for assessing exposure of valued assets to hazards, delivered to a government agency in a standardized format that facilitated future updates and public governance over data sharing.
To accomplish this, BGC designed a data model and analysis pipeline that had sufficient performance for the iterative processing of large multi-hazard and asset datasets and that could be packaged for government agency development of a data portal. Within the data model, hazards were defined as areas which exceed hazard-specific intensity thresholds and/or annual probability of occurrence; these binary hazard data were the primary input to the analysis pipeline for each hazard type. The list of assets to be included in the analysis was determined through a series of consultations with project stakeholders aimed at identifying which assets are most important and what data was available consistently for the entire province. The result of the analysis was a set of exposure metrics representing population counts, monetary values of property exposed to hazards, and the lengths of transportation and utility networks within hazard zones summarized using a uniform 1.5 km x 1.5 km grid. These metrics were delivered along with documentation of the data model, the data, and the codebase for the analysis pipeline.
The resulting analysis revealed spatial patterns of hazard exposure and provided actionable insights to support provincial-scale risk management. This work represents a foundational step in risk assessment and mitigation planning. It offers a means of prioritizing local-scale risk assessments within a jurisdiction as vast as British Columbia, enabling focused resource allocation and informed decision-making. Collaboration was central to the project's success. In association with Sage on Earth Consulting , BGC engaged with multiple stakeholders to refine inputs and validate assumptions, and ensure the outputs were accessible and meaningful. The results are designed for government-managed web access to both data inputs and analysis outputs, promoting transparency and usability for diverse audiences.
This provincial hazard exposure assessment highlights the importance of integrating data, geospatial analysis, stakeholder collaboration, and practical tools to address the complex challenges posed by natural hazards in British Columbia. The findings not only advance the understanding of hazard exposure but also lay the groundwork for more detailed, localized risk assessments and targeted mitigation efforts.
How to cite: Carter, R., Holm, K., Safaie, S., Teelucksingh, M., Wang, J., and Buchanan, M.: Leveraging modern geospatial data science techniques for multi-hazard exposure analysis in British Columbia, Canada, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10685, https://doi.org/10.5194/egusphere-egu25-10685, 2025.
The increasing complexity of multi-hazard risk environments demands innovative, systematic knowledge management and analysis tools. To address this challenge, the EC-funded HORIZON project PARATUS analysed past disaster events and current risks across four multi-hazard case studies: Romania, Turkey, the Caribbean, and the Alps, employing Impact Chains as its primary analytical framework. Impact Chains proved successful in supporting risk analysis, providing an intuitive graphical conceptual representation of risk which can be co-developed with both domain experts and stakeholders. It allows highlighting the interactions among hazards, impacts, exposure, and vulnerability, including their cascading effects, while explicitly accounting for risk reduction and climate change adaptation measures. However, as the complexity of multi-hazard risk conditions increases, so do the impact chains, possibly resulting in exceedingly complicated representations. Also, purely graphical models might not be able to convey the necessary amount and quality of information needed to analyse complex multi-hazard events.
To overcome these limitations, we developed an enhanced knowledge management system (KMS) to systematically store and review the impact chains developed for the four PARATUS case studies. This system builds upon the existing Climate Risk Planning and Managing (CRISP) tool for development programmes (https://crisp.eurac.edu/). While the CRISP tool was designed to provide climate risk knowledge for Agri-Food systems, the PARATUS analysis extends this scope to multiple sectors and enables a systematic review of impact chains. The resulting Impact Chain KMS hence acts as an interactive knowledge repository for consulting and browsing information within the impact chain, fostering knowledge transfer and learning.
The system presents risk elements in both visual and tabular formats, organising the impact chain factors into categories: hazards, impacts, vulnerabilities, risk reduction or adaptation measures, exposure, and risks. Each factor is documented with descriptions, tags, sources, and connections to other risk elements.
SPARQL Protocol and RDF Query Language leverage the analysis beyond the impact chain knowledge management system. Transforming the Impact Chain database into an RDF-compatible format enabled deeper offline exploration through sophisticated analytical approaches. These tools enabled detailed exploration of relationships between hazards, vulnerabilities, and impacts, helping identify critical nodes within the system. Furthermore, generating visual representations and quantitative overviews offered clear, evidence-based insights into intricate relationships and dependencies.
This study highlights the value of the Impact Chain KMS in advancing multi-hazard risk analysis by enabling systematic exploration of complex risk relations. Analysing the impact chains produced within the PARATUS project through the KMS contributes to getting insights into underlying patterns of hazard-impact cascading effects and vulnerabilities across diverse geographical contexts. These insights can potentially support decision-making for risk reduction strategies and can be adapted for multihazard risk analysis in other regions.
How to cite: Olaya Calderon, L. J., Cocuccioni, S., Renner, K., Campalani, P., Romagnoli, F., and Pittore, M.: Advancing Multi-Hazard Risk Analysis: An Innovative Information System for Impact Chains-based Systematic Review and Knowledge Storage., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9920, https://doi.org/10.5194/egusphere-egu25-9920, 2025.
Shifts in changing climatic pattern trigger modification in landscape, consequently intensifying the susceptibility to a range of hazards, creating a complex trajectory of environmental challenges. This research project has explored climate-induced vulnerability and risk assessment in the rapidly changing landscape of Seti River Sub-Basin within Nepalese Himalayas. Vulnerability in the region has been analysed based on exposure, sensitivity, adaptive capacity and associated indicators. The study leveraged satellite imageries, historical climate data and geospatial tools along with socioeconomic, topographic, and climatic indicators, IPCC frameworks (AR4 and AR5) and index based modeling. The research results show that the region is highly susceptible to landslide and flood hazards driven by geological setting, elevation factors and socioeconomic factors in addition to low adaptive capacity accompanied by extreme climatic events. The settlements and cultivated lands of the local Madi, Seti, Bhunge and Phusre rivers are at the risk of flood hazards while the upper slopes in Machhapuchhre and Pokhara are highly exposed to landslide hazards. Administratively, Pokhara Metropolitan city, Machhapuchhre and Rupa Rural municipalities are positioned as highly, moderate and low rank in terms of vulnerability ranking, respectively. The research underscores the need of localized risk management strategies and resilience planning. The vulnerability and risk frameworks applied in this study will be imperative and applicable in the mountainous region of Nepal and elsewhere.
How to cite: Rijal, S. and Rimal, B.: Multi-hazard vulnerability and risk assessment in the Nepalese Himalayan region using IPCC AR4 and AR5 frameworks, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13439, https://doi.org/10.5194/egusphere-egu25-13439, 2025.
With increasing frequency and severity of climate risks, communities must further adopt Climate Risk Management (CRM) strategies. As a key component, Climate Risk Assessments (CRA) identify and evaluate climate risks across hazards, areas and sectors. Various CRA frameworks have been proposed and implemented by research, policy and practice. One key gap identified is the effective integration of quantitative and qualitative aspects in CRA to develop comprehensive results as well as ensure integration of various perspectives. For this, it is necessary to understand how quantitative and qualitative risk aspects come together in combined approaches to support and balance each other.
In the context of the EU Horizon 2021 project CLIMAAX, we developed a comprehensive CRA framework adapted for the European regional and community level. The Framework unites approaches for risk quantification (provided in the CLIMAAX Handbook) and at the same time encourages qualitative risk input through participation of experts, stakeholders and vulnerable groups. Our approach seeks to respond to needs, recent advancements and best practices in the CRA field by integrating insights from European National Adaptation Plans and Strategies, peer-reviewed literature, as well as existing CRA frameworks and international standards. The framework was collaboratively developed with five European pilot regions and considers survey responses from the CLIMAAX Community of Practice to ensure feasibility and applicability while upholding adaptive flexibility.
The CRA Framework is operationalized through a five-step assessment cycle (Scoping, Risk Exploration, Risk Analysis, Key Risk Assessment, Monitoring & Evaluation). These steps are supported by principles of social justice and equity, participatory processes, and technical considerations such as future scenarios. In the quantitative Risk Analysis step the Framework is strongly supported by multiple risk workflows estimating climate risk. The other four steps provide entry points for qualitative risk assessment perspectives, thus requiring translation and interdisciplinary thinking. We innovatively contextualise the risk analysis outcome as quantitative and qualitative aspects are processed together. Through an indicator-based evaluation of risk severity, risk urgency and resilience capacity we consider Key Risks in a multi-hazard risk context.
By collecting data from users within the CLIMAAX project, we will assess how qualitative as well as semi-quantitative risk perspectives can benefit and complement quantitative risk estimations as applied in the risk workflows. Further, by effectively integrating diverse perspectives, the framework aims to bridge the translation gap between risk assessment and CRM practices towards fostering resilience.
How to cite: Bachmann, M., Mechler, R., Higuera Roa, O., Pirani, A., Pal, J., Mozzi, G., Stuparu, D., and Mazzoleni, M.: Combining quantitative and qualitative risk aspects for adaptive and flexible climate risk assessment , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8462, https://doi.org/10.5194/egusphere-egu25-8462, 2025.
Consecutive events, where two or more disasters occur in succession before recovery from the first event has been completed, have non-linear impacts on societies that may often surpass the effects of disasters that occur in isolation. This work underscores the pivotal role of recovery in shaping the cumulative impacts of consecutive disasters, offering key insights into the challenges, opportunities, and long-term implications of consecutive disasters for post-disaster recovery and risk management in the context of increasingly frequent and intense hazards.
Incomplete recovery hinders the ability of communities to respond to subsequent events, creating compounding challenges that can lead to non-linear and potentially irreversible societal changes. With climate change affecting the frequency and severity of extreme weather events, the likelihood of consecutive disasters and interval time between events are projected to change, affecting the time available for recovery between events. We have reviewed the implications of consecutive disasters for societal recovery, identifying key processes that contribute to non-linear impact interactions. While consecutive disasters can create many challenges that complicate disaster recovery, recurrent disaster exposure can also present opportunities for social learning, transformation, and increased resilience and preparedness over time. Based on insights from scientific studies and real-world examples, we discuss challenges and opportunities related to recovery across different societal dimensions—such as human settlements, public health, socio-political systems, and the economy—under the influence of consecutive disasters. We have also evaluated how the effects of consecutive disasters on disaster recovery can, over time, result in social tipping-points, characterised by non-linear and potentially irreversible societal transitions, offering a long-term perspective on the cumulative effects of consecutive events.
Lastly, we evaluated existing methodologies for analyzing recovery dynamics in the context of consecutive disasters, highlighting gaps and limitations in the current body of knowledge. Based on these findings, we propose a research and policy agenda aimed at addressing these gaps, improving disaster recovery research, which will ultimately support societies to effectively manage consecutive disasters in the face of increasingly frequent and intense hazards.
How to cite: Buijs, S. L., Kropf, C. M., De Ruiter, M. C., Juhel, S., Stalhandske, Z., and Sauer, I. J.: Challenges and opportunities of consecutive disasters for societal recovery, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3252, https://doi.org/10.5194/egusphere-egu25-3252, 2025.
In the summer of 2018, large parts of Scandinavia faced record-breaking heat and drought, leading to increased mortality, agricultural water shortages, hydropower deficits, and higher energy prices. The 2018 heatwave, coupled with droughts leading to wildfires, was described as a multi-hazard event, defined as compounding events.
The goal of this presentation is to better understand the economic impact of the 2018 multi-hazard events in Scandinavia. In this analysis, we utilize empirical data to assess the physical impacts in agriculture, forestry, and energy sectors. Furthermore, we evaluate the indirect economic impacts of the 2018 multi-hazard event using a global multi-sectoral and multi-regional Computable General Equilibrium (CGE) model, GRACE (Global Responses to Anthropogenic Changes in the Environment). The GRACE model does not only describe the interactions among producers and between producers and consumers in the domestic region but also considers the interactions between local and global economies through international trade.
Our economic assessment reveals varying and wide-spreading results across sectors and regions, particularly in Europe. The 2018 multi-hazards resulted in reductions in agriculture, energy and forestry output as the direct impacts. The sectoral-specific impacts also transfer to other sectors in the Scandinavian economy. For example, we find a decrease in manufacturing production caused by reduced intermediate inputs of agriculture, energy and forestry goods. At the same time, we also find an increase in the production of oil and gas due to the substitution effect of less electricity production.
Furthermore, the compound event of 2018 also affected the trade of forestry goods because of the vital role of Scandinavia in the international wood market. This led to a moderate yet widespread effect on GDP losses, affecting not only the Scandinavian region but also trading patterns, particularly in Europe. This result emphasizes the importance of including the market effect of cross-border trade when analyzing the impacts of compound events in the Scandinavian region.
This project is supported by the European Union’s Horizon 2020 funded project MYRIAD-EU (Grant 101003276).
How to cite: Ma, L., Daloz, A. S., Ducros, G., Tiggeloven, T., and C. de Ruiter, M.: Multi-hazards in Scandinavia: Economic impacts of compound heatwaves, droughts and wildfires in 2018, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6873, https://doi.org/10.5194/egusphere-egu25-6873, 2025.
Compounding or cascading disasters, marked by the occurrence of multiple or consecutive hazards, lead to several impacts on both individual and collective levels, surpassing those of single-hazard disasters. Despite their severe consequences, global and regional impact databases still record disasters using a single hazard lens. This is the case of Brazil, which is confronted with intricate dynamics of overlapping hazards. To address this gap, we reclassified natural hazard-related disasters recorded in the Brazilian Integrated Disaster Information System (S2iD) database spanning 1991-2022 into different compounding and cascading disaster categories. We identified 2,236 co-occurring disasters, 30,913 spatially compounding disasters, and 1,338 temporally compounding disasters. A permutation test revealed expected significant co-occurrences, such as urban floods and landslides, droughts, and wildfires, alongside surprising pairings like droughts and cold waves. Using the apriori algorithm, we found significant event sequences, including wildfires followed by droughts, landslides after flash floods, and landslides preceding storms. Our analysis shows an increasing time trend in compounding and cascading disasters, predominantly occurring in regions northeast, south, and midwest. Notably, the impacts of these compounded disasters are greater than those of single-hazard events. These results underscore the need to integrate a multi-hazard perspective into disaster databases in Brazil and beyond. By accounting for the interactions between disasters, policymakers, and practitioners can design more robust adaptation measures that address interconnected risks.
How to cite: Nunes Carvalho, T. M., Zscheischler, J., and de Brito, M. M.: Compounding and cascading disasters in Brazil, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9277, https://doi.org/10.5194/egusphere-egu25-9277, 2025.
The interconnected nature of climate-driven hazards poses significant challenges for risk management and disaster preparedness. Compound Flooding (CF) in estuarine and coastal regions exemplifies this complexity, where the interaction of drivers such as storm surges, extreme rainfall, and river discharge generates cascading impacts that traditional univariate assessments cannot fully address. As climate change accelerates the occurrence of CF, advancing methods to characterize these interactions and translating this knowledge into adaptive strategies is essential for reducing risks and building resilience.
This study combines a multivariate framework for estimating joint return periods with an exploration of preparedness strategies to address the intricate challenges posed by CF. Applied to the Santoña estuary in Northern Spain, it employs copula-based models to analyse dependencies among CF drivers and estimate joint return periods in a high-dimensional context. The analysis not only enhances our understanding of extreme events but also provides practical tools to improve risk assessments. Building on these findings, a systematic literature review examines the evolution of preparedness measures, highlighting advancements such as hybrid early warning systems and integrated infrastructure. However, persistent barriers—including fragmented governance, limited coordination, and insufficient consideration of behavioural and psychological factors—continue to constrain their effectiveness.
Together, these insights emphasize the need to rethink how to manage compound flooding—bridging governance gaps, fostering collaboration among scientists, policymakers, and communities, and integrating technical innovation with people-centered strategies. Such frameworks must not only respond to immediate challenges but also adapt to the evolving uncertainties that define the complex risk landscape of CF.
References
- Del Jesus, M., Urrea Méndez, D., & Gomez Rave, D. V. (2024). Return period of high-dimensional compound events. Part I: Conceptual framework. Hydrology and Earth System Sciences Discussions, 2024, 1-27.
- Eilander D, Couasnon A, Leijnse T, Ikeuchi H, Yamazaki D, Muis S, et al. (2023). A globally applicable framework for compound flood hazard modeling. Nat Hazards Earth Syst Sci. Feb 27;23(2):823–46.
- Van Den Hurk BJJM, White CJ, Ramos AM, Ward PJ, Martius O, Olbert I, et al. (2023). Consideration of compound drivers and impacts in the disaster risk reduction cycle. iScience. Mar;26(3):106030.
- Ward PJ, Daniell J, Duncan M, Dunne A, Hananel C, Hochrainer-Stigler S, et al. (2022) Invited perspectives: A research agenda towards disaster risk management pathways in multi-(hazard-)risk assessment. Nat Hazards Earth Syst Sci. Apr 26;22(4):1487–97.
- Zscheischler, J., Martius, O., Westra, S., Bevacqua, E., Raymond, C., Horton, R. M., ... & Vignotto, E. (2020). A typology of compound weather and climate events. Nature reviews earth & environment, 1(7), 333-347.
How to cite: Gomez Rave, D. V., Urrea Mendez, D. A., Scolobig, A., and del Jesus, M.: Understanding and Preparing for Compound Flooding, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9471, https://doi.org/10.5194/egusphere-egu25-9471, 2025.
This presentation will show preliminary results from a project looking at how the multi-hazard concept can be embedded into household preparedness plans, particularly in low-income settings. The first component of the project is a systematic review of the academic literature that addressed two questions: (a) “what are the components of a ‘good’ household preparedness plan and its uptake?” and (b) “to what extent is the concept of multi-hazards embedded into household preparedness planning research”? For each question, a range of keywords were developed and input into Web of Science, returning 427 and 177 relevant papers respectively. Papers were categorised by (i) methodological approach, (ii) geographical scope, (iii) hazards considered, and (iv) aspects of the household preparedness plan such as specific actions, uptake success and intended audience. For research question (a), papers were compared to Sutton and Tierney’s (2006) eleven general principles of household preparedness. Key findings about the current body of literature include:
- A narrow methodological scope – the majority of papers reviewed adopted quantitative survey approaches which tend to inadequately capture the complex interplay of factors which determine levels of household preparedness.
- A narrow geographical scope – the majority of papers reviewed apply to middle- and high-income countries and urban areas within, meaning the recommendations emerging from them are not easily applicable in Global South contexts, and may even be counterproductive.
- A single hazard or hazard agnostic approach – many papers either focused on a narrow range of specific hazards or implied relevance to ‘all hazards’. Largely this is done in a multi-layer single hazards approach, or under the assumption that being prepared for one hazard results in improved preparedness for other hazards, which misses potential compounding interactions between hazards and/or preparedness actions.
- Studies often focus on barriers to preparedness, rather than taking a critical collaborative approach to co-creating tools that are useful, useable and used.
This literature review and our research findings will inform a proof-of-concept toolkit to support both households and organisations in developing household preparedness plans that is (i) mixed-methods, (ii) targeted at small to medium urban centres in the Global South, (iii) specifically address how both hazards and preparedness actions may interact to compound the impacts and/or benefits and (iv) centres affected community voices, promoting accessible approaches in line with Sendai Framework Priority 4.
How to cite: Taylor, F., Gilmour, M., McGowran, P., and Gill, J.: How does the concept of household preparedness apply in a multi-hazards context? Results from a systematic literature review. , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18331, https://doi.org/10.5194/egusphere-egu25-18331, 2025.
Traditional approaches to disaster risk assessment often consider natural hazards in isolation, overlooking the complex interplay between hazards, which can significantly affect overall impacts. Compound flood events, characterised by co-occurring or preceding anomalous conditions, may exacerbate flood impacts and result in greater damage. This study investigates the effects of five compound flood events—flood sequence, drought-to-flood, cold-to-flood events, hot-to-flood sequence, and compound flood and wind—and their relationship with disaster vulnerability on flood impacts at a sub-national level across Europe from 1981 to 2020. Historical flood records are obtained from the extensive HANZE database, which includes detailed regional information, event timelines, and associated losses. Recorded flood impacts are spatiotemporally matched with associated hazards computed from ERA5, enabling a thorough comparison of isolated versus compound flood impacts. This results in a new dataset of multi-hazard events based on disaster records and climate reanalysis data. Using this dataset, our analysis explores the trends of compounding hazards on flood impacts by examining physical interactions at the hazard level and changes in vulnerability. This approach represents a step forward in disentangling the contributions of these factors to flood risk, with the goal of informing more resilient community strategies and effective disaster risk reduction in an era of complex crises.
How to cite: Ronco, M., Tilloy, A., Corbane, C., Feyen, L., Paprotny, D., Jager, W., Claassen, J., Tiggeloven, T., Riemann, L., Matano, A., Delforge, D., Kummu, M., Sibilia, A., and Ward, P.: Exploring Vulnerability Dynamics Associated with Compound Flood Impacts Across European Regions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19024, https://doi.org/10.5194/egusphere-egu25-19024, 2025.
Disaster Risk Management (DRM) has been evolving under the pressure of new challenges brought by increasingly frequent and severe multi-hazard events. These events are more likely to impact multiple countries at once, exposing common and specific vulnerabilities of neighbouring communities. One prominent and recent example for Europe comes from the flood events in 2021, considered one of the most destructive hydrological disasters of the 21st century. In Europe, the July 2021 floods claimed over 200 lives, causing widespread disruption and economic loss exceeding 50 billion euros.
The resulting shared but distinct experiences call for joint reflection from scientists and stakeholders from the impacted countries and regions – an exercise whose significance we are only beginning to understand.
This study aims to cross-examine the impacts of the 2021 flood events in Romania and the Netherlands, alongside the vulnerabilities that contributed to them and the adaptation options employed to address them. Drawing from a wide range of sources (e.g., scientific papers, official reports, administrative acts, hydro-meteorological datasets, and news reports), two distinct Impact Chains were developed, one for each country. From these models, we elicited lessons regarding the best practices and blind spots in DRM.
The Impact Chains revolve around the most severely affected areas in the two case studies: Alba County in the northwest of Romania and Limburg province in the southeast of the Netherlands. The chains include cascading hazards such as floods, heavy rainfall, strong winds, and landslides. To ensure their accuracy and reliability, the models were calibrated and validated through stakeholder surveys conducted in each case study area.
Employing a set of Kumu metrics and other custom-designed metrics, the two Impact Chains were analysed to identify the most prominent flood impacts, vulnerabilities, and adaptation options. The comparative analysis provided key insights into the DRM approaches in Romania and the Netherlands, which were leveraged to pinpoint both strengths worth of replication and weaknesses that should be avoided. Notable best DRM practices refer to effective search and rescue operations in both countries, the simplification of flood damage compensation procedures in Romania , and the swift evacuation and accommodation of the population in Limburg. In terms of critical blind spots, both countries are yet to design (multi-)hazard management strategies that factor in pandemic conditions and that also proactively address vulnerabilities rather than merely mitigating flood impacts.
These DRM lessons offer relevant answers to the crux questions that arise following major hazardous events, such as the floods of 2021: What can be done to fend off such severe impacts in the future? and What can we learn from the experience of other countries? By bringing together examples of best practices and pitfalls of DRM, this study fosters constructive dialogue grounded in shared experiences.
This research opens the way to further Impact Chain-based cross-country comparisons of multi-hazards, in an effort conducive to collaboratively deciphering the interplay of multi-risk in diverse contexts and to linking it with country- or region-specific DRM policies and practices.
How to cite: Albulescu, A.-C., Armaș, I., De Ruiter, M., Endendijk, T., and Stotle, T.: Shared floods, shared lessons: Best DRM practices and blind spots. An Impact-Chain cross-country analysis of the 2021 floods in Romania and the Netherlands, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3489, https://doi.org/10.5194/egusphere-egu25-3489, 2025.
Many regions worldwide are increasingly facing multi-hazards and systemic risks that threaten their socio-economic stability and environmental resilience. Island regions, particularly those heavily reliant on tourism, are uniquely vulnerable due to a convergence of structural and systemic challenges, including geographical isolation, dependence on external imports, resource limitations, and fragile ecosystems. These factors heighten their exposure to environmental and economic shocks. The impacts of climate change, natural hazards, and global crises, such as the COVID-19 pandemic, have further exposed the tourism sector’s susceptibility to cascading and compounding risks. Effective multi-risk strategies and policies in tourism-dependent island regions require adaptive, cross-sectoral approaches that address these interdependencies and promote resilience. In this context, risk misperceptions present significant barriers to the development of comprehensive policies by distorting priorities, fragmenting decision-making, and impeding cross-sectoral collaboration.
Using the Canary Islands as a case study, this research examines how stakeholder perceptions and misperceptions hinder the development of effective multi-hazard risk policies, with a focus on tourism interdependencies. A participatory, cross-sectoral framework was applied, analyzing qualitative data from semi-structured interviews and focus groups with diverse stakeholders, including representatives from tourism, agrifood, energy, water sectors, as well as researchers, local authorities, and emergency response services. Our findings reveal that stakeholder perceptions are often hazard-specific and sector-oriented, leading to a lack of recognition of interconnections between sectors, multi-risks, cascading impacts, and dynamic vulnerabilities.
These misperceptions result in fragmented policy responses, inadequate resource allocation, and limited integration of long-term resilience measures.
To address these challenges, this paper introduces an innovative categorization of risk misperceptions into four clusters: i) Underestimation, where stakeholders downplay the likelihood or impact of hazards; ii) The Single-Sector Fallacy, reflecting a narrow focus on sector-specific risks while ignoring cross-sectoral interdependencies; iii) Overconfidence, stemming from an overreliance on existing systems or capacities; and iv) Climate Stability Assumptions, rooted in a misunderstanding of the pace and severity of climate change impacts. This categorization makes a significant contribution to risk research and policy-making by offering a dynamic and actionable framework to diagnose the root causes of ineffective risk management. By breaking misperceptions into distinct clusters, it provides a nuanced understanding of specific challenges, each paired with targeted intervention opportunities. For example, scenario-based workshops address underestimation, cross-sector dialogues to dismantle silos from the Single-Sector Fallacy, and tailored communication campaigns to address misconceptions about climate risks. This structured approach enhances the ability of policymakers to develop practical, evidence-based tools that address misperceptions directly, fostering more comprehensive and effective multi-hazard risk strategies.
How to cite: Padrón-Fumero, N.: Cross-sectoral Multi-Hazard Risk Perceptions and Misperceptions in Tourism-Dependent Islands: A Canary Islands Case Study, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20551, https://doi.org/10.5194/egusphere-egu25-20551, 2025.
Europe faces a variety of different natural hazards both from its natural state as well as from a changing climate. Dozens of different perils affect European societies and businesses every year. In addition, some of these perils also overlap in space and time demanding additional resilience from affected communities. Unsurprisingly, there have been many different undertakings to quantify Europe’s hazards and risks. However, there is no comprehensive aggregation of all those hazards and how they potentially interact with each other. Within the MYRIAD-EU Horizon 2020 project, we have developed an extensive collection and assessment of open hazard models for Europe and aggregated their results in the context of various exposures like population, GDP and sectoral data like tourism expenditure or capital stock.
This collection of overlapping European “exposure-at-risk” provides an unique and holistic perspective into the occurrence of natural disasters, from all kinds of climate risk indicators for today and the upcoming decades to physical risks likes earthquakes, sea level rise, storms, wildfires and many more. It combines both probabilistic and stochastic assessments and thus can provide multi-hazard and multi-risk interactions for any place in Europe.
The comprehensive representation of natural and climate change-related hazards has been combined with an extensive collection of exposure for the sectors of finance, infrastructure and energy, agriculture and tourism as well as ecosystems and cross-sectoral metrics on an A21 level. Each of these systems comes with respective vulnerability equations. Risk can be evaluated on a probabilistic or deterministic basis. Deterministic scenarios both stem from historic and stochastic model depending on the assessed peril.
In summary, we showcase a database and toolbox to assess historic, deterministic and probabilistic metrics on a single- and multi-risk basis for all of Europe using integrated results on a NUTS3 level and at other spatial levels.
How to cite: Schaefer, A., Daniell, J., Brand, J., Maier, A., Girard, T., and Khazai, B.: Europe’s Exposure-At-Risk: Comprehensive multi-risk assessments from climate to catastrophe in tourism, finance, agriculture and other sectors, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16674, https://doi.org/10.5194/egusphere-egu25-16674, 2025.
Archetype-based classifications are a well-established method to categorize certain environments, systems or elements, according to the characteristics that differentiate them and make them unique. Typically, the final aim of archetype-based classifications is to facilitate the design of adaptation strategies.
In the context of critical infrastructures (CI), archetype-based classifications are particularly valuable for assessing climate risks across different time horizons and climate change scenarios. This proposal presents a comprehensive methodological framework to use archetypes to identify and define adaptation options in the context of the climate risk framework of the Intergovernmental Panel on Climate Change (IPCC).
The proposed framework adopts a multidimensional approach to characterize climate risks archetypes, incorporating physical, economic, and social dimensions. Through an indicator-based methodology, it identifies analogous infrastructures—those with similar climate risk patterns—and groups them into archetypes. The final objectives of this methodological framework are: first, to identify analogous infrastructures (i.e., infrastructures that present a similar climate risk pattern and, therefore, that are classified in the same archetype) and; secondly, to design adaptation trajectories for the CI based on their classification for the different climate change scenarios, optimizing the adaptation planning and management in the short, mid and long-term.
To illustrate the applicability of this methodology, the framework has been applied as a case study to European airports. Using the proposed approach to characterize the risk components —hazard, exposure and vulnerability—, airports have been classified into climate risk archetypes, identifying risk patterns across the physical, economic, and social dimensions. This case study exemplifies the utility of the framework for identifying analogous infrastructures and informing about effective adaptation options and pathways, helping in decision-making processes.
Beyond its analytical contributions, the framework enhances risk communication by offering a comprehensive overview of climate risks and their potential impacts. This facilitates engagement with stakeholders, including infrastructure owners and operators, fostering coordinated efforts to adapt to climate risks and build CI resilience. The scalability and adaptability of the framework make it a valuable tool for managing climate risks in diverse infrastructure systems and regions.
How to cite: Barrios-Crespo, E., Torres-Ortega, S., and Diaz-Simal, P.: Towards Resilient Critical Infrastructures: An Archetype-Based Approach to Climate Risk and Adaptation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17225, https://doi.org/10.5194/egusphere-egu25-17225, 2025.
Accumulation of high-resolution data relevant to water resources management and policy is fast and accelerating. The related analytic approaches to harness this data are also in rapid evolution. However, the distance form data analysis to policy making remains vast, as policy level actors usually appreciate spatially aggregated information on units such as river basins or provinces, and parallel consideration of various issues such as hazards, stressors, exposure factors, vulnerabilities, and risks, which still rarely are brought together by data scientists in scales that would readily communicate with planning units of water resources. Further, scaling from these planning units to local conditions is of great value. China, as a sizable and geographically heterogeneous country, is subject to a high diversity and blend of water related stressors, hazards, and conditions of exposure and vulnerability. We present results of the exposure and vulnerability of continental China’s eight major water stresses (variability, overuse, groundwater problems, floods, droughts, organic pollution, salinity, eutrophication). To be maximally policy compatible, this gridded high-resolution geospatial analysis employs the multiplicative risk scheme of the United Nations Sendai Framework for Disaster Risk Reduction and IPCC (risk = stress x exposure x vulnerability) and is combined with multivariate statistical pattern recognition (unsupervised learning based on eigenvalue analysis). The results unveiled five distinct zones in continental China, each with a characteristic risk profile, for both provinces and river basin planning units.
How to cite: Varis, O. and Zhao, D.: Recognition of policy relevant spatial patterns from high resolution multirisk data – the case of China’s water risk portfolio, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9478, https://doi.org/10.5194/egusphere-egu25-9478, 2025.
The growing global exposure to multi-hazard events highlights the need for a comprehensive understanding of how vulnerability interacts with these hazards, particularly in regions with lower socio-economic development, as vulnerability amplifies the impacts and hinders recovery efforts, perpetuating cycles of poverty and inequality. Here, we provide a global level analysis of multi-hazard exposure and disparities in socio-economic vulnerabilities. Our findings reveal that most of the global population has been exposed to multi-hazards (84% of total population). Our analysis discloses a discernible global trend as we observe disparities of individuals with lower socio-economic development are significantly more likely to being exposed to multi-hazards more frequently. The same pattern also persists at regional scales and underscores a critical intersection between natural hazards and socio-economic vulnerability, where certain populations are disproportionately affected. When looking into the intersection of compounding vulnerabilities based on overlapping social identities and disparities, we find that this pattern persists and exacerbates in some regions. In the face of climate change and increasing inequalities in the world, recognizing and addressing these trends are essential, not only from a humanitarian perspective but also for advancing global development agendas and climate justice. These compounded risks faced by marginalized communities should be better aligned with global initiatives like the Sustainable Development Goals (SDGs) to ensure equitable and resilient societies.
How to cite: Tiggeloven, T., Stolte, T., Claassen, J., Chang, C.-W., Paszkowski, A., Schneiderbauer, S., Yotsui, S., and van Maanen, N.: Multi-hazards in an unequal world, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1005, https://doi.org/10.5194/egusphere-egu25-1005, 2025.
The compounding effects of multiple hazards are increasingly recognised as critical for understanding risk and informing decision-making. However, hazards are often treated as discrete and independent entities. This conventional approach frequently overlooks the intricate interactions between hazards and their combined impacts on specific locations. Such limitations can lead to inaccurate risk estimates, undermining the effectiveness of preparedness and response strategies. As the shortcomings of single-hazard approaches become more apparent, there is growing recognition of the need for a comprehensive framework that integrates stakeholder perspectives and scientific insights. This integration can enhance multi-hazard risk management strategies, improving resilience and better aligning with the complexities of a changing climate and evolving hazard landscapes. Therefore, this paper examines multi-hazard information to local-level decision-making in Disaster Risk Management (DRM) and Climate Change Adaptation (CCA), with a focus on Essex as part of the MEDiate ('Multi-hazard and risk-informed system for enhanced local and regional disaster risk management') project, funded by the Horizon Europe. Essex, a low-lying county with a 905 km coastline and a high population density concentrated in southern coastal regions, is significantly susceptible to extreme wind and rainfall events, storm surges, and flooding. Through this case study, we demonstrate the generation of tailored multi-hazard information through policy reviews, analyses of spatially compounding extreme wind and rainfall events, and stakeholder engagement workshops. The results revealed that UK national policies acknowledge multi-hazard risks, DRM and CCA approaches largely remain single-hazard focused. The result of spatially compound event analysis indicate increases in wind speed and rainfall intensity by 2050, with coastal and southwestern Essex identified as high-exposure regions with a 100-year event, the mean daily maximum wind speed, recorded at 10.7 ms-1 during the baseline period, is anticipated to rise to 11 ms-1 by 2050. The stakeholder workshop highlighted the need for multi-hazard information to be compatible with existing systems, tailored to specific purposes, accessible, and integrative. This study developed a methodology to support multi-hazard risk-informed decision-making by generating practical and applicable insights for planning and managing risks, ultimately enhancing climate change adaptation.
How to cite: Cha, Y., White, C., Adnan, M. S. G., Arosio, M., and Yousaf, Z.: Incorporating Multi hazard approach to disaster risk management and climate change adaptation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20670, https://doi.org/10.5194/egusphere-egu25-20670, 2025.
Standardized hazard definitions are a key element of the analysis of disasters. Without them, monitoring and reporting of the impacts of the hazards is difficult, and so is the development of effective early warning systems and response plans. Forecasting of future events and the generation of disaster risks reduction strategies are also hindered by a lack of standardized definition. To address this gap, in 2019 the UN Office for Disaster Risk Reduction (UNDRR) and the International Science Council (ISC) established a Technical Working Group to identify the full scope of hazards relevant to the Sendai Framework for Disaster Risk Reduction as a basis for countries and other actors to review and strengthen risk reduction policies and risk management practices. The resulting UNDRR/ISC Hazard Information Profiles (HIPs) were published in 2021.They provide to a broad range of users standardised definition and information on more than 302 hazards organized into 8 groups: meteorological and hydrological, extraterrestrial, environmental, geological, chemical, biological, technological and societal.
Following on recommendation in the UNDRR/ISC HIPs for regular review and update, experts from different disciplines, types of organizations (United Nations agencies, academia, government agencies, intergovernmental organizations and the private sector) and geographical regions are again working together to review the UNDRR/ISC HIPs. This process is systematically reviewing all sections of the current HIPs to identify potential updates in alignment with new scientific information. and decide on the inclusion of additional evidence additionally addressing the multi-hazard context of each hazard.
One of the main additions to the updated version of the HIPs is a section on multi-hazard context. The experts are specifically reviewing the interrelations between the hazards in a multi-hazard approach. The HIPs aim to summarize direct interactions between hazards in a concise and visual way.
In the future, the HIPs will be coded to be machine actionable, to support a broader range of applications when machine readability is extremely useful, for example, for analysis of large databases and datasets. This is especially relevant in the context of disaster risk management and of loss and damage associated to climate change.
This second review will conclude in 2025, with the release of the enhanced UNDRR/ISC Hazard Information Profiles at the Global Platform for Disaster Risk Reduction. The updated document will continue to inform a broad community and support data analysis resulting in better early warning and event forecast and disaster risk management and planning.
How to cite: Jacot Des Combes, H. and Murray, V.: The updated UNDRR/ISC Hazard Information Profiles – Standardized hazard definition and information to support hazard understanding, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15451, https://doi.org/10.5194/egusphere-egu25-15451, 2025.
The efficacy of early warning systems in saving lives and reducing other losses and damages is widely recognized. However, these systems often lack information about the potential impacts on people, assets, and systems. Impact-based early warnings that consider information on exposure and vulnerabilities could fill this gap, enabling a more effective public response and preparedness - notably for vulnerable groups often disproportionately affected by climate extremes. The increasing cost of climate extremes and the focus on non-economic losses and damages from climate change underpins the need to advance risk knowledge, notably integrating vulnerability and exposure information into existing EWS. The UNDRR-funded EarlyWarning4IGAD project addresses this gap by supporting countries in the Greater Horn of Africa to transition from existing hazard-based to impact-based early warning systems.
Building on desk study, expert interviews, and stakeholder consultations, we present a novel approach for impact-based early warning for floods and droughts in the Greater Horn of Africa by integrating data and information on exposure and vulnerability into existing hazard-based systems. Thereby, one particular element is the co-creation of conceptual risk models with and for different vulnerable groups, such as (i) small-scale farmers for crop losses, (ii) vulnerable segments of society for harm to people due to floods, or, more specifically focusing on (iii) women and girls, (iv) people with disabilities, and (v) people in camp settings. In doing so, we show how such risk knowledge can be used to inform impact-based early warnings and ultimately integrated into existing operational flood and drought early warning systems at the regional level, as well as where remaining challenges for operationalization lie.
How to cite: Thalheimer, L., Pfeiffer, S., Cotti, D., Dewi, M., Alfieri, L., Okoth, V., Amdihun, A., Wanjohi Nyaga, J., Werners, S., and Hagenlocher, M.: Towards actionable impact-based early warning for floods and droughts in the Greater Horn of Africa, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16937, https://doi.org/10.5194/egusphere-egu25-16937, 2025.
Within the framework of the European project titled “Multi-hazard and risk informed system for Enhanced local and regional Disaster risk management” MEDiate (Grant agreement ID: 101074075), one of the main expected outcomes is a platform where a robust decision support system is implemented. The latter is intended to assist the responsible administrations in taking actions to mitigate the impacts of extreme natural events. The MEDiate platform effectively serves as the container for the project results to make them available to stakeholders.
The MEDiate DSS is calibrated for four European testbeds, even if the platform implements a modular framework to achieve a replicable and scalable solution. Tools for uploading data for new areas are also provided. The MEDiate platform can be conceived as divided into two modules. The first module is designed to calculate damages and losses on the exposed asset. This module considers one hazard at a time, the combination of multiple compound (temporal and spatial) hazards, and the combination of hazards that trigger others. The second module is dedicated to mitigation actions. In this module, with the assistance of artificial intelligence, the list of mitigation actions is defined. These actions are then processed by adopting the Multi-Criteria Decision Method (MCDM) to ultimately identify the most effective action.
This research presents the structure of the DSS platform developed in MEDiate and its applications for the hazards considered within the project: compounding coastal and riverine flooding, extreme heat and drought, extreme wind and precipitation, and extreme precipitation and landslides—in four European testbeds: Oslo (Norway), Nice (France), Essex (UK), and Múlaþing (Iceland), respectively.
How to cite: Borzi, B., Cantoni, A., Arosio, M., Meslem, A., Huang, C., Galasso, C., Otarola, K., Cremen, G., Komendantova, N., Yeganegi, M.-R., Danielson, M., Trevlopoulos, K., and Gehl, P.: Implementation of a Decision Support System (DSS) to guide local and regional administrations in the mitigation of impacts due to Multi-(hazards), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17739, https://doi.org/10.5194/egusphere-egu25-17739, 2025.
Climate change poses a profound risk to farming activities, threatening agricultural productivity and livelihoods through increasing temperatures, erratic rainfall patterns, and frequent extreme weather events. These challenges raise critical questions about the resilience of farming systems, particularly under diverse socio-economic and environmental pressures. Resilience must be understood in terms of both system-level dynamics and individual actors, whose decision-making processes exhibit significant heterogeneity. Farmers’ unique preferences, perceptions, and strategies necessitate well-defined policies that consider individual behaviors to enhance resilience. Agent-based modeling (ABM) offers a robust framework to address these challenges by explicitly representing the diversity of actors and their behaviors while simulating the impacts of climate threats and policy interventions on farming systems.
This study adopts a novel agent-based framework, ABNexus, designed to analyze the resilience of the Adda River farming system in northern Italy. ABNexus integrates an ABM with a distributed-parameter water balance crop yield model, IdrAgra, to provide high spatial resolution and behavioral flexibility. The model uses survey data collected from 460 local farms to calibrate farmer profiles, capturing the diversity of decision-making processes based on farm characteristics, climate change awareness, perceived impacts, and adaptation strategies. Farmers were categorized into three distinct clusters—risk-averse, risk-neutral, and risk-taker— reflecting behavioral traits that influence their decision-making criteria within the ABM framework. We also implemented different behavioral modes, ranging from profit maximization under perfect foresight to differentiated risk aversion under uncertainty, and assessed their alignment with observed decisions over the past 20 years.
Building upon this validated framework, we assessed the resilience of the Adda River basin farming system under various climate change scenarios, such as an increased frequency of severe drought years. We further explored the impact of targeted policy interventions, such as subsidies for the adoption of water-efficient irrigation technologies.
Our results highlight the importance of incorporating behavioral heterogeneity in agricultural modeling. Historical analysis revealed that behavioral assumptions significantly influence the alignment of simulated decisions with real-world observations, underscoring the need for detailed behavioral representations. Preliminary findings from scenario testing indicate that targeted subsidies for irrigation technology adoption can enhance system resilience. However, the magnitude and distribution of these benefits vary across different behavioral assumptions, reflecting farmers’ diverse responses to policy interventions. This research provides valuable insights into the complex interplay between human behavior, climate change, and agricultural system resilience. The ABNexus framework offers a valuable tool for exploring the potential impacts of various climate change scenarios and evaluating the effectiveness of policy interventions.
How to cite: Gazzotti, P., Ricart, S., Gandolfi, C., and Castelletti, A.: Behavioral heterogeneity and system resilience in the face of climate change: an agent-based modeling approach in northern Italy, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4740, https://doi.org/10.5194/egusphere-egu25-4740, 2025.
Despite global initiatives, such as the Early Warnings for All initiative, operational realities lag behind when implementing people-centred Multi-Hazard Early Warning Systems (MHEWS) that consider multi-hazard interactions and take a first-mile, systems approach in the Global South.
This session will share perspectives from Practical Action, an international development organisation working in Latin America, Africa and Asia, to explore the diverse needs of the most at-risk and marginalised, and how core concepts of multi-hazard thinking integrate into different pillars and cross-cutting components of a MHEWS.
The session will highlight the mismatch between current ambitions and realities on the ground. Drawing on extensive experience from Practical Action, we will identify opportunities and challenges of moving towards MHEWS, emphasising the need for localised, inclusive strategies that genuinely address the diverse needs of the most vulnerable populations and fully encompass the meaning of multi-hazards, including hazard interrelationships, the dynamics of risk components, and the complexity of multi-hazard impacts.
How to cite: Budimir, M., Šakić Trogrlić, R., Almeida, C., Arestegui, M., Chuquisengo Vásquez, O., Cisneros, A., Cuba Iriarte, M., Dia, A., Lizon, L., Madueño, G., Ndiaye, A., Ordoñez Caldas, M., Rahman, T., RanaTharu, B., Sall, A., Uprety, D., Anderson, C., and McQuistan, C.: Perspectives from the Global South of people-centred multi-hazard early warning systems: opportunities and challenges , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4507, https://doi.org/10.5194/egusphere-egu25-4507, 2025.
Compound drought-wildfire event is increasing trend in its frequency and severity worldwide, driven by the interaction between drought and wildfire, as seen in the 2017 California wildfires and 2019-20 Australian wildfires. However, there is still the lack of a methodology to quantitatively estimate the risk of compound drought-wildfire disaster. Therefore, this study presents a methodology to estimate the risk of compound drought-wildfire disaster using a Drought scenario based Fire Weather Index (DFWI) and projects the future risk of compound drought-wildfire disaster based on Social Shared Pathway (SSP) climate change scenarios. Gyeongsangbuk-do province was selected as the study area which is a wildfire prone area. We estimated the risk of compound drought-wildfire disaster and found that it is about 2.9 times greater than the risk of a single wildfire disaster. Based on the SSP climate change scenarios, the projected risk of compound drought-wildfire disasters was 1.01 to 1.70 times greater than current levels. Monthly risk assessment indicated the risks from July to October would increase. The study presented a new methodology for quantitative risk analysis and the future projections of the compound disasters. From the analysis, we have known that the measures or new design criteria considering the compound disasters should be required utilized for disaster prevention and for reducing the risk. The results of this study are expected to be used as the controversial issue for the development of new design criteria or measures for the prevention of the compound disaster.
Acknowledgements: This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. 2022R1A2C2091773).
How to cite: Kim, K., Lee, H., and Kim, H. S.: Future Risk Projection of Compound Drought-Wildfire Disaster Under SSP Climate Change Scnerios, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1637, https://doi.org/10.5194/egusphere-egu25-1637, 2025.
Transport infrastructure is critical for societal functioning allowing for the movement of goods and services whilst facilitating societal connections between regions. Additionally, transport infrastructure is varied and geographically extensive; it includes roads, railways, and associated assets such as embankments, retaining walls and railway lines. These assets are vulnerable in different ways and are exposed to different hazards with a varied spatial spread; for example, extreme precipitation and earthquakes can trigger landslide and slope failures in mountainous regions potentially leading to blockages of road networks. Whilst flooding may submerge roads and damage railway infrastructure leading to ballast scour causing delays and incurring large repair costs in both instances. Moreover, multiple hazards can occur at the same time with the potential to interact, such as landslides following flooding caused by heavy rainfall or earthquakes triggering landslides causing landslide dams. Considering this, the goal of this work is to develop a multi hazard risk assessment framework for transport infrastructure exposed to multiple different and interacting natural hazards under future climate change. This provides a more holistic and accurate representation of multi hazard risk when compared to the study of single hazards, making a multi hazard risk assessment better able to take into consideration the full scope of risk threatening infrastructure systems. To conduct this research, Taiwan was selected as a case study as it represents a fascinating and dynamic landscape with advanced transport systems exposed to multiple different hazards, making it the perfect living lab to study multi hazards and their interactions. The work sought to determine the multi hazard risk of combined flooding, landslide and seismic landslides affecting transport systems on the eastern coast of Taiwan. This study simulated hazard events by integrating existing multi-hazard simulation software with new slope stability mapping software. A slope stability model employing the infinite slope model and factor of safety was generated to map slope stability under precipitation and earthquake conditions. Additionally, the Synxflow hazard modelling package was used to simulate the behaviours of landslide runouts and flooding under typhoon conditions to understand hazard behaviours. In tandem with this, GIS techniques were employed to map these combined risks within the catchment. To determine the risk to transport systems a segment-specific risk assessment was conducted, breaking down the transport systems into smaller segments to identify the area’s most at risk. Preliminary results of this show large swathes of transport systems vulnerable to multiple hazards threatening to block transport systems and cut of communities. Early results indicate that increased precipitation due to climate change is likely to exacerbate this threat, leading to more frequent road and rail closures and higher costs for repairs and rerouting.
How to cite: Doley, R., Xia, X., Lin, C.-Y., Su, W.-R., Ferranti, E., and Quinn, A.: Multi - hazard modelling and risk estimation for transport systems along the eastern coast of Taiwan exposed to flooding, debris flows and seismic landslide events , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2180, https://doi.org/10.5194/egusphere-egu25-2180, 2025.
Disasters that occur in buildings and urban spaces have a profound impact on people's daily lives, often exacerbating anxiety. In the case of buildings, the financial repercussions of damage can be substantial, and there is also a possibility of physical injuries and fatalities among occupants. Consequently, there is an imperative to assess the risk of disasters in buildings and to devise measures that ensure safety.
The building risk analysis model developed in this study was designed to meet three criteria. First, it should be capable of responding to various disaster types, allowing the addition or removal of disaster categories as needed. Second, it should be able to present disaster risk at the building level. Third, the results must be easily comprehensible so that countermeasures can be prepared based on the assessed risk. To this end, we developed a building disaster risk analysis model to evaluate building-level risks for individual disaster types and to link these results. A multidimensional matrix was employed to assess fire, flood, and landslide risks at the building level.
We then proceeded to analyze the fire, flood, and landslide risks of buildings in a sample area and linked the results. Machine learning and deep learning techniques were applied to the risk analysis. The integration of these three risk categories resulted in the classification of buildings into eight distinct categories—ranging from “very risky” to “safe”—based on the number of high-risk disaster types. A total of 32,079 buildings were assessed in the target area, of which 48 buildings (0.15%) were identified as being at high risk of both fire and flood, primarily situated along rivers and boulevards. Conversely, 47 buildings (0.15%) were at high risk of both fire and landslide, mainly located in forested areas. No buildings were found to be at high risk for all three disaster types. A total of 95 buildings (0.3%) were determined to be at high risk for two or more disaster types.
A comprehensive approach to disaster risk mitigation necessitates the establishment of a building-level disaster risk check system. This system would be informed by the risk characteristics of each disaster type and the regional distribution of high-risk buildings. By leveraging this information, it would be possible to delineate inspection areas and items, as well as prepare countermeasures to ensure building safety. The establishment of a service that can assess disaster risk on a building-by-building basis will empower residents and users to proactively identify safety concerns and implement countermeasures, thus transitioning from a passive reliance on government assistance to a more autonomous and proactive approach to disaster mitigation.
How to cite: Heo, H. K., Hyeon, T., and Kim, J. W.: Linking Disaster Risk Assessment at the Building Unit Level to Risk Reduction and Management, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5495, https://doi.org/10.5194/egusphere-egu25-5495, 2025.
Atoll islands will be increasingly affected by climate-related changes. These changes will impact multiple dimensions of the atoll islands’ socio-ecosystems, challenging their ability to recover and adapt. In this context, integrated risk assessments are needed to support adaptation strategies. Yet, such assessments are difficult due to knowledge gaps, limited data, uncertainties about climate change, and the complex interplay between climatic and non-climatic drivers. Recognizing this issue, we propose a probabilistic approach to integrate expert knowledge and uncertainties.
In this work, we developed a Bayesian Network model using a conceptual model structure and expert judgments previously used to assess the risk to habitability for 2050 and 2090 on four atoll islands in the Indian and Pacific Oceans (Duvat et al., 2021). This model allows us to assess climate-related risks in atoll islands and the potential impacts of adaptation measures. We explore the advantages and limitations of this tool to model complex systems. The advantages of this approach include the explicit treatment of uncertainties and the ability to query expert knowledge in non-trivial ways. For example, expert judgments can be used to assess the risk to habitability and future uncertainties, as well as to address inverse problems, such as identifying factors that may lead to risks exceeding specific thresholds.
Our work suggests that Bayesian Networks, despite requiring a certain level of expertise for their implementation, could be effectively used to evaluate climate-related risks and the adaptation potential of complex socio-bio-physical systems.
Keywords: Climate change risk, Atoll islands, Bayesian networks, Uncertainties, Climate adaptation
How to cite: Badillo Interiano, M., Rohmer, J., Duvat, V., and Le Cozannet, G.: Assessing atoll island future habitability in the context of climate change using Bayesian networks, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7368, https://doi.org/10.5194/egusphere-egu25-7368, 2025.
Disruptions to transportation infrastructure can isolate markets, reduce job opportunities, and hinder access to social services, leading to significant impacts that extend beyond the immediate loss of life and physical damage. The Brenner corridor is a key transalpine route for travel, commuting, and freight, operating as a central axis within the north-south European transport system. In particular, the cross-border Brenner pass, connecting Italy and Austria, is the most important on a European scale, handling a substantial daily traffic volume, with an average of 6,540 freight and 26,481 passenger vehicles in 2023. Despite its importance, this corridor is highly vulnerable to various natural hazards, particularly gravity-induced processes. This study presents a multi-hazard framework for transport infrastructure, designed to address challenges arising from natural hazards and major human-induced events that together can disrupt traffic flow along the Brenner corridor. Natural hazards, including shallow slides, debris flows and rockfalls, are addressed by two different modeling system: the Fast-Shallow Landslide Assessment Model (FSLAM) and the lumped mass rockfall propagation model (RockGIS). While, human-induced events, encompassing road accidents and maintenance activities, are analyzed using historical data provided by local stakeholders. Preliminary results reveal the complex interrelation between multiple hazards, emphasizing how individual events may occur either simultaneously (compound) or consecutively (cascading), causing cumulative effects across time and space along the transportation network. This study highlights the importance of understanding the spatial and temporal interconnections between different events, and aims to provide a dynamic multi-hazard susceptibility map for developing adaptive and resilient transport systems in hazard-prone regions.
How to cite: Pantaleoni Reluy, N., Lantada Zarzosa, N., Hürlimann, M., Wenzel, T., Höfler, F., Marr, P., and Glade, T.: Integrating natural and human-induced hazards for transport infrastructure along the cross-border Brenner corridor, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9417, https://doi.org/10.5194/egusphere-egu25-9417, 2025.
The Strait of Messina (hereafter SoM), separating Sicily from continental Italy, is prone to different, high-grade, geological hazards, including energetic seismicity (as the 1908 M 7.1 Messina-Reggio Calabria earthquake) and diffuse mass movements, triggered by intense rainfalls, as the 1 October 2009 landslide, which destroyed several little villages immediately southward of Messina, causing 37 causalities. Climatic changes pose further treats, caused by the intensification of rainfalls, which modifies the runoff/infiltration ratio, and sea level rise, fostering the intrusion of the saline wedge into coastal groundwater bodies. The landscape of the SoM area is dominated by a complex interdigitation of natural and built environments, where the evolutive dynamics of a part could trigger profound perturbations in the other, and vice versa.
Efficient environmental monitoring networks represent an indispensable tool for developing correct multi-risk assessments, and related mitigation plans. Their implementation in the SoM area is one of the aims of the WP5 “NEMESI” of the Italian PNRR project MEET, leaded by INGV, financed in the framework of the European Next Generation EU initiative.
An important part of this network will consist of hydrogeochemical stations, acquiring near real time data from state-of-the-art sensors, able to produce reliable information over time.
The strategy for designing this network has been developed as follows.
First, only parameters potentially influenced by the different hazard-generating processes acting in the SoM area have been selected, excluding those for which no efficient, or too much expensive (for the project budget) sensors are presently available.
Second, geological, geomorphological, hydrogeochemical and seismic data have been analysed, also applying geostatistical tools, for extracting a first general list of potential sites (springs, wells, piezometers, drainage galleries, surface water bodies) candidate to host the network.
Third, all sites affected by unsurmountable logistic (absence of mobile network coverage for data transmission, impossibility of building structures hosting the instrumentation, etc.) and/or administrative (time to obtain permission of using the site not compatible with the project deadline) limitations have been excluded.
The remaining sites have been equipped with low cost dataloggers, integrated by periodic surveys, for verifying that, over a complete hydrological year at least, the recorded variations were compatible with the network aims: presence of transients emerging over a pure seasonal cycle.
After the preliminary monitoring, the final list was extracted, preferring sites where variations of one or more physic-chemical parameters should represent a proxy of one or more hazard-generating processes. Some examples are: i) changes in water electrical conductivity due to saline wedge intrusion, ii) variations of temperature and piezometric levels induced by permeability changes driven by seismic and aseismic deformations, iii) changes in oxygenation, turbidity and dissolved CO2, which can be controlled by both eutrophication and mixing with deep volatiles, whose flux is driven by neotectonic activity.
The final aim is producing open access data of interest for the different stakeholders, including, but not limited to, the scientific community, the shellfish food industry, urban planners, water companies, public agencies, general contractors involved in civil infrastructures construction.
How to cite: Cangemi, M., Madonia, P., Aronica, G. T., Mattia, M., Risica, A., Selvaggi, G., and Doglioni, C.: A multi-(hazard) risk approach for maximizing the efficiency of a hydrogeochemical monitoring network in the Strait of Messina (Italy) area., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10413, https://doi.org/10.5194/egusphere-egu25-10413, 2025.
Climate change is increasing the frequency and severity of extreme weather events, presenting substantial risksto both natural and constructed settings. In seismically active areas, the interplay between climate-induced events and geophysical processes may intensify seismic hazards, affecting essential infrastructure and ecosystems. The complex project "Competence Center for Climate Change Digital Twin Earth for forecasts and societal redressement: DTEClimate", funded within the framework of the National Recovery and Resilience Plan of Romania, consists of five other digital twin projects, including the project "The research center for climate change due to natural disasters and extreme weather events (REACTIVE )" coordinated by the National Institute for Earth Physics.
The REACTIVE project addresses these challenges by investigating the multi-hazard interplay between atmospheric, hydrosphere, and lithosphere at both local and national scales. The project utilizes historical and real-time data from seismic, GNSS, infrasound, and marine monitoring networks, concentrating on high-risk infrastructure locations such as nuclear power stations, cyanide tailings ponds, oil refineries, and water dams. A primary objective is to evaluate the impact of extreme weather events, including intense precipitation and abrupt temperature changes, on seismic risk in these susceptible regions. REACTIVE improves the efficacy of monitoring stations in the Black Sea region by incorporating advanced data processing techniques into current early warning systems. The project enhances links to European and national monitoring infrastructures, promoting a collaborative framework for hazard assessment. The results encompass enhanced predictive models for seismic events affected by climate extremes and practical insights for risk assessors, infrastructure managers, and regulators. REACTIVE enhances resilience and knowledge in responding to the intricate dynamics of multi-hazard threats associated with climate change.
How to cite: Ionescu, C., Antonescu, B., Petrescu, L., Constantin, A. P., Ghica, D., Nastase, E., Grecu, B., Toader, V., Moldovan, I. A., Ene, D., and Anghel, M. N.: When Climate Meets Seismology:Exploring Multi-Hazard Risks in a Changing Planet, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16008, https://doi.org/10.5194/egusphere-egu25-16008, 2025.
Historical geodatabases are crucial resources for the analysis and management of susceptibility, hazard, and risk. Regarding landslides, they provide valuable insights into the location, date, type, size, activity, and triggering factors of such events, as well as the resulting damage. Similarly, for floods, affected areas can be identified and damage inventories systematically updated, highlighting the most impacted sectors.
This study, conducted within the framework of the Next Generation EU—Italian NRRP, Mission 4, Component 2, Investment 1.5, call for the creation and strengthening of ‘Innovation Ecosystems’, building ‘Territorial R&D Leaders’ (Directorial Decree n. 2021/3277)—project Tech4You—Technologies for climate change adaptation and quality of life improvement, n. ECS0000009, presents the initial results of the development of a GIS-based historical database for landslide and flood analysis and hazard zonation in the “Costa Viola” area, Calabria region (South Italy).
The study area is located along the southern sector of the Tyrrhenian coast, encompasses the municipalities of Bagnara Calabra and Scilla. This area is recognized as one of the Calabria’s most important tourists destination. However, its specific geological and geomorphological features, combined with a high frequency of intense meteorological events, make it highly susceptible to geo-hydrological risks.
This work presents the most significant findings of a historical investigation into rainfall-induced landslide and floods and their impact on the transportation network over the past 120 years. Historical data were gathered from a wide range of documentary sources sources, including technical reports, historical archives, scientific literature, and newspapers.
In addition, the geodatabase includes geological and topographical, infrastructure maps, a Digital Elevation Model, pre-existing landslide inventory maps, and climatic data. After the implementation of the geodatabase and update of the inventory map, we explored the characteristics of the landslides, analyzing landslide distribution and creating a landslide density map. We also explored landslide frequency for lithology, soil types and several morphological attributes (elevation, slope gradient, slope curvature, etc.), considering both all landslides and classified landslide types. Furthermore, a density map of historically flooded areas during the study period was developed.
The first results indicate that the study area has been repeatedly affected by landslide events, primarily involving debris slides, rockfalls, and debris flows. These slope movements have caused significant damage to roads and railways crossing the study area and often represents a sort of continuum with high-bedload floods, characteristic of the typical ravines shaping the hydrographic network of this Mediterranean region. The research confirms the vulnerability of the area, with 175 damaging events recorded between 1911 and 2024, corresponding to an average frequency of approximately 1.5 damaging event per year. These events show both a tendency to recur in specific areas, as well as a significant rise in frequency over recent decades. This trend is likely influenced by several factors: an increased availability and reliability of information sources, heightened attention to the damaging phenomena, the expansion of elements at risk, and the effects climate change.
How to cite: Petrucci, O. and Conforti, M.: Historical geo-database for multi-hazard zoning in the Costa Viola area (southern Calabria, Italy), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20442, https://doi.org/10.5194/egusphere-egu25-20442, 2025.
Preserving cultural heritage from natural hazards is of paramount importance due to the role that cultural heritage plays in supporting community resilience and economic activities. Therefore, being able to map the risk faced by cultural heritage, especially in a multi-risk perspective, is useful to provide a policy-making tool which highlights hotspot areas.
In this work, we present a preliminary version of a multi-risk map of cultural heritage at the national scale considering flood, earthquake, landslide and wildfire hazards, in Italy. The exposure dataset provided by the Italian Ministry of Culture counts ca. 180-thousand-point elements grouped into three classes (Architecture, Archaeological, green open space) and 393 typologies (e.g., archive, arch, abbey etc.). In order to categorize the elements in a more convenient fashion, a taxonomy of 30 classes is defined by intersecting common geometric properties of the elements (e.g., tall, subterranean, equidimensional etc.) with the type of structure (e.g., defensive architecture, buildings potentially containing valuable items, etc.). For each hazard, a qualitative classification of the vulnerability of each taxonomic element has been assigned based on expert judgement and literature studies. As source of hazard information, the national landslide inventory (provided by Istituto Superiore Per La Protezione E La Ricerca Ambientale), the flood risk management plans (by Hydrographic District Authorities), the peak ground acceleration map (by Istituto Nazionale di Geofisica e Vulcanologia) and the wildfire hazard map (CIMA Research Foundation) have been adopted. Single risk hotspots and a multi-risk map have been produced by preliminary selecting the municipal boundaries as scale of aggregation of the results.
To the best of our knowledge, this is the first work attempting to merge national-scale datasets to produce a multi-risk map for cultural heritage. Our ambition for the future is to extend this method to other types of risk and countries.
Acknowledgments: This study was carried out within the RETURN Extended Partnership and received funding from the European Union Next-GenerationEU (National Recovery and Resilience Plan – NRRP, Mission 4, Component 2, Investment 1.3 – D.D. 1243 2/8/2022, PE0000005).
How to cite: Intrieri, E., Arrighi, C., Bianchini, S., Cardinali, V., Castelli, F., Centauro, I., De Stefano, M., Fiorucci, P., Gatto, A., Marra, A. M., Meschi, G., Segoni, S., and Trucchia, A.: Mapping multi-risk for cultural heritage at the national scale, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17319, https://doi.org/10.5194/egusphere-egu25-17319, 2025.
The 2021 Tajogaite eruption of the Cumbre Vieja volcano, is one of the longest and most destructive eruptions recorded on La Palma, Canary Islands. The eruption lasted from September 19 to December 13, 2021, following a 50-year dormancy. This hybrid event was characterized by pulsatory activity, extensive lava flows, tephra fallout, and gas emissions, leading to the evacuation of over 8,000 residents, destruction of more than 2,800 buildings, and significant disruptions to infrastructure and economic sectors, including tourism, agriculture, and energy sectors. This eruption serves as a benchmark for assessing multi-hazard scenarios under current and projected future conditions.
We create a volcanic eruption sequence under current conditions for La Palma based on the previous 2021 eruption by simulating ash dispersal and deposition using Fall3D, a 3D Eulerian model, and lava flows based on the stochastic model MrLavaLoba.
Outputs, such as deposit thickness, ground load, and lava coverage, are integrated with socioeconomic and infrastructure datasets to assess exposure and potential damages with emphasis on the tourism sector. Infrastructure connectivity losses for electricity, water and roads are examined as part of the study.
In addition, the same volcanic eruption is simulated for 2050 under consideration of a preceding drought event on La Palma. This future scenario aims to illustrate the impact past events will have under future climate and socioeconomic conditions, as well as look into the dynamics of exposure and vulnerability along the pathway from 2021 to 2050.
As the quantitative outputs often only tell part of the story, semi-quantitative and qualitative methods are also used including the production of a Tourism Resilience Scorecard using qualitative and semi-quantitative indices.
Our findings underscore the critical need for integrating multi-disciplinary data and stakeholder engagement in developing actionable hazard and resilience strategies in the tourism sector. These scenarios not only deepen our understanding of past events but also provide a roadmap for mitigating future risks in the face of compounding environmental and societal challenges. This work has been completed as part of the MYRIAD-EU Project.
How to cite: Maier, A., Schäfer, A., Khazai, B., Daniell, J., Girard, T., Brand, J., Padron-Fumero, N., Diaz Pacheco, J., and García González, S.: Multi-Hazard Risk Assessment on La Palma: Building Resilience through Insights from Past and Future Impacts , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16748, https://doi.org/10.5194/egusphere-egu25-16748, 2025.
Globally, natural disasters have increased significantly in recent decades, with the CRED and UNDRR reporting 7,348 events between 2000-2019 [1]. These disasters caused 1.23 million deaths, impacted over 4 billion people, and resulted in economic losses of approximately $2.97 trillion. A large proportion of these disasters were climate-related, such as heatwaves, droughts, and floods. If the current warming trajectory continues, failure to meet the Paris Agreement goals could lead to a 10% loss in global economic value by 2050 [2]. In response, the ICARIA project aims to enhance understanding of climate-induced, complex disaster impacts and develop sustainable adaptation strategies. Focusing on critical infrastructure at risk from climate change, we study the Pinzgau region of Salzburg, with particular emphasis on fluvial flooding and storm hazards under changing climatic conditions. To assess these hazards, global CMIP6 models were dynamically downscaled using two regional climate models (WRF and CCLM) with resolutions of 5 km and 2 km, respectively, for the scenarios SSP1-2.6 and SSP5-8.5. Climate indicators, such as maximum precipitation (rx1day) and wind gusts (wsgsmax), were analysed to capture both historical (1981-2010) and future hazard trends. Observations were validated against the high-resolution CHELSA reanalysis dataset. Hydrological modeling of fluvial flooding used the physically simplified SFINCS model to simulate high-resolution flood dynamics (up to 1 m) for extreme rainfall events. Future projections will incorporate downscaled climate scenarios to estimate hazard shifts under varying emission pathways. The frequency of compound events will be analysed in the historical period as well as in a changing future. Furthermore, the change in the regions vulnerability after such an event (dynamical vulnerability) shall be investigated and exploited. Initial results indicate significant discrepancies in temperature and precipitation patterns between models for the Salzburg region. For 1981-2010, both models show cold biases compared to CHELSA, with deviations of 1°C in the north and up to 5°C in the southwest. The underestimation of maximum temperatures aligns with a notable overestimation of annual precipitation, particularly in the coarser WRF model (5 km resolution). Precipitation patterns are more consistent in CCLM (2 km resolution), which shows smaller deviations overall. Climate change signals (CCS) for Salzburg project substantial increases in maximum temperatures, with localized rises exceeding 6°C under SSP5-8.5. CCLM driven by EC-EARTH shows more pronounced changes compared to WRF driven by MPI. Annual precipitation trends differ: while WRF predicts increases of up to 15% under SSP5-8.5, CCLM outputs suggest slight decreases. Preliminary hydrological modeling of an extreme rainfall event shows a 12-hour lag in peak flood depths compared to local station data but achieves strong alignment in maximum flood depths, demonstrating SFINCS’s potential for accurate flood impact assessments. These findings underline the importance of multi-hazard climate risk assessments to inform disaster risk reduction and adaptation strategies, particularly for critical infrastructure in vulnerable alpine regions.
[1] https://www.undrr.org/publication/human-cost-disasters-overview-last-20-years-2000-2019
[2] https://www.swissre.com/institute/research/topics-and-risk-dialogues/climate-and-natural-catastrophe-risk/expertise-publication-economics-of-climate-change.html
How to cite: Hasel, K. and Bügelmayer-Blaschek, M.: ICARIA: Impacts of compound storm and flooding events in a mountainous region, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18236, https://doi.org/10.5194/egusphere-egu25-18236, 2025.
