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.

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.

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.