We place particular emphasis on the multifaceted human impacts of climate change - beyond traditional damage-cost metrics - encompassing health, livelihoods, well-being, and other critical dimensions of human life. The session will showcase insights from European climate risk assessments which develop science-based, impact-driven decision-support tools to enhance local and regional adaptive capacity. These projects integrate physical and social sciences, promote Nature-Based Solutions, support multi-level climate governance, and employ participatory approaches to co-produce adaptation pathways aligned with the EU Mission on Adaptation to Climate Change by 2030, but longer time horizons are also envisaged.
We invite contributions that:
-present innovative, interdisciplinary methods for assessing climate risk that integrate physical hazard data with socio-economic vulnerability and adaptive capacity analysis.
- explore equity-focused socio-economic evaluations, including capability-based approaches to understand how climate change affects what individuals and communities can do and be.
- investigate the role of Nature-Based Solutions in building resilience.
- examine cross-sectoral and cascading impacts of extreme events on human systems.
- showcase community-based and participatory methods (e.g., stakeholder consultations, Living Labs) for co-developing transformative adaptation strategies.
- demonstrate decision-support tools that translate complex risk assessments into actionable local adaptation and mitigation plans.
By bringing together diverse perspectives, empirical evidence, and methodological innovations, this session will advance the science–policy interface for climate adaptation, contributing to climate-resilient development pathways for metropolitan and regional contexts across Europe and beyond.
Orals: Mon, 4 May, 08:30–12:25 | Room 0.14
Developing climate-resilient pathways requires an integrated view of risk that combines physical hazards with socio-economic vulnerability and adaptive capacity under future uncertainty. Within the SPARCCLE project, this is achieved by developing a probabilistic climate risk assessment framework for Europe that highlights the highest and recurrent impact patterns of climate extremes, as well as the challenges these pose for adaptation planning.
Building on the core components of risk, namely hazard, exposure, and vulnerability, we integrate the MESMER climate emulator with the CLIMADA risk assessment platform to generate large ensembles of spatially explicit hazard realizations for extreme temperatures under custom emission pathways and global mean temperature trajectories. These hazards are combined with detailed exposure data, focusing on population exposure to extreme heat and accounting for future demographic change. Location-specific socio-economic vulnerabilities, including age structure, gender, and income inequality, are incorporated through hazard-specific impact functions.
The use of a climate emulator enables exploration of a wide range of plausible futures, capturing dominant and recurrent spatiotemporal risk patterns as well as low-probability, high-impact outcomes that are often missed by limited climate model ensembles. This probabilistic framework allows us to identify regional hotspots of risk, assess where adaptation needs are greatest, and explore where adaptation constraints and limits may emerge under different climate and socio-economic pathways, reflecting alternative future challenges for Europe.
Using heat-related impacts as a detailed application, we assess whether projected adaptation efforts are sufficient to close future adaptation gaps across regions and scenarios. The framework is designed to be scalable to multisectoral analyses and to feed into integrated assessment models and decision-support tools. By linking physical hazards, socio-economic vulnerability, and adaptive capacity in a unified probabilistic approach, this work supports forward-looking climate risk management and strengthens Europe’s preparedness for diverse future climate and socioeconomic challenges.
How to cite: Pierini, L., Petersen, A.-K., Martyr, R., Andrijevic, M., Kropf, C., Zhu, Q., Quilcaille, Y., Gudmundsson, L., Seneviratne, S. I., Bresch, D. N., and Schleussner, C.-F.: Probabilistic Assessment of Future Climate Risks and Adaptation Across European Scenarios, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21144, https://doi.org/10.5194/egusphere-egu26-21144, 2026.
Climate change is projected to affect agricultural systems and labour input efficiency in a spatially heterogeneous manner and propagate globally to production, trade, and income outcomes across regions. This study examines, within the CROSSEU project, the impacts of climate change on agriculture and labour productivity from a global perspective, with a focus on subnational-level analysis across EU27 and the UK, while also considering their main trade partners. To assess the economy-wide implications of climate-induced impacts on agricultural outputs and labour productivity we use a subnationally disaggregated version of the ENGAGE model (ENvironmental Global Applied General Equilibrium). RCP4.5 and RCP8.5 climate change scenarios have been chosen to extract the climate shocks applied within this study.
First, to assess the implications of warming on agricultural outputs, we use estimates of crop yield responses to temperature increases. Second, empirical evidence of heat stress effect on labour productivity have been used to estimate the reduction of work capacity due to rising temperatures across the entire economy on sectors such as agriculture, manufacturing, and services.
Reduce crop yields will trigger sharp price spikes that disproportionately affect lower-income regions, underscoring a widening global equity gap. While production losses and price increases reduce global income and welfare, their regional impacts create winners and losers. Global GDP remains relatively stable under yield shocks but regional disparities in income and welfare intensify. Tropical and subtropical developing regions not only face yield and production losses but also reduced export competitiveness, resulting in larger welfare losses. The findings highlight the need for targeted adaptation strategies in vulnerable regions and reinforce the importance of ambitious global mitigation efforts to address the unequal distribution of climate risks.
Labour efficiency reduction constrains economic activity altering relative production costs and income generation across sectors and regions. Labour productivity impacts depend on regional economic structures, factor income composition, patterns of intersectoral linkages and international trade. We extract productivity losses effects and transmissions through changes in production, prices, incomes and poverty levels. Across scenarios, productivity losses translate into reductions in sectoral output, GDP, and welfare, but the extent varies substantially across regions. As reduced incomes and price adjustments propagate, the consequences become increasingly evident in welfare and poverty outcomes, particularly in developing regions where households rely heavily on labour earnings. This synthesis suggests that priorities for action should be guided primarily by where labour productivity losses translate into welfare and poverty impacts, rather than by sectoral output or GDP effects alone.
Rather than treating yield or labour shocks in isolation, the economy-wide model ENGAGE reflects regional intersectoral linkages and trade flows to simulate systemic effects. This comprehensive assessment supports policymakers in anticipating direct and indirect consequences of climate impacts—such as regional income disparities, pressure on trade and changes in comparative advantages — and in crafting coordinated, cross-sectoral adaptation responses.
How to cite: Dessens, O., Calzadilla Rivera, A., and Khraizat, Z.: Systemic assessment of societal and human vulnerabilities from agricultural yields and labour productivity shocks under two climate change scenarios., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20273, https://doi.org/10.5194/egusphere-egu26-20273, 2026.
Assessing socio-economic vulnerability remains a key challenge in climate risk analysis, as vulnerability is traditionally grounded in social science concepts that are difficult to quantify spatially and consistently. This research explores how Earth observation (EO) data can contribute to assessing socio-economic vulnerability by identifying EO-derived indicators that serve as proxies for social and economic dimensions of risk.
Building on the ESA-funded EO4MULTIHAZARDS project, the study investigates how remotely sensed data can complement conventional socio-economic datasets to represent complex human systems, including exposure patterns, infrastructure quality, access constraints, and indicators of deprivation. By systematically linking EO-derived variables with established vulnerability frameworks, the research tests innovative methods to bridge physical observation and human-centred climate risk assessment.
The work aims to advance interdisciplinary approaches to climate risk analysis by demonstrating how EO-based proxies can support equity-focused adaptation planning, place-based and inclusive climate resilience strategies, and local and regional decision-making under data scarcity. By translating physical observations into representations of socio-economic conditions, the study contributes to closing the gap between hazard-focused risk assessments and actionable, human-centred climate adaptation strategies.
How to cite: van Maanen, N., de Ruiter, M., and Ward, P.: Leveraging Earth Observation to Assess Socio-economic Vulnerability, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17461, https://doi.org/10.5194/egusphere-egu26-17461, 2026.
Hydropower is a cornerstone of Europe’s low-carbon electricity system, yet its reliability is increasingly challenged by intensifying droughts under climate change. Existing assessments of drought risks to hydropower predominantly focus on average water availability or well-studied regions, and rarely quantify how extreme drought duration, frequency and intensity differentially shape plant-level shortfalls worldwide, limiting coordinated adaptation planning.
Here, we compile a global dataset of 28,725 hydropower plants across 165 countries and apply 15 climate–hydrology model combinations under SSP1–2.6, SSP3–7.0 and SSP5–8.5 to identify drought events, characterize extremes in duration, frequency and intensity, and estimate plant-level generation shortfalls while accounting for hydraulic head variations during droughts. We then assess how heterogeneous drought patterns impact hydropower shortfalls across plants, countries and river basins, with a particular focus on Europe.
Under SSP3–7.0 (2030–2060), global annual hydropower losses reach 52–173 TWh yr⁻¹ (median 114 TWh yr⁻¹), with generation during drought periods declining by 28% – 49% (median 46%). Europe experiences average losses of 12 - 36 TWh yr⁻¹ (median 21 TWh yr⁻¹), corresponding to a 21% - 46% reduction (median 40%) in drought-period output. Across Europe, drought-related shortfalls are most commonly associated with long-duration events, affecting around 74% of installed capacity in major producing countries such as France, Spain, Italy, Norway and Sweden. However, Europe exhibits the highest regional share of frequency-related impacts globally (10%), exceeding the global average, with particularly strong signals in smaller national systems such as Hungary (49%) and Switzerland (13%). High-intensity droughts account for 17% of European capacity, also above the global average, with localized hotspots in eastern and southern Europe, including Moldova (75%), Latvia (57%) and basins in Greece (15%+).
Beyond large stations, we find that small and medium-sized hydropower plants (<100 MW) contribute approximately 56% of total European cumulative losses, rising to nearly 80% under long-duration, low-intensity drought regimes. This highlights a critical source of socio-economic vulnerability, as widespread small-scale facilities underpin regional electricity supply, local livelihoods and energy security.
By resolving drought risks at the plant scale and linking distinct drought patterns to uneven losses across Europe, this study provides an impact-driven evidence base to support targeted adaptation, inclusive resilience planning and decision-making aligned with European climate adaptation objectives.
How to cite: He, Y., Sun, Y., Zhou, J., Kai, K., Adriano, V., Guan, D., and Byers, E.: Impacts of drought patterns on global and European hydropower plant shortfalls, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16988, https://doi.org/10.5194/egusphere-egu26-16988, 2026.
This paper combines percentile-level household income data from the World Bank’s Poverty and Inequality Platform with high-resolution ERA5 climate indicators to econometrically estimate the distributional effects of frequency- and intensity-adjusted measures of heatwaves, coldwaves, droughts, and extreme precipitation across more than 140 countries. Our findings show that extreme weather events are regressive: heatwaves, coldwaves, and droughts depress incomes at the lower end of the distribution by substantially more than at the upper end, leading to higher Gini coefficients and wider 90/10 income gaps. These effects vary markedly across countries, with substantially larger distributional impacts in arid and temperate climates and in economies with greater agricultural dependence and lower adaptive capacity. Taken together, our results suggest that extreme weather events are associated with substantial and uneven distributional consequences that can systematically widen income disparities within countries. This underscores the importance of climate adaptation and social protection policies that explicitly account for distributional impacts, particularly in economies and regions characterised by high exposure and vulnerability.
How to cite: Vasilakos, N., Zhang, S., Jenkins, K., and Forstenhaeusler, N.: Climate Shocks and Income Inequality: Some first econometric results from the CROSSEU project, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12994, https://doi.org/10.5194/egusphere-egu26-12994, 2026.
Europe is the fastest growing continent and climate-related disasters such as wildfires, heatwaves, and floods are becoming increasingly frequent and severe, posing escalating threats to both ecosystems and human societies (EEA, 2024). Acute and chronic climate hazards highlight not only ecological vulnerabilities but also social and institutional weaknesses, testing the institutional capacity of communities to absorb and adapt. The IPCC (2014) defines vulnerability as “the propensity or predisposition to be adversely affected” and notes that Socio-Economic Vulnerability (SEV) is shaped by social, economic, and political factors that influence how people are exposed to hazards and how well they can adapt or recover. We approach the concept of SEV through the analytical lens of the 3 As & T framework (Bahadur et al., 2015), thus assessing the societal capacity to anticipate, adapt, absorb and transform in the face of climate risks and extreme events. Our analysis synthesizes different approaches and methods; however, we focus on the medium and long-term capacity of European regions to cope with climate hazards and enhance their environmental and socio-economic resilience. Using regional data (NUTS3 and NUTS2 level) we construct regional SEV profiles drawing upon the synthesis of established SEV frameworks and including a rich set of indicators measuring sensitivity and adaptive capacity. We adopt a two-step spatial analytical framework. First, we use Moran’s I to identify statistically significant spatial clustering of vulnerability and resilience across European regions, highlighting hotspots and cold spots and mapping the geographic concentration of climate-related risks. Second, we estimate a Spatial Durbin Error Model (SDEM) to examine the socioeconomic and institutional determinants of regional resilience, capturing both direct and spatial spillover effects of social capital, governance quality, institutional capacity, and economic diversification - factors that are often neglected in climate adaptation policy design. Finally, we utilize metropolitan area specific data from the HEU CARMINE project to elaborate on the interplay of specific SEV attributes and documented hazards for eight pilot regions. This complementary analysis acts as a ‘zoom-in’ on highly exposed urban systems, enabling comparisons across the eight CSAs and the derivation of transferable insights for targeted adaptation actions. The development of the SEV profiles is grounded in the participatory, multi-actor approach of the CARMINE Living Labs and the Stakeholder Community Hub, where stakeholders assess cross-sectoral interdependencies and uncertainties and link SEV characteristics to documented climate threats and impacts. Our results underscore the importance of sound institutions to enhance the effectiveness of adaptation measures and reveal that resilience is shaped not only by local conditions but also by significant spatial spillover effects across regions.
Acknowledgements: This work has received funding from the European Union’s Horizon Europe programme under Grant Agreement No. 101137851 (CARMINE).
How to cite: Koundouri, P., Dellis, K., Giannakis, E., and Triantafyllidou, A.: Spatial Patterns of Socioeconomic Vulnerability and Institutional Resilience in the EU – Evidence from the CARMINE project, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17465, https://doi.org/10.5194/egusphere-egu26-17465, 2026.
Bridges play a vital role in enabling mobility and economic activity; however, a significant portion of the existing bridge inventory is nearing or has already surpassed its intended service life. This growing problem is intensified by climate change, which is likely to accelerate deterioration and increase the likelihood of damage. At the same time, limited maintenance budgets make it increasingly difficult for bridge managers to decide where to intervene first. Current bridge prioritisation practices typically depend on expert-assigned weighting schemes that emphasise physical condition and network importance, while giving little attention to social equity and community-level consequences. As a result, populations that are most vulnerable to infrastructure failure are often underrepresented in decision-making.
To overcome these shortcomings, this study proposes a new assessment framework that combines structural vulnerability of bridges with social vulnerability of the communities they serve, allowing county-scale prioritisation that supports fairer allocation of maintenance resources. The methodology advances existing practice in several ways. It augments conventional bridge evaluation models by introducing ground subsidence susceptibility as an additional hazard indicator. It also expands the bridge assessment by adding adaptive capacity as a third dimension alongside traditionally used network criticality and damage susceptibility due to structural health and natural hazards. This new adaptive capacity metric captures economic strength, inspection demand and spaceborne monitoring potential of bridges in a county. Indicator weighting is derived objectively through principal component factor analysis, removing reliance on subjective expert judgement. In addition, a bivariate mapping approach is used to jointly visualise and interpret social and structural vulnerability while still preserving their individual contributions.
The framework was implemented for 22298 bridges across 58 counties in California. Results indicate that several counties in Northern California experience the greatest combined vulnerability, where deteriorating bridges coincide with limited institutional capacity and higher social disadvantage. This demonstrates that approaches focused only on engineering conditions and network role can unintentionally reinforce inequalities by failing to identify locations where disruptions would cause the most harm to communities. The analysis also reveals a strong association between socially vulnerable areas and favourable satellite-based monitoring coverage in California, suggesting that remote sensing can be strategically targeted to improve equity in infrastructure management. Overall, the proposed framework offers a practical means of strengthening resilience while more effectively addressing the needs of vulnerable populations.
How to cite: Giardina, G., Malinowska, D., Petrova, K., Milillo, P., Reale, C., and Blenkinsopp, C.: County-scale assessment of bridge vulnerability using structural and social indicators , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13533, https://doi.org/10.5194/egusphere-egu26-13533, 2026.
Climate change and ecosystem degradation constitute a systemic societal challenge, with impacts shaped not only by physical hazards but also by social vulnerability and institutional capacity. Understanding how climate risks translate into differentiated human impacts is therefore critical for effective and equitable adaptation. The Belgian Climate Risk Assessment (BCRA) adopts this perspective by assessing climate and ecosystem risks as societal risks with unequal human consequences, affecting health, livelihoods, living conditions and social cohesion.
Synthesising evidence across climate, health, economic and social systems, the assessment finds that climate change is likely to intensify existing social inequalities in Belgium through compounding and cascading effects, placing disproportionate burdens on vulnerable population groups. Risks related to heat, flooding, water stress, food price volatility, health system disruption, etc. interact with socio-economic factors such as income, housing quality, age, health status and access to services. These interactions generate spatially concentrated patterns of vulnerability, particularly in urban environments and historically disadvantaged areas, where physical exposure coincides with limited adaptive capacity.
Despite relatively strong social protection systems, the BCRA identifies structural gaps in preparedness. Climate-related social vulnerabilities remain insufficiently integrated into adaptation planning, preventive measures are underfinanced, and institutional fragmentation constrains coordinated, place-based responses. The assessment further shows that adaptation measures have significant distributional implications: without explicit attention to equity, they risk reinforcing existing vulnerabilities rather than reducing risk.
At the same time, the BCRA demonstrates that anticipatory and targeted adaptation can reduce risk while delivering co-benefits. Eco-conscious social protection mechanisms can play a key role in strengthening societal resilience. Place-sensitive interventions, including nature-based solutions, can address physical hazards while strengthening health, well-being and social resilience. By embedding social vulnerability analysis within a national climate risk framework, the BCRA strengthens the science–policy interface by translating complex risk interactions into decision-relevant evidence for equitable, impact-driven adaptation across governance levels, directly supporting European climate resilience objectives.
How to cite: Barnard, E.: Climate Risk as a Societal Challenge: Social Vulnerability in the Belgian Climate Risk Assessment, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13215, https://doi.org/10.5194/egusphere-egu26-13215, 2026.
Extreme climate events are increasing and have a significant impact on national infrastructure and society. As a result, governments and industry are investing more into climate adaptation strategies. However, despite these challenges the ultimate longer-term solutions via climate transition policy are under increased scrutiny as negative effects on society with respect to economic growth are highlighted [1].
For researchers this poses a challenge to strengthen the social and economic case for climate policy. More persuasive modelling is needed to make the economic case and greater understanding of social impact such as the potential greater impact of policy on specific parts of society are needed. A good example of this is vehicle access to cities based on car emissions and the perception such policies adversely target members of the population who are unable to afford a new compliant vehicle.
An approach to address this challenge is through finer grained modelling of risk with respect to policy impact on a wide range of societal and economic factors are required. This modelling will help balance transition and adaptation strategies with economic and societal impact. The CROSSEU project aim to do this, CROSSEU a pan European research project addressing this issue by developing climate risk models collaboratively to strengthen cross stakeholder support for climate policy [2].
CROSSEU is making the process behind this risk analysis transparent and open for wider collaboration. The project has developed an Integrated Assessment Framework (CROSSEU IAF) based on the Data Analysis for National Infrastructure (DAFNI) platform [3] to store both models and data. However, the strength in the platform is that it provides a tool for the collaborative development of risk models and adaptation strategies based on models and data linked to the platform.
This collaborative platform enables a wide range of stakeholders to provide inputs into the application of climate models in different scenarios. This is done by utilisation of data and models on the platform in workflows that represent different use cases and requirements.
The CROSSEU IAF platform is unique in that it is free to use and provides a base for research outputs to be integrated by other users providing industry and government access to these resources. This form of collaboration will strengthen the support for future climate action. Within the project, the CROSSEU IAF will make available outputs from 8 case studies spanning diverse geographies and multiple climate risks.
The presentation will describe the current utilisation of the CROSSEU IAF platform. How it is being used to better manage and understand social and economic impacts of climate policy. It will explore the projects case studies and identify work beyond the project in managing climate risk and the development of adaptation strategies.
- Weber, Pierre-François, et al. "The intersection between climate transition policies and geoeconomic fragmentation." (2025).
- Some, Shreya, et al. "Cross-Sectoral Climate Change Risk Hotspots in Europe: Insights from CROSSEU Case Studies." EGU General Assembly Conference Abstracts. 2025.
How to cite: Kirkham, T., Vasilakos, N., Boorman, P., Bowyer, P., Kasap, S., Jenkins, K., Dessens, O., Stevenson, K., Zoldoske, T., and Perkins, B.: A collabortive platform to support the socially aware creation and modelling of climate policy, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6506, https://doi.org/10.5194/egusphere-egu26-6506, 2026.
Climate adaptation strategies must go beyond identifying physical hazards to address socio-economic vulnerabilities and human impacts. The CROSSEU project exemplifies this approach by integrating climate science, socio-economic analysis, and participatory methods to develop actionable insights for resilience planning. A core outcome of the project is the CROSSEU Decision Support System (DSS), designed to translate complex climate risk information into insights for policymakers and other stakeholders. Hosted on the Data Analysis for National Infrastructure (DAFNI) platform and integrating the World Energy & Meteorology Council (WEMC) Teal visualisation tool, the CROSSEU DSS is designed to enable interactive exploration of regional climate risks by combining geophysical data with demographic and economic indicators to inform equitable adaptation strategies.
A beta version of the CROSSEU DSS is now operational, featuring an initial case study on heat-related mortality in the Czech Republic. This first version of the application illustrates how rising temperatures combined with demographic trends amplify health risks, particularly for vulnerable urban populations. To ensure the DSS meets practical needs, its functionality and user experience are being co-produced through stakeholder engagement.
By integrating multi-sectoral data and visualisations, the CROSSEU DSS will support evidence-based decision-making aligned with the EU Mission on Adaptation to Climate Change. Ongoing work is expanding the DSS to include further case studies across multiple regions and sectors with enhanced interactive features, all refined through direct stakeholder feedback via participatory approaches. This tool demonstrates how interdisciplinary, user friendly resources can help bridge the gap between raw hazard data and practical, equity-focused adaptation strategies, promoting more climate-resilient policymaking across Europe.
How to cite: Boorman, P., Kasap, S., Fraser, D., Troccoli, A., Urban, A., and Naz, F.: Bridging Physical Risk and Human Impacts: The CROSSEU Decision Support System for Climate Resilience in Europe, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18612, https://doi.org/10.5194/egusphere-egu26-18612, 2026.
The DamageCost model provides a methodological and modelling framework to support comprehensive and multi-sectoral economic damage assessments of flooding from pluvial, coastal, and riverine sources. Developed as an open-source QGIS plugin, the model rests on open geographical data and includes depth-damage functions for multiple economic sectors and supplemented by more detailed socioeconomic data on people in flooding risk areas. The skills of the model and methodological issues related to socioeconomic assessment of flooding are illustrated in relation to a case study for a Danish city (Esbjerg) and an assessment of flooding risks for Denmark. The DamageCost model is from a socioeconomic perspective assessing risks of flooding events as a basis for decision making on adaptation strategies. To examine the sensitivity of adaptation solutions towards uncertainties in climate projections and assumptions applied to the economic assessment, several climate change scenarios can be combined with variations in the applied damage functions. Applications of the model in the national context of Denmark projected total flood damages from storm surges of up to 32 billion EUR over the next century. Additionally, the local case study identified a seawall height with a net benefit of 36 million EUR and revealed that floods disproportionately affect lower-income households. Its co-created nature and management by a municipal partnership facilitate the mainstreaming of risk assessment into local planning, and policy relevance has in this way been supported. Future developments include updated damage functions, adding new sectors and creating a generic cost database to support international applications.
How to cite: Skougaard Kaspersen, P., Houmøller Veng, E., Some, S., Drews, M., and Halsnæs, K.: The DamageCost Model: A Co-created Open-Source Tool for Assessing the Socioeconomic Impacts of flooding, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3176, https://doi.org/10.5194/egusphere-egu26-3176, 2026.
The paper investigates factors that could increase households’ vulnerability to coastal flooding. In recent years, social and individual vulnerability has been recognized as an important part of climate risk assessment and management. Climate risks are the result of a combination of hazard, exposure and vulnerability, and including vulnerability indicators in climate risk assessments is a way of acknowledging that the inherent capabilities of different individuals and communities make them susceptible to adverse impacts of climate hazards. The study is part of a large body of literature using social vulnerability indicators to capture which geographical areas are most vulnerable to natural hazards. Often, the indicators used to identify vulnerable areas are chosen based on data availability and are not validated empirically with the actual consequences of natural hazards. Therefore, this study aims to contribute to the literature by investigating the extent to which vulnerability indicators can explain differences in adaptive capacity and the consequences of natural hazards.
For the study, a survey was sent out to households living in coastal areas of Denmark that were impacted by two different coastal floods in 2023. The survey was distributed to one person per address in the study area (no.=123,000). In total, more than 16,000 people completed the survey, out of which some were directly affected by the floods, some were indirectly affected, and some were not affected at all. After data collection the survey data was combined with detailed micro-level data on demographic, socioeconomic and housing characteristics of the respondents.
First, the complete sample is used to test the empirical relationship between a set of demographic and socioeconomic variables and four different measures of adaptive capacity, controlling also for individual flood risk perception, worry, coping appraisal, flood experience, confidence in authorities and geographic characteristics. Based on the survey, adaptive capacity is in the paper measured by flood awareness, implementation of mitigation measures, and neighborhood ties. This analysis shows what characterizes people with a higher capacity to adapt, who are better prepared prior to a flood, and are better suited to cope with the consequences, potentially minimizing long-term impacts.
Second, a smaller subsample consisting only of respondents who indicated that they had had flooding in their homes is used to analyze the empirical relationship between demographic and socio-economic characteristics and how severely people are impacted by flooding. This is measured by the renovation time and costs of households, and whether people have experienced different types of stress reactions after the flooding of their home. These results show what characterizes people that suffer most from the consequences of coastal flooding, and thereby which groups are most vulnerable to coastal flooding of their homes.
The results of this study can be used to guide which vulnerability indicators should be used to identify vulnerable areas in Denmark, and other places with high flooding risks, and inform decision-making on climate adaptation that meets a wider range of social and well-being objectives than what can be measured in terms of material damages on buildings and other assets.
How to cite: Houmøller Veng, E. and Halsnæs, K.: Insights into social factors shaping coastal flooding vulnerability, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3548, https://doi.org/10.5194/egusphere-egu26-3548, 2026.
Coastal regions are globally threatened by increasing inundation risks due to climate-induced sea-level rise, intensifying storm surges, and anthropogenic pressures. Understanding the spatial interplay of the physical and socioeconomic drivers of vulnerability is critical for effective risk reduction. This study conducts a high-resolution spatial analysis of three vulnerability components along the Kerala coast, India; coastal characteristics, coastal forces, and socioeconomic components. Coastal characteristics include geomorphology, elevation, landward and seaward slopes, shoreline change rates, and continental shelf width. The coastal forces component comprises tide, significant wave height, sea-level anomalies, and extreme events. The socioeconomic component evaluates land use/land cover, population density, road networks, tourist hotspots, and coastal protection structures.
The spatial distribution of coastal characteristics indicates that coastal plains and floodplains, covering nearly 20 percent of the study area, are dominated by low elevation and gentle slopes that favour prolonged water retention and increased exposure to coastal flooding. Areas below 10 m elevation exhibit limited natural buffering against tidal inundation and storm surge impacts. Gentle landward slopes and flatter nearshore bathymetry promote inland penetration of wave energy. Persistent shoreline erosion and a narrow continental shelf, which enhances nearshore wave energy concentration. Coastal forcing components further modulate flood vulnerability, contributing to elevated coastal water levels and these conditions spatially coincide with zones historically impacted by catastrophic events like the 2004 Indian Ocean tsunami. Socioeconomic vulnerability is concentrated in urbanized coastal stretches, where built-up areas constitute ~65% of high-vulnerability zones, supporting population densities exceeding 5000 persons/km². Critical infrastructure and tourist hubs are predominantly located within this high-exposure corridor, increasing potential impacts. Existing hard-engineered defenses are spatially limited and insufficient to mitigate the compound risk.
The spatial characterization of vulnerability-driving components provides a robust foundation for integrated coastal vulnerability assessments related to coastal flooding driven by sea-level rise, storm surges, and wave action, and supports evidence-based coastal planning and climate adaptation strategies along the Kerala coast.
How to cite: Renu, S., Pramada, S. K., and Arunkumar, R.: Spatial Analysis of Coastal Vulnerability Indicators Along the Kerala Coast, India, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15983, https://doi.org/10.5194/egusphere-egu26-15983, 2026.
Federal disaster assistance programs aim to reduce flood risk through hazard mitigation, yet whether these investments produce equitable outcomes remains unclear. We examine 30-year cost-effectiveness of federally funded home elevations following Hurricanes Katrina and Rita, analyzing how mitigation effectiveness varies across flood return periods and racial groups. Using the IPCC risk framework, we integrated flood depth data, building attributes, federal funding records, and demographic data. Flood risk was quantified as average annual loss (AAL), and mitigation effectiveness was assessed through percentage risk reduction and benefit-cost ratios (BCR).
Results reveal that AAL in high-frequency flood zones (≥10-year) is ten times higher than low-frequency zones (≥200-year). Critically, elevation achieves 95% risk reduction in high-frequency zones but only 53% in low-frequency zones, where severe flood depths exceed elevation heights. White populations are overrepresented in high-frequency zones (disproportionality ratio 1.8–2.1), while non-white populations are overrepresented in low-frequency zones (ratio 1.1). Chi-square analysis confirmed that BCR outcomes differ significantly by race (χ² = 29.04, p < 0.001): 71–72% of low-BCR investments serve non-white majority areas, while 72% of cost-effective investments serve white majority areas.
We do not argue that federal allocation is biased—risk-based efficiency criteria are appropriate. However, this approach produces structurally inequitable outcomes: non-white populations receive investments where elevation is fundamentally less effective. To address this disparity, we applied equity-weighted BCR analysis, demonstrating that incorporating social vulnerability into project evaluation would justify investments in communities currently excluded under efficiency-only criteria. These findings offer a decision-support framework for balancing efficiency with equity in climate adaptation policy.
How to cite: Al Assi, A., Mostafiz, R. B., and Friedland, C.: Beyond Cost-Effectiveness: How Risk-Based Flood Mitigation Allocation Produces Racially Inequitable Outcomes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8651, https://doi.org/10.5194/egusphere-egu26-8651, 2026.
Alpine regions in Europe are increasingly affected by short-duration, high-intensity precipitation events, leading to localised floods and flash floods that generate severe and spatially uneven impacts. In these contexts, where settlements, economic activities and critical infrastructure are often concentrated in narrow valley areas, such events pose growing challenges for regional adaptation planning. Moreover, climate change is expected to exacerbate both the frequency and intensity of convective precipitation extremes, amplifying flood-related risks in territories already characterised by complex topography and limited capacity to absorb hydrological shocks, partly due to high land-use pressures. Most flood risk assessments have traditionally focused on hazard exposure and physical vulnerability, often neglecting the welfare dimension of climate impacts. As a consequence, they provide limited guidance for comparing adaptation options in terms of their societal benefits. Based on these premises, this study firstly provides an integrated assessment of flood risk and adaptation benefits that combines high-resolution hydroclimatic impact modelling with stated preference valuation of avoided damages. Drawing on a case study in northeastern Italy, we quantified both the evolution of flood exposure under two future climate time horizons (2041–2050 and 2090–2099) and the economic value that residents assign to reducing flood impacts across five land-use domains: residential areas, productive areas, road infrastructure, agricultural land, and tourism-related facilities. The hydroclimatic impact modelling reveals a progressive intensification of flood exposure across all land-use domains. End-of-century projections indicate particularly severe impacts in mountainous zones, where the flooded surface reaching up to 21% for road infrastructure and 25% for agricultural land. The stated-preference valuation, based on a discrete choice experiment administered to a representative sample of 2,000 residents, shows that individuals assign the highest marginal economic value to the protection of residential areas, followed by productive areas, agricultural land and roads. Tourism-related facilities receive the lowest valuation, indicating that not all exposed domains are perceived as equally critical from a societal welfare perspective. Combining physical projections with economic evidence, we derived population-level estimates of the societal benefits of flood impact reduction. The resulting welfare indicators offer a transparent benchmark for evaluating the societal desirability of alternative adaptation strategies. We derived a monetary threshold against which the cost of an adaptation measure can be compared to determine whether the investment is socially justified. This study is the first integration of hazard modelling and stated preference valuation. Our findings enhance the operational relevance of climate risk assessment and supports the design of adaptation strategies that reflect both physical exposure and socially perceived value. It also provides insights to inform evidence-based climate governance in regions facing intensifying hydroclimatic risk.
How to cite: Franceschinis, C., Piracci, G., Dallan, E., Borga, M., and Thiene, M.: Integrated assessment of the societal welfare benefits of flood adaptation under different climate change scenarios: Evidence from northeastern Italy, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5802, https://doi.org/10.5194/egusphere-egu26-5802, 2026.
Climate change is intensifying heat extremes in cities, where dense built environments amplify thermal exposure and increase risks to human health, productivity, and well-being. Urban Heat Island (UHI) effects, driven by impervious surfaces, reduced vegetation, and altered surface energy balances disproportionately burden urban populations, particularly vulnerable groups such as the elderly, low-income households, and those with limited access to cooling or green space. Nature-based solutions (NBS), including urban greening and de-sealing, offer substantial potential to mitigate urban heat by restoring local cooling processes. However, effective heat adaptation requires more than identifying locations with the largest temperature reductions: policymakers must also consider how many people are affected, which population groups are exposed, and where elevated heat coincides with social vulnerability and limited adaptive capacity.
This contribution presents a prototype machine learning-based framework for modeling hyperlocal land surface temperature (LST) as a function of land cover and urban form, and for linking heat exposure to human-centered impacts, using Leipzig, Germany as a case study. At the core of the framework is a machine-learning model that predicts pixel-level LST from satellite-derived land-cover information, spectral indices, and selected indicators of urban morphology. By learning the relationship between local land-cover configurations and surface temperature under city-wide climatic conditions, the model generates high-resolution heat maps that reveal fine-grained spatial variation in thermal exposure and its underlying drivers.
To move beyond purely physical measures of urban heat, predicted LST patterns are integrated with socio-economic and demographic indicators, including population density, land use, and proxies for vulnerable population groups. This coupling enables heat exposure to be assessed in relation to the distribution of people and social characteristics across the urban landscape, highlighting where high temperatures intersect with heightened risks to health and well-being. The framework thus supports an explicitly impact-oriented perspective on urban heat.
Finally, the framework provides a basis for evaluating the cooling potential and distributional implications of nature-based solutions, such as targeted greening or de-sealing interventions. By linking land-cover changes to both thermal effects and population exposure, the approach can inform spatially targeted, socially aware heat mitigation strategies and support urban climate adaptation planning that prioritizes both effectiveness and equity.
How to cite: Wussow, P., Wussow, M., and Neumann, D.: From Urban Heat to Human Impact: A Machine Learning Framework for Equity-Sensitive Climate Adaptation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5836, https://doi.org/10.5194/egusphere-egu26-5836, 2026.
Using Geographic Information System (GIS) outputs as a tool to inform policy decision-making is an increasingly popular approach in addressing climate change challenges. Maps and geospatial visualisations are typically well understood across multiple disciplines, including non-experts, thus removing technical barriers to subject matter and transcending the boundaries of organisational structures and working regimes related to climate change adaptation. However, the impacts of climate change at the local scale, particularly across metropolitan regions, are complex and often heterogeneous across different areas. The geospatial variables necessary to compile a holistic climate risk and vulnerability indicator therefore vary from place to place, and research into developing such maps across the world highlights that there is no “one size fits all” approach. Using GIS, this study compares different statistical methodological approaches to mapping climate risk and vulnerability for Birmingham, UK, where a co-created climate risk and vulnerability assessment (CRVA) map is already embedded in local authority decision-making. The same underpinning variables and spatial resolution (100m) across methods are used, considering approaches to aggregating variables in different ways, involving weighting techniques. Comparing the results serves as a validation exercise in utilising the most appropriate approach for the city of Birmingham and has broader implications for the West Midlands region of the UK, where the CRVA is being upscaled and enhanced further in collaboration with the regional authority for targeted climate change adaptation planning. Further research to replicate this study for other metropolitan regions would potentially highlight the strengths and weaknesses of geospatial methodological approaches more robustly. While this study does not intend to provide a single solution to climate risk mapping, it instead aims to draw out key implications from a spatial perspective of selecting one approach over another for decision-making purposes.
How to cite: Greenham, S., Desai, N., and Ferranti, E.: To weight, or not to weight? Comparing methodological approaches in mapping climate risk and vulnerability for metropolitan regions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8380, https://doi.org/10.5194/egusphere-egu26-8380, 2026.
Climate change is increasingly impacting urban areas worldwide. Climate risks such as heat waves and other extreme weather events threaten health, productivity and urban infrastructure. However, these impacts are not equally distributed across society. Some population groups and neighborhoods are being hit harder than others, with inhabitants from disadvantaged socioeconomic backgrounds, low-income households and the elderly being disproportionally affected. In response, cities are attempting to rapidly implement various mitigation and adaptation strategies that often include nature-based solutions such as expanding urban vegetation to combat heat effects. However, the economic consequences of these interventions for urban residents remain underexplored, raising key questions about whether such strategies alleviate or exacerbate social inequalities.
This study addresses these questions by analyzing the relationship between the urban heat island (UHI) effect, urban vegetation, and residential property values across 15 metropolitan regions in the United States and Germany. To do so, we adopt a data-driven approach that combines property transaction and listing data with satellite imagery of ground cover obtained from the Copernicus Sentinel-2 program from 2015 to 2025. Through geospatial analysis, we quantify a "green premium" - a markup on real estate prices - and its development over time and in regions that are heterogeneous with respect to economic activity, climate zones and urban landscapes. Using this approach, we can identify wealth impacts of urban vegetation and changes in its perceived importance for home buyers over the past 11 years. By further integrating high-resolution thermal data, we examine how local microclimates and green space coverage influence housing values at the neighborhood level. We explore how these effects vary across different socioeconomic and demographic contexts with a focus on equity implications and climate vulnerability, contributing to the growing interdisciplinary literature on climate adaptation, urban planning, and environmental justice.
How to cite: Reining, A., Wussow, M., Zanocco, C., and Neumann, D.: Neighborhood-level Effects of Urban Greening on Heat Mitigation and Property Prices, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14243, https://doi.org/10.5194/egusphere-egu26-14243, 2026.
The aim of this study is twofold, first we estimate the effects of temperature on mortality distinguishing by several population groups. Second, we explore the mitigative effects of issuing a heat warning on the heat-mortality relationship. To this end, exploiting the errors in weather forecasts, we manage to compare days with similar meteorological conditions but different heat warning statuses. We employing a fixed-effects model applied to 1323 German sub-national areas between 2018 and 2023. We instrument the likelihood of issuing a warning with the error in wind forecast leveraging on the fact that underestimating wind leads to an underestimation of perceived temperatures (PT) in the hot rage and in turn to a lower probability of issuing heat warnings. We find an optimal temperature range of [10,15) PT C° with mortality increasing faster as temperature become hotter compared to colder. Nonetheless the effects are highly heterogeneous across age groups and gender, with older people more sensitive both to cold and hot temperatures and female more sensitive to cold ones. Moreover, we observe that the effects of a hot day least for at least 3 days and that consecutive hot days are up to 45% more lethal than isolated ones. Furthermore, areas that are on average warmer are better adapted to heat but did not improve their adaptation significantly between 2005 and 2023. Finally, heat impacts on mortality are moderated by the presence of heat warnings. The contribution of our results is threefold. First, we identify the most vulnerable groups both to heat and cold. Second, we reveal the crucial role of meteorological alerts in enhancing people’s adaptive capacity to climate change. Third, we underscore the importance of accurate weather forecasts for public safety.
How to cite: Savazzi, F., Linsenmeier, M., and Wenz, L.: Heat and Cold Mortality: Adaptation and Warnings, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22093, https://doi.org/10.5194/egusphere-egu26-22093, 2026.
Urban heat risk is commonly assessed through physical hazard indicators and static heat hotspot maps, which are effective for identifying “hot spots” but provide limited insight into who is exposed to heat, when and where exposure occurs, and how long exposure persists. In reality, heat-related impacts are shaped by the cumulative thermal burden experienced through daily routines, occupational heat exposure, and mobility constraints. Moving beyond identifying where it is hot, efficient and equitable urban heat adaptation therefore requires quantifying the population-level heat burden experienced by residents and identifying strategies that can meaningfully reduce it. However, the lack of metrics to quantify residual heat exposure constrains local governments’ ability to assess adaptation effectiveness and identify adaptation limits. To address this gap and to enable the measurement of human-centered, quantifiable heat burden, we propose a conceptual shift from heat hazard to dynamic exposure, defined as population-level cumulative exposure differentiated by activity patterns and spatial locations across occupational, gender, and age groups, thereby explicitly incorporating vulnerability and behavioral dimensions of heat burden. By combining temperature distributions derived from a microclimate model with resident group activity patterns generated through behavioral analysis, we model city-level dynamic heat exposure and express it as time above a heat threshold to enable linkage with heat-related health impacts. The approach is applied to a case study of Suwon, South Korea. Modelled cumulative heat exposure is validated using Living Lab outcomes, specifically real-world exposure data collected from residents using portable temperature sensors. Future levels of dynamic heat exposure are evaluated under alternative future climate and socio-economic conditions. The effectiveness of heat adaptation portfolios, including technical, institutional, and behavioral options, is assessed in terms of their potential to reduce population-level heat exposure, drawing on evidence from the literature. We further conduct an illustrative analysis to examine how adaptation portfolios can reduce regional heat burden and to estimate the magnitude of residual exposure that may persist under future conditions. The results show that the proposed dynamic heat exposure model aligns closely with real-world observations, reproducing comparable patterns of cumulative heat exposure across population groups. Our result indicates that workers experience approximately 60% longer heat exposure durations than other groups. In addition, individuals in their 50s are exposed both for longer periods and at higher temperatures. The findings further suggest that conventional outdoor weather-station-based approaches may underestimate human heat exposure by approximately 30%. By quantifying urban heat burden as population-level dynamic heat exposure, this study moves beyond static hazard indicators to capture when, where, and to whom heat risk is actually experienced. This human-centered metric enables the evaluation of adaptation policy portfolios and move forward to ambitious goals. From a policy perspective, the approach supports needs-based local adaptation planning by aligning interventions with spatiotemporal exposure patterns and population groups facing the greatest constraints.
How to cite: Park, S., Park, C., and Cho, K. D.: From Heat Hazard to Dynamic Exposure: A Human-Centered Assessment of Urban Heat Burden for Evaluating Adaptation Limits, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9251, https://doi.org/10.5194/egusphere-egu26-9251, 2026.
Posters on site: Mon, 4 May, 14:00–15:45 | Hall X5
Mountain regions exhibit pronounced elevation-dependent climate change, with strong implications for snow regimes, cryosphere-related hazards, and ecosystem processes. In avalanche-prone areas, these climate signals directly affect both avalanche release conditions and the effectiveness of forest ecosystems as natural protection. Identifying regional and elevation-dependent climate change signals is therefore essential for understanding future avalanche dynamics and associated ecosystem-mediated risk regulation.
This work explores the future climate change signals throughout the 21st century (under RCP4.5 and RCP8.5 scenarios) for understanding the possible shifts in snow avalanche hazard conditions across the Alps and Carpathian Mountains. Using avalanche-relevant climate hazard indices derived from temperature and snow variables, we assess the expected changes across elevation bands. We relate these signals to the spatial distribution of coniferous forests and how they protect against avalanches - a regulating ecosystem service.
Results reveal clear elevation-dependent climate signals affecting avalanche-relevant conditions, with marked contrasts between lower and higher elevation zones. In both mountain systems, changes in snow-related indices indicate a shift in avalanche climate hazard conditions, particularly at mid-elevations where warming and altered snow persistence are most pronounced. Spatial analysis highlights that coniferous forests, identified as key providers of regulating ecosystem services, overlap unevenly with zones experiencing the strongest climate signals, implying potential future mismatches between hazard regulation capacity and changing avalanche conditions.
Stakeholder-informed assessments indicate that forest-based protection remains a highly prioritised adaptation option, but its long-term effectiveness may be increasingly constrained by climate-driven changes in snow and temperature regimes. Overall, the CROSSEU results demonstrate that elevation-dependent climate change signals are shaping the environmental context in which avalanche-protective forest ecosystems operate. By linking regional climate change signals with ecosystem service provision, this study provides a comparative perspective on how elevation-dependent climate change may influence natural hazard regulation in mountain regions. The CROSSEU findings contribute to improved understanding of climate impacts in high-elevation environments and support climate-resilient adaptation strategies that account for both changing snow regimes and ecosystem dynamics.
This research was funded by the "Cross-sectoral Framework for Socio-Economic Resilience to Climate Change and Extreme Events in Europe (CROSSEU)" project, under the European Union’s Horizon Europe Programme (Grant agreement No. 101081377).
How to cite: Micu, D.-M., Amihaesei, V.-A., Ontel, I., Paraschiv, M.-G., Cheval, S., Bothe, O., Bowyer, P., Quinti, G., Adamescu, M., Halnæs, K., and Some, S.: Climate change signals in avalanche-protective forest ecosystems of the Alps and Carpathian Mountains: Insights from the CROSSEU Project, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9470, https://doi.org/10.5194/egusphere-egu26-9470, 2026.
Future temperature-related mortality in the Czech Republic is projected to change under the combined influence of climate change and population ageing. This study quantifies cold- and heat-attributable mortality across 14 regions using daily temperature and mortality data from 1994-2020 and age-specific exposure-response functions. The analysis presents the latest results developed within CROSSEU’s Heat Case Storyline, focusing on future heat- and cold-related health risks. Future mortality burdens were projected by combining EURO-CORDEX regional climate model simulations under RCP4.5 and RCP8.5 with population projections based on Shared Socioeconomic Pathways (SSPs) from the Wittgenstein Centre. Estimates were produced under two analytical frameworks: a climate-only scenario assuming a constant population structure and a combined climate-demographic scenario incorporating changes in population size and age composition.
To account for potential adaptation to heat, an adaptation framework was defined based on historically observed changes in the Minimum Mortality Temperature (MMT) and exposure-response functions, reflecting shifts in population vulnerability over time. Within this framework, four heat adaptation pathways were specified for each SSP, corresponding to (i) no adaptation, (ii) limited adaptation associated with a 10% attenuation of heat-related risk, (iii) strong adaptation corresponding to a 50% risk reduction, and (iv) near-complete adaptation corresponding to a 90% reduction. These adaptation pathways are conceptually linked to changes in MMT and ERFs but are not quantified in the present analysis and will be evaluated in subsequent work.
All quantitative results presented here assume no or constant adaptation to temperature. Under the climate-only scenario (RCP8.5, late century), the annual cold-attributable fraction (AF) is projected to decline slightly, while the heat-related AF increases modestly. When population ageing is incorporated, the cold AF increases by approximately 4.5%, and the heat AF rises by around 1%. Relative to historical levels, national cold-related mortality increases by approximately 48%, and heat-related mortality increases by approximately 50% under the combined climate-demographic scenario. Comparisons with a constant-population framework indicate that population ageing is associated with an additional 45-50% increase in future temperature-attributable mortality.
Overall, the results illustrate how projected temperature-related mortality depends on assumptions about future climate, demographic change, and population vulnerability, underscoring the importance of integrating climatic and demographic processes in long-term health impact assessments.
How to cite: Naz, F., M Vicedo-Cabrera, A., Huber, V., Jenkins, K., Dogan, T., Kyselý, J., Plavcová, E., and Urban, A.: Projected Temperature-Related Mortality in the Czech Republic Under Climate and Demographic Change with Adaptation Scenarios, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19402, https://doi.org/10.5194/egusphere-egu26-19402, 2026.
Climate adaptation is essential to reduce the risks of climate change and to ensure long-term resilience. As climate risks increase, so does the need for climate adaptation, supported by risk-informed decision-making and policy. Modelled projections of future climate and socioeconomic scenarios increasingly guide climate policy and decision-making, however, current modelling frameworks often lack a nuanced representation of adaptation. At the same time, adaptation planning and decision-making requires approaches able to develop flexible and adaptive management strategies that account for uncertainties and reflect specific adaptation objectives, such as adaptation pathways. These are flexible and robust sequences of adaptation options that span the adaptation solution space which is a multidimensional space within which adaptation is enabled and implemented.
By projecting constraints on the adaptation solution space under future climate and socioeconomic scenarios, our research explores the link between global climate modelling and adaptation pathways approaches. Projecting dimensions of adaptive capacity allows for the identification and anticipationof possible barriers to adaptation, and establishing of enabling conditions that lead to a wider adaptation solution space. As biophysical and socio-economic changes constrain the range of adaptation options available in the future, we assess the potential adaptation uptake along a set of different climate and socioeconomic scenarios for European regions. We use a range of socioeconomic indicators as proxies for the potential for the uptake of specific adaptation options. Based on the statistical analysis of the observed implementation levels, we project and map the potential uptake of several adaptation options into future along the Shared Socioeconomic Scenarios, and additional stress-testing scenarios. Our study focuses on Europe using a variety of risks, including heat-related health impacts, and wildfire risk to forestry.
This research bridges top‑down climate modelling with bottom‑up adaptation planning to assess how socioeconomic conditions can shape the future adaptation solution space. This approach helps to assess socioeconomic limits to adaptation and the future adaptation solution space, and further enables a more nuanced representation of adaptation in climate impact studies. The results can inform local adaptation planning in terms of outlining the availability of individual adaptation options as part of adaptation pathways development, as well as identifying key socioeconomic factors in constraining adaptation uptake potential. Addressing such constraints in adaptation policy on different levels can widen the solution space, and ultimately, inform climate-resilient planning and decision-making.
How to cite: Petersen, A.-K., Zeller, Z., Andrijevic, M., Schleussner, C.-F., and Martyr, R.: Projecting the adaptation solution space to inform a climate-resilient Europe, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20119, https://doi.org/10.5194/egusphere-egu26-20119, 2026.
The French "CatNat" regime provides mandatory natural disaster coverage based on national solidarity, using a uniform rate for all homeowners. However, the increasing availability of high-resolution geoscience data challenges this uniformity. This is notably the case for Clay Shrink-Swell (CSS) risk, which has become a primary cost driver in the last years. Does the shift from national pooling to granular risk segmentation threaten the viability of such solidarity regimes?
To answer this question, we combine empirical analysis with theoretical modeling. First, utilizing a large-scale collection of insurance quotes, we identify a fragmented market where insurers leveraging granular hazard maps coexist with traditional "pooling" actors. Second, to capture the long-term dynamics of this fragmentation, we develop a game-theoretic model of market equilibrium. This model allows us to explicitly simulate how risk selection strategies impact affordability and access to coverage. Our findings suggest that while granular segmentation improves pricing accuracy, it risks creating "insurance deserts" for vulnerable areas. Finally, this technical evolution undermines the regime's solidarity principle, potentially reducing the socio-economic resilience of communities facing increasing climate geohazards.
How to cite: Dalbarade, R., Charpentier, A., Barry, L., Hillairet, C., El Hassani, H., Bamansor, A., Hénaff, Q., and Blaquière, S.: When Climate Hazard Granularity Challenges Risk Pooling: A Spatial Perspective, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19737, https://doi.org/10.5194/egusphere-egu26-19737, 2026.
VESTAP, a climate decision support tool offered by the South Korean government, supports sector-specific vulnerability assessments for local and regional governments based on the IPCC AR4 framework. As a multi-indicator, spatially based assessment tool, VESTAP conceptualizes vulnerability as a composite of climate exposure, sensitivity, and adaptive capacity, with sub-indicators derived from administrative-unit-level data and aggregated using weighted sums. However, the current assessment of building vulnerability to flooding has limited capacity to reflect the highly localized distribution of key risk factors driving pluvial flooding, which tend to emerge heterogeneously within administrative units. As a result, improvements in spatial discrimination for priority area identification and in the explanatory power of assessment results are required.
Effective climate adaptation requires the precise identification of vulnerable areas to support priority setting. Pluvial flooding, the focus of this study, occurs within urban areas due to insufficient drainage capacity and topographic water retention during heavy rainfall, with risk factors often concentrated at highly localized scales. It is widely recognized that administrative-unit-level assessments are insufficient for identifying flood-prone areas under such conditions. Recent studies have addressed this limitation by quantifying the spatial distribution of risk factors at finer spatial units-such as parcels, households, and grids-and by integrating physical models with socio-economic indicators to better capture spatial heterogeneity.
This study aims to improve a government-offered vulnerability assessment for Suwon, South Korea, by enhancing spatial resolution and indicator composition to provide actionable information for local adaptation planning. Compared to a baseline setup (S0), five improvement strategies are introduced: (1) region-specific adjustment of indicator weights, (2) incorporation of nationally available spatial explanatory datasets, (3) addition of literature-based key indicators, (4) transition from simple aggregation to an overlapping analytical approach, and (5) integration of municipality-produced datasets. The results of each pilot application are quantitatively compared in terms of changes in the spatial patterns of vulnerable areas, and their validity is evaluated through consistency with observed flood damage records and recovery and prevention investment histories. In addition, interviews with local government officials are conducted to assess practical relevance and usability.
By diagnosing the existing vulnerability assessment framework for pluvial flooding in light of theory and prior research, and by comparing pilot application results, this study examines the potential for improving spatial sensitivity and assessment validity. The findings provide more precise and explainable evidence to support priority setting and resource allocation for local climate adaptation planning.
How to cite: Lee, J., Cho, K. D., Kim, S. R., Kim, E., and Park, C.: Improving Government-Provided Urban Flood Vulnerability Assessment for Adaptation Decision Support, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16254, https://doi.org/10.5194/egusphere-egu26-16254, 2026.
As climate change increasingly impacts ecosystems, economic activity, and human well-being, Europe is accelerating the development of coherent and effective climate action under the umbrella of the Paris Agreement and the EU Green Deal. This research evaluates the dynamics and effectiveness of existing mitigation and adaptation policies and governance frameworks at the European Union level and within eight European countries: Austria, the Czech Republic, Denmark, France, Germany, Italy, Romania, and the United Kingdom.
This work combines an extensive review of primary EU and national policy documents in force in 2025, with insights from 42 semi-structured interviews with key informants, including experts from European institutions, national decision-makers, research organisations, and civil society representatives. The interviews provide critical insights into actual implementation dynamics, political priorities and challenges, and the institutional barriers that shape climate action beyond formal planning commitments.
The analysis focuses on the core pillars of climate policy, examining objectives, timeframes, and sectoral coverage across key socio-economic sectors such as energy, transport, agriculture, health, infrastructure, and water management. A focal point is the tension between sustainable development, mitigation and adaptation, as mitigation policies are relatively mature and supported by robust EU monitoring, while adaptation remains heterogeneous and under-prioritised or under-financed. The findings reveal significant gaps in the operationalisation of climate strategies, short-termism and polarisation or weak institutional cooperation, despite the steady development of the formal strategic settings, the limited but useful involvement of civil society, the limited actual focus on societal issues and legislative gaps, among others.
Our findings inform the development of the CROSSEU Decision Support System, ensuring the tool reflects real-world governance constraints and stakeholder needs. By identifying where synergies emerge and where institutional bottlenecks constrain progress, the research supports the translation of climate-socio-economic risks data into actionable, socially-informed decision pathways. Furthermore, the strong national specificities highlight the need for understanding the local context and the relevance of comparative research for fostering equitable and resilient climate strategies at the European scale.
This research was funded by the "Cross-sectoral Framework for Socio-Economic Resilience to Climate Change and Extreme Events in Europe (CROSSEU)" project, under the European Union’s Horizon Europe Programme (Grant agreement No. 101081377).
How to cite: Falcescu, V., Quinti, G., Ludvig, A., de Melo, K., Cheval, S., Declich, A., Feudo, F., Halnæs, K., Judes, T., Marta, F., Micu, D., Some, S., Štětinová, V., Urban, A., Yousef, L., and Bothe, O.: Effectiveness of the mitigation and adaptation policies and governance across Europe: Insights from the CROSSEU project, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9271, https://doi.org/10.5194/egusphere-egu26-9271, 2026.
Understanding physical climate hazards, risks, and impacts should be integrated with socio-economic contexts and policy-governance frameworks to support effective climate resilience and decarbonisation pathways. Science-based decision-making across sectors and scales, combined with a participatory approach, is essential in the current European policy landscape.
This work synthesises and integrates research outcomes from three Horizon Europe projects: CARMINE, CROSSEU, and OPTFOR-EU. These initiatives show the way multifaceted risk-vulnerability-impact assessments and extensive stakeholder engagement can inform regional planning for enhanced resilience, nature-based climate adaptation, and decarbonisation pathways.
CARMINE focuses on local and regional adaptation planning, combining high-resolution climate projections with socio-economic vulnerability indicators, spatial planning data, and stakeholder knowledge. This integrated approach is designed to support cities and metropolitan regions in identifying locally specific risk profiles and prioritising adaptation measures for building climate resilience in various environmental and socio-economic contexts across Europe. CROSSEU addresses systemic and cross-sectoral dimensions of climate change impacts by analysing how climate risks cascade across socio-economic sectors (i.e., agriculture, transport, tourism, forestry, health, social justice), infrastructure, and land-use. The project explores how institutional fragmentation and policy misalignment can hinder coordinated adaptation actions, underlying the importance of cross-sectoral and multi-level governance. OPTFOR-EU translates vulnerability and risk insights into operational decision-support tools for decarbonization. Applying optimisation and robust decision-making approaches, the project explores adaptation and decarbonisation options, such as NBS, forest management strategies, and low-carbon development pathways, under deep climate and socio-economic uncertainty. Together, the three projects are implemented through a portfolio of case studies spanning multiple European climatic zones, socio-economic and governance contexts, and land-use systems, enabling comparative analysis and strengthening the robustness and transferability of the results.
Across the three projects, there are several shared methodological and practical advances: (i) the integration of quantitative vulnerability assessment and risk metrics with qualitative and participatory inputs for a context-based decision-making, (ii) insights of policies and governance capacity for effective adaptation and decarbonisation planning, (iii) evaluation of social risks and equity between climate change impact and pressing need for action, and (iv) strong alignment between analytical science-based ouputs and EU climate ambitions and policy framework, including EU Adaptation Strategy, The European Green Deal, regional and urban planning strategies and risk management frameworks.
All three initiatives provide perspectives on how research can better support actionable, equitable, and climate resilience strategies. Key lessons learned highlight the need to: move beyond sectoral-specific and hazard-oriented assessments toward more integrated, multi-level decision-oriented approaches that connect urban, regional, and forest systems; embed vulnerability analysis directly into policy and planning workflows; and design flexible, robust pathways that jointly address climate resilience and decarbonisation, urban adaptation and risk management objectives
How to cite: Cheval, S., Falcescu, V., and Micu, D.: From Climate Risk to Policy Action: Decision-Oriented Approaches for Urban Adaptation, Regional Planning and Forest Strategies under EU Climate Frameworks, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18306, https://doi.org/10.5194/egusphere-egu26-18306, 2026.
Posters virtual: Fri, 8 May, 14:00–18:00 | vPoster spot 4
EGU26-11292 | Posters virtual | VPS7
Urban Flood Risk Assessment Using High-Resolution 3D Building Models and Multi-Temporal Meteorological DataFri, 08 May, 15:09–15:12 (CEST) vPoster spot 4
Urban areas are increasingly exposed to flood hazards due to climate change, densification and growing urbanization. Remote sensing datasets can be used to monitor the floods and warn the population. Much more, simulations of hazards, using high resolution geospatial datasets combined with meteorological data can be derived. In this case, solutions prior to the events can be implemented, so increasing the resilience of cities to natural hazards.
This study presents a high-resolution 3D urban model of Brașov, Romania, developed from an airborne photogrammetric datasets acquired in 2025, and its application in urban flood risk assessment. The 3D building models were obtained using footprints from the national topographic database and the height derived from the computed normalized Digital Surface Model (nDSM). For the flood modelling the hydrological network and land cover data were used.
To assess flood risk, time series precipitation dataset was analyzed and used in the modelling framework. The combined analysis under different scenarios, enabled the identification of flood areas and the estimation of the number of exposed buildings. The results highlight the importance of high-resolution 3D urban data for understanding flood dynamics in complex urban settings and support decision-making processes related to urban planning, risk mitigation, and climate resilience. The output also represents a starting point for a Digital Twin for Brașov.
How to cite: Pârvu, I., Cuibac, I., Pârvu, A., Pârvulescu, N., Corneanu, I., Cheval, S., Crăciunescu, V., Dumitrescu, A., Amihaesei, V., Gabrian, Ș., Dinicila, Ș., and Tudose, N.: Urban Flood Risk Assessment Using High-Resolution 3D Building Models and Multi-Temporal Meteorological Data, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11292, https://doi.org/10.5194/egusphere-egu26-11292, 2026.
EGU26-21729 | ECS | Posters virtual | VPS7
When Adaptation Follows Hazard, Not Vulnerability: Flood Loss and Damage in AssamFri, 08 May, 15:24–15:27 (CEST) vPoster spot 4
Assam, one of India’s most flood-prone states, has a vulnerability to climate change that is shaped by a complex socio-political context and increasing biophysical pressures. A range of policies and on-the-ground initiatives have been introduced to support climate change adaptation (CCA). However, understanding what works, where, and how remains critical for advancing effective and equitable adaptation. This study addresses this gap by examining Assam, a historically flood-prone state that experiences significant loss and damage each year.
Despite widespread exposure to floods, loss and damage across Assam is uneven. In several districts, high vulnerability rather than flood intensity drives severe economic and non-economic loss and damage. In some cases, districts with relatively low flood hazards experience high loss and damage due to social, economic, and institutional vulnerabilities. Differences in the type and quality of adaptation implementation further shape these outcomes.
To examine the role of adaptation in reducing and managing loss and damage, qualitative fieldwork was conducted in three districts representing different drivers of flood impacts. Majuli, a river island that experiences floods almost every year, records relatively low loss and damage. This is largely due to lower vulnerability and the presence of effective adaptation measures. Long-term structural interventions and community-led practices have enabled adaptation to move beyond coping towards more transformative pathways.
In contrast, Barpeta, a district exposed to high flood hazard, experiences high loss and damage due to high socio-economic vulnerability. Deep inequalities, uneven community distribution, limited adaptive capacity, and local political dynamics constrain effective adaptation. As a result, adaptation efforts in Barpeta have largely progressed only from coping to intermediate, incremental adaptation, despite decades of recurrent flooding.
The third case, Udalguri, is located farther from the Brahmaputra and is primarily affected by flooding from smaller tributaries. Although flood intensity is relatively low, the district experiences high loss and damage, particularly loss of human life. Flooding is a relatively recent phenomenon in this area, and communities are poorly prepared. High vulnerability, driven by inadequate adaptation strategies, persistent social inequality, and pronounced caste–class differentiation, has kept adaptation responses at the coping stage, with little progression towards incremental change.
Insights from expert interviews, key informant interviews, focus group discussions, and community interactions reveal that adaptation planning in Assam is largely guided by flood hazard levels rather than vulnerability. This hazard-focused approach results in unequal protection and leaves highly vulnerable communities exposed to severe loss and damage, not only economic but also high non-economic, which is not even documented.
Overall, the findings demonstrate that flood impacts cannot be understood through water levels alone. Vulnerability fundamentally shapes how floods are experienced and how damaging they become, particularly in relation to non-economic loss and damage. By foregrounding lived experiences and overlooked forms of loss, this study argues for a shift in adaptation planning beyond physical flood control. Policies must recognize vulnerability, systematically document non-economic losses, and support locally grounded, socially just adaptation pathways that protect people, not only infrastructure. This is especially critical in regions like Assam, where social vulnerability continues to turn even moderate floods into human tragedies.
How to cite: Vyas, S., Barua, A., and Mallikarjuna, C.: When Adaptation Follows Hazard, Not Vulnerability: Flood Loss and Damage in Assam, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21729, https://doi.org/10.5194/egusphere-egu26-21729, 2026.
