Impact-based forecasting and warning systems (IbFWs) are transforming early warnings by turning hazard forecasts into expected impacts, making alerts actionable and risk-informed while advancing the UN’s Early Warnings for All (EW4All) vision for 2027. However, their operational maturity and extension from single-hazard to multi-risk contexts remain uneven. This work builds on international collaboration through the Weather and Climate Science for Service Partnership (WCSSP) India programme, a UK–India initiative supporting the development of risk-based forecasting for high-impact weather in multi-risk contexts.

This study presents the synthesis of two global surveys on multi-risk IbFWs, capturing perspectives from 143 practitioners in 68 countries and 64 researchers across 25 countries. The surveys explored global experiences, evidence, and challenges in developing and implementing multi-risk IbFWs and were implemented in the six official United Nations languages to maximise accessibility and reduce language barriers.

The results reveal gaps globally, with no fully operational multi-risk IbFWs identified that provide detailed, quantified forecasts and warnings. Most current platforms manage multiple hazards primarily as independent events and incorporate only limited impact-based functionalities, underscoring significant opportunities for enhancement and innovation. Insights from 18 countries illustrate diverse tools and approaches for multi-hazard communication, while exposing differences in interpreting “multi-risk” and “impact-based” concepts. Respondents agree that future progress and innovation relies on improved availability of impact data and stronger multi-risk assessment capacity.

The survey findings provide actionable insights to accelerate the development of multi-risk IbFWs, highlighting the need for improved impact data availability and integrated risk assessment. These advances are essential to protect communities from weather and climate hazards through effective early warnings, timely action, and stronger resilience.

How to cite: Bianco, M., Brown, E., Lumbroso, D., White, C., and Kolusu, S.: Global evidence of operational multi-risk Impact-based Forecasting and Warning systems, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18533, https://doi.org/10.5194/egusphere-egu26-18533, 2026.

EGU26-18533

Download Close

The global Early Warnings for All Initiative calls for universal access to multi-hazard early warning systems. Yet what multi-hazard means when applied practically to an early warning system remains unclear and realities on the ground lag behind. Most early warning systems, in practice, are designed for single hazards and fail to account for how communities at risk face hazards that interact in several ways. This can result in confusing messages or contradictory advice, precisely when people at risk need a clear course of action.

This work seeks to address the gap in understanding how multi-hazard early warning systems can be operationalised in the global South. It considers how to design and implement people-centred multi-hazard early warning systems that explicitly account for differentiated vulnerabilities and capacities, and how age, gender, disability, language, social status, etc., shape whether people can receive, trust, and act on a warning.

Case studies from the Zurich Climate Resilience Alliance’s work in the Philippines, Nepal, and Peru will highlight the capacities and considerations needed to design people-centred multi-hazard early warning systems. In particular, this research reflects on the existing capacities and priorities for multi-hazard resilience across the four pillars of early warning systems: disaster risk knowledge; monitoring and forecasting; warning and dissemination; and preparedness and response. From this work, we critically assess where national early warning systems are on the multi-hazard early warning system spectrum, explore actions for progressing forward on the spectrum, and reflect on how to integrate community-based and inclusive approaches to ensure that messages and early actions are co-designed with those most at risk.

How to cite: Waddell, J., Arestegui, M., Uprety, D., Uprety, B., Budimir, M., Sakic Trogrlic, R., and de Ruiter, M.: Perspectives from the global south: How to move towards truly multi-hazard early warning systems, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7325, https://doi.org/10.5194/egusphere-egu26-7325, 2026.

EGU26-7325

Download Close

There is a growing push to evolve away from early warning systems that focus exclusively on what a hazard might be (e.g., in terms of magnitude or intensity), towards approaches that facilitate more meaningful decision-making based on the societal impacts a hazard might cause. These advanced, impact-based early warning systems should integrate alert or action thresholds that are calibrated using risk metrics derived from relevant engineering vulnerability models and (uncertain) forecasts of potential event amplitudes. Several impact-based (i.e., risk-informed) decision-making approaches for early warning have been proposed in the literature to address this requirement, particularly in the context of earthquakes and floods.  They have been designed for application to a range of infrastructure, including railways, ports, roads, and buildings.

However, current risk-informed early warning approaches implicitly assume that the associated decision to trigger (or not) action is being made in a single-hazard context, where the incoming event is the first hazard to which the infrastructure of interest has been exposed. This means that their alert thresholds are calibrated based on engineering vulnerability models (or other related information) for intact infrastructure assets, which could lead to suboptimal decision-making in multi-hazard-prone regions where infrastructure may have already experienced prior damage.  

We address this important limitation by introducing a risk-informed early warning decision-making framework for explicit application in multi-hazard contexts.  The framework builds on previous earthquake early warning-related studies to provide a means of impact-based decision making on early warning alert issuance (action triggering) in the face of (possibly uncertain) existing infrastructure damage conditions due to previous events. The framework can handle a flexible amount of information related to the prior state of an engineering asset, from a definitive description of damage to probabilistic data on the intensity of the previous event it was exposed to. We demonstrate the framework for a hypothetical case-study building in the context of an earthquake sequence, considering a range of information about its initial conditions. We find that the best action for a given incoming event can depend on the building’s initial state, reinforcing the importance of accounting for damage accumulation when making decisions to issue early warnings.

How to cite: Cremen, G.: Towards Risk-informed Decision Making on Early Warning in a Multi-hazard Context, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9288, https://doi.org/10.5194/egusphere-egu26-9288, 2026.

EGU26-9288

Download Close

Effective Multi-Hazard Early Warning Systems (MHEWS) rely not only on the accuracy of the weather forecasting models but importantly on their alignment with human dynamics and the natural and built environment. Risk assessment frameworks available at this stage often treat populations as static, fixed in residential locations regardless of the time of day or hazard onset and progression (Chen et al., 2023). This residence-based approach masks the true exposure of population in transit – individuals commuting, attending school or travelling. They may be physically exposed in low-vulnerability zones while possessing high social vulnerability (e.g., lack of local knowledge or support networks), or vice versa. Recent developments in mobility-based exposure assessment demonstrate that human activity patterns significantly alter vulnerability distributions across space and time, with exposure estimates varying by up to 40% between static and dynamic scenarios during peak activity (Rajput et al., 2024).

Our exercise introduces a methodological framework to operationalise social behavioural geography within a quantitative risk assessment model. Using the CLIMADA (CLIMate ADAptation) impact modeling platform (Aznar-Siguan & Bresch, 2019), we compare two distinct exposure scenarios for a compound hazard event in Ireland: (1) a static 'Residential' baseline assuming population distribution based on census residential locations, and (2) a more dynamic 'Activity-Based' scenario that integrates 2022 Irish Census data on Working From Home (WFH) patterns and commuting flows to redistribute social vulnerability based on diurnal activity patterns. This activity-based approach accounts for temporal mobility, capturing where people could be located during different times of day rather than solely where they reside.

By shifting the analytical focus to socially vulnerable populations in motion, this approach reveals "hidden hotspots" of risk, namely areas where physical hazard severity may be moderate, but the temporal convergence creates compounding crisis conditions (e.g. traffic jams or social event scenarios). Our methodological framework demonstrates that incorporating dynamic population distributions alters exposure assessments, with implications for emergency response resource allocation and warning dissemination strategies. We advocate for a paradigm shift in warning issuance protocols: when possible, transitioning from purely geographic alerts to behaviour-responsive, time-sensitive warnings that account for where people are during hazard events, not merely where they live (Haraguchi et al., 2022). This human-centric characterisation of exposure provides actionable insight for emergency managers and enhances the effectiveness of MHEWS for mobile individuals.

References:

Aznar-Siguan, G., & Bresch, D. N. (2019). CLIMADA v1: A global weather and climate risk assessment platform. Geoscientific Model Development, 12(7), 3085-3097. https://doi.org/10.5194/gmd-12-3085-2019

Chen, X., Hu, Y., Chi, G., & Chen, J. (2023). Assessing dynamics of human vulnerability at community level – Using mobility data. International Journal of Disaster Risk Reduction, 95, 103964. https://doi.org/10.1016/j.ijdrr.2023.103964

Haraguchi, M., Nishino, A., Kodaka, A., & Lall, U. (2022). Human mobility data and analysis for urban resilience: A systematic review. Environment and Planning B: Urban Analytics and City Science, 50(1), 7-27. https://doi.org/10.1177/23998083221075634

Rajput, A. A., Liu, C., Liu, Z., Zhao, J., & Mostafavi, A. (2024). Human-centric characterization of life activity flood exposure shifts focus from places to people. Nature Cities, 1, 290-301. https://doi.org/10.1038/s44284-024-00043-7

How to cite: Bukowski, F., Gavin, E., and Murray, L.: Dynamic Population Exposure in Multi-Hazard Early Warning Systems: An Activity-Based Approach Conceptual Method, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17459, https://doi.org/10.5194/egusphere-egu26-17459, 2026.

EGU26-17459

Download Close

Effective tsunami early warning systems rely on fast and robust hazard forecasting. While Nonlinear Shallow Water (NLSW) models accurately predict wave dynamics, their high computational cost on CPUs limits their practical use in time-sensitive early warning contexts. Parallel computing on GPUs offers a solution. Celeris Advent (Tavakkol and Lynett, 2017) implements GPU-accelerated numerical simulation but operates on uniform Cartesian grids that can exhibit Earth-curvature-related distortions in trans-oceanic domains.

This study proposes a numerical framework for basin-scale tsunami propagation modelling using a conservative finite volume method (FVM) on a non-uniform orthogonal grid. Conventional plate-carrée grids are straightforward to implement, while their latitude-dependent physical cell dimensions may introduce anisotropic numerical diffusion and compromise temporal stability. Rather than transforming spherical coordinates into generalized curvilinear equations, the proposed approach constructs a non-uniform orthogonal mesh in physical space and explicitly incorporates cell areas and interface lengths into the conservative finite volume formulation. Within this framework, geometric representation and numerical flux evaluation are treated separately to maintain conservation and stability on non-uniform grids. The NLSW equations are discretized using the second-order Kurganov–Petrova central-upwind scheme (Kurganov and Petrova, 2007), with geometric factors integrated through normalization of flux divergence terms by cell areas and interface lengths, while avoiding explicit metric tensor formulations. Initial tsunami generation is computed using the Okada (1985) model based on seismic fault parameters.

The proposed method is designed for GPU parallel computing architectures and is intended for application to large-scale grid computations relevant to basin-scale tsunami forecasting. Standard tsunami benchmark tests are employed to check that the solver can reproduce key nonlinear processes. The framework is further applied to the 2011 Great East Japan Earthquake tsunami as an illustrative example of trans-Pacific propagation modelling.

Beyond numerical performance, the spatio-temporal tsunami fields produced by the framework may be useful for integration into downstream decision-support environments, such as interactive visualization and virtual-reality-based tools for scenario exploration and training.

How to cite: Kang, J. and Son, S.: A GPU-accelerated framework for basin-scale tsunami propagation in early warning applications, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19562, https://doi.org/10.5194/egusphere-egu26-19562, 2026.

EGU26-19562

Download Close

For coastal areas located close to offshore seismic sources, earthquake risk is inherently multi-hazard: intense ground shaking and tsunami inundation can occur in rapid succession, with very short lead times for protective actions. In these near-field settings, traditional Tsunami Early Warning Systems (TEWS), which rely on seismic source parameters available several minutes after origin time, may provide alerts that are only marginally earlier than tsunami arrival, limiting their effectiveness.

In this study, we evaluate the integration of rapid earthquake magnitude and location estimates from QuakeUp, an impact-based Earthquake Early Warning System (EEWS), into a tsunami early warning workflow. QuakeUp processes real-time seismic observations to issue initial earthquake alerts within a few seconds, based on fast estimates of magnitude, location, and potential damage zone, supporting immediate risk mitigation for ground shaking. These estimates are then simultaneously used to initialize Probabilistic Tsunami Forecasting (PTF), enabling a coordinated multi-hazard warning strategy in which earthquake and tsunami risks are addressed within a unified, time-critical framework.

We present a real test case to quantify the earliness and accuracy of EEWS-derived source parameters and assess their impact on tsunami forecasting. A hindcast of the 30 October 2020 Mw 7.0 Aegean Sea earthquake, whose tsunami reached nearby coastlines in approximately 10 minutes, shows that the EEWS delivers stable and accurate hypocenter and magnitude estimates about 40 seconds after origin time. These estimates are comparable to those provided by the operational Early-Est system, which become available only after several minutes in the Mediterranean region. When used to initialize a PTF procedure, the EEWS-based source characterization yields coastal runup estimates in reasonable agreement with observations, despite the substantially reduced warning latency.

To further assess the robustness of the results obtained in the real case, we analyze a second scenario based on 150 simulated seismogram datasets for earthquakes in the Messina Strait (Southern Italy), a region characterized by high exposure and extremely short tsunami travel times. For events with moment magnitudes between 6.0 and 7.0, the analysis confirms that the integrated EEWS–TEWS workflow can provide reliable source estimates within one minute, supporting its applicability to near-field tsunami early warning. 

This study provides the first demonstration of a combined EEWS–TEWS approach for near-coastal tsunamigenic events, highlighting its potential for dual risk mitigation within a multi-hazard early warning perspective. Future work will focus on testing performance in an operational setting, including the effects of network latencies and configuration-dependent efficiency. In addition, the EEWS technique employed, by providing a preliminary mapping of the most damaged zone, offers a promising perspective for extracting early constraints on seismic source geometry. This information could further reduce uncertainty in near-field tsunami inundation forecasts.

How to cite: Scala, A., Rea, R., Bernardi, F., Elia, L., Lorito, S., Colombelli, S., Festa, G., Romano, F., Amato, A., and Zollo, A.: Toward a multi-hazard earthquake–tsunami early warning system: a feasibility study, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20069, https://doi.org/10.5194/egusphere-egu26-20069, 2026.

EGU26-20069

Download Close

Across Europe, multiple natural hazards increasingly converge as climate change intensifies the frequency and severity natural hazards, yet early warning systems (EWS) remain organised around single hazards. This institutional and technical fragmentation leaves exposed populations without integrated warnings for compound threats that define contemporary disaster risk. Identifying where multiple hazards converge with high societal exposure is essential for prioritising investments in integrated multi-hazard early warning systems (MHEWS). Here, we present an AI-driven approach combining deep learning-based susceptibility mapping with comprehensive exposure analysis to reveal priority regions where Europe's early warning infrastructure falls short. We address this research gap by adapting a convolutional neural network architecture to European susceptibility mapping of a range of hazards including flood, wildfire, landslide, tsunami, drought, heatwave, extreme wind, volcanic eruption and earthquake. We introduce spatial partitioning to prevent data leakage, generate probabilistic susceptibility outputs, and employ Shapley additive explanations values to interpret model drivers. Our analysis reveals that a quarter of Europeans live in regions susceptible to three or more hazards, with critical exposure hotspots concentrated in coastal and Southern Europe and major river basins where population density, economic assets, and agricultural infrastructure converge with high multi-hazard susceptibility. These findings provide an evidence base for strategic allocation of resources toward integrated EWS in regions where single-hazard approaches are demonstrably insufficient.

How to cite: Tiggeloven, T., Palmerio, J., Ferrario, D., Ronco, M., Albergo, E., Ward, P., and Torresan, S.: Mapping the multi-hazard early warning gap: AI-based susceptibility analysis reveals hotspots where Europe needs integrated warning systems, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9898, https://doi.org/10.5194/egusphere-egu26-9898, 2026.

EGU26-9898

Download Close

Plasmodium vivax is the most geographically widespread malaria parasite, with billions of people at risk of transmission. While malaria is now largely regarded as a tropical disease, historically, P. vivax extended far into temperate regions, including Europe and North America. Its distribution is strongly influenced by hydroclimatic conditions, particularly surface temperature and the availability of standing water for mosquito breeding. Today, international travel and trade occasionally introduce the parasite into non-endemic regions, and future climate change could amplify these risks and shift viable transmission zones.

Previous global estimates of malaria suitability often relied on precipitation as a proxy for surface water availability, neglecting hydrological processes and oversimplifying both present-day conditions and future projections. Here we extend our previous work on P. falciparum transmission in Africa and present hydrologically informed global estimates of P. vivax transmission suitability using a multi-model ensemble of climate and hydrology simulations. By explicitly incorporating hydrological processes, we identify river corridors as key areas of suitability, aligning with historical observations of malaria transmission patterns. This approach provides a more realistic representation of water availability compared to precipitation-based models.

Our findings indicate that future warming will reduce thermal constraints on transmission, particularly in northern latitudes, expanding potential P. vivax suitability into temperate regions. Europe, North America and Asia show future net increases in transmission suitability and a sensitivity to emissions pathway. However, when hydrology is considered, water availability emerges as a critical limiting factor under future climates. Regions such as southern Europe and western North America are projected to become increasingly water-limited, restricting transmission potential. This trend is absent in precipitation-only models. Conversely, areas with persistent or extreme flooding may experience heightened receptivity, suggesting that outbreaks could become more closely associated with hydrological extremes in the future. With more hydrological extremes projected, this finding places greater emphasis on the role of flood events in driving future P. vivax outbreaks. Such integration of both climate and hydrology in malaria suitability assessments can help inform malaria surveillance strategies and public health planning in both endemic and non-endemic regions.

How to cite: Smith, M., James, W., Gosling, S., Mroz, E., Smith, T., and Thomas, C.: Flooding and water-availability impacts future global limits of Plasmodium vivax malaria, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12563, https://doi.org/10.5194/egusphere-egu26-12563, 2026.

EGU26-12563

Download Close

Quantifying exposures to environmental factors such as pollution, temperature, noise, coastal flooding or green space is essential in determining the human exposome, i.e. the totality of human environmental exposures. This is subsequently crucial for quantifying the contribution of the exposome to human health. Major challenges in determining convincing exposure estimates are i) using a multitude of harmonised environmental factors, often originating from different disciplines such as hydrology, ecology or atmospheric sciences ii) using high spatial and temporal resolution datasets and incorporating mobility proxies to appropriately represent human activities and iii) datasets with continental or global extent to evaluate spatial patterns and to incorporate large-scale impacts, for example of climate change. For a rational and convenient exposure assessment performed by epidemiologists it is desired that estimates are easily accessible without the burden of performing the computations themselves.

To address these challenges, we developed an exposure assessment workflow to process a set of environmental factors. These include factors beneficial for human wellbeing, such as accessibility to green space, as well as factors with negative health impacts, such as high temperature or earthquake risks. The workflow uses open-source software and datasets. The processed environmental factor datasets are on global scale at 1km or 100m resolution. Human mobility, represented by buffer calculations on each cell, and aggregations to e.g. administrational units were calculated in a processing workflow implemented in LUE (https://zenodo.org/records/16792016) and computed on the Dutch national supercomputer Snellius. The data sets were then combined with global population density maps to estimate the human exposome for each grid cell. In our presentation we illustrate the exposure assessment workflow and show spatial patterns of exposure estimates. The datasets are made accessible via a SpatioTemporal Asset Catalog in the Global Environmental Exposure Dataspace (GEESE), a subproject of the SAGE European Green Deal Data Space (https://www.greendealdata.eu/).

How to cite: Schmitz, O., Kuipers­­­, E., Griffioen, R., Loffredo, L., Bood, R.-J., Oonk, R., and Karssenberg, D.: Global exposure assessment of environmental risk factors, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9405, https://doi.org/10.5194/egusphere-egu26-9405, 2026.

EGU26-9405

Download Close

The Santorini volcano, Greece, attracts global scientific interest and constitutes a top tourist destination. The 17th century BCE eruption (“Minoan event") was likely the largest ever experienced by humanity. It was associated with significant tephra falls, earthquakes, and tsunamis inundating the eastern Mediterranean basin. Global climate changes were attributed to the Minoan event. Geological and archaeological evidence supports that the Minoan event drastically influenced eastern Mediterranean civilizations. Minoan tephra layers formed key horizon markers driving revisions of the Mediterranean civilization chronology. Comparative studies indicate great similarity between Santorini and Krakatoa, but the Minoan eruption exceeded in size the 1883 CE Krakatoa eruption. During historical times the volcanic cycle in Santorini restarted with eruptions of smaller size and magma emplacement in the caldera, thus shaping the Kamenae (Burned) islands, exactly as happened with the post-1883 generation of the Anak (Child) island in the Krakatoa caldera. In 1650 CE, a violent eruption occurred at the submarine Kolumbo volcano, which is situated a few kilometers outside the Santorini caldera but very likely is fed by the same magmatic chamber. Further research is needed to understand if magma generation at depth is possibly controlled by the occurrence of large-magnitude intermediate-depth earthquakes. The 1650 CE eruption and associated strong earthquakes and tsunamis caused loss of life and significant destruction. After several small-to-medium eruptive episodes during the 18th-20th centuries, Santorini has remained dormant since 1950. However, on 9 July 1956, the area to the east of Santorini was ruptured by a magnitude 7.7 tectonic earthquake, which, along with its large tsunami, caused extensive loss of life and destruction in the entire southern Aegean Sea. Submarine surveys indicate that the 1956 rupture zone possibly belongs to the same NE-SW-trending fracture zone passing from the Kolumbo and Santorini volcanoes. There is no historical evidence for similar tectonic earthquakes occurring in the past. Data-driven probabilistic seismic hazard assessment utilizing incomplete and uncertain earthquake catalogues indicates that the 1956-type earthquakes may have very long repeat times. During 2025, an unusual cluster comprising thousands of earthquakes but with a maximum magnitude of only 5.3 and sources at distances of 20-40 km to the east of Santorini caused extensive social anxiety. This was magnified because of two reasons. First, preventive measures taken by civil protection authorities were unprecedented. Second, uncontrolled public statements were expressed by specialists and non-specialists about imminent eruptions and forthcoming large earthquakes, which raised important geoethical challenges. The seismic crisis received international attention because Santorini is a spot of worldwide tourist interest. More than 13,000 people evacuated voluntarily. For the interpretation of the cluster, the “seismic swarm” hypothesis appears more as a “deus ex machina” explanation than a convincing scientific result. The competing “foreshocks-mainshock-aftershocks” model fits the data better. Santorini is a key volcano offering results valuable for better understanding the behavior of many volcanoes around the globe, revealing global climate impacts of volcanic origin, deciphering unknown aspects regarding prehistoric civilizations in the Mediterranean, and providing important lessons learned for volcanic and other geohazard management.  

How to cite: Papadopoulos, G.: Large volcanic eruptions, earthquakes, and tsunamis in Santorini: a multi-hazard physical laboratory of global interest, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3519, https://doi.org/10.5194/egusphere-egu26-3519, 2026.

EGU26-3519

Download Close

Hurricanes can cause long periods of moisture entering residential buildings, which can lower indoor air quality and lead to respiratory health problems such as asthma and allergy. Previous studies have mostly focused on the immediate effects of flooding, but less attention has been given to the role of compound weather hazards such as rainfall and wind after a hurricane event. This study examined how total rainfall and wind speed can exacerbate the impacts of hurricanes on indoor air quality in terms of mold respiratory outcomes. We used a database from 60 buildings affected by Hurricanes Ida and Ian, collected during the winters of 2021 and 2022. The database was based on survey questionnaires, laboratory analyses, field inspections, ground measurements and flood hindcasts. Among these building, 25 were located in Louisiana (New Orleans and Baton Rouge), eight in the northeastern United States (New York and Philadelphia), and 27 in central and southern Florida (Fort Myers, Orlando, and Miami). The dataset included inspection data, laboratory measurements of indoor and outdoor mold spore in terms of several species, respiratory health issues (new symptoms), hindcasted flood depths, rainfall, wind speed. The weather data were processed into various mold-influencing variables, including total rainfall depth, number of rainy days, rainfall intensity, and wind characteristics. To explore the relationships, L1-regularized (LASSO) logistic regression was used to model (1) whether residents reported post-hurricane respiratory symptoms and (2) whether they reported any level of symptom severity. Although no strong statistically significant relationships were found using traditional regression methods, the LASSO analysis showed modest and consistent associations between cumulative post-hurricane rainfall and the time since hurricane landfall with both respiratory outcomes. These results suggest that post-hurricane rainfall events contribute to respiratory health effects, but it is not the main controlling factor; indoor mold indicators were more strongly related to maximum flood depth during the hurricanes. Overall, the findings suggest that longer exposure to moisture after a hurricane may play a role in respiratory health problems. Our results showed the importance of considering compound weather conditions rather than a single extreme event like hurricanes when evaluating respiratory health risks and planning for indoor resilience after natural disasters.

How to cite: Ahmadisharaf, E., Suliman, A. A., Azimi, P., Pakdehi, M., Kaiser, S., Keshavarz, Z., Abdelrazig, Y., and Allen, J.: Impacts of compound weather events on indoor mold and respiratory health issues in indoor environments, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4044, https://doi.org/10.5194/egusphere-egu26-4044, 2026.

EGU26-4044

Download Close

INTRODUCTION

Climate change increasingly threatens human health, ecosystems, and food systems worldwide. Extreme weather events, associated with climate change, such as floods, droughts, and typhoons, disproportionately affect vulnerable populations, worsening sociodemographic risks and limiting healthcare access. Tuberculosis (TB) care is especially vulnerable due to complex diagnostics and long treatment (6–18 months), yet evidence on program adaptation and geospatial solutions remains scarce. This study examines how climate-related disasters disrupt TB services in low- and middle-income countries and how geospatial tools can strengthen resilience.

METHODS

We conducted a scoping literature and desk review, followed by a qualitative exploratory study comprising 10 semi-structured interviews (2 online, 8 in-person) with purposefully selected TB program implementers experienced in climate-related disaster events across eight high TB burden countries: Bangladesh, Ethiopia, Kenya, Nigeria, Pakistan (2), the Philippines, Zambia, and Zimbabwe (2). The interview tool was guided by concepts from the Saunders Climate Change & TB Analytical Framework such as climate-related impact, TB program consequences and health system challenges. Synthesized Narrative Exploration, an interview method entailing the further exploration of summarized findings from a desk review to build on prior knowledge, was employed. All interviews were transcribed, coded and analyzed using NVivo software.

RESULTS

Reported disasters included flooding, drought, heat waves, typhoons/cyclones, rising lake water levels, silting and landslides. Participants explained that vulnerable populations experience major disruptions during disasters including displacement and isolation among others, directly impacting access to TB services. They noted TB risk increased due to overcrowding in displacement camps, malnutrition, and psychological stress. At the same time, TB care and treatment can be disrupted during disasters due to damaged infrastructure, supply chain issues, staff reallocation to other (emergency) services, etc., leading to suspension of screening and testing, while treatment adherence is affected by longer travel distances and increased costs. In addition, TB medication is poorly tolerated on an empty stomach, and thus treatment interruptions occur when loss of crops and daily income leads to missed meals.

Participants describe needing timely, granular and integrated information on patients, services, risks and resources to keep TB care functioning and effective during disasters. Specific information needs highlighted include more location‑specific information on TB patients and vulnerable groups, as well as near‑real‑time information on health facility functionality and service availability to support adaptive planning and continuity of essential health services during emergencies. However, critical information is often fragmented across siloed, non-interoperable databases, that are not always accessible to the TB program for timely decision-making.

CONCLUSION

Climate-related disaster events disrupt TB diagnosis, treatment continuity and success, and increase transmission risk. During crises, data needs, and especially spatial granularity, rise sharply, yet existing health information systems do not provide the information that is needed. Integrating interoperable geospatial platforms within current systems can support mapping displaced patients, monitor facility functionality and accessibility, and align climate risk with TB burden. Further research is needed to define data needs across health-system levels and practical solutions within existing infrastructure.

How to cite: Bakker, M. I., Kwizera, L., Okere, N., Ifejube, O. J., Umutesi, J., Sultana, R., Latif, A., Alba, S., and Yaghmaei, N.: Resilient TB Care in the Face of Climate-related Disaster Events: Opportunities for Geospatial Solutions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15024, https://doi.org/10.5194/egusphere-egu26-15024, 2026.

EGU26-15024

Download Close

Multiple disasters that occur simultaneously or in short succession, with impacts that overlap in space and time, are referred to as multi-hazard events. Such events can create societal impacts that can be significantly worse than the sum of the individual events, due to the dynamics and interconnected nature of the disasters. Additionally, response and recovery become more complex, for instance due to depletion of financial and human resources and damaged infrastructure. Quantitative, large-scale studies that assess systematic differences between single- and multi-hazard events remain limited due to the lack of  suitable, consistent, and scalable data. There are a few studies that do provide more quantitative generalized comparisons between single and multi-hazard impacts on a large scale, using disaster impact databases like EMDAT and DESINVENTAR, but these are not able to assess the dynamic changes in impact and recovery that occur after the event. 

In this study, we use consistent Visible Infrared Imaging Radiometer Suite Nighttime Light (VIIRS NTL) daily Black Marble data as a satellite-based data proxy for disaster impact and recovery. We provide a global-scale analysis of different geological, meteorological, and hydrological hazards between 2012-2019, comparing areas affected by a single hazard to areas affected by multiple disaster events with a time lag of 14 and 28 days. The results reveal systematic differences in impact and recovery profiles between single- and multi-hazard events. These findings demonstrate the potential of satellite-based proxies for generalisable, large-scale assessments of disaster impacts and recovery dynamics, supporting policymakers, humanitarian organisations, and risk assessment studies in anticipating emerging challenges in a future where increasingly frequent and intense hazards increase the likelihood of consecutive disasters.

How to cite: Buijs, S. L., de Ruiter, M., Hu, Y., Yamazaki, D., and Ward, P.: Multi-hazard impacts and recovery: A global assessment using Nighttime Light Satellite Data , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1068, https://doi.org/10.5194/egusphere-egu26-1068, 2026.

EGU26-1068

Download Close

How to cite: Chen, X., Juvakoski, A., and Varis, O.: A continental analysis on water-related risks in Africa , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17865, https://doi.org/10.5194/egusphere-egu26-17865, 2026.

EGU26-17865

Download Close

Coastal waterfronts are among the most dynamic and vulnerable parts of the urban fabric, concentrating population, economic activity, critical infrastructure and cultural heritage at the land-sea interface. These areas are increasingly exposed to interacting climate hazards and cascading impacts, demanding a shift from single-hazard assessments to a multi-risk perspective consistent with recent IPCC guidance. Here we present a methodology to identify and compare “Urban Climate Risk Archetypes” across the waterfronts of 31 major European coastal cities, providing an evidence base to support risk-informed adaptation planning.

We discretize the coastal urban zone using a 25×25 m grid within a 300 m coastal buffer to capture fine-scale spatial heterogeneity. Risk is assessed through a compound framework that integrates hazard intensity, exposure, and vulnerability across seven interrelated hazards: coastal flooding, heatwaves, wildfires, drought, extreme precipitation, sea-surface temperature anomalies, and extreme winds. This approach explicitly takes into account the interactions of climate hazards and compound events within risk. Exposure is quantified using economic, physical, demographic, and territorial indicators, while vulnerability is represented through human, infrastructural, and ecosystem fragility profiles, incorporating variables such as age structure, access to health services and income-related sensitivity.

To handle high-dimensional, multi-hazard information and enable cross-city comparability, we apply a hybrid unsupervised learning workflow to derive recurrent risk patterns within 14 land-use groups. The resulting clusters define “risk archetypes” that transcend geography, revealing how comparable waterfront configurations (e.g., industrial port areas versus residential areas or existing marinas) can exhibit similar multi-risk signatures across different European regions. Archetypes are evaluated for present conditions using historical data and for future climates using projections for 2050-2070 and 2080-2100 under SSP2-4.5 and SSP5-8.5.

The archetype framework supports decision-making by (i) highlighting hotspots where multiple hazards co-locate with high exposure and vulnerability, (ii) enabling transfer of adaptation lessons between cities with similar risk profiles, and (iii) clarifying synergies and trade-offs among measures across land-use contexts. Overall, the approach offers a scalable pathway from multi-risk diagnosis to targeted adaptation strategies that strengthen urban waterfront resilience under compound and cascading extremes.

How to cite: Milla-Torres, A. J., Lopez Lara, J., Lucio Fernández, D., and Losada Rodríguez, I. J.: Urban Climate Risk Archetypes: A Multi-Hazard Assessment of European Waterfronts, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17297, https://doi.org/10.5194/egusphere-egu26-17297, 2026.

EGU26-17297

Download Close

Effective risk management in multi-hazard contexts represents a key focus of the Italian RETURN project (Multi-risk science for resilient communities under a changing climate). Within this framework, a Multi-Criteria Decision Analysis (MCDA) approach has been developed to support the prioritization of risk reduction strategies. The proposed framework integrates three complementary dimensions of the problem at stake: (i) the optimization of risk reduction in complex multi-hazard settings, accounting for all relevant dimensions of risk (i.e., impacts on individual well-being, the built environment, public services, the natural environment, communities, business activities, and the financial system); (ii) the assessment of the economic, social, and environmental sustainability of proposed actions under current and future climate change conditions; and (iii) the systematic integration of stakeholders’ values, preferences, and objectives into the decision-making process. To achieve these goals, the framework combines multiple methodologies, including multi-hazard impact modelling for the definition of ex-ante and ex-post risk scenarios, expert-based assessments to evaluate long-term sustainability, and participatory processes to ensure effective stakeholder engagement. The MCDA framework provides a valuable decision-support tool for informed, transparent, and inclusive decision-making, aligned with efforts to enhance community resilience and sustainability, and is particularly relevant for policymakers, practitioners, and civil protection agencies.

How to cite: Molinari, D., Asaridis, P., Balingit, A., Boni, M. P., Cetara, L., Fontanella Pisa, P., Fraschini, F., Gallazzi, A., Muratori, S., Ongaro, M., Ottonelli, D., Padovan, G., Romagnoli, F., and Vigotti, F.: Prioritization of risk reduction strategies by multi-criteria decision analysis: a multi-hazard approach, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5833, https://doi.org/10.5194/egusphere-egu26-5833, 2026.

EGU26-5833

Download Close

Climate change is driving wildfires to higher elevations, yet the hazard cascades that follow the burning of pristine tropical mountain ecosystems remain largely unexplored. We present an integrated multi-hazard risk assessment methodology combining quantitative remote sensing with qualitative humanitarian and community data, addressing the challenge of characterising cascading hazards in data-scarce mountain environments. Here, we apply this approach to analyse the long-term cascade following a February 2012 wildfire that burned 31 km² of forest and wetland in Uganda's Rwenzori Mountains National Park. We document ten major floods since 2012, including two debris floods in 2013 and 2020 that affected 200,000 people requiring large-scale humanitarian responses. Post-fire increases in erosion and mass movement have widened the River Nyamwamba sevenfold since 2012, breaching copper-cobalt mine tailings and mobilising an estimated 744,000 tonnes of waste into the river resulting in widespread pollution of the river and floodplains. Slow vegetation recovery at high altitudes and positive feedbacks between hazards have prolonged this high-risk state, demonstrating how hazard interactions compound to sustain elevated risk beyond typical post-fire recovery periods.

This study demonstrates how the characterisation of multi-hazard cascades and their interactions enable identification of management entry points in resource-constrained settings. However, challenges remain in multi-hazard risk management across spatial and temporal scales; montane environments globally, especially those without a history of fire, suffer from inadequate monitoring infrastructure and limited understanding of post-fire hazard interactions. The intensity and persistence of the Rwenzori hazard cascade highlights how wildfires in mature, fire-sensitive mountain ecosystems can impose long-lasting risks on downstream communities. We recommend that post-fire risk assessments be triggered at lower thresholds of burn area and severity when fires occur in fire-sensitive mountain ecosystems, and that investment in long-term monitoring be prioritized to capture the full temporal evolution of hazard cascades.

How to cite: Day, M., Veness, W., Ross, A., Bamutaze, Y., Han, J., Mulangwa, D., Mwesigwa, A., Ntale, E., Tindimugaya, C., Guma, B., Stephens, E., and Buytaert, W.: The multi-decadal hazard cascade of a tropical mountain wildfire, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21635, https://doi.org/10.5194/egusphere-egu26-21635, 2026.

EGU26-21635

Download Close

Climate Risk Assessment (CRA) consists of four components based on the IPCC framework: (a) hazard, (b) exposure, (c) vulnerability, and (d) response/adaptation. Such assessment is essential not only to understand how each hydroclimatic hazard can have an impact on urban areas, but also to develop climate adaptation strategies. 

Although a wide range of  tools for  CRA have been developed, several challenges  limit their consistent application in the urban environment. First, a typical urban area can be exposed to multiple natural hazards, which requires a framework to assess multi-hazard multi-risk impacts. Furthermore, characteristics of hydroclimatic hazards (e.g., magnitude and spatio-temporal variations) can alter due to climate changes. Finally, future projections are scenario-based, which inevitably introduces uncertainty in CRA. 

In this context, CLIMAAX presents a comprehensive CRA toolbox including a series of practical workflows in terms of Python scripts, each focusing on a specific climate hazard. Together, the workflows enable consistent multi-hazard assessments. The hazards considered in the CLIMAAX toolbox include river and coastal flooding, heavy rainfall, urban heatwaves, relative and agriculture droughts, wildfire, heavy snowfall and blizzards, and windstorm. The toolbox is available for implementation to any European region, but it can be extended  to other regions with minor modifications to input data. To select climate projections, the CLIMAAX toolbox provides a workflow assessing bias and uncertainty of climate models/scenarios for any region in Europe. Using the CRA outputs, the toolbox supports key risk assessments that account for severity, urgency and capacity, enabling the integration of risk responses as the final step of CRA.

This study has a twofold aim. First, it attempts to showcase applications of three CLIMAAX workflows, including river flooding, heavy rainfall, and coastal flooding, to the city of Genoa, Italy. Genoa’s river networks have experienced multiple flood events, like the ones in November 2011 and October 2014. Furthermore, the city is also affected by intense rainfall, as shown by the heavy precipitation event in November 2025, which caused flash flooding and street inundation. Moreover, coastal flooding represents an additional hazard, with  the October 2018 event impacting beaches and coastal infrastructure. Based on the CRA results, river flooding was identified with the highest risk priority in Genova.  

Second, flooding hazard-specific risk outputs were translated into a spatially-explicit data-driven assessment of public-private adaptation infrastructure options at the city scale. Building on the CLIMAAX workflows, neighborhood-scale risk layers were mapped for pluvial flooding from heavy rainfall, fluvial flooding along Genoa’s river network, and coastal flooding to study adaptation options targeting different risk components. For a set of these options, alternative deployment strategies were explored, and avoided impacts alongside capital expenditures and operation and maintenance costs were quantified. This enables sub-city cost-benefit comparison of individual and combined infrastructures that best align with severity, urgency and capacity constraints, producing a basis for prioritizing adaptation pathways across Genoa’s neighborhoods.
Acknowledgement: This research work was carried out as part of the CLIMAAX project with funding received from the European Union’s Horizon Europe – the Framework Programme for Research and Innovation (2021-2027) under grant agreement No. 101093864.

How to cite: Niazkar, M., Ferrari, L., Aboudrar-Meda, A., Falchetta, G., and Mysiak, J.: Climate Risk Assessment and Adaptation Options Assessment: Application of CLIMAAX toolbox for Genoa, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19793, https://doi.org/10.5194/egusphere-egu26-19793, 2026.

EGU26-19793

Download Close

Multi-hazard disturbance regimes shape ecosystems and long-term societal responses to risk, yet they are rarely captured in global classifications. We introduce hazomes, a description of terrestrial multi-hazard disturbance regimes based on open-source intensity and return period data for eight major hazard types. Hazomes characterizes the long-term hazard environments under which ecosystems and societies have recently evolved, providing a regime-scale perspective relevant to disaster risk reduction and climate change adaptation.

Using two complexity–diversity metrics, we show that hazomes capture patterns of disturbance complexity that are not represented by climate zones or biomes. We further demonstrate that geographically distant regions, including cities, can share the same hazome, indicating similar disturbance histories. Such hazard disturbance analogues offer opportunities to study convergent ecological adaptation and cultural learning, and to support cross-regional transfer of adaptation and risk management strategies.

By shifting the focus from individual events to long-term disturbance regimes, the hazomes framework complements existing multi-hazard assessments and supports regime-oriented analyses of resilience under climate change.

How to cite: Kropf, C. M., Hülsen, S., Stalhandske, Z., Hantson, S., Ward, P. J., Wens, M. L. K., Peleg, N., Bresch, D. N., and Steinmann, C. B.: Hazomes beyond climate zones: global multi-hazard disturbance regimes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2787, https://doi.org/10.5194/egusphere-egu26-2787, 2026.

EGU26-2787

Download Close

India’s increasing exposure to hydro-meteorological hazards under climate change calls for integrated, large-scale risk assessment methods that surpass traditional single-hazard frameworks. This study introduces a pioneering composite multi-hazard index for India at pixel and administrative levels, utilizing a multi-hazard susceptibility mapping framework with a CNN U-Net-based deep learning architecture. This framework captures spatial vulnerability patterns for four critical hydro-meteorological hazards: floods, droughts, heatwaves, and cyclones. The framework exploits the capability of deep learning to extract complex spatial relationships from diverse geospatial datasets, including digital elevation models and their derivatives (e.g. slope, curvature), climatological variables (e.g. temperature, rainfall, solar radiation), hydrological parameters (e.g. groundwater storage, TWI, soil moisture), and land cover classifications, enabling a high-resolution (90 metres) pixel-level hazard susceptibility prediction across India’s diverse physiographic landscapes. The hazard inventory data used for model training and validation were systematically compiled from reliable global and national primary and secondary datasets available in the public domain. Susceptibility mapping exhibited strong predictive accuracy, surpassing 90% across various hazard types. The maps effectively identify high-risk zones within river basins, coastal regions, and interior areas, demonstrating the robustness of the deep learning framework for nationwide assessments. Flood susceptibility is prominent in the Indo-Gangetic Plain, the Western regions, Northeast, and parts of the Eastern Ghats, while heatwaves are concentrated in the Indo-Gangetic Plains and the central Indian plateau. Regions such as the Indo-Gangetic Plain, Eastern Ghats, and Eastern Coast are particularly susceptible to multiple hazards, underscoring their significance for multi-hazard disaster risk management and climate adaptation strategies. The methodology demonstrates the scalability and operational feasibility of using deep learning for multi-hazard assessment, effectively capturing spatial patterns. It offers a transferable framework adaptable to regions facing complex climate-driven hazards, which can heighten overall risk through combined impacts. The multi-hazard index enables comparison of hazard exposure and vulnerability across regions, supporting multi-risk spatial planning, disaster preparedness, and climate adaptation at various governmental levels.

How to cite: Rachit, R., Mohanty, M. P., Pandey, A., and Gupta, A. K.: Development of a Multi-Hazard Index for India: Applying CNN U-net Deep Learning framework to major Hydro-Meteorological Extremes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6401, https://doi.org/10.5194/egusphere-egu26-6401, 2026.

EGU26-6401

Download Close

This paper develops an evidence-based database of multi-hazard interrelationships in a data-scarce context that extends beyond the primary focus on cascading and amplifying interaction mechanisms. The methodology is applied to Kerala, India. Drawing on academic literature, grey literature, and media sources, the database captures both well-documented and underreported hazards and their interactions, whether historically observed or theoretically possible. The final database contains evidence of 22 distinct hazard types across six hazard groups and 137 potential hazard interrelationships. To support interpretation, an adapted hazard interaction matrix was developed that extends existing frameworks by (i) incorporating a broader range of interaction mechanisms beyond traditional cascading and amplifying effects, and (ii) enabling representation of three-way hazard interactions, advancing beyond conventional pairwise models. Results indicate that while cascading and disposition alteration mechanisms dominate the interrelationships observed in Kerala, 26% of identified interactions arise from other mechanisms. This demonstrates that restricting analyses to a limited subset of interaction types does not fully capture the region’s multi-hazard complexity. The matrix was further enhanced to capture seasonal variation in interaction potential throughout the year. Incorporating seasonality reveals distinct temporal windows of elevated interaction potential shaped by monsoon rainfall and temperature variability. When applying seasonal filters, the number of potential interrelationships identified was reduced by approximately 10%. This study demonstrates that interaction-focused, seasonally informed frameworks can reveal multi-hazard dynamics that may otherwise be overlooked when analysing only a subset of hazard types and interaction mechanisms.

How to cite: Desai, A., Barendrecht, M., Jalayer, F., and Taylor, F.: An extended hazard interaction matrix for analysing multi-hazard complexity in data-scarce regions: An application to Kerala, India, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14573, https://doi.org/10.5194/egusphere-egu26-14573, 2026.

EGU26-14573

Download Close

Volcanic eruptions rarely occur as isolated hazards. Instead, they produce interacting or cascading processes and, at times, interact with other non-volcanic hazards. Volcanic activity can produce hazards such as tephra fall, lava flows, or pyroclastic flows, which may trigger secondary hazards including fires, floods, and lahars. In a changing climate, eruptions may also intersect more frequently with external events such as tropical storms or wildfires, amplifying their impacts and complicating risk management. Past examples, such as the 1991 Pinatubo eruption during Typhoon Yunya, or the lava flows and tephra from the 2021 Tajogaite eruption on La Palma, show how compounding hazards can extend the impacts of eruptions far beyond the volcanic slopes and intensify damage to the built environment and agriculture. Despite these observations, the global patterns of such occurrences remain largely unquantified, and volcanic hazards are still often considered in isolation, leaving a gap in understanding the wider multi-hazard context in which eruptions occur.

In order to fill this gap and understand where volcanic multi-hazards may happen in the future, a first step is to look back at the past to identify where volcanic hazards have coincided with other hazards. In this project, we interrogate past event datasets, including the Global Volcanism Program eruption list and the MYRIAD-HESA multi-hazard event dataset, to identify global locations where hazards coincided in the past. We define a volcanic multi-hazard event as an eruption during which at least one additional volcanic or non-volcanic hazard occurs within a size-dependent radial buffer around the volcano and within the eruption time window. Events are classified by volcano type, VEI (Volcanic Explosivity Index), and length of eruption.

Hazard interactions were grouped into geophysical events, meteorological events, and climatological extremes, and preliminary results reveal that tsunamis, tropical cyclones, and heatwaves dominate interacting hazards within these categories. Multi-hazard events are most often associated with stratovolcanoes when analysed at the eruption level. To explore implications for risk and exposure, we identify areas of increasing population using GHS-POP global datasets, highlighting Southeast Asia as a key exposure hotspot of rapidly growing urban populations. This approach provides new insights into volcanic multi-hazard environments and represents a first step towards identifying where future multi-hazard events may intersect with growing exposure, informing integrated multi-hazard risk assessment.

How to cite: Meredith, E. S. and de Ruiter, M. C.: Volcanic eruptions in a multi-hazard world: a global assessment of past volcanic multi-hazard events, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3081, https://doi.org/10.5194/egusphere-egu26-3081, 2026.

EGU26-3081

Download Close

The increasing frequency and intensity of water-related hazards pose growing threats to infrastructure systems worldwide. These events often occur as compounded or consecutive hazards, amplifying the impacts and challenging existing disaster risk management (DRM). Despite progress in both structural and non-structural mitigation measures, extreme hydrologic events continue to cause severe economic, social, and environmental damage due to infrastructure failures.

Here we present the results of an international initiative aimed at identifying critical gaps in the management of water-related hazards affecting infrastructures. Specifically, we investigate the interconnections among different hazard types and assess the effectiveness of mitigation strategies. By systematically mapping past water-related hazard events and their impacts from minor impairments to complete structural failures, we assess the presence and performance of both structural (e.g., flood barriers, resilient designs) and non-structural (e.g., early warning systems, land-use planning) measures.

Drawing on case studies, we seek to determine whether successful risk mitigation practices can be effectively transferred across different geographical and socio-economic contexts. We aim to contribute to a more integrated and adaptive approach for enhancing infrastructure resilience, combining engineering solutions, governance strategies, community engagement, and climate adaptation measures.

How to cite: Ridolfi, E., Moccia, B., de Ruiter, M. C., Sakic Trogrlic, R., Kreibich, H., Micheli, L., Ascani, A., and Alessi, R. and the Water-related hazard impacts on infrastructure and mitigation case studies Research Team: Water-related hazards and infrastructure failures: insights from a global assessment of risk mitigation practices, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7263, https://doi.org/10.5194/egusphere-egu26-7263, 2026.

EGU26-7263

Download Close

Transport systems cover vast areas across diverse terrains and climates. As an example of critical infrastructure, they are essential for economic and social connectivity worldwide. However, this extensive spatial reach also makes them highly vulnerable to a wide range of geohazards. Among these, landslides and flooding triggered by extreme precipitation or seismic activity pose serious risks to road networks, particularly when they occur as cascading or compound events. Road networks are highly interconnected and therefore susceptible to cascading failure; when a single link is disrupted, traffic redistributes across adjacent routes, generating congestion that propagates through the wider system and reduces overall network performance.

In response to these challenges, we present a modular multi hazard risk assessment framework that combines hazard simulation with transport network modelling to evaluate the effects of interacting geohazards on transport infrastructure. Landslide susceptibility is assessed using a slope stability analysis based on the infinite slope model and factor of safety under both precipitation driven and seismic loading conditions. The Synxflow modelling package is then applied to simulate shallow landslide runout and flood inundation. These outputs are then integrated within a GIS environment to produce composite hazard layers, which are translated into road passability classifications using depth and velocity thresholds tailored to different vehicle categories.

To assess how these hazards affect movement across the network, we apply a transport modelling framework, which enables the simulation of vehicle movement under conditions where road links are partially or entirely blocked by landslides or flooding. Our work offers a practical tool to capture delays, diversions, and loss of accessibility caused by multi-hazard events.

How to cite: Doley, R., Xia, X., Ferranti, E., and Quinn, A.: An integrated multi hazard risk framework for modelling transport system disruption from landslide and flood events, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14915, https://doi.org/10.5194/egusphere-egu26-14915, 2026.

EGU26-14915

Download Close

This presentation introduces a database of household-level preparedness advice prescribed for 19 natural hazards, synthesised from authoritative sources. While preparedness is often assumed to be hazard-agnostic, we demonstrate that although many actions are effective across multiple hazards, some forms of preparedness may increase vulnerability or exposure to other hazards. These actions are termed asynergistic.

The database is structured around 19 broad hazard types (e.g. earthquake, flood) and six overarching preparedness themes relevant at the household scale (e.g. household knowledge of past events, household subsistence). Within these themes, we identify 38 specific preparedness categories, such as structural design and food and water subsistence. Drawing on our recent review of the household preparedness literature, the database adopts a broad and inclusive interpretation of preparedness (e.g. accounting for gendered practices) and is designed to be applicable to majority-world, low-income contexts.

Preparedness actions were compiled from key sources that households commonly consult, including government guidance and International and Regional Red Cross and Red Crescent Societies (acknowledging that the review was not exhaustive). This resulted in a database of more than 490 recommended preparedness actions across the 19 hazards (including duplication across hazards).

We find that many actions are shared across multiple hazards and can be considered synergistic (e.g. maintaining a three-day supply of food and water). Many actions are also not mutually exclusive, such as vegetation management and maintaining access to emergency cash, subject to time and resource constraints. However, a subset of actions are asynergistic, whereby preparation for one hazard may increase vulnerability to others, particularly when hazards occur simultaneously or in sequence. For example, sealing windows and doors to protect against gas-based hazards (e.g. volcanic eruptions, wildfires) may impede evacuation during an earthquake. We also identify more subtle tensions in seemingly synergistic actions, such as storing subsistence items upstairs to reduce flood damage, which may increase losses during wind-related hazards.

We argue that this database can support the development of more nuanced, locally tailored preparedness advice when used alongside multi-hazard risk registers. More broadly, this work provides an evidence base that challenges assumptions of hazard-agnostic preparedness and highlights the need to explicitly consider synergies and asynergies in household risk reduction.

How to cite: Taylor, F., Gill, J., Thompson, H., McGowran, P., Gilmour, M., and Nicklebur, J. M.: Household preparedness is not ‘hazard agnostic’: a review of key preparedness advice from a multi-hazard perspective , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3110, https://doi.org/10.5194/egusphere-egu26-3110, 2026.

EGU26-3110

Download Close

Past events demonstrate that multi-hazard situations can lead to amplified impacts when single hazards interact. Such interrelations are often constrained within clear temporal or spatial boundaries and can be interpreted from a systemic perspective. For example, impact-chain approaches can be used to map and interrelate triggering hazards, secondary processes, and exposed elements including respective vulnerabilities. Analysing historical events therefore provides valuable insight into plausible hazard interrelations and experienced consequences relevant for present and future risk assessments.

Transferring this systemic understanding from site-specific event-based analyses to an extended spatial scale, however, remains challenging. Scale-dependent generalisation can lead to a loss of process detail, while the quantification of hazard interrelations is often based on hypothetical yet plausible scenarios rather than deterministic forecasts. In this context, the aim is not to predict specific events and respective consequences, but rather to explore potential outcomes under defined hazard interrelation assumptions.

Here, a stepwise multi-hazard risk assessment framework is applied, progressing from (i) identification of relevant hazards and their spatial and temporal interrelations, to (ii) the evaluation of exposed elements and their vulnerability, and finally (iii) the derivation of a multi-hazard risk index. The framework is applied to the transalpine Brenner Corridor between Innsbruck and Bolzano, a key European transport axis. Snow avalanches, debris flows, and river floods are combined in an interrelation-aware manner to account for co-occurrence, pre-conditioning, and trigger-related effects. Historical event analysis along the corridor indicates that debris flows dominate hazard occurrence during summer months and generally don’t interfere with motorway infrastructure, but with the federal and local roads instead.

The exposed transport infrastructure is analysed using an OpenStreetMap-based road network dataset, which is restructured into road classes including motorway, secondary, residential and unclassified roads. Functional vulnerability indices are derived to reflect differences between road segments, including structural characteristics, network redundancy, and traffic-related exposure. To capture variability in exposure, minimum, average, and maximum traffic scenarios are considered for motorway and federal road segments. The results highlight how accounting for hazard interrelations and traffic-dependent exposure alters the spatial risk index for road segments, underlining the importance of interrelation-aware multi-hazard risk assessments for critical alpine infrastructure.

How to cite: Wenzel, T., Marr, P., Höfler, F., Pantaleoni Reluy, N., and Glade, T.: Scenario based assessment of interrelating multi-hazards affecting the Brenner Corridor’s road infrastructure, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19992, https://doi.org/10.5194/egusphere-egu26-19992, 2026.

EGU26-19992

Download Close

Heatwaves and coldwaves pose a major threat to human lives, infrastructure, and economic sectors globally. Implementing effective management measures and improving public safety in the face of these hazards requires precise knowledge of the spatial distribution of vulnerability.

This study primarily aims to identify the key socio-economic vulnerability indicators for each of these two climate hazards. It then develops vulnerability models for Morocco by combining available census data with population mapping to generate indicators at the finest possible spatial resolution.

The results of this approach highlight the spatial distribution of both types of vulnerability and identify the most exposed regions in Morocco. This work thus serves as a strategic decision-making tool to target critical areas and enhance disaster prevention

How to cite: Essoussi, S., EL morjani, Z. E. A., and Sadiq, A.: Spatial Distribution of Socio-Economic Vulnerability to Heat and Cold Waves in Morocco, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1112, https://doi.org/10.5194/egusphere-egu26-1112, 2026.

EGU26-1112

Download Close

Building on insights from the MYRIAD-EU project, which ran from 2021-2025, we reflect on the advances and challenges made in terms of moving towards a more holistic approach to disaster risk management, in which a multi-(hazard-)risk approach is central. We synthesise advances made in terms of definitions, frameworks, data, tools, and applications, and reflect on how knowledge was co-produced within the project. Based on our experiences, we outline several avenues for continued scientific research: continue the mainstreaming and mutual understanding of concepts and definitions; continue developing a strong evidence base of how multi-(hazard-)risk both shapes, and is shaped by, risk dynamics over space and time; further developing methods for providing both current and future multi-(hazard-)risk scenarios; increasing the availability of appropriate, solutions-oriented, usable tools; more explicitly including equity issues and equitable disaster risk reduction and adaptation; continue extensively testing and coproducing multi-(hazard-)risk knowledge in in-depth case studies; supporting the development of Multi-Hazard Early Warning Systems; and strengthening opportunities for Early Career Researcher leadership and empowerment within project structures.

How to cite: Ward, P. and the MYRIAD-EU synthesis team: Reducing Risk Together: moving towards a more holistic approach to multi-(hazard-)risk assessment and management, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1868, https://doi.org/10.5194/egusphere-egu26-1868, 2026.

EGU26-1868

Download Close

The frequency and impact of natural hazards are increasing globally, driven by factors such as population growth, urbanization, and the effects of climate change. Canada is no exception, as the country is warming at twice the global rate. As the second largest nation in the world, Canada faces a diverse array of natural hazards. However, floods, wildfires, landslides and extreme rainfall are the most prevalent and impactful events affecting communities across the country.

Severe weather further increases the probability of multiple hazards occurring, especially in areas of Canada that are already vulnerable. There are many aspects in characterizing how existing hazard interrelationships emerge, through compounding, cascading or triggering means, and limited data to capture this. The complexity of these interactions stem from the different metrics and data representations required to capture each single natural hazard. Although natural hazards, their related climate conditions, and underlying mechanisms have been studied, there is limited documentation regarding the characterization of multi-hazard events at the national scale. This gap may result in the exclusion of multi-hazard risks from risk assessments, potentially leading to inaccurate evaluations of associated risks.

Our study reviews public datasets of natural hazards in Canada, to layer the occurrence and localizations of hazards to expand on data repositories for multi-hazard study use. The analysis highlights current gaps in available data and the limitations still facing multi-hazard research such as categorizing hazard type combinations based on incomplete or biased records and defining spatial and temporal patterns. Analysis underscores the occurrence of cascading multi-hazard events across Canada, particularly landslides triggered by other natural processes such as extreme rainfall. Comparing datasets helps quantify and characterize limitations and provides a baseline for better understanding the climate conditions and mechanisms of multi-hazards in Canada. 

How to cite: Hoyos, S. and Goetz, J.: Data Limitations and Opportunities in Canadian Multi-Hazard Research, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8503, https://doi.org/10.5194/egusphere-egu26-8503, 2026.

EGU26-8503

Download Close

Compound disasters refer to situations in which a primary hazard directly or indirectly triggers secondary hazards, forming a chain of interconnected disaster processes. With the intensification of global warming in recent years, extreme weather events have become increasingly frequent, thereby increasing the likelihood of compound disaster occurrence. Against this background, this study aims to integrate the failure probabilities of multiple hazards under future climate scenarios using a reliability-based approach and to propose indicators applicable to compound disaster assessment.

The climate data used in this study are obtained from the Taiwan Climate Change Projection Information and Adaptation Knowledge Platform (TCCIP), which provides statistically downscaled CMIP6 simulation outputs sourced from the Earth System Grid Federation (ESGF). Analyses are conducted for three future periods, namely the near future (2021–2040), mid-term future (2041–2060), and far future (2080–2100), based on which future scenario rainfall events are generated.

Taking Jinshan District, New Taipei City, Taiwan, as a case study, this research evaluates the risks associated with different hazard types under future climate scenarios. The failure probabilities of individual hazards are subsequently integrated through reliability analysis to identify areas prone to compound disasters. The results are expected to provide a scientific basis for disaster prevention planning and risk governance by relevant authorities.

How to cite: Lin, P. and Liao, K.: Compound Disaster Risk Analysis under Future SSP Scenarios, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9364, https://doi.org/10.5194/egusphere-egu26-9364, 2026.

EGU26-9364

Download Close

Extreme hydrometeorological events (EHEs) represent a growing challenge for central-northeastern Argentina, where climatic variability interacts with structural socio-economic inequalities to shape spatially differentiated patterns of vulnerability and risk. This study develops a subnational‑scale assessment that integrates physical hazard indicators with socio-economic, demographic, and environmental variables to evaluate vulnerability and multi-hazard risk to EHEs at both long-term and short-term timescales.

Risk is evaluated at the subnational scale for 1991–2020 as the interaction between EHE hazards and regional vulnerability. Hazards are derived from ERA5 reanalysis data and examined both individually—distinguishing long-term hazards such as prolonged water excesses and deficits, and short-term hazards including heatwaves, intense precipitation, and flash droughts—and jointly through multi-hazard indices. Individual EHE hazards are evaluated based on their frequency, duration, and intensity. Vulnerability is conceptualized through exposure, sensitivity, and adaptive capacity, using census and geospatial information provided by national agencies. Exposure reflects the spatial overlap between population, crop yields, and critical infrastructure. Sensitivity captures demographic and socioeconomic fragility, as well as environmental susceptibility. Adaptive capacity encompasses healthcare, technological, and educational resources. Individual and multi-hazard risks are then computed by integrating standardized hazard indices with the vulnerability index.

The region exhibits an overall medium level of vulnerability, but with significant spatial contrasts. Central Argentina—including part of the country’s core crop region, where population and economic activity are concentrated—shows medium‑to‑low vulnerability, driven by high exposure yet moderated by low sensitivity and high adaptive capacity. In contrast, central‑northern Argentina—characterized by limited agro‑industrial and technological development—exhibits high vulnerability due to elevated sensitivity and restricted adaptive capacity, despite comparatively lower exposure levels. These patterns reflect broader regional socio‑environmental inequalities, where structural deficits intensify climate impacts. Regarding EHE hazard risks in the study region, heatwaves and long-term extreme precipitation deficits emerge as the highest-ranking risks both locally and regionally, coinciding with elevated hazard levels in the northern and northwestern areas, where vulnerability is likewise greatest. Although the eastern and northeastern areas exhibit the highest hazard levels for intense precipitation and long-term precipitation excesses, the associated risk is moderated by their medium vulnerability. Flash drought risk remains low and spatially restricted. Multi-hazard analysis reveals that the long-term combined risk is the highest and most widespread, whereas the short-term multi-hazard risk is more localized but strongly dominated by heatwaves.

This study provides an integrated framework for understanding subnational vulnerability and multi-hazard risk to EHEs in Argentina. The results show that the socio-environmental conditions act as amplifiers or attenuators of EHE hazards, shaping the resulting risk across the region. Moreover, the dominance of long-term multi-hazard risk indicates that prolonged climatic stresses can intensify the impacts of short-term extremes. These findings underscore the need for differentiated adaptation strategies: reducing exposure in the south through improved land‑use planning, infrastructure development, and climate‑resilient agricultural management, and strengthening adaptive capacity in the north through investments in health, education, and institutional systems. Despite limitations related to data availability and indicator selection, the results offer actionable insights for territorial planning and climate adaptation.

How to cite: Pierrestegui, M. J., Lovino, M. A., Masaro, L., and Müller, G. V.: Assessing subnational vulnerability and multi-hazard risk to extreme hydrometeorological events in Central-Northeastern Argentina, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12896, https://doi.org/10.5194/egusphere-egu26-12896, 2026.

EGU26-12896

Download Close

The risk-informed decision-making relies on the risk assessment results for reducing and managing the disaster risk. The general structure of decision models for risk-informed decision-making is based on measuring disaster risk across various decision scenarios. The disaster risk measurements are integrating the estimated exposure and disaster impacts with probabilistic assessments of natural hazards’ occurrence and co-occurrence. As such, it is crucial to estimate the impact of disaster under different conditions. The estimation of disaster impact should take into account the dynamic changes of the risk drivers (including the variables that can be affected by disaster risk management, DRM, strategies) as well as the decision criteria that decision makers can use to reduce and manage disaster risk. In other words, the disaster impact needs to be forecasted over time while considering the risk factors under different DRM strategies. In addition to physical characteristics, some of the disaster risk factors are socioeconomic variables (e.g., national and sub-national gross income, population density, etc.), which have their own dynamics over time. Once the causal effects of these variables on the disaster impact are determined, they can be included in the disaster impact forecasting models. This study presents a forecast framework for short-term disaster impact and its connection to different decision models for risk-informed decision-making. The theoretical disaster impact forecasting framework is used to investigate the role of socioeconomic variables in forecasting the impact of earthquakes and tsunamis in India. The results show the statistical significance of the variables in the human development index (HDI) as well as the subnational vulnerability index, SGVI, (published by Global Data Lab, GDL). These results show the predictive causality of socioeconomic factors and provide a platform for tracking the cascading impacts and sequential decision-making.

How to cite: Yeganegi, M. R. and Rovenskaya, E.: Disaster impact forecasting for risk-informed decision making with socioeconomic indices: evidence from earthquake-tsunami in India, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21655, https://doi.org/10.5194/egusphere-egu26-21655, 2026.

EGU26-21655

Download Close

Traditional approaches to impact assessment for weather-related hazards focus upon the direct impacts from those hazards, such as those due to physical contact with floodwaters. Examples include loss of life or injury due to drowning or accidents during flooding, or damage to buildings and infrastructure. Indirect impacts from flooding occur outside the inundated area, often as a result of disruption caused by direct impacts. Examples of indirect impacts include economic losses from business interruptions, reduced productivity, and repair costs, health impacts such as outbreaks of waterborne diseases or mental health issues, supply chain disruptions, affecting food, fuel, and essential goods. 

Impact-based forecasting and warning systems typically only assess direct impacts, however extreme weather events can affect far more people and assets than those directly exposed to the hazard.  

Building on a traditional assessment of direct impacts of the flood hazard, an assessment for India of the indirect impacts was carried out following a method developed for Denmark, by Prall et al. (2024). Hazard data was collected from the Copernicus fluvial flood maps. Exposure was calculated using WorldPop population datasets. Vulnerability was determined using the Indian 2011 census. Indirect impacts were calculated using data on critical infrastructure and applying an estimate of the impacted population. Assessments assume that impacts to critical infrastructure are weighted evenly, although the method allows for specific weightings to be applied.

Using 2011 census data, we determined social flood risk, where this reflects the potential adverse impact of flooding on people and communities, based on the interaction between flood hazard and social vulnerability. Social flood risk includes indicators that increase resilience (e.g. literacy, neighbourhood social capital) and those indicators that decrease resilience (e.g. age, wealth, disability, language). Social flood risk was then applied at the resolution of the Copernicus flood map grid cells (100 metres) and then aggregated to a district level.

The assessment of direct and indirect risks, together with the social flood risk, allows disaster risk reduction experts and practitioners to better understand more fully the populations and assets exposed to extreme weather events as well providing valuable insights into population resilience.

Our research has shown how a national scale assessment of direct and indirect impacts can be developed for India. Ultimately, such methods could be used as part of operational impact-based forecasting and warning systems, to more accurately predict the wider impacts, and thus improve preparedness and response to weather-related hazards.

This work builds on international collaboration through the Weather and Climate Science for Service Partnership (WCSSP) India programme, a UK–India programme advancing impact-based forecasting for high-impact weather in multi-risk and cascading hazard contexts.

How to cite: Body, R., Terlinden-Ruhl, L., Brown, E., Lumbroso, D., Lanyon, J., and Rao Kolusu, S.: A national scale assessment of direct and indirect flood impacts and social flood risk in India , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13205, https://doi.org/10.5194/egusphere-egu26-13205, 2026.

EGU26-13205

Download Close