Heat extremes, are already one of the deadliest meteorological events and they are projected to increase in intensity and frequency due to rising CO2 concentrations. The resulting risks of extreme temperature events to society may increase dramatically with large regional differences, and society will need to adapt locally if the worst impacts are to be avoided.
This session therefore welcomes a broad range of new research addressing the challenge of extreme heat and its impacts, with studies focusing on the Global South particularly welcome. Suitable contributions may: (i) assess definitions, the drivers and underlying processes of extreme heat in observations and/or models; ; (ii) assessing vulnerability and exposure to extreme heat associated with diverse socio-economic impacts (iii) address forecasting and monitoring of extreme heat at seasonal to sub-seasonal time scales; (iv) focus on societal response and adaptation to extreme heat, including the implementation of anticipatory action, heat-health early warning systems, and effective heat adaptation and management solutions; (v) introduce transdisciplinary research frameworks for assessing societal relevant heat extremes and complex and compounding heat-related impacts on human health, economic productivity, and the environment.

With global climate change affecting the frequency and severity of extreme meteorological and hydrological events, it is particularly necessary to develop models and methodologies for a better understanding and forecasting of present-day weather induced hazards. Future changes in the event characteristics as well as changes in vulnerability and exposure are among the further factors for determining risks for infrastructure and society, and for the development of suitable adaptation measures. This session considers extreme events that lead to disastrous hazards induced by severe weather and climate change. These can, e.g., be tropical or extratropical rain- and wind-storms, hail, tornadoes or lightning events, but also (toxic) floods, long-lasting periods of drought, periods of extremely high or of extremely low temperatures, etc. Papers are sought which contribute to the understanding of their occurrence (conditions and meteorological development), to the augmentation of risks and impacts due to specific sequences of extremes, for example droughts, heavy rainfall and floods, to assessment of their risk (economic losses, infrastructural damages, human fatalities, pollution), and their future changes, to studies of recent extreme events, to the ability of models to reproduce them and methods to forecast them or produce early warnings (in line with the “Early Warnings for All” initiative, launched in March 2023 by the United Nations and the World Meteorological Organization), to proactive planning focusing on damage prevention and damage reduction. In order to understand fundamental processes, papers are also encouraged that look at complex extreme events produced by combinations or sequences of factors that are not extreme by themselves. The session serves as a forum for the interdisciplinary exchange of research approaches and results, involving meteorology, hydrology, environmental effects, hazard management and applications like insurance issues.

Worldwide, frequency and intensity of extreme floods are increasing, causing direct consequences in terms of loss of life and properties. Cutting-edge monitoring and simulation technologies have become instrumental for guiding flood risk management. A range of physical/conceptual hydrological and hydrodynamic models and data-driven models (e.g., Artificial Intelligence, which includes Machine Learning) with their associated uncertainties are available to inform flood risk assessment and management, including prevention and preparedness. Such techniques provide a platform for the scientific community to explore the drivers of flood risk and to build up effective approaches for flood risk mitigation.
The objective of this session is to bring together experts, researchers, and practitioners to present and discuss recent developments in the field of flood inundation mapping, flood hazard mapping, risk assessment, and flood risk management. Topics such as 1D, 2D and 3D modelling for flood risk assessment, emergency action planning, dam & levees break analysis , different flooding scenarios with (structural and non-structural) defences and without them, their associated uncertainties and sensitivity analysis and flood impact analysis at all stages are also welcome.
Invited Speaker:
Prof. Bruce Malamud, Department of Geography, Durham University, UK (https://www.durham.ac.uk/staff/bruce-malamud/)

As our climate system climbs through its current warming path, temperature and precipitation are greatly affected also in their extremes. There is a general concern that climate change may also affect the magnitude and frequency of river floods and, as a consequence, that existing and planned hydraulic structures and flood defences may fail to provide the required protection level in the future. While a wide body of literature on the detection of flood changes is available, the identification of their underlying causes (i.e. flood change attribution) is still debated.
In this session, we invite contributions on works on how floods of different kinds (e.g., fluvial, pluvial, urban, coastal, …) and their impacts on the landscape are related to climate extremes (of precipitation and temperature) and how these extremes are related to large-scale predictors (e.g. climate oscillations, teleconnections) on different spatio-temporal scales. This session invites contributions on (but not limited to) the following questions:
- What are the large-scale predictors of climate extremes that are relevant to river floods and their change?
- What is the role of spatio-temporal scales when mapping climate to flood extremes?
- How are changes in mountain climate affecting downstream floods?
- How do changes in thunderstorms and convective precipitation alter flood risk associated with river floods?
- How are climate extremes and river floods of different types related to each other?
- What are the most useful methodologies for flood change attribution?
- What are the most useful datasets for flood change attribution?
Mapping climate to flood extremes is of interest from both theoretical and practical perspectives. From a theoretical point of view, a better understanding of the connection between climate extremes and floods will help to attribute flood changes to their underlying climatic drivers. From a practical point of view, the identification of climate indices relevant to flood extremes may allow to better incorporate climate projections in the assessment of flood hazard and risk, leading to a more informed selection of adaptation measures compared to what is now possible.

Climate change and socio-economic developments will further increase the risk of floods and droughts. To prepare for these challenges, societies need to step up their investments in adaptation. Cross-border cooperation on adaptation is of crucial importance, as shown by recent disasters such as the 2021 floods in Western Europe.

While hydrological systems (e.g. river basins) often cross administrative borders (federal state or national), cooperation between these different parts is often insufficient. For example, interventions or adaptation measures upstream often have negative consequences for the risk on countries and communities downstream. Moreover, early-warning systems require accurate (real-time) data from upstream areas, which can be sensitive to share (e.g. reservoir levels). Lastly, emergency response greatly benefits from international cooperation. A lack of understanding and the absence of cooperation across borders hampers the design of effective adaptation strategies and policies.

Therefore, this session aims to increase our understanding of flood and drought management in transboundary contexts, including (international) river basins, aquifers and reservoirs. We encourage research in all parts of the disaster risk reduction cycle and on different spatial scales (international, regional and local).

Topics of interest include, but are not limited to:

1) Risk analysis of floods and/or droughts in small and large (international) river basins, including upstream/downstream cost and benefit dynamics;
2) Flood and drought forecasting, early-warning, and early-action systems to improve disaster preparedness;
3) Socio-economic disaster impact studies, such as those derived from (post-) disaster surveys, to increase knowledge on people’s behavior, disaster damages, response and recovery;
4) Challenges and opportunities in governance and integrated water resources management for transboundary aquifers and river basins;
5) The implementation and effectiveness (including co-benefits) of Nature-Based Solutions.
6) Case studies of international cooperation in flood and drought management.

Lightning is the energetic manifestation of electrical breakdown in the atmosphere, occurring as a result of charge separation processes operating on micro and macro-scales, leading to strong electric fields within thunderstorms. Lightning is associated with tropical storms and severe weather, torrential rains and flash floods. It has significant effects on various atmospheric layers and drives the fair-weather electric field. It is a strong indicator of convective processes on regional and global scales, potentially associated with climate change. Lightning produces nitrogen oxides, which are a precursor to ozone production. Thunderstorms and lightning are essential parts of the Global Electrical Circuit (GEC) and control the fair weather electric field. They are also associated with the production of energetic radiation up to tens of MeV on time scales from sub-millisecond (Terrestrial Gamma-ray Flashes) to tens of seconds (gamma-ray glows).

This session seeks contributions from research in atmospheric electricity with emphasis on:

Atmospheric electricity in fair weather and the global electrical circuit
Effects of dust and volcanic ash on atmospheric electricity
Thunderstorm dynamics and microphysics
Middle atmospheric Transient Luminous Events
Energetic radiation from thunderstorms and lightning
Experimental investigations of lightning discharge physics processes
Remote sensing of lightning and related phenomena by space-based sensors
Thunderstorms, flash floods, tropical storms and severe weather
Connections between lightning, climate and atmospheric chemistry
Modeling of thunderstorms and lightning
Now-casting and forecasting of thunderstorms using machine learning and AI
Regional and global lightning detection networks
Lightning Safety and its societal effects
Planetary lightning in the solar system and beyond

Nature-based solutions and eco-engineering interventions aim to work with natural processes to mitigate increased incidence in hydrometeorological extremes due to climate change. Examples of nature-based solutions include the addition of large wood or vegetation patches, floodplain reconnection, and the creation of blue-green urban infrastructures. The aims and design strategies for these interventions build on hydrological, biogeomorphic, and geochemical processes at multiple spatial and temporal scales including ecohydraulic interactions with vegetated canopy flows and large wood, sediment transport, and feedbacks with ecologic processes. Implementation and assessment frameworks for nature-based solutions are rapidly developing, with many challenges and open questions remaining. Therefore, an improved understanding of basic process-based function of nature-based solution designs and development of modelling strategies are urgently needed to ensure intervention efficacy meet the challenge of mitigating increasing extremes in a changing climate.

This session aims to form a broad range of cross-sector scholarship, including academic researchers, water managers, community stakeholders, and independent researchers. We invite you to submit abstracts broadly related to the following topics:
• Design of resilient nature-based solutions under a changing climate (floods versus droughts)
• Frameworks to evaluate nature-based solutions
• Modelling strategies of nature-based solutions: physical and numerical
• Field investigations of nature-based solutions including remote-sensing
• Implications of nature-based solutions on flow structures and sediment transport
• Ecological impacts and ecosystem services of nature-based solutions
• Management and maintenance of nature-based solutions
• Case studies of successful nature-based solution strategies including socio-economic aspects

Volcanoes are complex systems capable to cause catastrophic impacts. Understanding, modelling and forecasting volcanic hazards is challenging because they encompass a wide range of processes from grain to flow scales, whose complexity often require a multidisciplinary approach to quantitatively model them. In fact, there is always a need for the development of robust and reliable models for forecasting volcanic hazards, both syn- and post-eruptive.
Syn-eruptive hazards include gravity-driven flows (e.g., pyroclastic density currents, rock avalanches), volcanic plumes and gas emission and dispersion, which can all be theoretically described by computational fluid dynamics, and experimentally modelled. But application of experimental and numerical modelling results to large-scale natural processes is often not straightforward due to scaling issues and simplifications of the modelled systems.
Uncertainty management is a central issue in volcanic hazard analyses and a plethora of statistical methods have attempted to quantify uncertainty in both hazard modelling and eruption forecasting. The data underlying models for both eruption occurrence and hazard propagation are multi-scale, multi-dimensional and nonlinearly correlated, and often not representative of the volcano's potential behaviour. Additional knowledge is often required to manage causal links, and to extrapolate outside of the perceived bounds of existing data.
Post-eruption, understanding the origin, transport and emplacement mechanisms of volcanic deposits is fundamental for accurately reconstructing accumulation histories of ancient and modern volcano-sedimentary records, thus helping to assess future hazards and their potential economic impacts. Many knowledge gaps in these records could be reduced by bringing together multidisciplinary specialists and methods, combining classical field-based work with novel laboratory modelling approaches.
The session aims at advancing volcanic hazard estimation and response through multidisciplinary approaches, including:
• A better description of uncertainty in volcanic hazard estimates through the use of statistical, analogue, surrogate and synthetic data,
• Field studies of volcanoclastic features in sedimentary records,
• Analysis of the short- and long-term downstream effects of volcanic events on active landscapes (landslides, lahars, re-sedimentation, flooding etc.).
• New developments in statistical, experimental and computational modelling.

The session aims to offer a multidisciplinary approach to volcanic risk management profiles, with analyses focusing on institutional issues and management organization of what can be done to prevent the event itself. It is a matter of seeking a systemic perspective that involves all the different actors in a single response, from the technical-scientific side and from institutional one.

When a volcano erupts, providing information on hazardous volcanic phenomena, their effects, and the eruption's duration is crucial. However, eruptions are complex phenomena governed by interactions of many processes, which are often nonlinear and stochastic. Numerous uncertainties in the involved parameters make precise predictions of specific events in time and space usually unattainable; that is, volcanic eruptions can be intrinsically unpredictable. Despite these limitations, significant progress has been made in forecasting volcanic hazards and, in specific circumstances, in making predictions. Improvements in forecasting are closely related to the wealth of data from enhanced monitoring techniques, such as satellite observations, and tremendous advances in computing power. This has led to the increased use of data-driven approaches, including artificial intelligence (AI) techniques, to address volcanic hazards. Machine learning, a type of AI in which computers learn from data, is gaining importance in volcanology not only for monitoring purposes (i.e., in real time) but also for hazard analysis (e.g., modeling tools). Looking to the future, AI models can be combined with physical constraints to bridge the gap between data-driven methods and physical modeling, thereby increasing the interpretability of AI predictions. This offers an alternative approach to dealing with the strongly nonlinear and time-dependent character of volcanic phenomena. Several hybrid strategies, utilizing growing computational resources, are currently being developed to achieve greater flexibility and full synergy between numerical physics-based simulations, machine learning, and data-driven approaches. This multidisciplinary session invites contributions focusing on enhancing traditional ground-based volcano monitoring systems through technological innovation in satellite remote sensing and computational methods, integrating deep-learning, data-driven approaches, and physics-based simulations, to better understand and forecast volcanic hazards.

Volcanic hazards pose significant threats to communities and environments, necessitating robust and accurate assessments to inform risk mitigation strategies. These methods are essential to capturing the complex and dynamic nature of volcanic systems, which are characterized by significant variability and uncertainty. In this regard, understanding and predicting volcanic phenomena requires a comprehensive approach that integrates observations, field measurements, and advanced modelling techniques.
This session seeks to bring together contributions that focus on the quantification of the natural variability of the volcanic activity. Contributions that propose combination of field data, novel methodologies, innovative uses of technology, and new physical and statistical modelling approaches will be particularly encouraged. By fostering discussions and sharing insights, we aim to drive forward the development of more comprehensive and integrated approaches to volcanic hazard assessment and risk mitigation.

The recent eruptions of Fukutoku-Oka-no-ba (Japan) and Hunga Tonga-Hunga Ha’apai (Tonga) volcano, which triggered a catastrophic tsunami due to the collapse of the Hunga caldera in January 2022, have shown that submarine volcanoes cannot only pose a serious threat to the population and infrastructure of the coastal areas in their immediate neighborhood but also a high potential risk to regions far away from the source. Submarine volcanoes located in shallow waters may also inject significant amount of volcanic ash and gases in the atmosphere. However, the operational monitoring of submarine volcanoes remains a challenge because of the lack of systematic in-situ measurements, such as water sampling for physio-chemical parameters (e.g., turbidity, sea surface temperature, chemical composition, salinity). Moreover, although permanent arrays (e.g., seismic networks) can provide continuous information on the volcanic processes in the deep ocean, they are generally located at regional distances from the sub-marine volcanoes. An effective and continuous monitoring of underwater volcanic activity is essential for recognizing possible signs of unrest that could prelude to potentially destructive tsunamigenic eruptions.
This session focuses on methods (e.g., satellite data-based identification and mapping of discolored water or floating pumice rafts) and systems (e.g., seismometer and hydroacoustic arrays) developed for analyzing submarine volcanic activity. Contributions to the monitoring of recent submarine eruptions (e.g., Anak-Krakatau, Late’iki, Home Reef, Kavachi) and relative effects are welcome, with a particular focus on results achieved by using multidisciplinary, integrated and innovative approaches of data analysis (e.g., statistical and machine learning techniques).

One of the major goals in volcanology is to improve our understanding of the processes that lead to volcanic eruptions, as well as those that occur during the eruptive events. The rate of mantle melting, the volatile content in primary melts, and the intracrustal accumulation and transfer of fluids and melts play a major role in modulating the evolution of volcanic activity over time. Moreover, they affect the magnitude and style of eruptions, regardless of the geodynamic context in which a volcanic system forms. These processes can be assessed through geochemical (fluids and rocks analyses) and petrological monitoring. Few eruptions worldwide (e.g. the 2021 La Palma and the 2020-2022 Mt. Etna eruption) allowed geologists to perform real-time monitoring and systematic sampling of gases, lava and/or tephra before and throughout the duration of an eruption. This approach helps to reconstruct magmatic processes and follow ongoing magmatic dynamics almost in a sequential and chronologically accurate way.
The syn-eruptive geochemical and petrological monitoring is carried out following well-defined procedures developed to rapidly produce datasets that, integrated with information from other monitoring techniques, help understanding the magmatic processes driving volcanic phenomena. These findings can be complemented with more extensive studies that require additional time and produce other datasets, aimed at investigating detailed aspects of pre-eruptive and eruptive processes. Overall, geochemical and petrological monitoring activities are highly challenging, but critical for understanding the evolution of ongoing volcanic crises, identifying mid/long-term precursors of future eruptions and providing robust scientific tools to support the decisions of the Authorities responsible for crisis management.
Our intent is to enhance the dialogue among scientists, who are the ‘providers’ of geochemical, petrological and other multidisciplinary data/results, and Decision-Makers, who are the primary ‘users’ of this information during a volcanic crisis. The aim is to leverage the experience gained from past or ongoing eruptions and unrest crises to highlight the strengths and weaknesses of geochemical and petrological monitoring of volcanic eruptions, and to define guidelines and best practices to apply in order to fulfil the requests of Decision-Makers for the management of a volcanic crisis.

Tephra pose significant hazards to human health, infrastructure, and the environment, especially in regions surrounding active volcanoes. Assessing tephra hazards requires knowledge of the physical processes governing tephra generation, dispersal, and fallout, obtained through a multidisciplinary approach that combines field observations, experimental data, and computational models. For instance, field measurements play a critical role in gathering real-time and post-event data on tephra fallout, particle size distribution, and deposit thickness, providing ground-truth data that helps refine models. Recent developments in remote sensing and drone technology are also enhancing the time and spatial resolution as well as the accuracy of tephra transport and deposition processes. Meanwhile, analog experiments offer controlled environments to simulate eruptive processes, plume dynamics, and wind interactions, shedding light on the behavior of tephra during different eruption phases. These experiments allow us to improve our comprehension of ash aggregation and sedimentation processes such as Settling-Driven Gravitational Instabilities (SDGIs). Numerical modeling, driven by field and experimental data, allows for detailed simulations of tephra dispersal and fallout under various eruption scenarios and atmospheric conditions. Advances in computational power and algorithm development are improving the precision of models, allowing us to tackle challenging physical factors such as unsteadiness, particle-turbulence interactions, variable entrainment, thermal disequilibria, ash aggregation, and compressibility. Models enable better forecasting of ash cloud trajectories and deposition patterns. Models also assist in risk assessments, providing insights into potential impacts on aviation, agriculture, and urban areas. This session welcomes any contribution and advances on the aforementioned points related to tephra hazards, potentially emphasizing the synergy between fieldwork, analog experiments, and numerical modeling.

Subduction zones generate numerous natural hazards, including volcanism, earthquakes and tsunamis, and shape the landscape through a series of processes lasting from seconds to millions of years. Their dynamics are driven by complex feedbacks between stress, strain, rock transformation and fluid migration along and across the plate interface, from shallow to deep environments. Despite their utmost importance, the intricate time-sensitive thermo–hydro–mechanical–chemical (THMC-t) processes remain largely puzzling. This is essentially due to the complexity of integrating observations across multiple spatial, magnification and temporal scales (from the nanoscale and the grain boundary size to the plate interface, and from seconds to millions of years).

Our session aims, therefore, at gathering recent advancements in observatory techniques, monitoring and high-resolution imaging of i) the plate interface kinematics, ii) the accretionary wedge, iii) the subducting slab, and iv) the mantle wedge in active and fossil subduction interfaces. This includes studies from a wide range of disciplines, such as seismology and geodesy, geodynamics, marine geosciences, field-based petrology and geochemistry and microstructure, rock mechanics and numerical modelling. We particularly encourage initiatives that foster collaboration between communities to achieve a comprehensive understanding of subduction systems through space and time.

Debris flows are among the most dangerous natural hazards that threaten people and infrastructures in both mountainous and volcanic areas. The study of the initiation and dynamics of debris flows, along with the characterization of the associated erosion/deposition processes, is of paramount importance for hazard assessment, land-use planning, design of mitigation measures and early-warning systems. In addition, climate change may expose more mountain areas to higher hazard, and further research is needed to understand the consequences of this.
A growing number of scientists with diverse backgrounds are studying debris flows and lahars. The difficulties in measuring parameters related to their initiation and propagation have progressively prompted research into a wide variety of laboratory experiments and monitoring studies. However, there is a need of improving the quality of instrumental observations that would provide knowledge for more accurate modelling and hazard maps. Nowadays, the combination of distributed sensor networks and remote sensing techniques represents a unique opportunity to gather direct observations of debris flows to better constrain their physical properties. At the same time, computer-aided hazard assessment and mitigation design are undergoing a revolution due to the widespread adoption of AI and of data-driven numerical models.
Scientists working in the field of debris flows are invited to present their recent advancements. In addition, contributions from practitioners and decision makers are also welcome. Topics of the session include field studies and documentation, mechanics of debris-flow initiation and propagation, laboratory experiments, modelling, monitoring, impacts of climate change on debris-flow activity, hazard and risk assessment and mapping, early warning, and alarm systems.

Large mass movements in rock, debris, and ice in glacial masses, represent enormous risks. These complex systems are difficult to describe, investigate, monitor, and model. Hence a reliable model of these phenomena requires acquisition and analysis of all available data to support successive steps up to the management of Early Warning systems.
Large instabilities affect all materials (rock, weak rocks, debris, ice), from low to high altitudes, evolving as slow or fast complex mass movements. This and the complex dependency on forcing factors result in different types and degrees of hazard and risk. Some aspects of these instabilities are still understudied and debated, because of difficult characterization and few cases thoroughly studied. Regional and temporal distribution, relationships with controlling and triggering factors are poorly understood resulting in poor predictions of behavior and evolution under present and future climates. How will it change their state of activity under future climatic changes? How this will impact on existing structures and infrastructures? How can we improve our predictions? Relationships among geological and hydrological boundary conditions and displacements are associated with the evolution in space and time of thermo-hydro-mechanical controls as well as the properties of the unstable mass. Even for well-studied and active phenomena warning thresholds are mostly qualitative, based on semi-empirical approaches. Hence a multidisciplinary approach and robust monitoring data are needed. Many modeling approaches can be applied to evaluate instability and failure, considering triggerings, and failure propagation, leading to rapid mass movements. Nevertheless, these approaches are still phenomenological and have difficulty explaining the observed behavior. The impacts of such instabilities on structures represent a relevant risk and an opportunity in terms of investigations and quantitative measurements of the effects on tunnels, dams, and roads. The design of these structures and knowledge of their expected performance are fundamental.
We invite to present case studies, share views and data, discuss monitoring and modeling approaches and tools, to introduce new approaches for threshold definition, including advanced numerical modeling, Machine Learning for streamline and offline data analyses, development of monitoring tools, and dating or investigation techniques.

Landslides and slope instabilities are natural hazards that cause significant damage and loss of life around the world each year. Yet, their triggering mechanisms are still an open area of research. Landslide-prone areas are characterized by highly heterogeneous properties and subsurface dynamics, where, for example, changes in the fluid pathways, geomechanical parameters, and subsurface structures can occur over time-scales ranging from second/minutes to months/years, requiring radically different approaches for their identification and prediction. Hence, there is a need to develop a suite of novel methods for studying landslide and slope instabilities architecture as well as their temporal and spatial changes in internal structure and properties. The complexity of the problem requires the application of innovative research methods in data acquisition, methodology and the integrated interpretation of geophysical, geotechnical and geological data.

This session invites abstracts presenting novel and emerging trends and opportunities for landslide and slope instabilities reconnaissance, monitoring, and early-warning, particularly applying multi-method approaches. Presentations showing the integration of various geophysical and remote sensing techniques, especially using machine learning or time-lapse surveys, are especially welcome. Likewise, presentations focusing on determining the geomechanical parameters of mass movements using geological (boreholes, geomechanical or other surveys) and geophysical studies are also in the scope of the session. Since slope instabilities are a cross-disciplinary problem, any contributions on avalanches, natural or engineered slopes, or climate-induced slope instabilities are warmly invited.

Slope instability phenomena – affecting diverse materials with a variety of mechanisms (e.g., earthslides, rockfalls, debris flows) – are recognised to be driven by weather patterns largely differing in terms of variables (precipitation, temperature, snow melting) and significant time span (from a few minutes up to several months). However, local modifications induced by human intervention, such as socio-economic-induced land use/cover changes, reduced soil management due to land abandonment, or the implementation and maintenance of Nature-Based Solutions, are recognised to play a key role in defining landslide hazard and risk. In turn, these local human-induced factors can be strongly influenced by weather dynamics. For instance, hydrological and thermal regimes regulate vegetation suitability, then land cover and, in turn, landslide hazard and risk.
A clear and robust evaluation of how ongoing and expected global warming and the resulting climate change can affect these factors and, hence, landslide risk represents a clear key need for practitioners, communities, and decision-makers.
This session aims to provide a discussion forum for studies concerning the analysis of the role of climate-related variables and slope-atmosphere interaction on landslide triggering, propagation, and activity and/or on the effectiveness of protection measures across different geographic contexts and scales. Test cases and investigations (by exploiting monitoring and modelling) to evaluate ongoing and future landslide activity are welcome. Furthermore, investigations focused on data-driven approaches (Machine Learning, AI), through which the variations induced by climate and environmental changes on triggering, dynamics, and hazard are analysed, are greatly welcome.

Alpine mass movements, rockfalls, rockslides and rock avalanches are among the primary hazards and drivers of landscape evolution in steep terrain. The physics of rock slope degradation and dynamics of failure and transport mechanisms define the hazards and possible mitigation strategies and enable retrodictions and predictions of events and controls.

This session aims to bring together state-of-the-art methods for predicting, assessing, quantifying, and protecting against rock slope hazards across spatial and temporal scales. We seek innovative contributions from investigators dealing with all stages of rock slope hazards, from weathering and/or damage accumulation, through detachment, transport and deposition, and finally to the development of protection and mitigation measures. In particular, we seek studies presenting new theoretical, numerical or probabilistic modelling approaches, novel data sets derived from laboratory, in situ, or remote sensing applications, and state-of-the-art approaches to social, structural, or natural protection measures. We especially encourage contributions from geomechanics/rock physics, geodynamics, geomorphology and tectonics to better understand how rockfall, rockslides and rock avalanches act across scales.

Innovative contributions dealing with mass movement predisposition, detachment, transport, and deposition are welcome on (i) insights from field observations and/or laboratory experiments; (ii) statistical methods and/or artificial intelligence to identify and mapped mass movements; (iii) new monitoring approaches (in-situ and remote sensing) applied at different spatial and temporal scales; (iv) models (from conceptual frameworks to theoretical and/or advanced numerical approaches) for the analysis and interpretation of the governing physical processes; (v) develop strategies applicable for hazard assessment, mitigation and protection. We also aim at triggering discussions on preparedness and risk reduction, and studies that integrate social, structural, or natural protection measures.

At EGU 2025, this session has its 20th edition. Since 2006, it builds a growing community and network at EGU and beyond for senior scientists as well as young researches.

Landslides can trigger catastrophic consequences, leading to loss of life and assets. In specific regions, landslides claim more lives than any other natural catastrophe. Anticipating these events proves to be a monumental challenge, encompassing scientific curiosity and vital societal implications, as it provides a means to safeguard lives and property.
This session revolves around methodologies and state-of-the-art approaches in landslide prediction, encompassing aspects like location, timing, magnitude, and the impact of single and multiple slope failures. It spans a range of landslide variations, from abrupt rockfalls to rapid debris flows, and slow-moving slides to sudden rock avalanches. The focus extends from local to global scales.

Contributions are encouraged in the following areas:

Exploring the theoretical facets of predicting natural hazards, with a specific emphasis on landslide prognosis. These submissions may delve into conceptual, mathematical, physical, statistical, numerical, and computational intricacies.
Presenting applied research, supported by real-world instances, that assesses the feasibility of predicting individual or multiple landslides and their defining characteristics, with specific reference to early warning systems and methods based on monitoring data and time series of physical quantities related to slope stability at different scales.
Evaluating the precision of landslide forecasts, comparing the effectiveness of diverse predictive models, demonstrating the integration of landslide predictions into operational systems, and probing the potential of emerging technologies.

Should the session yield fruitful results, noteworthy submissions may be consolidated into a special issue of an international journal.

Landslide early warning systems (LEWS) are cost effective non-structural mitigation measures for landslide risk reduction. For this reason, the design, application and management of LEWS are gaining consensus not only in the scientific literature but also among public administrations and private companies. LEWS can be applied at different spatial scales of analysis, reliable implementations and prototypal LEWS have been proposed and applied from slope to regional scales.
The structure of LEWS can be schematized as an interrelation of the following main components: monitoring, modelling, forecasting, warning, response. However, tools, instruments, methods employed can vary considerably with the scale of analysis, as well as the characteristics and the aim of the warnings/alerts issued. For instance, at local scale instrumental devices are mostly used to monitor deformations and hydrogeological variables with the aim of setting thresholds for evacuation or interruption of services. At regional scale hydro-meteorological thresholds are widely used to prepare a timely response of civil protection and first responders. Concerning modelling techniques, analyses on local slopes generally allow for the use of numerical models, while statistical, probabilistic and physical-based models are widely used for large areas.

This session focuses on LEWS at all scales and stages of maturity, from prototype to active and dismissed ones. Test cases describing operational application of consolidated approaches are welcome, as well as works dealing with promising recent innovations, even if still at an experimental stage.
Contributions addressing the following topics will be considered positively:
- real-time monitoring systems (IoT)
- prediction tools for warning purposes
- in-situ monitoring instruments and/or remote sensing devices
- warning models for issuing warning
- operational applications and performance analyses
- machine learning techniques applied for early warning purposes

Under the influence of global climate change, urban expansion and human activities, landslide events occur frequently every year around the world, posing a great threat to human life and property safety, especially in less developed regions. The global increase in damaging landslide events has attracted the attention of governments, practitioners and scientists to develop functional, reliable and (when possible) low-cost monitoring strategies. Numerous case studies have demonstrated how a well-planned monitoring system of landslides is of fundamental importance for long and short-term risk reduction.

Today, the temporal evolution of a landslide is addressed in several ways, encompassing classical and more complex in situ measurements or remotely sensed data acquired from satellite and aerial platforms. All these techniques are adopted for the same final scope: measure landslide motion over time, trying to forecast future evolution or, at least, reconstruct its recent past. Real time, near-real time and deferred time strategies can be profitably used for landslide monitoring, depending on the type of phenomenon, the selected monitoring tool and the acceptable level of risk.
Remote sensing methods, such as radar Interferometry, photogrammetry, LiDAR or optical imaging represent valuable approaches in understanding landslides characteristics, especially when integrated with traditional ground-based monitoring techniques and when analysed with machine learning approaches.

This session follows the general objectives of the International Consortium on Landslides, namely: (i) promote landslide research for the benefit of society, (ii) integrate geosciences and technology within the cultural and social contexts to evaluate landslide risk, and (iii) combine and coordinate international expertise. Considering these key conceptual drivers, this session aims to present successful monitoring experiences worldwide based on both in situ and/or remotely sensed data.

The session is expected to present various topics of innovative applications of remote sensing techniques, as well as case studies in which multi-temporal and multi-platform monitoring data are exploited for risk management. The integration and synergic use of different techniques is welcomed, as well as newly developed tools or data analysis approaches, including big data management strategies. Specific relevance is given to the evaluation of the impact of landslides on cultural heritage.

Evolving climate patterns and land use changes, coupled with improved monitoring capabilities, are contributing to a notable increase in seismic and infrasound detections of surficial mass movements. These events — landslides, rock/ice/snow avalanches, debris flows, lahars, pyroclastic density currents, glacial processes, etc. — can pose significant hazards, and there is a pressing need to better understand, characterize, and mitigate them. While these sources are not routinely monitored in real-time like earthquakes, ever-expanding seismic and infrasound networks offer opportunities for rapid early warning and post-event detection and analysis. Improved data sources and techniques can also help search for reliable precursors to catastrophic failure and can be used to characterize existing slope instabilities.

This session explores innovative methods that improve our comprehension of these non-earthquake seismic and acoustic sources and enhance our ability to characterize and monitor them and mitigate their associated hazards. We invite presentations that investigate various types of surficial mass movements by leveraging seismic and/or infrasound techniques, including the application of machine learning or inclusion of ancillary constraints through ground-based, airborne, and satellite imagery or other geophysical data streams. Topics of interest encompass — but are not limited to — source detection, location, characterization, modeling, and classification; precursory signal analysis; monitoring; innovative instrumentation (e.g., distributed acoustic sensing, nodal sensors, large-N arrays/networks); and hazard mitigation.

Landslide Inventory Maps (LIMs) are the simplest tool to report the spatial distribution of landslides in a territory. They can be prepared using different techniques and base data (e.g. remote sensing images), each bringing intrinsic limitations and potential sources of mapping errors, hence affecting the overall accuracy and reliability.
LIMs are a precious source of information for any subsequent analyses in landslide research (e.g., land management and planning, model training and validation, susceptibility, hazard, and risk assessment, among others). A common operational assumption carried out when using such data is to consider them as “correct”, which results in transferring/propagating the mapping error(s) to the subsequent products.
Recent research works have defined the quality of LIMs as the result of three factors: geographic accuracy, thematic accuracy, and completeness/statistical representativeness. Geographic accuracy refers to the location, size, and shape of each landslide reported in the LIM. Thematic accuracy refers to the consistency of attributes assigned to each landslide in the LIM (e.g. classification, degree of activity, age/date of occurrence, among others). Completeness refers to the ratio of landslides reported in the LIM and the “ground truth”. Since the ground truth is hardly available, more recently the concept of statistical representativeness has been preferred, i.e. assuring that the statistical distribution of landslides reported in the LIMs is a statistically representative sample of the actual distribution of landslides in an area. Each of these aspects is currently under-explored in terms of evaluation/quantification/metrics, propagation, and handling/management in derivative maps.
Within this general framework, this session welcomes contributions specially focused on (but not necessarily limited to) the following topics:
• Definition of metrics (numeric, heuristic, morphometric, etc.) for the evaluation of mapping accuracy, errors, and uncertainty;
• Statistical modelling of mapping errors;
• LIMs quality assessment methods;
• Impact of error propagation in maps obtained from LIMs, including training of machine learning and/or AI-based detection algorithms, susceptibility models, hazard and risk assessment;
• defining links between LIMs quality and use limitations.

In contributions, all methods for the preparation of landslide inventories are welcome, from manual to semi- and fully automated.

The special session aims to delve into the transformative impact of Artificial Intelligence (AI) in the realm of landslide and Engineering Geological research. As the fields of geoscience and engineering evolve, the integration of advanced technologies becomes increasingly crucial for understanding and mitigating natural hazards. This session will showcase cutting-edge applications of AI techniques, demonstrating their efficacy in landslide detection, prediction, and analysis. We invite researchers and experts to share their experiences, methodologies, and success stories in leveraging AI to enhance the accuracy and efficiency of landslide studies. Topics of interest include novel algorithms, data integration strategies, and real-world case studies that highlight the intersection of technology, geological research, and practice, fostering a collaborative environment for the exchange of knowledge and ideas. Join us as we explore the frontier of innovation, where AI converges with geological and engineering sciences to reshape the future of landslide and engineering geological research

Landslides and other types of ground failure (e.g., liquefaction and subsidence) are among the most damaging effects triggered by earthquake shaking. Observations from several recent earthquakes have shown that the death toll and destruction following strong earthquakes are not confined to the coseismic phase. Damaging mass movements are also observed in the post-seismic period due to disturbances caused by earthquakes. Overall, cascading earthquake hazards, and specifically landsliding in co- and post-seismic periods, are commonly treated separately, even though an integrated approach to the problem is clearly desirable. The purpose of this session is to provide a forum for discussion among researchers and professionals who study landslides and related hazards caused by seismic activity. It also aims to foster multidisciplinary research and collaboration among experts to better understand and mitigate earthquake-induced landslide hazards and risks in both co-seismic and post-seismic phases. Topics of interest include: (a) case histories of earthquake-triggered landslides analyzed at local or regional scales; (b) case histories of mass movements occurring in post-seismic periods; (c) assessments of landslide and other ground-failure hazards in relation to deterministic earthquake event scenarios or regional probabilistic evaluations; (d) application of numerical techniques to evaluate and portray seismic ground-failure hazards in co- and post-seismic periods; (e) studies regarding physical modeling of the influence of dynamic loading on slope stability and seismically induced landslide displacements; (f) site effects such as amplification and the influence of pre-existing landslide masses; (g) comparisons of regional differences in the factors associated with landslide occurrence; and (h) user requirements regarding hazard assessment and persisting challenges.

Climate-induced or anthropogenically triggered geohazards may cause damage to buildings, infrastructure and the environment. Climate-induced geohazards, such as landslides, floods or droughts, are known to exacerbate with climate change due to the increased frequency and intensity of rainfall and extreme weather events.

Solutions that use natural materials or mimic biological processes are increasingly being adopted to mitigate the triggering or propagation of such geohazards through improvement of the soil characteristics and its behaviour.

The use of vegetation on potentially unstable slopes and streambanks is an example of a Nature-Based Solution (NBS). Root-shaped anchors are an example of bio-inspired design used for soil reinforcement. Microbiological activity, biological exudates and fungi, can change both soil strength and hydraulic conductivity, improve erosion resistance and alter the rheology of the soil.

These NBS must combine ecological approaches with engineering design in order to provide practical solutions, whilst also maintaining/enhancing biodiversity and ecosystem services.

This session aims to stimulate multi- and interdisciplinary knowledge exchange of NBS, bio-based and bio-inspired solutions for landslides and erosion mitigation.

Contributions could originate from the fields of geotechnical engineering, ecological engineering, ecology, forestry, hydrogeology and agronomy, among others. Experiences of interactions between research and industry, with involvement of NBS entrepreneurs, are particularly welcome.

Topics of interest include, but are not limited to:
• Experimental (either laboratory or field) or numerical investigation of root biomechanics and plant water relation, hydrological and/or mechanical soil reinforcement by vegetation, or bio-based solutions for slopes or streambanks;
• Theoretical or empirical data-driven design methods used in geotechnical engineering for vegetated and bio-improved soils;
• Tools, approaches, and frameworks showing how NBS can mitigate geohazards and offer co-benefits;
• Upscaling potential of laboratory data to slope and catchment scales;
• Case studies of combined hard and soft engineering, stabilization works, or Ecosystem-based disaster risk reduction, especially involving design principles and performance assessment;
• Guidelines, reviews, and data repositories on NBS for risk reduction, with focus on NBS for infrastructure protection.

Landslide increasingly affect urban areas and transport infrastructure, due to rapid urbanization, climate change, and complex hydrogeological conditions. Anthropogenic activity associated with construction of housing, roads, and drainage systems modify surface water runoff and subsurface hydrology, strongly affecting slope stability [1]. Rapid urban development, especially in developing countries, results in unregulated buildings and poor or non-existing water drainage and water leakages, which cause in widespread slope instability under intense rainfall [2].
Landslide susceptibility maps based on statistical models may be ineffective at the urban scale. Physically based approaches may be suitable for including local anthropic changes and predicting slope stability in urban areas and along transportation routes [3]. They are specialized to landslide type, including reach distance and runoff, and take into account time-dependent triggering conditions [4, 5].
Numerical models can combine rain infiltration with measured rainfall, soil moisture and soil suction, local anthropic changes on the terrain, and may lead to effective early warning systems in urban areas [3, 6]. These considerations apply both to urban areas and transport routes, characterized by local and continued anthropic changes.
We invite contributions that explore:
(1) application of physically based models to landslides affecting urban areas and transport infrastructure, including but not limited to soil mechanics, hydrology, and geotechnical engineering;
(2) detection and monitoring of ground movements specialized for urban areas and transport routes, including the use of remote sensing technologies as well as ground-based techniques, and their integration with GIS and data analytics to provide real-time monitoring and early warning systems.
(3) effects of urban sprawl for slope stability, including interdisciplinary approaches, novel methodologies, and practical implementations in rapidly growing urban areas.
References
[1] Dille et al., Nature Geosci. (2022). DOI: 10.1038/s41561-022-01073-3
[2] Ozturk et al., Nature (2022). DOI: 10.1038/d41586-022-02141-9
[3] Bozzolan et al., Sci. Tot. Env. (2023). DOI: 10.1016/j.scitotenv.2022.159412
[4] Alvioli et al., Eng. Geol. (2021). DOI: 10.1016/j.enggeo.2021.106301
[5] Marchesini et al., Eng. Geol. (2024). DOI: 10.1016/j.enggeo.2024.107474
[6] Mendes et al., Geotech. Geol. Eng. (2017). DOI: 10.1007/s10706-017-0303-z

Many regions worldwide are coping with the climatic global change, which is causing an increase in extreme hydro-meteorological events. Shallow landslides involving the first meters of soil layers could increase significantly compared to current and past scenarios, modifying the susceptibility of a region and the frequency of their triggering. These phenomena provoke significant environmental damages, particularly in hilly and mountainous areas, with a general loss of shallow soil layers rich in organic matter and nutrients fundamental for agricultural areas and biodiversity. The triggering of these phenomena is related to the effect of intense rainfall events on usually unsaturated soils, with a predisposition related to the hydrological conditions present in soil layers. Hydrological field monitoring is, then, fundamental to understand the predisposing and triggering conditions of shallow landslides and to develop and calibrate reliable models for their spatio-temporal prediction.
This session aims to collect researches concerning the most recent progress on monitoring, predicting, and modeling shallow landslides at different spatial and temporal scales, covering a wide spectrum of approaches, from field and laboratory measurements to remote sensing techniques, modelling methods, and mitigation measures. We encourage presentations related to:
● laboratory or field models to assess the physical, geological, and hydrological conditions leading to the triggering of these phenomena;
● field hydrological monitoring for the assessment of predisposing and triggering conditions of shallow landslides;
● proximal and remote sensing methods for measurement and monitoring hillslopes prone to shallow landslides, to identify precursory evidence and to map new phenomena;
● development, application, and validation of models for the prediction of shallow landslides;
● effects of climatic global changes and land use changes on the susceptibility and hazards towards shallow landslides;
● mitigation measures to reduce the proneness of a territory towards shallow landslides.

The growing availability of multi-temporal landslide inventories, for example from multi-epoch LiDAR, InSAR, and monitoring, has precipitated a shift from static landslide susceptibility evaluations to a better understanding of both spatial and temporal variations in landslide activity. In parallel, the development of regional to global hydroclimatic models, re-analysis products, next generation remote sensing products, and compilations of in-situ observations (such as ERA5, SMAP-L4, and GSDR) is allowing researchers to obtain a broader understanding of the hydro-meteorological conditions that affect landslide activity: for example soil moisture, snow melt, precipitation, and meso and synoptic scale weather systems. Currently, researchers and practitioners are exploring how linkages between historical landslide activity and hydro-meteorological drivers can be integrated to improve data driven models for landslide situational awareness and early warning systems. This session seeks to bring together a wide range of perspectives from geomorphology, hydrology, meteorology, remote sensing, data science and beyond to share experiences and to spur future research advances and operational application development.

Subtopics may include:
• Constructing multi-temporal landslide activity data sets utilizing remote sensing data and/or point source terrestrial data
• Linking regional landslide activity trends and variability to hydro-meteorological, geological, morphological, or other conditions.
• Evaluating the suitability of different hydroclimatic models, re-analysis datasets, remote sensing products, and in-situ observations to different landslide and terrain types or research objectives
• Approaches to quantifying linkages between hydro-meteorological drivers and landslide activity
• Development and testing of new algorithms and infrastructure, including machine and deep learning approaches, to support weather-related landslide situational awareness and warning

Landslides are a landscape modelling process inducing geomorphological changes on slopes in coastal, hilly, and mountainous areas. Their occurrence is generally controlled by predisposing (e.g., morphology, lithological and structural setting, vegetation cover, land use, climate, etc.) and triggering factors (e.g., heavy rainfall and snowfall events, wildfires, earthquakes, human activity, etc.). Therefore, paying attention to these factors in landslide analyses is essential to set an organic correlation between climate regime, geological, morphostructural and seismic setting, and slope instability phenomena. This type of analysis, together with the investigation and monitoring of existing landslides, is critical for mitigating their impact on human settlements and infrastructure. Field investigation, coupled with remote sensing technologies are essential tools in the analysis of landslides and predisposing factors, offering the ability to collect detailed and accurate data over large and inaccessible areas. This session aims to explore the use of these different types of techniques: field survey and remote sensing techniques, including LiDAR (Light Detection and Ranging), InSAR (Interferometric Synthetic Aperture Radar), and optical satellite and drone imagery, for the detection, mapping, and monitoring of landslides. These technologies provide valuable data that enable the analysis of terrain morphology, identification of landslide-prone areas, and monitoring of ground movements. The integration of remote sensing data with traditional geotechnical and geomorphological approaches can enhance the understanding of landslide dynamics and improve the development of predictive modelling and scenario reconstruction. This session gathers field survey and remote sensing studies, methodological and case studies, to highlight the advancements in innovative approaches and their vital role in landslide and geomorphological risk assessment, contributing to the development of effective mitigation strategies and early warning systems.

This session aims to facilitate a collaborative and multidisciplinary dialogue that fosters the exchange of knowledge and expertise in landslide risk management. By integrating cutting-edge advancements in artificial intelligence (AI) with diverse perspectives from researchers, practitioners, and stakeholders, we seek to develop innovative solutions for landslide detection, monitoring, and risk assessment. The session will explore how AI-driven approaches can enhance traditional methodologies, offering new insights into early warning systems, hazard prediction, and mitigation strategies. Our goal is to create a visionary roadmap for AI-enabled landslide risk management, underpinned by scientific rigor and aimed at safeguarding communities worldwide from the impacts of landslides.

The assessment of the earthquake hazard and risk and the enhancement of the society’s resilience is greatly dependent on the knowledge of impact data sets of past earthquakes. For earthquakes that occurred in the historical period such data sets could be based on various types of historical documentation and in addition on geological observations and possibly on archaeological evidence. After the establishment and gradual improvement of macroseismic scales the earthquake impact data sets are translated to macroseismic intensity with the use of several methods and techniques. In the modern period the collection of macroseismic observations and the assignment of intensities has been expanded to the so-called citizen seismology. These new achievements are of significance to advance the methods that may contribute to the assignment of macroseismic intensities to historical earthquakes.
This session is devoted to the advancement of methods and techniques that may contribute to the compilation, storage and elaboration of impact data sets useful for the intensity characterization of historical earthquakes as well as for seismic hazard and risk assessment purposes. Welcomed to this session are also similar studies focusing on the collection and elaboration of impact data sets for other earthquake-related natural hazards, e.g. tsunamis and landslides, with the aim to help the assessment of hazards and risks.

Mitigating earthquake disasters invlolves several key components and stages, from identifying and assessing risk to reducing their impact. These components include: a) Analysis of hazards: examining the physical characteristics of ground shaking and its cascading effects on the natural/built environment. b) Vulnerability and exposure assessment: evaluating how structures and people are susceptible to hazards. c) Risk management: preparedness, rescue, relief, recovery, capacity building and overall resilience.
Given the complexity of earthquake disaster mitigation, a variety of seismic hazard and risk models can be adopted, at different spatial and temporal scales. These models incorporate diverse observations and require multi-disciplinary input. Testing and validating these methodologies, for all risk components, is essential for effective disaster mitigation.
We invite contributions on various aspects of seismic risk research and assessment, including both methodological and practical approaches. Topics include:
• Developing physical/statistical models, including those using artificial antelligence to assess earthquake risk factors such as hazard, exposure, and vulnerability. This also involves exploring innovative data collection and processing techniques, such as statistical machine learning;
• Estimating earthquake hazard and risk across different temporal and spatial scales and assessing the accuracy of these models against available observations;
• Conducting time-dependent seismic hazard and risk assessments that account for the impact of aftershocks and providing post-event information such as early warnings and alerts for effective emergency management;
• Analyzing earthquake-induced cascading effects such as landslides and tsunamis, and conducting multi-risk assessments that combine earthquakes with other hazards like flooding.
This interdisciplinary session aims to facilitate knowledge exchange and share best practices gained through various approaches. It will also highlight current deficiencies and suggest future research directions.

Seismic risk assessment is fundamental to understanding the potential damage earthquakes may cause to structures and infrastructure in specific regions. Deterministic and probabilistic seismic hazard and risk models serve as essential tools, support the design of resilient buildings, updating national building codes, and evaluating various risk metrics. Despite the development of numerous methodologies, significant challenges remain unresolved, highlighting the need for continued research and innovation.
The session addresses advances in various components of seismic risk
assessment: hazard, vulnerability, and exposure, at diverse spatial and temporal scales. The session encourages studies related to:
- The state-of-the-art in seismic hazard and risk assessment.
- Insights in characterization of seismic sources: faults and seismogenic zones.
- Advances in ground motion prediction equations: empirical and simulated attenuation models including stochastic and physic-based simulations that generate ground motions for regions with limited observational records. - The incorporation of site effects into seismic risk models.
- Recent developments in uncertainty quantification and reliability analysis. Also, strategies for managing uncertainty in decision-making processes related to seismic risk.
- Post-earthquake damage data from significant recent events to test and refine risk models.
Given the growing availability of data and technological advances, this session will
discuss present challenges and future expectations for seismic hazard and risk models.
We also encourage contributions that share lessons learned from real-world
applications of risk models in decision-making, including areas such as urban planning, resource allocation, and emergency response.

From the real-time integration of multi-parametric observations is expected the major contribution to the development of operational t-DASH systems suitable for supporting decision makers with continuously updated seismic hazard scenarios. A very preliminary step in this direction is the identification of those parameters (seismological, chemical, physical, biological, etc.) whose space-time dynamics and/or anomalous variability can be, to some extent, associated with the complex process of preparation of major earthquakes.
This session wants then to encourage studies devoted to demonstrate the added value of the introduction of specific, observations and/or data analysis methods within the t-DASH and StEF perspectives. Therefore, studies based on long-term data analyses, including different conditions of seismic activity, are particularly encouraged. Similarly welcome will be the presentation of infrastructures devoted to maintain and further develop our present observational capabilities of earthquake related phenomena also contributing in this way to build a global multi-parametric Earthquakes Observing System (EQuOS) to complement the existing GEOSS initiative.
To this aim this session is not addressed just to seismology and natural hazards scientists but also to geologist, atmospheric sciences and electromagnetism researchers, whose collaboration is particular important for fully understand mechanisms of earthquake preparation and their possible relation with other measurable quantities. For this reason, all contributions devoted to the description of genetic models of earthquake’s precursory phenomena are equally welcome.

The estimation of ground motion for future earthquakes is one of the main tasks of seismology. Among the processes affecting ground motion, local site conditions play a significant role. Earthquake site effects encompass several phenomena, such as amplified ground shaking due to local geological and topographical features, liquefaction events, ground failures, cavity collapses, and earthquake-triggered landslides. The estimation of these effects is a necessary step for seismic hazard and seismic risk mitigation as well as to build effective strategies for urban planning and emergency management.
This session aims to gather multidisciplinary contributions that bridge the fields of seismology geology, geotechnics, and engineering and will focus on the following topics:
- Site characterization and seismic microzonation;
- Empirical assessments of stratigraphic and topographic amplification effects;
- Quantitative evaluation of seismic site response in 1D, 2D, and 3D configuration;
- Earthquake-induced ground effects, such as landslides, liquefaction and cavity collapse;
- Soil-structure interaction and characterization of building response to seismic events;
- Proposals for integration and/or revision of building codes;
- Analysis of historical and cultural heritage sites.
The session also aims to collect results based on different geophysical techniques (e.g., earthquake data, ambient noise analysis, HVSR, array measurements, active surface wave prospecting, ERT, GPR, seismic refraction tomography, etc.) and their integration. Contributions regarding innovative methodologies as Distributed Acoustic Sensing (DAS) systems and dense arrays are well accepted.

New physical and statistical models based on observed seismicity patterns shed light on the preparation process of large earthquakes and on the temporal and spatial evolution of seismicity clusters.

As a result of technological improvements in seismic monitoring, seismic data is nowadays gathered with ever-increasing quality and quantity. As a result, models can benefit from large and accurate seismic catalogues. Indeed, accuracy of hypocenter locations and coherence in magnitude determination are fundamental for reliable analyses. And physics-based earthquake simulators can produce large synthetic catalogues that can be used to improve the models.

Multidisciplinary data recorded by both ground and satellite instruments, such as geodetic deformation, geological and geochemical data, fluid content analyses and laboratory experiments, can better constrain the models, in addition to available seismological results such as source parameters and tomographic information.

Statistical approaches and machine learning techniques of big data analysis are required to benefit from this wealth of information, and unveiling complex and nonlinear relationships in the data. This allows a deeper understanding of earthquake occurrence and its statistical forecasting.

In this session, we invite researchers to present their latest results and findings in physical and statistical models and machine learning approaches for space, time, and magnitude evolution of earthquake sequences. Emphasis will be given to the following topics:

• Physical and statistical models of earthquake occurrence.
• Analysis of earthquake clustering.
• Spatial, temporal and magnitude properties of earthquake statistics.
• Quantitative testing of earthquake occurrence models.
• Reliability of earthquake catalogues.
• Time-dependent hazard assessment.
• Methods and software for earthquake forecasting.
• Data analyses and requirements for model testing.
• Machine learning applied to seismic data.
• Methods for quantifying uncertainty in pattern recognition and machine learning.
• Effects of fluid diffusion on seismicity

Tsunamis can be generated by a variety of mechanisms, including earthquakes, landslides, volcanic activity and atmospheric disturbances. They can cause widespread damage and fatalities in coastal areas, highlighting the urgent need to advance tsunami science towards implementing effective disaster risk reduction measures and developing early warning systems. More than two decades after the great Indian Ocean tsunami of 2004, the field of tsunami science has evolved significantly, expanding into new research areas and regions. However, recent events, such as the 2022 Hunga Tonga - Hunga Ha'apai tsunami, have challenged the progress in tsunami science and warning, and raised further questions on modeling, hazard assessment and warning capabilities at different scales. They particularly underscored the importance of closer collaboration between different research fields and operational communities.
The range of topics currently addressed by the tsunami scientific community includes:

• Analytical and numerical modelling of tsunami generation, propagation and inundation from various triggering mechanisms, including single or multi-causative sources (from large subduction to more local earthquakes generated in tectonically complex environments, from subaerial/submarine landslides to volcanic eruptions and atmospheric disturbances),
• Deterministic and probabilistic tsunami hazard, vulnerability, and risk assessments, including a multi-hazard perspective,
• Forecasting tsunamis using emerging technologies, such as artificial intelligence,
• Early warning and monitoring, emphasizing innovative marine and seafloor observation methods, sensors and data processing techniques to improve the early characterization of tsunami sources and detection,
• Societal and economic impacts of tsunami events on coastal communities,
• Hazards perceptions, communication and engagement,
• Present and future challenges related to global climate change (e.g., the impact of sea level rise).

The overall goal of this session is to enhance our understanding of the tsunami phenomenon and to strengthen our capacity to build safer and more resilient tsunami communities. The session welcomes both specialized and multidisciplinary contributions covering any of the topics mentioned above, including observation databases, real-time networks, numerical and experimental modeling, hazard-vulnerability-risk assessments, and operational tools and procedures for more effective warnings.

In a warming world with rising sea levels the densely populated North Sea coasts are becoming increasingly more susceptible to more intense extreme wave events. Therefore, it is crucial to reconstruct past event intensities and chronologies to better assess coastal risks.Unfortunately, our knowledge of the impact of past storm surges and tsunamis on the North Sea coasts is still limited. Geological investigations, including onshore and offshore studies and modelling approaches, can enhance our understanding of the impacts that such events have had in the past, their recurrence through time and the hazard they pose. This session welcomes contributions on all aspects of (paleo-)tsunami and (paleo-)storm surge research, including studies that use established methods or recent interdisciplinary advances to reconstruct records of past events, or forecast the probability of future events.

Remote sensing and Earth Observations (EO) are used increasingly in the different phases of the risk management and in development cooperation, due to the challenges posed by contemporary issues such as climate change, and increasingly complex social interactions. The advent of new, more powerful sensors and more finely tuned detection algorithms provides the opportunity to assess and quantify natural hazards, their consequences, and vulnerable regions, more comprehensively than ever before.

Several agencies have now inserted permanently into their program the applications of EO data to risk management. In fact, EO revealed fundamentals for hazard, vulnerability, and risk mapping from small to large regions around the globe, during the pre/post-hazards, the occurrence of disasters, the emergency response and recovery phases. In this framework, the Committee on Earth Observation Satellites (CEOS) has been working for several years on disaster management related to natural hazards (e.g., volcanic, seismic, landslide and flooding ones), including pilots, demonstrators, recovery observatory concepts, Geohazard Supersites, and Natural Laboratory (GSNL) initiatives and multi-hazard management projects. Many case studies can be taken into account for natural hazards processes such as landslides, floods, seismic and tectonic studies, infrastructure damages and so on.

The session is dedicated to multidisciplinary contributions focused on the demonstration of the benefit of the use of EO for natural hazards and risk management. The research presented might focus on:
- Addressed value of EO data in hazard/risk forecasting models
- Innovative applications of EO data for rapid hazard, vulnerability and risk mapping, the post-disaster recovery phase, and in support of disaster risk reduction strategies
- Development of tools for assessment and validation of hazard/risk models
The use of different types of remote sensing data (e.g. thermal, visual, radar, laser, and/or the fusion of these) or platforms (e.g. space-borne, airborne, UAS, drone, etc.) is highly recommended, with an evaluation of their respective pros and cons focusing also on future opportunities (e.g. new sensors, new algorithms).

Early-stage researchers are strongly encouraged to present their research. Moreover, contributions from international cooperation, such as CEOS and GEO initiatives, are welcome.

SAR remote sensing is an invaluable tool for monitoring and responding to natural and human-induced hazards. Especially with the unprecedented spatio-temporal resolution and the rapid increase of SAR data collections from legacy SAR missions, we are allowed to exploit hazard-related signals from the SAR phase and amplitude imagery, characterize the associated spatio-temporal ground deformations and land alterations, and decipher the operating mechanism of the geosystems in geodetic timescales. Yet, optimally extracting surface displacements and disturbance from SAR imagery, synergizing cross-disciplinary big data, aggregating useful information by multimodal remote sensing fusion, and bridging the linking knowledge between observations and mechanisms of different hazardous events are still challenging. Therefore, in this session, we welcome contributions that focus on (1) new algorithms, including machine and deep learning approaches and multi-modal/platform integration, to retrieve critical products from SAR remote sensing big data in an accurate, automated, and efficient framework; (2) SAR applications for natural and human-induced hazards including such as flooding, landslides, earthquakes, volcanic eruptions, glacial movement, permafrost destroying, mining, oil/gas production, fluid injection/extraction, peatland damage, urban subsidence, sinkholes, oil spill, and land degradation; (3) multimodal remote sensing fusion to enhance information extraction related to hazards, agriculture, forestry, land management, and environmental monitoring; and (4) mathematical and physical modeling of the SAR products such as estimating displacement velocities and time series for a better understanding on the surface and subsurface processes.

Interferometric Synthetic Aperture Radar (SAR, InSAR) has boomed into an exceptionally potent tool for quantifying large-scale deformation with high spatial resolution. The last decade has witnessed a remarkable surge in the SAR satellite market, featuring various satellites like Sentinel-1, ALOS-2, and commercial counterparts. This wealth of SAR and InSAR results present a huge opportunity to improve our understanding of hazard processes across various temporal and spatial scales, including earthquakes, volcanic eruptions, landslides, glacier movements, underground fluid changes, sea-level rise, tsunamis, and more.
This session will explore innovative SAR/InSAR processing methodologies and illuminate fresh perspectives on the underlying physics governing these geohazards. We welcome contributions that encompass a wide range of topics, including but not limited to: (1) ingenious algorithms to mitigate SAR/InSAR errors, incorporating state-of-the-art tools such as deep learning; (2) advanced processing strategies for SAR big data; (3) natural hazard applications with SAR/InSAR and other complementary geophysical datasets like GNSS and seismic waveforms; (4) hazard assessments and disaster risk reduction in terms of vulnerability, capacity, and resilience.

European Ground Motion Service (EGMS) has significantly improved the ability to monitor and study geohazards using InSAR (satellite interferometry) data since its products became available for download in mid-2021. These interferometric products are provided by the Copernicus Land Monitoring Service (CLMS) under the responsibility of the European Environment Agency (EEA). EGMS overcomes the long-standing challenge of complex SAR (synthetic aperture radar) image processing, making ground displacement monitoring accessible to a wider range of users. EGMS provides millimetre-accurate measurements, which are available for download via the EGMS platform. EGMSdelivers full-resolution velocity and displacement time series for both ascending and descending satellite orbits (L2a product), aligned with the GNSS reference network within a common reference frame (L2b product), and computed displacement vectors in the vertical and E-W directions (L3 products), with a spatial resolution of 100 x 100 meter.
In this session, we welcome contributions that use EGMS data to monitor and analyse different kinds of geohazards. Topics of interest include subsidence, slow-moving landslides, sinkholes, groundwater and hydrocarbon exploitation, gas storage activities, mining impacts, volcanic activity, and many more. Or studies that transform EGMS into analysis ready products for e.g. coastal studies or climate change estimations. We also encourage studies that explore the impact of these geohazards on critical infrastructure and buildings, or that integrate EGMS data with other methods for improved geohazard assessment. We aim to highlight the versatility and value of EGMS data in understanding and mitigating the risks associated with natural and man-made induced geohazards. Contributions demonstrating innovative applications, cross-disciplinary approaches and case studies with practical implications are particularly welcome.

Wildfires pose a significant and growing threat to both human populations and the environment. Climate change exacerbates this risk by increasing the frequency, duration, and severity of wildfires. Rising temperatures, prolonged droughts, and shifting weather patterns create conditions more conducive to wildfire spread, expanding the range of vulnerable areas and turning wildfires into a complex global challenge.
The availability of high-resolution, geo-referenced digital data underscores the need for advanced tools to model wildfire dynamics. A critical task is transforming these vast datasets into actionable insights for stakeholders. Recent advancements in computational science, particularly in the development of innovative algorithms, are essential for understanding and addressing wildfire behaviour and vulnerability.

This session aims to bring together experts from geosciences, climatology, forestry and territorial planning to enhance our understanding of these critical fire-related dynamics and to explore innovative strategies for mitigation and resilience. By fostering interdisciplinary collaboration, we seek to advance the science of wildfire prediction, prevention, and post-fire recovery, ultimately contributing to more effective responses to the growing threat posed by wildfires in a changing climate.

We welcome contributions on topics such as:
• Methodologies for recognizing, modelling, and predicting wildfire spatio-temporal patterns.
• Pre- and post-fire assessments, including fire mapping, severity evaluations, and risk management.
• Long-term analysis of wildfire trends in relation to climate change and land use changes.
• Fire spread modelling and studies on fire-weather relationships.
• Post-fire vegetation recovery and phenology.
Join us in advancing the study of wildfires and developing strategies to mitigate their impact.

Recent wildfires have underscored the urgent need for a paradigm shift in how we allocate resources to wildfire risk management. While fire suppression remains critical, governments must prioritize and allocate more resources to wildfire prevention. Effective wildfire prevention requires a comprehensive approach to managing the wildland-urban interface (WUI), which is increasingly vulnerable to wildfire threats. This session aims to provide an in-depth overview of the current advancements in wildfire risk management within the WUI.
We encourage submissions covering a wide range of topics, including vulnerability and risk assessment methods, damage assessment approaches, studies on local adaptation strategies and vulnerability reduction, participatory methods, community and infrastructure resilience, public awareness and education, community preparedness, household self-assessment, stakeholder engagement, disaster risk reduction tools, emergency response, recovery, and lessons learned.
Moreover, while wildfires are a well-known risk in countries such as Portugal, Greece, and Australia, they represent an emerging threat in others, including Central and Northern Europe. As climate change exacerbates wildfire risks, countries with limited experience will face these challenges more frequently. We particularly welcome case studies from around the world, especially from regions with limited experience in managing wildfires in the WUI. By sharing diverse experiences and strategies, we aim to foster a comprehensive understanding of wildfire risk management and promote effective, globally applicable solutions.
This session is endorsed by the European project FIREPRIME (a pan-European program for wildfire-prepared communities) and the Austrian Waldfonds Project REVEAL (Local vulnerability assessment for buildings in Austria).

Forest fires are a serious threat throughout Europe and cause significant environmental and economic damage. They are becoming more intense and widespread as a result of climate change, particular forestry practices, deteriorating ecosystems and rural depopulation.
The European Commission is dedicating a great effort to support research actions, namely through TREEADS, SILVANUS, FIRE-RES, FirEUrisk and Firelogue projects aiming to contribute to solving major societal challenges around the growing problem of wildfires.
• TREEADS is based on state-of-the-art, high-TRL products united into a holistic Fire Management Ecosystem incorporating several innovative technologies and systems to optimise and reuse the available Socio-technological Resources in Prevention and preparedness, Detection and response, Restoration and adaptation.
• SILVANUS aims to provide a climate resilient forest management platform to prevent and limit the spread of forest fires and relies on environmental, technical and social sciences experts to support regional and national authorities responsible for wildfire management.
• FIRE-RES aims to implement an Integrated Fire Management approach and support the transition toward more resilient landscapes and communities to Extreme Wildfire Events in Europe. Moving on four main pillars (Extreme Wildfires’ behaviour and drivers, landscape and economy, emergency management, communication, and risk awareness) the project has been developing 34 Innovation Actions to allow the integration of fire management measures.
• FirEUrisk has developed a roadmap for integrated and holistic wildfire risk management and has produced a methodology to assess the various components of fire risk. It has proposed a methodology to classify vegetation and map it as a potential fuel for the entire European Territory, analysed several major fires that occurred in Europe in the past years, proposed guidelines for training firefighters and modelled future climate and socio-economic scenarios to assess the needs in fire risk management changes.
• Firelogue aims to synthesise research results and to integrate multiple perspectives on wildfire risk management by focusing on justice aspects. Addressing questions around distributive, procedural and restorative justice allows a better understanding of the implications of different measures, potentially lacking voices that need to be heard as well as efforts that may be needed to balance benefits and burdens.

Geologic materials, including rocks, soils, dusts, volcanic ashes, and cosmic dust, may contain elevated concentrations of elements and minerals which pose risks to human health and can be classified as toxic contaminants. These are released into the air by both natural processes (e.g., rock weathering, volcanic activity) and human disturbance of rock and soils for mining and construction works.
Exposure to mineral dust is a significant global contributor to many diseases. Although occupational diseases have declined in many regions due to the adoption of more strict regulations, the combined effects of ambient and household air pollution are associated with 6.7 million premature deaths annually, 89% of which occurred in low- and middle-income countries (WHO, 2022). Current research on hazardous mineral dusts is focused mainly on asbestos and elongated mineral particles, silica, silicates (i.e., erionite, talc, kaolinite), carbon particles, Ti- and Fe- oxides, volcanic ashes, cosmic dusts, and more in general composite dusts. Sustainability-oriented research in the frame of critical resource mining aims to develop innovative solutions to tackle the environmental dispersion of inhalable particulates, including conversion of hazardous wastes into non-hazardous and reusable new materials. Policymaking plays a crucial role in regulating exposure to potentially hazardous geological materials, through establishing safety standards, monitoring compliance, and addressing the management of hazardous waste sites. Effective policies can drive innovation and encourage the development of safer alternatives, as well as promote the mitigation of risks associated with natural and industrial sources of hazardous mineral dusts. The goal is to develop an integrated occupational and environmental approach (exposome) to control health hazards and raise awareness of the associated social and environmental impacts.
We invite submissions addressing all aspects of the occurrence of hazardous mineral dusts and their environmental, occupational, and non-conventional exposures, ranging from local to global scales. Contributions are welcome in the fields of medical and environmental mineralogy, geology, chemistry, medicine and health sciences, risk assessment, public health and regulation. We also encourage contributions focusing on risk mitigation, new solutions and future perspectives for these important materials.

Natural radioactivity fully affects our environment as a result of cosmic radiation from space and terrestrial sources from soil and minerals in rocks containing primordial radionuclides as Uranium, Thorium and Potassium. Among the terrestrial sources, Radon (222Rn) gas is considered the major source of ionising radiation exposure to the population and an indoor air pollutant due to its harmful effects on human health (cancerogenic, W.H.O.). Also, artificial radionuclides from nuclear and radiation accidents and incidents provide an additional contribution to the environmental radioactivity.
This session embraces all the aspects and challenges of environmental radioactivity including geological surveys, mineral and space resources exploration, atmosphere tracing with greenhouse gases and pollutant, groundwater contamination and a specific focus on radon hazard and risk assessment.
Studies about the use of fallout radionuclides as environmental tracers and the relevance of the radioactivity for public health, including the contamination from Naturally Occurring Radioactive Materials (NORM), are welcome.
Contributions on novel methods and instrumentation for environmental radioactivity monitoring including portable detectors, airborne and drones’ surveys and geostatistical methods for radioactivity mapping are also encouraged.

The purpose of this session is to: (1) showcase the current state-of-the-art in global and continental scale natural hazard risk science, assessment, and application; (2) foster broader exchange of knowledge, datasets, methods, models, and good practice between scientists and practitioners working on different natural hazards and across disciplines globally; and (3) collaboratively identify future research avenues.
Reducing natural hazard risk is high on the global political agenda. For example, it is at the heart of the Sendai Framework for Disaster Risk Reduction and the Paris Agreement. In response, the last decade has seen an explosion in the number of scientific datasets, methods, and models for assessing risk at the global and continental scale. More and more, these datasets, methods and models are being applied together with stakeholders in the decision decision-making process.
We invite contributions related to all aspects of natural hazard risk assessment at the continental to global scale, including contributions focusing on single hazards, multiple hazards, or a combination or cascade of hazards. We also encourage contributions examining the use of scientific methods in practice, and the appropriate use of continental to global risk assessment data in efforts to reduce risks. Furthermore, we encourage contributions focusing on globally applicable methods, such as novel methods for using globally available datasets and models to force more local models or inform more local risk assessment.

Natural hazards pose serious threats to human health, settlements and the environment. The nature of impacts can be monetizable or hard to measure through economic metrics. Impacts can occur immediately due to the effects of a physical forcing or might persist, evolve and aggravate or resolve in time.

This session aims at gathering researchers interested in the scientific advances related to the multiple facets of natural hazard impacts, i.e., direct, indirect, tangible and intangible losses.

The session welcomes novel approaches to address impact modelling, data analysis, uncertainty analysis, calibration/validation and theoretical frameworks across all natural hazard types, e.g., floods, droughts, earthquakes, wind storms etc.. The topics include but are not limited to:
- comprehensive assessment of the economic impacts of natural hazards, emphasizing the importance of robust cost evaluations for informed decision-making in disaster risk reduction, hazard management, cost-effectiveness and efficiency of risk reduction strategies, and climate change adaptation planning.
- cascading impacts from direct losses to systemic indirect losses, e.g., business interruption, disruptions to critical services.
- indirect and intangible impacts of natural hazards, which are increasingly significant in today’s interconnected socio-technological world. These include loss of irreplaceable items or ecosystem services, and the impacts on physical and mental health. Special attention will be given to the effects on specific population groups, such as socially vulnerable communities, and the long-term health impacts of climatic stressors. Given the complex nature of these impacts, the session will also focus on novel systemic approaches to assess the interplay of hazards with social vulnerability, particularly through the use of advanced data analysis techniques such as machine learning and spatial disaggregation.
- challenges posed by the lack of empirical data and the diversity of methodologies currently applied to assess the costs associated with different natural hazards and impacted sectors, e.g., agriculture, population, buildings etc.

Submissions are encouraged from those engaged in both theoretical and practical aspects of impact assessment, with a view to fostering interdisciplinary dialogue and advancing the field. Outstanding contributions will be highlighted as “solicited talks,” emphasizing their importance to the session’s goals.

Natural hazards, including multi-hazards, compound events and connected extremes, can put pressure on critical infrastructure systems and industry beyond their design specifications. Accidents or disruptions can lead to disastrous consequences and may have far-reaching impacts beyond the directly affected area. Especially in the light of ongoing climate change, urbanization, industrialization, and an ever increasing interconnected society, it is crucial to understand and incorporate such effects into planning and systemic risk assessments as well as to prepare for extreme events and worst-case scenarios .
This session aims to increase our understanding and modelling capabilities of the risk of natural-hazard triggered technological accidents and infrastructure failures with potentially severe societal, economic or environmental impacts. We invite contributions considering all aspects of NaTech risk, including but not limited to the topics described below:
* Methods for improving our understanding and monitoring capabilities, exposure and vulnerability of critical entities to (multiple) natural hazards.
* Data collection/database development and mapping of hazards, exposure and vulnerability of critical entities
* Collecting and analyzing empirical data of past events/disruptions to inform, validate and improve risk modelling.
* Methods for assessing and modelling natural-hazard triggered accidents and disruptions
* Methods for assessing and modelling direct, indirect, tangible, intangible or systemic impacts of natural-hazard triggered accidents or disruptions including complex, compounding and cascading effects
* Methods for improved impact forecasting capability and scenario building for enhanced stress testing of critical entities
* Methods for improved cross-discipline, cross-sector and cross-boundary disaster risk management and governance
* Methods to enhance understanding and knowledge and situational awareness of disaster-related risks by citizens

This session aims to advance the knowledge regarding systemic drought risks and their management through a holistic, multi-sectoral approach. If your research addresses any of the following challenging statements—whether to support, challenge, or redefine them—we warmly invite you to submit an abstract to our session.
1. All drought impacts arise from compound events
2. Droughts should be seen as a continuum of varying balances in water needs/availability, not isolated events
3. Drought hazard-impact relations are non-linear and multi-variate
4. Quantifying cascading drought risks and impacts is impossible
5. Early warnings alone are inadequate for effective drought risk mitigation
6. Focusing on the vulnerability of only one type of impacted system is insufficient for water management and adaptation
7. There is no single form of drought resilience
8. Low-risk perception, reduced awareness, and a biassed long-term drought memory hinder effective drought risk reduction
9. Political factors are the primary barriers to effective drought risk management
10. Drought impacts are always a failure of water management

With this inter- and transdisciplinary session, we aim to bring together scientists and practitioners from diverse fields, including socio-hydrology, hydrosocial studies, behavioral science, disaster risk management, and adaptation, to contribute conceptual advancements, new methodological approaches, and empirical studies.

The increasing frequency and severity of climate hazards such as drought and extreme heat stress demand effective strategies for risk management and resilience building. Leveraging artificial intelligence (AI) offers significant advantages for detecting, attributing, and establishing the causality of extreme and compound events, enabling more precise and timely responses. This session will explore cutting-edge approaches for climate hazard management by using AI to enhance the accuracy and reliability of climate information, prediction, observations and visualisations within an interdisciplinary framework, focusing on innovative methodologies for addressing climate hazards.

The session will emphasise the contributions of AI to the study of climate hazards by refining indicators, improving the accuracy of climate information, and advancing visualisations and communications. Additionally, participants will discuss AI’s role in optimising strategies for climate financing and ensuring rigorous compliance and reporting practices. By convening experts and practitioners, the session aims to integrate cutting-edge AI technologies with practical ones for risk mitigation, hazard attribution, and adaptation, strengthening resilience against the backdrop of evolving climate realities.

We welcome contributions from researchers, practitioners, policymakers, and interdisciplinary teams at the intersection of climate science, environmental policy and AI. We encourage submissions that offer innovative solutions, theoretical advancements, and practical applications, as well as case studies that showcase the integration of AI in climate risk management and communication. We also invite papers addressing the challenges and limitations of using AI in this domain, discussing policy and practice implications, and proposing frameworks for ethical and equitable AI-driven climate strategies. Collaborative projects and cross-disciplinary insights that bring new perspectives to climate resilience are highly encouraged.

The global interconnection of social systems often causes hazard impacts to exceed regional boundaries or socioeconomic sectors, propagating and amplifying their losses. In turn, successful disaster risk reduction and climate adaptation strategies engage citizens and stakeholders to attune to their conditions, capacities, and context. Urban areas are especially vulnerable to hazards, as they act as nodes in global networks, locate in exposed settings (e.g., in coastal areas or mountain slopes), and concentrate physical and social assets. Intensifying urbanisation trends and climatic change mean these positive and detrimental interactions will increase.
This session provides a forum for research that integrates citizens' and stakeholders’ knowledge in risk analysis and governance. We aim to collect recent scientific advances in the multifaceted societal contributions to climate vulnerability, exposure, and risk assessment and reduction. We are particularly interested in research that bridges participatory methods with risk assessment and policy development, including crowdsourcing risk information, volunteered geographic information, citizen and participatory science, and the integration of local and non-academic knowledge in scientific investigations. Additionally, we welcome other relevant applications of participatory research and policymaking in disaster risk assessment and reduction, and climate adaptation.
We call for experiences in citizen-centred and science-based research and policy, bringing evidence on:
- Transdisciplinary approaches and integrative methods in vulnerability and risk analysis, disaster risk reduction, and climate adaptation that combine knowledge from both academic and non-academic stakeholders.
- Innovative methods and data sources that leverage citizen and stakeholder knowledge into risk frameworks, including mixed methods research and non-academic knowledge integration with remote sensing, climate models, simulations, machine learning, and similar technologies.
- The interaction between societal dynamics and natural hazards, including the influence of urban development on the occurrence and impact of single and multiple natural hazards.
- Case studies and lessons learned that demonstrate the active involvement of citizens and other stakeholders in the design or the implementation of risk assessment frameworks, risk mitigation strategies, and governance actions.

Disasters caused by natural hazards often lead to significant and long-lasting, systemic disruptions of economic, social and ecological systems. These challenges are expected to intensify, propelled by the complex interplay of climate change and systemic risks. To improve both ex-ante disaster risk reduction and ex-post recovery, increasing attention is placed on strengthening the “disaster resilience” of communities, cities, regions and countries. However, a lack of empirical data and evidence, a high diversity in definitions, measurement approaches and applications of disaster resilience make it difficult to systematically understand the dynamics of resilience. This hinders targeted resilience strengthening investments and actions across all levels, that are increasingly demanded in the context of climate change adaptation, disaster risk reduction and sustainable development.

This session aims to discuss and improve the understanding of disaster resilience to various natural hazards (e.g., floods, droughts or wildfires) including compound events across spatial and temporal scales taking a systems approach. We encourage contributions focusing on the following topics:
• exploration of both process- and outcome-based evaluation methods, as well as innovative modeling approaches, including the use of remote sensing and climate data.
• concrete interventions (i.e. climate-smart agriculture, VSLA, field schools), adaptive planning processes, socio-technological solutions (i.e. EWS, NBS, built infrastructure) and the pivotal roles of social capital, adaptive capacity in fostering sustainable resilience and adaptation strategies.
• cross-learnings and linkages between natural hazard resilience and other systemic, complex contexts.
We encourage contributions that encompass local case studies, regional insights and global perspectives from multi- and transdisciplinary research endeavors.

Urban development has significantly moulded its surrounding environment over the last few centuries, impacting topographies, drainage pathways, river morphologies, coastal shoreline dynamics and climate patterns. These urban legacies can influence both the drivers and the preparatory conditions of “natural” hazards like floods or landslides. Urban expansion further amplifies the exposure and/or the vulnerability of populations to such hazards, especially in low-to-middle income regions where there is often a lack of urban planning and proper engineering design.
Despite the ubiquitous influence of urbanization on environmental processes, quantifying its relative role is challenging due to the great spatio-temporal variability of its impacts. This often results into the omission of a dynamic urban factor into hazard modelling, hindering, as a consequence, the identification of improved urban hazard mitigation strategies and the measure of their effectiveness.
As we navigate an era of environmental changes, with a projected urban population growth from 55% in 2018 to 68% by 2050, scientists must be prepared to offer evidence-based insights into alternative pathways that consider the mutual interactions between the natural environment, social dynamics, and urban development. This session thus aims to foster collaborations amongst geoscientists, social scientists and policymakers to bring evidence on:
The urban impact on the occurrence of natural hazards and multi-hazards;
Modelling strategies to include such evidence of urban impact for a better prediction or mitigation of (multi-)hazard occurrence;
Mitigation strategies that have been or show potential to be successful in reducing the occurrence and/or consequences of natural hazards by modifying detrimental urban practices. Such strategies might include local (e.g., traditional or indigenous) knowledge and practices.
Social and political barriers encountered in changing and/or enforcing urban management despite the existence of better disaster-resilient alternatives.

Resilient planning and investments have become essential for ensuring sustainable development and economic stability in the context of escalating climate-induced hazards. The designing of resilient investments are designed to anticipate, withstand, and recover from various shocks, disruptions, and stresses, by reducing vulnerability and enhancing adaptive capacity. This session explores integrating resilience into investment decisions by emphasising the importance of a systems approach that encompasses prevention, preparedness, response, and recovery. It also highlights the critical role of transitions in building resilience, focusing on how adaptive strategies and innovative solutions can facilitate the shift towards more resilient and sustainable communities. By addressing the interconnectedness of hazards, investments, and transitions, the session underscores the necessity of interdisciplinary collaboration and forward-thinking policies to foster long-term resilience and community well-being. The session welcomes theoretical and applied studies on initiatives to address climate-induced hazards and promote resilient Resilient investments have become essential for ensuring sustainable development and economic stability in the context of escalating climate-induced hazards. Resilient investments are designed to anticipate, withstand, and recover from various shocks, disruptions, and stresses by reducing vulnerability and enhancing adaptive capacity. This session explores integrating resilience into investment decisions by emphasising the importance of a systems approach that encompasses prevention, preparedness, response, and recovery. It also highlights the critical role of transitions in building resilience, focusing on how adaptive strategies and innovative solutions can facilitate the shift towards more resilient and sustainable communities. By addressing the interconnectedness of hazards, investments, and transitions, the session underscores the necessity of interdisciplinary collaboration and forward-thinking policies to foster long-term resilience and community well-being. The session welcomes theoretical and applied studies on initiatives to address climate-induced hazards and promote resilient planning and investments, ultimately enhancing governance and institutional policy mechanisms.

The rising concept “Climate resilience” can be defined as the capacity of actors, economies, ecologies or social-ecological systems to cope with and adapt to hazardous events associated with climate change and to transform in ways that secure possibilities for future generations to do it alike. Increasing studies are warning that climate change is a major threat to human societies and is projected to cause even greater loss and damage in near future, even if the currently planned mitigation goals are met. The question of how to maintain and enhance social resilience to climate change impacts is of utmost importance. Addressing climate resilience has become a key priority in fields like civil protection, urban planning, health care and others.
Against this background, this session aims to promote research exchanges of scholars from multiple disciplines on the status and dynamics of climate resilience studies. The relevant topics include, but are not limited to, the following:
• Theoretical explorations of scientific frameworks and components in climate resilience studies.
• Reviews of the research progresses in the field of climate resilience
• Methodological development for assessing and/or modeling climate resilience
• Local case studies, regional- and global-level perspectives of social resilience to climate impacts
• Particular focus on the resilience to climate-related hazards, e.g. flood, heat, drought, sea level rise
• Comparison studies of climate resilience over space and time
• Social, economic, technological, and political strategies for resilience building at all scales of society
• Practical implementations of resilience measures in various sectors, e.g. food, water and agriculture, transportation infrastructure, energy system, human settlements
• Possible future scenarios for enhancing social resilience to climate impacts

The vast majority of Long Linear Infrastructures (LLIs) were designed several decades ago, intended to operate in a climatic context vastly different from the one we face today. Global warming has led to the intensification of extreme meteorological events and has altered precipitation and temperature patterns, significantly increasing the vulnerability of LLIs to natural hazards.
Ensuring high levels of functionality and safety, particularly for the oldest yet still vital LLIs, has become an ongoing challenge. This challenge has driven a substantial increase in investments directed toward maintenance and the reassessment of associated risks.
In an era marked by climate change and committed to sustainability, it is clear that a new paradigm for the long-term management of LLIs is urgently needed. This approach must be multidisciplinary and multi-technological, capable of addressing the extensive spatial distribution of LLIs and the multitude of hazards they face, such as landslides, floods, drought cycles, and more.
We invite presentations on the following topics:
a. Monitoring Approaches and Sensing Techniques: Cutting-edge methods to detect, map, and measure natural hazards impacting LLIs and to assess the structural health of LLIs.
b. Modeling Strategies: Advanced techniques that leverage data to understand and predict processes leading to localized or widespread damage under evolving climate conditions.
c. Risk Assessment and Management Frameworks: Development of comprehensive frameworks through applications of big data analytics and machine learning that integrate real-time monitoring and predictive analytics to assess vulnerability, predict risks, and enhance the resilience of LLIs in the face of natural hazards.
e. Sustainable Design and Retrofitting: Strategies for retrofitting existing LLIs to improve their resilience and sustainability in light of future climate uncertainties.
f. Interdisciplinary AI Applications in LLIs: Exploring AI-driven solutions that merge engineering, environmental science, and urban planning to enhance LLI management under climatic shifts. This topic seeks innovative contributions on AI-enhanced simulations, lifecycle tools, and adaptive systems for robust infrastructure performance.
We encourage submissions that explore these topics and contribute to the development of innovative, sustainable solutions for the long-term management of LLIs in a changing climate.

The overall goal of this session is to share innovative approaches to multi-(hazard) risk assessments, including research on the characterisation of risk components (i.e., hazard, exposure, vulnerability, and capacity) in a multi-(hazard) risk setting, as well as novel applications of multi-hazard thinking in disaster risk reduction (DRR) and climate change adaptation.

Effective DRR requires evaluating multiple hazards and their interactions, as endorsed by the UN's Sendai Framework and reflected in the IPCC’s AR6 cycle. These frameworks highlight the need to understand how physical and societal factors shape disasters in a changing climate. Multi-(hazard) risk assessments examine how interactions and overlaps among hazards affect exposure and vulnerability, especially in the context of climate change and slow-onset hazards like pandemics, where dynamic changes are challenging to quantify.

This session aims to profile a diverse range of multi-(hazard) risk and impact approaches, including hazard interactions, multi-vulnerability studies, and multi-hazard exposure characterisation. By addressing the entire risk assessment chain—including risk analysis, evaluation, and management—this session seeks to identify potential research gaps, synergies, and opportunities for collaborations.

We encourage abstracts that present original research, case studies, and commentary throughout the disaster risk management cycle on topics such as: (i) multi-(hazard) risk methodologies addressing exposure, vulnerability, and impacts; (ii) tools for multi-(hazard) risk assessment, management, and inclusive risk-informed decision-making; (iii) methodologies for defining and managing multi-hazard scenarios for (near) real-time applications; (iv) cross-sectoral approaches to multi-(hazard) risk, incorporating physical, social, economic, and/or environmental dimensions; (v) uncertainty in multi-(hazard) risk and impact assessment; (vi) evaluation of multi-(hazard) risk under future climate conditions and slow-onset hazards, including pandemics; (vii) implementation of DRR measures from a multi-hazard perspective, focusing on synergies and conflicts between measures for different hazards; (viii) multi-hazard early warning systems; (ix) climate and impact attribution studies of complex extremes to better understand the role of climate change, exposure, and vulnerability concerning disaster impacts.

Impacts of the nature hazards are not limited to a specific geosphere but often impact multiple geospheres, subsequently affecting human life significantly. Natural hazards in the Earth system, such as earthquakes, tsunamis, landslides, volcanic eruptions, cyclones, and extreme weather, originate primarily in the lithosphere and troposphere, but they also affect the upper atmosphere and ionosphere. Monitoring the atmospheric and ionospheric disturbances associated with these hazards is beneficial for nowcasting their occurrences.

Solar activities, on the other hand, can induce geomagnetic storms that disturb the atmosphere through magnetosphere-ionosphere coupling. These disturbances can impact satellite operations, the precision and reliability of global navigation satellite systems, and may cause damage to power supply networks.

Therefore, there is an urgent need for instrumental arrays to monitor useful signals, novel methodologies to retrieve associated data, and numerical simulations to understand the interaction between the lithosphere (including the hydrosphere), atmosphere, and space (LAS).

In this session, we invite scientists interested in studying the interactions between the lithosphere (including the hydrosphere), atmosphere, and space. This includes, but is not limited to, natural hazards. The interaction between the multiple geospheres can be excited by numerous potential sources, ranging from lithospheric activities in the Earth’s interior to solar activities in the space beyond the Earth system. We welcome observations of parameters in one geosphere interacting with others, methodologies for detecting signals related to changes in other geospheres, and the construction of numerical models spanning multiple geospheres. The session aims to integrate scientists from distinct fields to improve and enhance our understanding of LAS interactions. Ultimately, this research aims to mitigate the loss of human life and property associated with natural hazards from both Earth and space.

Slow-onset events include multiple hazards like climate change, sea level rise, coastal erosion, riverbank erosion, drought, desertification, glacial retreat, soil degradation, ocean acidification, biodiversity loss etc. All these events are inherently land degradation processes and therefore, have a detrimental impact on livelihood and sustainability of the affected population. Even though they have a pervasive and long term impact, there is a tendency to give more importance to sudden events like earthquakes, landslides etc that cause large scale loss to life and property. This means that a concerted effort to develop risk reduction strategies for slow-onset events is lacking. International organizations such as the United Nations Framework Convention on Climate Change (UNFCCC) and the Sendai Framework acknowledge the limitations of our current risk reduction framework for slow-onset events. They agree that there are notable gaps in our understanding of these events and therefore, in developing effective disaster risk reduction plans. Thus, the proposed session aims to fill this gap by welcoming papers from around the globe that investigate various slow-onset hazards and their impact as land degradation processes. The session also aims to identify common strategies that can be developed into risk reduction approaches for slow-onset events.

Society faces immense challenges when natural hazards and disease outbreaks co-occur. Disasters associated with natural hazards are often also public health emergencies. For example, in the midst of the COVID-19 pandemic, the immediate response phase after natural hazard events was often complicated, because of travel restrictions and local lockdown measures. This arguably led to increased exposure to other hazards such as earthquakes (e.g. the 2020 Zagreb earthquake). Natural hazards can also trigger the outbreak of diseases, such as cholera and diarrhoea outbreaks following the devastating floods in Pakistan in August 2022. The co-occurrence of natural hazards and diseases creates cascading effects that worsen the overall impact. A limited understanding of these cascading impacts creates operational, ethical, and decision-making challenges for society, disaster management, and aid organisations.

Recent events underscore the critical need to enhance our scientific understanding of the complex interactions between natural hazards, society, public health and disease outbreaks. Equally pressing is the imperative to advance our modelling capabilities, enabling us to capture the nuances of risk stemming from multi-hazard scenarios and disease outbreaks. Additionally, we must deepen our grasp of the synergies and trade-offs inherent in disaster risk reduction measures when addressing this multifaceted challenge.

This session serves as a platform to bolster our understanding of the convergence of disasters, public health and disease outbreaks. We invite abstracts studying all aspects of this co-occurrence, such as cascading impacts, including health impacts that follow from natural hazards, difficulties that arise when natural hazards and diseases coincide, and challenges and lessons for adaptation management facing natural hazards and diseases. We are particularly keen to see new developments in measuring - for example through integration of remote sensing with public health and socio-demographic datasets - and modelling these interactions. Discussions on the compounding effect of climate change on health outcomes, and the spatial and temporal variability of exposures and vulnerabilities to these complex hazards are also strongly encouraged.

All the forecasts are connected to some level of uncertainty. When the forecast is applied to natural hazards, existing uncertainty may become critical, as significant changes in the forecasts may play a major role in the definition of risk reduction actions.

While this is pervasive across all natural hazards, significantly different approaches have been defined in the different disciplines of Earth Sciences, both in the definition of methods to quantify uncertainty, and in the selection of specific communication strategies for decision-makers or for the general public. Indeed, the need of accounting for and communicate uncertainty, coupled with the capacity of developing adequate models to this aim, strongly influenced how and at which level uncertainty has been included and communicated in forecasting models.
This session is dedicated to foster cross-discipline exchange of existing experiences as well as ongoing efforts in the quantification, communication, and use of uncertainty in decision-making along the different disciplines of Earth Sciences.

The increasing interconnections between socio-economic, technological, and natural systems have amplified risk complexity, raising the likelihood and impact of multi-hazard events. This highlights the urgent need to understand complex risk dynamics and develop effective adaptation strategies. Unlike single-risk assessments, multi-risk approaches offer a holistic understanding of risk interactions and compounding effects for better adaptation planning.

Emerging technologies such as artificial intelligence, digital twins, remote sensing, decision-support tools, and early warning systems are transforming systemic risk assessment and management. They offer new ways to understand multi-risk dynamics and enhance disaster risk management and climate adaptation strategies.

This session provides a platform to explore the latest technological advancements and innovations in systemic risk assessment across various sectors and regions. It will feature presentations and discussions highlighting the role of cutting-edge technologies in advancing systemic disaster risk management and climate adaptation planning.

We particularly encourage submissions of research, case studies, and practical applications that showcase how these technologies can provide valuable insights into the complexities of multi-risk dynamics, optimize decision-making, and enhance resilience-building efforts.

Potential research topics include, but are not limited to:

- Multi-Hazard Early Warning System and Impact-Based Multi-Hazard Forecasting, providing timely alerts for potential compounding hazards and risks.

- Decision-support tools, open source software and novel risk assessment methods co-developed with stakeholders to enhance the preparedness of first responders and decision-makers to multi-risk.

- Cutting-edge Artificial Intelligence and Machine Learning tools for multi-hazard, multi-sector risk and systemic risk management.

- Novel technologies for data collection and generation, including Large Language Models and remote sensing.

- Application of network science and digital twin technologies to model systems holistically, accounting for cascading and compounding dynamics.

- Innovative approaches in communications, knowledge-sharing and capacity building in multi-hazard risk assessment.

- Best practices enabling the transferability of the developed innovations to different territorial contexts and hazards (knowledge transfer).

Urban systems are complex, interconnected entities where physical, social, economic, and environmental factors interact dynamically. A holistic understanding of urban systems is essential for strengthening resilience to multi-hazard risks and climate-related hazards. It uncovers interdependent vulnerabilities and cascading effects, while also providing insight into how communities, institutions, and infrastructure respond and adapt to change.
This session explores advanced methodologies for multi-hazard risk assessment and climate adaptation in urban and metropolitan areas. Emphasizing multi-scale, interdisciplinary approaches, it aims to develop a comprehensive understanding of multi-hazard interactions and their impacts on urban systems. The session explores both quantitative and qualitative methods to model risks and vulnerabilities across physical, socio-economic, health, and environmental dimensions, addressing the complexities of emerging challenges. It encourages the development of effective risk management solutions and urban planning strategies that align with global initiatives such as the UN Sendai Framework and NextGenerationEU recovery plans.
We encourage submissions addressing i) methodologies for assessing dynamic urban vulnerabilities and exposure to multi-hazard risks, including climate change-induced hazards; ii) methodologies and tools for understanding cascading and compounding effects on physical, socio-economic, and environmental systems, and their implications for disaster risk reduction; iii) strategies and pathways for enhancing urban resilience through governance transformation, comprehensive risk management, and designing solutions for carbon neutrality and climate adaptation; iv) case studies that test multi-risk mitigation and adaptation strategies; v) decision-support tools for assessing and implementing mitigation actions in urban settlements; vi) urban labs and city-scale exercise for risk scenarios evaluation; vii) co-design, capacity building and development of tools addressing the non-technical actors of public institutions, stakeholders of civil society, and the population.

This session focuses on modelling approaches tackling multi-hazards, as well as multi-risks, considering their interdependencies, amplifying factors and cascading effects.
Multi-hazards and consequently multi-risks have gained wider attention over the past years but pose a challenge to the scientific community in quantifying their (local) impacts. Single hazard models that simulate local hazards such as flooding based on meteorological input data are applied commonly providing the base for better estimation of future risks (hazard*exposure*vulnerability). However, quantifying the effect of one hazard on the intensity of compound or consecutive hazard(s) poses a challenge since it depends on the intensities of each single event and the time lag between these two. Considering these challenges, simulating multi-risks and accounting for cascading effects adds another layer of complexities that are tackled differently.
Therefore, this session encourages studies focusing on tackling the interdependencies through modelling approaches, as well as studies focusing on the time dependency of consecutive events. As climate change is amplifying intensities and frequencies of extreme events, studies working on investigating the changes in frequency and intensity of mutli-hazards under different warming scenarios are highly encouraged to submit.

Hazardous phenomena such as landslides, debris flows, lava flows, tsunamis, earthquakes or floods, are pervasive in the Earth system and cause severe losses of life and property worldwide, every year. These phenomena tend to be extremely complex and may occur in relative isolation but also compounded with other phenomena, thus posing significant challenges for single- and multi-hazard assessments. If the interaction between hazard and the human environment is considered (e.g. water pumping and the availability of fresh water), the hazard quantification becomes even more complicated.

Generally, the data needed to quantify hazard are scarce (particularly for large, infrequent events) and as such purely data-driven methods have limited application. Hence, a comprehensive mapping of unobserved, yet likely or possible, events to properly quantify the hazard commonly relies on the use of computer models, or simulators. These simulators tend to be sophisticated, to capture the underlying physics, and, consequently, computationally-demanding. Thus, strategies to reduce the total number of simulations required for different purposes, like uncertainty quantification, model calibration, optimisation and/or forecasting, are constantly sought.

One popular strategy is the use of ‘surrogate models’ (e.g. statistical emulators, machine-learning techniques, etc.), which can be defined as computationally-cheaper, statistical models aimed at reproducing the behaviour of the simulator as closely as possible, so they can be used as a (fast) substitute of the latter. This turns, for instance, uncertainty quantification for probabilistic hazard assessment into a computationally-tractable problem.

In this session, we would like to collectively explore the recent application of surrogate models in quantitative single- and multi-hazard assessments, to better understand common and unique issues arising from different hazardous phenomena and/or local-to-regional contexts (e.g. diverse topographic and/or bathymetric configurations). Another key goal is discussing future developments in the area, for example, challenges in modelling systems with high-dimensional input-output spaces, with a vision of comprehensive hazard assessments contributing to effective and efficient risk management of these phenomena.

Thunderstorms often pose a significant risk to human life and damage to property and infrastructures through lightning, fast floods from heavy precipitation, hail and strong winds. On the other hand, lightning-induced wildfires (LIWs) are a central component of the fire regime in remote and mountainous regions, as well as a major component of wildfire crises, large wildfires and extreme fire events across the world. In addition, lightning strikes are a significant cause of tree mortality, especially in tropical forests. Therefore, lightning and thunderstorms not only cause direct and highly localized, short-term impacts, but lightning can have large and long-term effects on ecosystems and society.

We invite scientists interested in the relationships between lightning, environment and other natural hazards such as lightning fires and severe thunderstorms. We encourage researchers studying lightning-related topics with potential implications for humans and ecosystems to participate in this session. Thus, this session aims to gather a diverse profile of researchers to increase the awareness of the environmental aspects of lightning and multi-hazard interactions, as well as to identify research gaps, synergies and opportunities for future collaborations. We welcome diverse scientific contributions including (but not restricted to):
• Description of lightning occurrence, climatology, statistics, and associated environmental characteristics.
• Modeling, projections and nowcasting of lightning occurrence and thunderstorms.
• Lightning-induced wildfires, including their ignition, drivers, behavior, detection and modeling, extreme fires, dry lightning and long continuing current, natural fire regime in remote and populated regions, pyrocumulonimbus and lightning, etc.
• Lightning detection networks, observation of lightning, including from space-based sensors, and lightning, thunderstorm and lightning fire data products.
• Thunderstorms tracking, dynamics, types, behavior and severe weather.
• Impacts of lightning on ecosystems and society, such as tree injuries and mortality, effects of LIWs on the carbon cycle and climate feedbacks, human and animal causalities, and damages to infrastructures.

This session will delve into the utilization of Earth Observation (EO) for disaster risk reduction (DRR), highlighting its critical role in understanding and managing multi-(hazard-)risks. EO provides data that significantly enhances our ability to monitor and reduce the impacts of disasters on both global and local scales. Central to this is the availability of a tremendous archive of EO data and an expanding spectrum of new sensors at increasing spatial and temporal resolution. The growing volume of EO data requires novel data assimilation techniques to maximise the benefit for multi-(hazard-)risk assessment.

Our primary objectives for this session are to curate a high-quality collection of presentations showcasing the state-of-the-art in EO applications for DRR, facilitate a broad exchange of knowledge, datasets, methods, models, and best practices among scientists. Effective disaster risk reduction and the planning of resilient communities necessitate a comprehensive evaluation of multiple hazards and their interactions. This holistic approach is endorsed by frameworks such as the UN Sendai Framework for Disaster Risk Reduction (UNDRR).

We welcome abstracts that showcase innovative applications of EO data for DRR, particularly those addressing multi-(hazard-)risks. We look for applications involving EO data both in data-rich and -poor regions used to investigate multiple hazards and their interactions, characterize exposed elements and their vulnerability levels and dynamics within the context of compound, cascading and complex risk conditions. Additionally, we seek contributions that identify future research directions and challenges in EO for DRR. Topics of interest include the use of EO to assess socioeconomic processes relevant to understanding and reducing vulnerabilities, particularly in humanitarian contexts; improving our understanding of multi-(hazard-)risks, such as compound heat and drought events; and enhancing insights into hydroclimatic extremes and geophysical hazards through EO data.

Geo-hydrogeological hazards pose a serious threat around the world, compromising the safety of human life, the protection of economic activities, ecosystems and biodiversity, environmental and archaeological assets. Among natural disasters, those related to geo-hydrological phenomena, such as floods and slope instabilities, play a particularly critical role in mountainous regions. Surface landslides, rapid earth/debris flows, and soil erosion are the mass wasting phenomena most influenced by rainfall events over the slopes, while overflowing of water onto dry lands and sediment transport during high flow events are processes driven by hydrology at the catchment scale. The variations in intensity, frequency and duration of rainfalls due to climate change could translate into an exacerbation of ground effects and substantial increase in the risk in the urbanised areas, therefore in the costs associated with geo-hydrological phenomena. Gaining insight the factors that influence the development of a weather-related phenomenon and the impact on exposed elements and therefore assessing risk is essential for developing resilient communities capable of facing future climatic challenges.
We invite contributions on all facets of geo-hydrological hazard in the context of climate variability, exploring the theoretical aspects of prediction up to the consequent space-time landscape evolution and risk management. This includes studies on individual hazards, multiple hazards, or interactions and cascades of hazards. We also encourage contributions that explore the application of scientific methods in practice and the effective use of data to mitigate risks.

Contributions focusing on, but not limited to, novel developments and findings on the following topics are particularly encouraged, even presenting case studies:
- Characteristics of weather and precipitation patterns leading to extreme and high impact events;
- Advanced methodologies and cutting-edge techniques for predicting geo-hydrological phenomena, covering elements such as impact location, timing, magnitude, spatial evolution etc.;
- Ground effects assessment and landscape evolution in different risk contexts of both single and multiple events;
- Relationships between the climate change and the increasing hazard phenomena in their complexity and heterogeneity;
- Vulnerability and hazard mitigation procedures;
- Strategies for increasing preparedness, and self-protective response as preventive actions.

Both anthropogenic climate change and internal climate variability are affecting the uncertainty of climate risks associated with many natural hazards around the world. Anthropogenic climate change is expected to increase, the frequency and magnitude of droughts, heatwaves, flooding, wildfires, and tropical cyclones, with severe societal impacts. However, trends and risk vary regionally and are often associated with uncertainties in climate projections.

Understanding and accurately projecting the changes in these hazards, their compounding nature, and how they may interact with local socioeconomics and population changes over the coming decades and centuries requires conversations across a broad range of disciplines: physical sciences, climate risk-modelling, statistics and machine learning, geography and social sciences. Recent record breaking extreme weather events highlight the urgent need to improve our scientific understanding and modelling capacities for installing climate services, early warning schemes and adaptation measures to the future risk.

This session aims to showcase recent research progress investigating natural environmental hazards, improvement in modelling, and projections over decadal to century timescales. It will foster discussion to identify outstanding research questions and form new collaborations, for instance which hazards receive less attention in the community for specific geographical regions? Or what hazard sectors should work more closely with weather and climate scientists for progress to be made?

We invite contributions on the changing risk and prediction from natural hazards, including but not limited to studies of:
- Detection and attribution of climate hazards and impacts
- Climate Hazard and Impact Modelling
- Climate change trends in hazards on decadal to centennial timescales
- Drivers and Trends in Compound Weather Extremes
- Extreme Weather Early warning Systems
- Global weather and climate teleconnections and their links to environmental hazards and impacts

Compound extremes occur when multiple extreme events happen simultaneously or sequentially, often amplifying their impacts. Heatwaves and droughts, floods and cyclones, droughts and pests, extreme precipitation events and landslides, climate-related diseases and food insecurity are some examples of compound extremes. In low-income countries, these events can be particularly devastating due to limited resources and infrastructure. Compound extreme events, exacerbated by climate change, present profound challenges for low-income countries, threatening food security, water resources, livelihoods, and socio-economic development. Building resilience to these extreme events requires a comprehensive understanding of their underlying drivers, including climate variability, human activities, and socio-economic conditions.
This session seeks contributions that:
1) Examine the various dimensions of compound extremes, such as their frequency, intensity, duration, and spatial distribution, using advanced risk assessment approaches.
2) Propose innovative and cost-effective mitigation strategies, including early warning systems, flood/drought-resistant agricultural practices, and sustainable water management techniques, aimed at enhancing resilience and adaptive capacity in low-income regions.
By fostering interdisciplinary collaboration among researchers, policymakers, and stakeholders, this session aims to develop valuable insights and practical strategies for strengthening resilience to compound extremes in low-income countries, integrating scientific research with local knowledge and community involvement.

Atmospheric hazards can cause significant socio-economic damages and therefore it is of paramount importance that their impacts and historical variability are well understood by those in the insurance and financial sectors. These groups are expected to deal with climate risk on multiple timescales, for example through enhanced risk assessments.

As the climate continues to change, an understanding of changes to frequency, severity, exposure, and vulnerability are all required for a multitude of different perils. Furthermore, attention needs to be paid to emerging risks, and also to global regions that may be more vulnerable in the future. This understanding will aid planning and potential operational changes for those in the private sector.

This session will explore studies on historical impacts, modelling of hazards, understanding of variability, risks from climate change, and quantifications of exposure and vulnerability. Submissions are encouraged from both academic studies, and research projects from within the insurance and financial sectors. In particular, submissions are encouraged that focus on:

- Quantification of historical variability in hazards around the globe
- High resolution modelling of impactful perils
- Studies on compound or correlated risks
- Assessments of future changes or trends in either hazard, exposure, or vulnerability with climate change
- Techniques for assessing hazards in climate models
- Use of large ensembles for modelling risks
- Studies on emerging hazards such as drought/wildfire

Transdisciplinary research offers a powerful approach to tackling complex challenges in natural hazards and risk management, but it also presents unique challenges, particularly for early career scientists and practitioners. This short course is specifically designed to equip early career participants with practical tools and strategies for effectively engaging in and contributing to transdisciplinary projects. By focusing on the cross-fertilisation of hard and social sciences, the course will provide actionable insights into how to communicate across disciplines, deliver impactful research, and find common ground for collaboration. Participants will engage in hands-on activities and discussions, drawing from the experiences of leading projects such as The HuT (https://thehut-nexus.eu), PARATUS (https://www.paratus-project.eu), MYRIAD (https://www.myriadproject.eu), and DIRECTED (https://directedproject.eu). Attendees are also welcome to join the scientific session and splinter meeting that are part of this unified path, allowing them to choose between engaging in the entire programme or specific parts according to their interests.

Effective risk communication is crucial for enhancing public understanding and response to disaster risks. This short course is designed to equip students, early-career scientists, experienced researchers, and science communicators with advanced tools and strategies for effective risk communication. Participants will learn about fundamental principles of risk communication, cognitive biases, risk perception, and the use of media and social media in conveying risk information. The course will also address how to adapt communication strategies to different environments and audiences, beyond the traditional sharing of scientific data. Contributing to the European Commission’s disaster resilience goal no. 2 on ‘Prepare - Increasing risk awareness and preparedness of the population’ and the preparEU programme, the course will provide practical skills to improve risk communication efforts and foster more resilient communities. Attendees are welcome to join the scientific session and splinter meetings, creating a unified path for those interested in a comprehensive exploration of risk communication

During this short course, which is open to anyone with a general interest in plate tectonic processes, we will introduce the participants to the principles and application of analogue models in interpreting tectonic systems.

Tectonic processes act at different spatial and temporal scales. What we observe today in the field or via direct and indirect measurement is often just a snapshot of processes that stretch over hundreds or thousands of km, and take millions of years to unfold. Thus, it is challenging for researchers to interpret and recontrust the dynamic evolution of tectonic systems. Analogue modeling provides a tool to overcome this limitation, allowing for the physical reproduction of tectonic processes on practical temporal and spatial scales (Myr → hrs, km → cm/m). Of course, the reliability of analogue models is a function of the assumptions and simplifications involved, but still their usefulness in interpreting data is outstanding.

In this course we will go through the following outline:
- Aims and history of analogue modelling
- Model setups and materials
- Model scaling
- Monitoring techniques
- Interpreting model results
- Interactive demonstration: Running a live model :)
- Q&A

The final aim of this short course will be to present analogue modeling as a valid technique to be applied side by side with observations and data from the real world to improve our interpretation of the evolution of natural tectonic systems. We also intend to inspire the course participants to develop and run their own analogue tectonic modeling projects, and to provide them with the basic skills, as well as directions to find the additional resources and knowledge required to do so.

This short course is part of a quintet of introductory 101 courses on Geodesy, Geodynamics, Geology, Seismology, and Tectonic Modelling. All courses are led by experts who aim to make complex Earth science concepts accessible to non-experts.

Code is read far more often than it's written, yet some still believe that complex, unreadable code equates to a better algorithm. In reality, the opposite is true. Writing code that not only works but is also clear, maintainable, and easy to modify can significantly reduce the cognitive load of coding, freeing up more time for scientific research. This short course introduces essential programming practices, from simple yet powerful techniques like effective naming, to more advanced topics such as unit testing, version control, and managing virtual environments. Through real-life examples, we will explore how to transform code from convoluted to comprehensible.

Scientists have now been sounding the alarm about the climate and ecological crisis for decades. Each new report further outlines the necessity to radically change course, to rapidly reduce CO2 emissions and more generally human impacts on the environment if we are to avoid disastrous consequences on societies and ecosystems. Yet, these warnings have invariably been met with insufficient responses, political inertia, or worse active denial or institutionalised efforts to delay action. Meanwhile, a strong climate movement has emerged, led primarily by young activists demanding immediate climate action to ensure a liveable planet and a just future for all. A growing number of scientists and academics have also been starting to contemplate which roles they could most effectively take on in these movements, either from joining or providing external.

The growing interest and associated curiosity towards these movements from the scientific community was confirmed by the large attendance to EGU24’s events about academic activism. At the same time, many academics are unsure about where to start, how and where to find like-minded colleagues and grass-root organisations, or how to set up campaigns and actions to push for change at their institutions and beyond. This short course aims at bridging this gap by providing first-hand experience and practical tools to academics eager to organise within or outside their institution, and/or mobilise fellow colleagues to join climate actions. Equally important, the course will touch on relevant aspects of mental health: From the perspective of climate anxiety, to difficult-to-navigate dynamics within the movement, to a more general activist fatigue.

The course will be divided into 3 parts:
1. A starters part, with a short introduction on possible roles for academics in the climate movement, followed by presentations from experienced organisers about setting up a campaign at your own university, mobilising colleagues and organising events
2. A group work part, where participants will choose one proposed case as an example for the organisation of a campaign or event, and discuss it as a group, based on the input part and their own knowledge
3. A debriefing part, where some of the groups will present their work to the rest of the participants. Potential critical aspects related to organisational roadblocks, internal group dynamics, or repercussions that might come with certain forms of activism will be discussed

Science for policy is the practice of integrating scientific knowledge into policymaking to ensure that scientific evidence is available for policymakers when making decisions. There are some basic considerations for engaging in science for policy that can help get you started, from considering how you frame your message, looking for windows of opportunity, and more.

This session will start by diving into some of the basics of policy, enabling participants to understand what science for policy is and how they can start engaging with it. The tips for engaging are relevant to all career stages and will also help you understand the different paths available depending on the level of engagement you are interested in.
The session will then introduce experts working on the science for policy interface to highlight specific skills that researchers can develop to increase their policy impact and provide some practical examples.

Earth System Science is witnessing an ever-increasing availability of textual, digital trace, social sensing, mobile phone, opportunistic sensing, audiovisual, and crowdsourced data. These data open unprecedented new research avenues and opportunities but also pose important challenges, from technical hurdles to skewed coverage, difficulties in quality control, and reproducibility limits.

Textual data is a case in point. Digital newspaper repositories, social media platforms, and archives of peer-reviewed articles provide vast amounts of digitalized text data. At the same time, large language models, such as ChatGPT, have opened new scalable ways of extracting research-relevant and actionable information from texts. However, such models are far from unbiased and may not be transparent, interpretable, or open access, hindering reproducibility. The same holds true for other types of data and associated data mining methods, such as knowledge extraction from images, audio, and videos.

This session welcomes abstracts that explore using text and other emerging data sources in Earth System Sciences, especially in hydrology, natural hazards, and climate research. The session scope spans data analysis methodologies, scientific advances from the analysis of emerging data, and broader perspectives on the opportunities and challenges that these data sources present. Specific topics include but are not limited to, for example: assessment of natural hazard impacts (e.g. floods, droughts, landslides, temperature extremes, windstorms), real-time monitoring of disasters, evidence synthesis, public sentiment analysis, policy and awareness tracking, discourse and narrative analyses, natural language processing, large language models, social media analysis, historical data rescue, image mining, deep learning, and machine learning.

Early Warning Systems (EWS) are critical tools for safeguarding societies against the growing threat of natural hazards, particularly as climate change increases the frequency and intensity of extreme events. However, as risks become more complex—driven by multi-hazard events, compound risks, and broader systemic challenges — conventional EWS approaches must evolve. This session will focus on cutting-edge developments and novel methodologies that enhance the effectiveness and reach of EWS, with an emphasis on integrating Artificial Intelligence (AI) and fostering transdisciplinary collaboration.
This session invites contributions that explore innovative approaches to EWS across the entire warning chain, from observations, to hazard and impact forecasting, warning production, communication and decision-making. Special attention will be given to multi-hazard, compound, and complex systemic risks, and the integration of both cutting-edge technological advancements and trans-disciplinary approaches. Thus, we welcome contributions related to artificial intelligence (AI), machine learning, remote sensing, and big data analytics for the development and implementation of EWS as well as contributions that examine the integration of physical and social science, including community-based warning systems, risk perception, and communication strategies towards the goal of the UN led “Early Warnings for All” initiative. This session seeks to enhance preparedness and response by reviewing case studies, methodological advancements, and theoretical contributions, that address observational innovations for early detection of hazards, advanced weather and hazard forecasting systems, and impact-based forecasting.
By addressing both the technical and societal aspects of EWS, this session aims to foster dialogue between disciplines, ensuring that future systems are more inclusive, equitable, and effective at reducing risks in the face of a changing climate. We seek abstracts from a diverse range of fields, including climate science, meteorology, hydrology, geoscience, engineering, and social sciences including policy studies, psychology, or communication science, to explore how novel approaches can enhance the resilience of communities to multi-hazard risks.

Nature based Solutions to address growing risk of Urban Heat Islands interacting with Climate Change

Convenors:
Shalini Dhyani (SD, Female, India), Jagdish Krishnaswamy (JK, Male, India), Soojeong Myeong (SM, Female, S. Korea) and Sharon Onyango (SO, Female, Kenya)


Institutional affiliations:

SD: Environmental Impact Assessment, Audit and Policy, National Environmental Engineering Research Institute, Nagpur India
JK: School of Environment and Sustainability, Indian Institute for Human Settlements, Bengaluru India
SM: Korea Environment Institute, Sejong, S. Korea
SO: Department of Landscape and Environmental Sciences, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya
This session on Nature based solutions to address growing risk of urban heat islands interacting with climate change aims to foster interdisciplinary research related to restoring green-blue infrastructure across cities in different continents, using of remote sensing and geo-spatial approaches, modeling, socio-ecological studies to put forward the complexity that is often hidden by simplifying hypotheses and approaches (sector-based silo approach, homogeneity of environments, etc). In this session we welcome interdisciplinary papers which explore the risk, and challenges related to UHI effects and the potential cases of implementing NbS as a mitigation approach.

Despite extensive efforts, losses from natural hazards are still on the rise. While climate change plays a crucial role in increasing the frequency and magnitude of many hazards, other factors such as changes in exposure and vulnerability remain poorly understood. This session will delve into the reasons behind and seek to identify the key risk drivers responsible. Addressing these challenges is vital for developing sustainable risk reduction strategies and providing societies with long-term adaptation plans to effectively manage climate risks.
The frequency and magnitude of many natural hazards are evolving, with climate change exacerbating these changes. However, the dynamic nature of hazard triggers and cascading effects is often overlooked in current mitigation and adaptation strategies. Most existing mitigation and adaptation measures, including technical interventions and land-use planning, rely on static concepts, whereas the effects of hazards are inherently dynamic.
Exposure is a critical component of risk assessment, and it is likely to increase in the future as human settlements expand and industrial activities intensify. However, there is limited information on the spatio-temporal dynamics of exposure at different scales. To accurately quantify the evolution of risk, this information must be analysed alongside the effectiveness of existing technical mitigation measures. This analysis is also essential for contributing to discussions on the impacts of climate change on exposed communities, particularly in the context of shared socio-economic pathways (SSPs).
Understanding the vulnerability of elements at risk is another key objective in reducing future losses. Current models used to describe vulnerability require further validation through empirical data, laboratory experiments, and alternative assessment methods. Integrating observational methods other techniques and incorporating additional dimensions of vulnerability, particularly institutional vulnerability, is essential.
We invite submissions that integrate these topics, including hazard and exposure analysis, vulnerability assessment, adaptation strategies, and disaster risk reduction tools. The session will focus on the interactions between landscape processes and human activities, promoting transferable and adaptive approaches to risk management. Contributions should aim to identify the key risk drivers behind natural hazard losses through a holistic examination of risk components.

Infrastructure delivers essential services to communities, underpins economic activities, and acts as a first line of defence against shocks and disasters. With the increasing intensity and frequency of hazards, infrastructure disruptions are occurring more often, leading to substantial economic and societal impacts. The increasing unpredictability of natural hazards and geopolitical events poses a serious threat to the stability of these systems that facilitate the movement of people and resources. Rapid population growth, dynamic socio-political scenarios and unplanned development only exacerbate these risks, heightening the likelihood of widespread disruption. To enhance the resilience of these network systems, it is essential to identify and protect critical components whose failure could lead to significant disruptions. Strengthening resilience through robust mitigation measures and recovery strategies is essential to ensuring the continuity and sustainability of critical services in the face of an evolving, uncertain world.

We invite submissions of theoretical, methodological, and empirical studies that enhance our understanding of future risks and explore innovative, resilient strategies for transportation, trade ( i.e., food and water), and ecological systems. We welcome contributions spanning local case studies, regional analyses, and global perspectives, particularly from multi- and transdisciplinary research efforts. Special interest is given to studies focused on:-

i) Identifying regional and global stressors impacting infrastructural systems.
ii) Impact of external stressors on interdependent infrastructure systems.
iii) Quantifying the resilience of built and natural infrastructure systems.
iv) Designing effective recovery and restoration strategies.
v) Influence of climate change and shifting geopolitical landscapes on infrastructure resilience.
vi) Implementation of resilience policy from isolated or multi-hazard perspective.

The current climate change has been shown to exacerbate extreme weather events, such as storms with exceptionally strong winds, hurricanes and medicanes, prolonged temperature extremes, heavy rainfall and flooding. Climate scenarios predict an intensification and increased frequency of these extremes that, in addition to endangering people's health and lives, can have destructive impacts on human activities. Not surprisingly, the United Nations states that 'extreme weather events have come to dominate the disaster landscape of the 21st century' (McClean, 2020). In this context, disaster prevention, risk reduction, and adaptation to climate change impacts have become imperative requirements for our society.
Among the most impacted consequences are the deterioration, loss of functionality, or even structural damage to buildings and infrastructures crucial to society, such as health centers, transport infrastructure, energy production and distribution, manufacturing sites, and government buildings. These infrastructures play a crucial role in socio-economic activities and are particularly susceptible to weather stress as they are built to have a long lifespan; damage to these infrastructures has a particularly important impact on society as a whole. Still, the progress in adaptation planning of such critical assets remains low. This can be ascribed also to the lack of reliable numerical models to determine meteorological stressors from extreme events, and tools that actionably predict structural damage.
Addressing these complex challenges necessarily requires interdisciplinary work between experts from climate and atmospheric science, materials and structural analysts, social and economic science, who are the primary focus of this session. The aim is to bring together and present in an integrated manner the latest research advances in the assessment, mitigation and adaptation of risk associated with extreme events for assets. The session encompasses various topics including modelling and quantification of meteorological stresses with numerical or experimental techniques; risk assessment of extreme events; assessment of social, cultural and economic impacts on society. The session emphasizes methodologies for determining meteorological exposures of assets, forecasts of near future extreme events impacts, operational models for damage and structural stability of infrastructures, and analysis of direct and indirect socio-economic cascading damages.

Extreme weather events such as tropical cyclones, heatwaves and floods threaten populations around the world. Climate change is increasing the frequency and intensity of many kinds of extreme weather events, which can combine with community exposure, inequalities and vulnerabilities to cause substantial harm. There is growing literature at the intersection of the natural and social sciences studying the impacts of extreme weather events on populations as well as peoples’ behavioral, attitudinal, and emotional responses. For instance, studies have investigated how extreme weather and climatic changes influence food and water security, conflict and security risks, and health outcomes. Additionally, the field of environmental human mobility has witnessed remarkable progress in data collection, analytical methods, and modeling techniques. Further research has examined the responses of individuals and households to these threats, including climate-related emotions, environmental concerns, and climate policy support. These studies have been conducted in interdisciplinary settings, where social scientists closely collaborate with natural scientists to study populations that have been, or will be, impacted by extreme weather events.

Yet only few studies are currently harnessing the full potential of interdisciplinary collaborations in this space and several challenges pertaining to the choice of methods and the scale of analysis (e.g., regional, national) remain underexplored. This session aims to provide a platform for interdisciplinary work on extreme weather events and invites contributions from natural and social scientists interested in interdisciplinary studies on the societal impacts of and responses to extreme weather events. Furthermore, we highlight the topic of human (im)mobility with a perspective on addressing recent advancements, methodological innovations, novel use of data, challenges, or future prospects in modeling human mobility in the past, present, and future.

We invite contributions including but not limited to studies of:

- Environmental attitudes and behaviors influenced by extreme events
- Health and wellbeing effects of climate change and extreme events
- Migration and displacement due to extreme events
- Food production and security in relation to extreme weather
- The interplay between climate change, environment, and conflict
- Methodological challenges to interdisciplinary collaborations

The complexity of natural hazards and their impacts on society calls for a comprehensive approach to disaster risk reduction and resilience. This scientific session will present cutting-edge research and insights from transdisciplinary projects that address multi-risk challenges. Focused on the Disaster-Resilient Societies (DRS) and Multi-Risk Thematic Areas, the session will showcase innovative methodologies and findings from European-funded projects such as The HuT (https://thehut-nexus.eu), PARATUS (https://www.paratus-project.eu), MYRIAD (https://www.myriadproject.eu), and DIRECTED (https://directedproject.eu). We also welcome contributions from other projects and organisations to enrich the discussion. Attendees will gain a deeper understanding of how integrating diverse technical and social science perspectives can enhance our ability to mitigate and adapt to complex disaster risks. Participants are encouraged to join the short course and splinter meeting that complement this session, creating a unified path that allows for engaging in the entire programme or specific parts based on individual interests.

Natural hazards (e.g., earthquakes, volcanic eruptions, floods, landslides and ground subsidence), their cascading effects and societal risks, can strongly influence, and be influenced by human activities (e.g., migration, construction, architectural design, urban planning, forestation, deforestation, damming and drainage re-routing). The relationship between environmental risks and human behavior is dynamic in space and time. Understanding and using well this transdisciplinary interconnectedness is critical for improving disaster preparedness, urban planning, and environmental management. Investigating such complex relationships requires innovative joint analysis of the modern big earth observation data (e.g., optical, hyperspectral, GRACE, GNSS, RADAR, LiDAR), together with historical and paleo records of multi-hazards (e.g., literature, catalogue, geomorphology, and trenching), as well as anthropogenic (e.g., indigenous wisdom and tales), demographic (e.g., population, ethnicity, age), and developmental (e.g., economy, public policy) datasets. This session solicits contributions that employ earth observation (especially imaging geodesy) and interdisciplinary data sets for disaster risk reduction. We aim to encourage transdisciplinary discussions between data providers, researchers, and stakeholders, and thus welcome instrument designers, geodesists, natural scientists, social scientists, historians, anthropologists, engineers, architects, policy makers, and community workers to come together to celebrate success and highlight challenges in the integration of earth observation data in promoting resilience building and sustainable development.

As highlighted by the UN development goals, climate change is a reality to which we need to adapt. However, the many disciplines required to effectively plan and adapt to climate change often work in isolation. For example, physical climate modelling, hydrology, and hazard impact and risk assessment are largely separate disciplines with difficulties interacting due to different terminologies and backgrounds. Moreover, until recently, climate modellers did not have the capability to generate long-term projections at a spatial and temporal resolution useful for impact studies.

With the advent of kilometre-scale atmospheric models, called convection-permitting models CPMs, high resolution remote sensed data sets, and global sub-daily rainfall observations, we are now in a position to bridge the gap between disciplines, sharing knowledge and understanding. With all these tools at our disposal we have substantially improved the representation of sub-daily precipitation characteristics and have model output at a spatial resolution closer to what many impacts modellers, for example hydrologists, need. Now is the time to exploit these high-resolution, consistent datasets as input for impact studies and adaptation strategies; to foster interdisciplinary collaboration to build a common language and understand limitations and needs of the different fields; to learn together how to provide policymakers with information that can be used to design effective measures at to adapt to climate change as well as to inform mitigation decisions.

This interdisciplinary session invites contributions that address the linkages between high-resolution climate scientists, impact modellers, and end users with a special focus on:
- Recent advances in climate modelling for impact studies, particularly using high resolution convection- permitting models.
- Bias correction techniques to overcome bias in climate models affecting impact models.
- Analysis of the uncertainty propagation from climate into impact models.
- Improved understanding of processes that will alter hazards resulting from climate change.
- Novel use of new and existing observational data sets in characterising and quantifying climate change hazards.
- Examples of good practice, storylines and communication to both stakeholders and policymakers.

It is undeniable reality the fact of increasing frequency and severity of natural hazards on a global scale. A trend that seems likely to continue in the future, as a consequence of increase in extreme weather events and climate change, constituting one of the most significant risks for the natural, technological and human environment. This session concerns the use of Geoinformatics technologies, specifically the use of Geographical Information Systems and Remote Sensing technologies as well as Artificial Intelligence methodologies, in order to understand the mechanisms of the manifestation and evolution of catastrophic phenomena, mostly related to floods, landslides, droughts and wildfires.
New data, remotely or in-situ acquired, advanced methodologies for their analysis and integration aimed at managing natural hazards are welcome in this session. Particular emphasis is placed on the application of explainable Artificial Intelligence methods, through techniques such as Shapley Additive explanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME), Permutation Importance, Partial Dependence Plot, Explainable Boosting Machine, etc., aimed at understanding the decision-making mechanism in problems related to the occurrence and evolution of natural hazards. Participants will be exposed to state-of-the-art technologies and practical applications to gain a full picture of the possibilities available for building applications of good disaster management practices. The intention of the session is to present successful cases that cover natural hazards in different environments and climate scenarios, leveraging cutting-edge technologies and contributing to the formation of a safer and more resilient society in the light of increased environmental challenges.

Between 1980 and 2022, weather- and climate-related extremes caused economic losses of assets estimated at EUR 650 billion in the EU. To face this challenge, increasing with ongoing warming and the continuous rise of the number, value and interconnexion of assets, it is necessary to stimulate and coordinate the European effort on disaster risk reduction (DRR), explicitly accounting for the changing socio-environmental conditions. To this aim, innovative holistic and integrative approaches are required including reinforced collaborations between -among others- geosciences, climate sciences, engineering, data and digital sciences, and human and social sciences (in particular geography, history, economic and financial sciences, behavioral sciences). These different disciplines are now heavily involved in DRR, but still work too much in silos and / or, sometimes, without direct interaction with society. Grounding on the approach developed in the France 2030 Risks-IRIMA program, we propose a session that emphasizes inter and transdisciplinary methodological approaches of DRR, so as to better detect, quantify and anticipate risks due to weather extremes and climate change. The aim is to understand their impact resulting from extreme events, multiple risks, cascading effects, multi-scale dynamics, etc. in an explicit non–stationary framework able to account for the full complexity at play. Challenges include the improvement of the coupling between human and socio-economic issues and the physical components of risks, the development of adapted risk measures and quantification tools, better use of data and citizen knowledge, and of new technologies, particularly those of information science, as well as the development of risk projections at different temporal horizons. Also, the seamless chain between data acquisition and assimilation to modelling, decision support and policy implementation for crisis management and anticipation of future risks related to climate change and anthropization should be reinforced. Through this renewed effort, research on risk science should strongly contribute to the sustainable transformation of society, improving altogether societal well-being, risk awareness, and reduction of the social and economic impacts of crises, and fostering innovation at the science-society interface.

Extreme climate and weather events, associated disasters and emergent risks are becoming increasingly critical in the context of global environmental change and interact with other stressors. They are a potential major threat to reaching the Sustainable Development Goals (SDGs) and are one of the most pressing challenges for future human well-being.
This session explores the linkages between extreme climate and weather events, associated disasters, societal dynamics and resilience. Emphasis is laid on 1) Which impacts on ecosystems and societies are caused by extreme events (including risks emerging from compound events)? 2) Which feedbacks and cascades exist across ecosystems, infrastructures and societies? 3) Where do these societal and environmental dynamics threaten to cross critical thresholds and tipping points? 4) Can we learn from past experiences? 5) What are key obstacles towards societal resilience and reaching the SDGs and Sendai Framework for Disaster Risk Reduction (SFDRR) targets, while facing climate extremes and compound events?

We welcome empirical, theoretical and modelling studies from local to global scale from the fields of natural sciences, social sciences, humanities and related disciplines.

As the impacts of climate change become more pronounced, urban areas face significant challenges. With the increasing frequency of extreme weather events, rising sea levels, heat waves, and other climate-related challenges, cities must find ways to protect their populations, infrastructure, and ecosystems. Furthermore, future risks from the changing climate and associated systemic risks challenge existing assessments, and demand holistic future-oriented investigations that generative methods provide. Urban simulation tools like agent-based models, and cellular automata have emerged as essential instruments in this endeavor, offering a means to visualize, predict, assess, and respond to climate change's complex and multifaceted impacts. Therefore, our session aims to delve deeply into the transformative role of urban simulation models in enabling cities to understand, plan for, and respond to these climate challenges. The session will showcase the latest advancements in simulation technology and explore integrating these tools into holistic urban planning and policy-making processes, through which cities can develop robust strategies to mitigate climate risks and enhance resilience.
Contributions are welcome on:
● New urban simulation methods that support risk, exposure, and vulnerability assessments in urban environments, including urban growth, urban morphology, infrastructure, population dynamics, and ecosystems.
● Explore the challenges associated with developing and implementing urban simulation models within the context of climate change adaptation.
● Discuss opportunities for improving simulation accuracy and relevance through emerging technologies integration, such as artificial intelligence, big data analytics, and IoT.
● Case studies from cities that have effectively used simulation models to guide their climate adaptation efforts

Nature-based Solutions (NbS) are actions to protect, conserve, restore, sustainably use and manage natural or modified ecosystems, that address socio-economic and environmental challenges, while simultaneously providing human well-being, resilience and biodiversity benefits (UNEA, 2022). Within the framework of a global ecosystem approach, NbS must encompass ecological, societal, political, economic and cultural issues at all levels, from the individual to the collective, from local to national, from the public or private sphere.

As recently highlighted by IPCC and IPBES, climate change and biodiversity degradation cannot be separated, and must be considered together. For this reason, this session is especially focused on the way NbS can act as climate change adaptation solutions. Considering various ecosystems (marine and coastal, urban, cropland, mountainous, forest, rivers and lakes,.,), NbS as interventions for climate adaptation includes the adaptation to: sea level rise (flooding and erosion), changes of the water regime (floods, droughts, water quality and availability), rise in temperatures (heat waves, forest fires, drought, energy consumption), plant stress and increase of pests (variation of yields, forest dieback), to minimize their associated social and economic negative impacts.

Therefore, this session aims to promote interdisciplinary research related to ecosystem restoration, preservation and management, to put forward the complexity that is often hidden by simplifying hypotheses and approaches (sector-based silo approach, homogeneity of environments, ...).

Specific topics of interest are the followings:
- Complexity: nature of ecosystems and the risk of oversimplification, interconnection between NbS and complementary areas, consideration of uncertainties (future climate and associated impacts...)
- Scales: spatial scales with the integration of NbS in their environment, and temporal scales considering sustainability over time, variability of bio-physical processes and climate change effects
- Ecosystem services: understanding the bio-geophysical processes, spatial shift between the location of NbS and the location of beneficiaries, modification under climate change (threshold, inflection point), co-benefits or on the contrary degradation and negative effects
- Assessment and indicators: measurement and modelling protocols to evaluate NbS performances, capacity to measure the complexity, resilience and stability of the solutions.

Mountains are complex social-ecological systems and natural laboratories in which to tangibly explore and understand how drivers and processes of global change manifest in specific places. In this session, we invite inter- and transdisciplinary contributions that examine past, present, and future environmental change, their associated impacts for ecosystems and people in mountain environments, and measures taken to address these impacts. This session is open to conceptual as well as empirical measurement and/or modelling or scenarios studies of mountain climate, cryosphere, ecology, hazards, and hydrology, which also incorporate studies on intersecting socio-economic dimensions and risks. Mountains as complex terrain can be difficult to adequately parameterize in (climate) models and many areas of the world lack high-elevation monitoring infrastructure that can record data at the relevant locations, densities, scales, frequencies, and resolutions needed. Likewise, there is a need to capture and account for socio-economic changes such as demographic and land-use change and their projections to improve our understanding of how hazards, vulnerability, and exposure interact in terms of impacts and risks.
We particularly welcome contributions that describe how steps are being taken to address such knowledge gaps, including high-elevation integrated monitoring efforts, observations along elevational gradients, climate downscaling strategies and remote sensing innovations, and integration methods that include societal data and information to characterise and represent a more comprehensive systems approach to global change. As 2025 marks the UN-declared International Year for Glaciers' Preservation, and the kick-off to the UN Decade of Action for Cryosphere Sciences, this session especially invites contributions that take a multi-disciplinary perspective and approach to addressing the challenges and opportunities posed by a changing cryosphere in mountain regions, with particular attention to the human dimensions associated with adaptation and resilience.
This session is endorsed and supported by the Mountain Research Initiative and the Institute for Interdisciplinary Mountain Research of the Austrian Academy of Sciences.

Marine geological processes cover a range of different disciplines and their understanding usually requires an interdisciplinary approach. The interaction of tectono-sedimentary, physical oceanographic, chemical and biological mechanisms in marine geological processes are important. These range from sediment erosion and deposition, to hydrothermal and fluid flow systems, early diagenesis and geomicrobiology, and long-term evolution of ocean-basins. Such processes may take place in shallow or deep, in tropical and glacial environments, and they may be natural or partly human-influenced. Climate-ecosystem and material cycling induced perturbations in marine geological processes have occurred in present and past, and potentially will also occur in the future. Several of these processes may also have a profound impact on human society, including Geohazards such as tsunamis generated by tectonic or mass-wasting events, coastal land and habitat loss in response to changed currents or river discharge, and sediment gravity flow in deep waters affecting human infrastructures. Moreover, marine geological archives contain records of climate change occurring in the past, that are relevant for present and potentially future changes. We encourage comprehensive and interdisciplinary abstracts within the broad field of marine geological processes or marine deposits that provide comprehensive evidence for present or past geo-physical and geo-(bio)chemical processes.

Geomythology is not only a perspective that allows for the reinterpretation of mythological narratives through the lens of extreme events, it is also an inclusive research approach that appreciates the value of oral tradition and local knowledge. These narratives and knowledge relate to geomorphological and hydrographic features, as well as geohazards.
Grassroots interpretations of the origins of geomorphological and hydrographic features, local knowledge, and the narratives associated with them – myths and legends – create a network of dependencies illustrating the interactions between humans and the environment. This synergy led to the emergence of a long neglected but now strongly promoted need for the protection of geoheritage. Incorporating a humanistic perspective into the study of geological processes, landforms, and hydrometeorological phenomena elevates the value of individual geosites to a much broader category: the geocultural heritage of civilizations. This approach supports the development of geotourism and holds potential for geoeducation.
The session aims to give new impetus to interdisciplinary discourse on the environment through the lens of geomythology.
We invite you to submit abstracts in the proposed thematic blocks; however, we are also open to new thematic proposals beyond those we have suggested:
• Meteor impacts, earthquakes, tsunamis, and volcanic eruptions in myths and oral tradition.
• The potential of research on local knowledge regarding geomorphological and hydrographic features, as well as geological processes and hydrometeorological phenomena.
• Oral tradition in the context of empirical evidence and the dating of geomorphological processes.
• Local knowledge about sudden phenomena and extreme events, such as rockfalls, landslides, extreme floods, karst phenomena, hailstorms, etc.
• Geomythical perspectives in oral traditions.
• From Geomythology to Geoheritage – exploring the often-elusive meanings of geosites.
• Geo-Mytho-Tourism – new types of local and regional geobrands.
• The potential of geomyths for geoeducation.

One of the most challenging aspects of communicating natural hazards to the public is quantifying the reach and effectiveness of efforts and activities aimed at raising awareness and mitigating risks.
Project funders, decision-makers, stakeholders, scientists, and reviewers often seek accountability and evidence of progress in public awareness and proactive measures. Unfortunately, there is no objective metric available to determine whether and how the public has understood the natural phenomenon, assessed the risks they face, reduced or mitigated the effects, and contemplated resilience. Relying on the occurrence of the next disaster to compare positive behavioral changes with those seen after previous events is neither feasible nor responsible.
This session aims to gather and share experiences in the field of risk communication primarily in terms of outcome evaluation, to quantify their effects in lessening the impact of disasters on families, homes, communities, and the economy, with the goal of proposing a framework or protocol to assess the success of outreach and educational initiatives.

The Early Warning for All initiative in alignment with the Sendai Framework for Disaster Risk Reduction (SFDRR) recognizes that increased efforts are required to develop life-saving risk-informed and impact-based multi-hazard early warning systems. Despite remarkable advances in disaster forecasting and warning technology, it remains challenging to produce useful forecasts and warnings that are understood and used to trigger early actions. Overcoming these challenges requires progress that goes beyond the improved skill of natural hazard forecasts. It is crucial to ensure that forecasts reflect on-the-ground impacts, provide actionable information and to understand which implementation barriers exist to do so. This, in turn, requires commitment to the creation and dissemination of risk and impact data as well as the collaborative production of impact-based forecasting services. To deal with these challenges, novel science-based frameworks have recently emerged. For example, Forecast-based Financing and Impact-based Multi-Hazard Early Warning Systems are currently being implemented operationally by both governmental and non-governmental organisations in several countries. This achievement is the result of a concerted international effort by academic, governmental/intergovernmental and humanitarian organizations to reduce disaster losses and ensure reaching the objectives of SFDRR. This session aims to offer valuable insights and share best practices on impact-based multi-hazards early warning systems from the perspective of both the knowledge producers and users. Topics of interest include, but are not limited to:
● Practical applications and use-cases of impact-based forecasts
● Development of cost-efficient early action portfolios
● Methods for translating climate-related and geohazard forecasts into actionable impact-based information
● Action-oriented forecast verification and post-processing techniques to tailor forecasts for early action
● Triangulation of indigenous and scientific knowledge for leveraging forecasts, multi-hazard risk information and climate services to last-mile communities
● Bridging the gaps in risk and impact data to support impact-based forecasting, collecting and expanding data on interventions to build an evidence base for early actions
● Innovative solutions to address challenges in implementing forecast-based actions effectively, including the application of Artificial Intelligence, harnessing big data and earth observations.

This interactive session aims to bridge the gap between research and practice in operational forecasting, with a focus on impact-based approaches for flood, water scarcity and multiple hazards.
Operational (early) warning systems are the result of progress and innovations in the science of forecasting. New opportunities have risen in physically based modelling, AI/machine learning, coupling meteorological and hydrological forecasts, ensemble forecasting, impact-based forecasting, and real-time control. Often, the sharing of knowledge and experience about developments are limited to the particular field (e.g. flood forecasting or landslide warnings) for which the operational system is used. Increasingly, humanitarian, disaster risk management and climate adaptation practitioners are using forecasts and warning information to enable anticipatory early action that saves lives and livelihoods. It is important to understand their needs, their decision-making process and facilitate their involvement in forecasting and warning design and implementation (co-generation).

The focus of this session will be on bringing the expertise from different fields together as well as exploring differences, similarities, problems and solutions between forecasting systems for varying hazards including climate emergency. Real-world case studies of system implementations - configured at local, regional, national, continental and global scales - will be presented. An operational warning system can include, for example, monitoring of data, analysing data, making and visualizing forecasts, impact-based solutions, giving warning signals and suggesting early action and response measures.

Contributions are welcome from both scientists and practitioners who are involved in developing and using operational forecasting and/or management systems for climate and water-related hazards, such as flood, drought, tsunami, landslide, hurricane, hydropower etc. We also welcome contributions from early career practitioners and scientists, and those working in multi-disciplinary projects (e.g. EU Horizon Disaster Resilience Societies).

Transportation systems are particularly vulnerable to weather conditions, with impacts that can range from minor delays to severe disruptions, compromising both safety and efficiency. As climate variability intensifies, the need to understand and predict these weather-related effects becomes increasingly urgent. The session "Transportation Meteorology: From Insights to Impacts, From Forecasting to Solutions" will delve into the vital role meteorology plays in transportation, offering an in-depth examination of the latest advancements in weather observations and forecasting specific to transportation, and their practical applications in developing resilient strategies to address these challenges.
This session encompasses a wide array of topics, including the effects of extreme weather events on various modes of transportation—such as road, rail, air, and maritime—the integration of meteorological monitoring and early warning systems into transportation networks to enhance decision-making, and innovative methods to strengthen infrastructure resilience. Additionally, the session also explores how advancements in transportation meteorology can contribute to the transformation toward more sustainable and climate-resilient transportation systems, supporting the global push for greener, more efficient infrastructure. Contributions in the form of case studies, research findings, and technological innovations are encouraged, as they showcase successful implementations and share valuable lessons learned.

Floods and droughts have major impacts on society and ecosystems and are projected to increase in frequency and severity with climate change. These events at opposite ends of the hydrological spectrum are governed by different processes that operate on different spatial and temporal scales and require different approaches and indices to characterize them. However, there are also many similarities and links between the two types of extremes which are increasingly being studied.
This session on hydrological extremes aims to bring together the flood and drought communities to learn from the similarities and differences between flood and drought research. We aim to improve the understanding of the processes governing both types of hydrological extremes and their interplay, develop robust methods for modelling and analyzing floods and droughts and their transitions, assess the influence of global change on hydro-climatic extremes, and study the socio-economic and environmental impacts of both types of extremes.
We welcome submissions that present insightful flood and/or drought research, including case studies, large-sample studies, statistical hydrology, and analyses of flood or drought non-stationarity under the effects of climate-, land cover-, and other anthropogenic changes. Studies that investigate both extremes or their interplay are of particular interest. We especially encourage submissions from early-career researchers.

Extreme hydro-meteorological events drive many hydrologic and geomorphic hazards, such as floods, landslides and debris flows, which pose a significant threat to modern societies on a global scale. The continuous increase of population and urban settlements in hazard-prone areas in combination with evidence of changes in extreme weather events lead to a continuous increase in the risk associated with weather-induced hazards. To improve resilience and to design more effective mitigation strategies, we need to better understand the triggers of these hazards and the related aspects of vulnerability, risk, mitigation and societal response.
This session aims at gathering contributions dealing with various hydro-meteorological hazards that address the aspects of vulnerability analysis, risk estimation, impact assessment, mitigation policies and communication strategies. Specifically, we aim to collect contributions from academia, industry (e.g. insurance) and government agencies (e.g. civil protection) that will help identify the latest developments and ways forward for increasing the resilience of communities at local, regional and national scales, and proposals for improving the interaction between different entities and sciences.
Contributions focusing on, but not limited to, novel developments and findings on the following topics are particularly encouraged:
- Physical and social vulnerability analysis and impact assessment of hydro-meteorological hazards
- Advances in the estimation of socioeconomic risk from hydro-meteorological hazards
- Characteristics of weather and precipitation patterns leading to high-impact events
- Relationship between weather and precipitation patterns and socio-economic impacts
- Socio-hydrological studies of the interplay between hydro-meteorological hazards and societies
- Hazard mitigation procedures
- Strategies for increasing public awareness, preparedness, and self-protective response
- Impact-based forecast, warning systems, and rapid damage assessment.
- Insurance and reinsurance applications

Significant empirical and theoretical advancements have revealed the departure of hydrometeorological processes from classical statistical models, highlighting the scaling behavior of their variables, especially extremes, across state, space, and time. These extremes, along with the general statistics of hydrometeorological processes, are crucial inputs for hydrological applications, which have increasing importance in the (re)insurance industry. Among the most common applications, catastrophe models are developed to manage risk accumulation; disaster response is used to prepare (re)insurers financially after major events; Real Disaster Scenarios are built to stress-test (re)insurers exposure both in the present-day and future climate.
For instance, in the context of a flood risk model, estimating design rainfall not only involves determining the absolute rainfall amount for a specific return period but also requires understanding the intra-event rainfall distribution, spatial extension, and rainfall intensities at neighboring stations. When these details are underestimated, it can easily turn into a poor risk assessment and weaker financial protection. Additionally, connections between hydrometeorological extremes and climatic oscillations, such as NAO or ENSO, and their evolution in a changing climate, provide insights for long-term risk management in the re-insurance sector, as required for regulatory purposes.
The integration of supporting information and the application of advanced AI approaches offer as well unprecedented opportunities to enhance these estimates. This session invites submissions, among others, on the following topics:
- Coupling stochastic approaches with deterministic hydrometeorological predictions to better represent predictive uncertainty.
- Developing robust statistics under non-stationary conditions for design purposes.
- Parsimonious models of hydrometeorological extremes across various spatial and temporal scales for risk analysis and hazard prediction.
- Improving the reliable estimation of extremes with high return periods, considering physical constraints.
- Linking underlying physics and hydroclimatic indices with the stochastics of hydrometeorological extremes.
- Exploring supporting data sets for additional stochastic information and utilizing novel AI and machine learning approaches.
- Applications carried out jointly by the (re)insurance industry and research institutions.

The socio-economic impacts associated with floods are increasing. Floods represent the most frequent and most impacting, in terms of the number of people affected, among the weather-related disasters: nearly 0.8 billion people were affected by inundations in the last decade, while the overall economic damage is estimated to be more than $300 billion.
In this context, remote sensing represents a valuable source of data and observations that may alleviate the decline in field surveys and gauging stations, especially in remote areas and developing countries. The implementation of remotely-sensed variables (such as digital elevation model, river width, flood extent, water level, flow velocities, land cover, etc.) in hydraulic modelling promises to considerably improve our process understanding and prediction. During the last decades, an increasing amount of research has been undertaken to better exploit the potential of current and future satellite observations, from both government-funded and commercial missions, as well as many datasets from airborne sensors carried on airplanes and drones. In particular, in recent years, the scientific community has shown how remotely sensed variables have the potential to play a key role in the calibration and validation of hydraulic models, as well as provide a breakthrough in real-time flood monitoring applications. With the proliferation of open data and models in Earth observation with higher data volumes than ever before, combined with the exponential growth in deep learning, this progress is expected to rapidly increase.
We invite presentations related to flood monitoring and mapping through remotely sensed data including but not limited to:
- Remote sensing data for flood hazard and risk mapping, including commercial satellite missions as well as airborne sensors (aircraft and drones);
- Remote sensing techniques to monitor flood dynamics;
- The use of remotely sensed data for the calibration, or validation, of hydrological or hydraulic models;
- Data assimilation of remotely sensed data into hydrological and hydraulic models;
- Improvement of river discretization and monitoring based on Earth observations;
- River flow estimation from remote sensing;
- Deep learning based flood monitoring or prediction
Early career and underrepresented scientists are particularly encouraged to participate.

Floods are extreme events that cause huge losses of lives and properties. As the consequences of climate change intensify, novel approaches in hydrology have become essential for developing robust flood risk mitigation strategies that aid in effective water resource management to foster sustainable development. Preparation, monitoring, and planning against the flood requires the generation of tools such as flood forecasting and predicting extreme flood events under climate change. The present session solicits novel contributions from the researchers to investigate and manifest revolutionary developments in the catchment hydrology by utilizing cutting-edge technologies such as Artificial Intelligence (AI), remote sensing, and process-based modeling. The combined use of these technologies is revolutionizing flood modeling and management methods and providing new avenues to analyze complicated hydrological processes that would improve the ability of ecosystems to adapt and recover from the impacts of climate change and challenges.

This session aims to bring together professionals from hydrology sciences and engineering to share their valuable and innovative insights, utilizing modern technologies on a variety of topics, including but not limited to the following:

• The paradigm shifts from conventional to modern learning approaches such as integrated, hybrid, and universal are crucial for the modeling of hydrological extremes.
• Regional modeling approach in hydrology for extreme event prediction in ungauged or poorly gauged basins.
• Real-time monitoring of extreme flood events using remote sensing, but not limited to optical, and Synthetic Aperture Radar (SAR).
• Explore the Physics-based AI, Generative AI (GAI), and Digital Twins including traditional AI in the field of flood risk mitigation.
• Discovering possibilities for integrated and innovative solutions using public participation for Food Risk Mitigation (FRM), including riverine, urban, and Glacial Lake Outburst Floods (GLOFs).
• Integrated watershed management (IWM) strategies that improve decision-making processes for flood mitigation and foster sustainable water resource management.

This session investigates mid-latitude cyclones and storms on both hemispheres. We invite studies considering cyclones in all different stages of their life cycles, from initial generation to the final development, including studies to large- and synoptic-scale conditions influencing cyclones’ growth to a severe storm, their dissipation, and related socioeconomic impacts.
Papers are welcome, which focus also on the diagnostic of observed past and recent trends, long- and short-term natural variability, as well as on future storm development under changed climate conditions. This will include storm predictability studies on different time and spatial scales. The session also invites studies investigating storm related impacts: Papers are welcome dealing with vulnerability, diagnostics of sensitive social and infrastructural categories and affected areas of risk for property damages and loss. Which novel risk transfer mechanisms are currently developed or used? Which novel mechanisms (e.g., adapted re-insurance products) are already implemented or will be developed in order to adapt to future loss expectations under anthropogenic climate change?

Drought and water scarcity affect many regions of the Earth, including areas generally considered water rich. The projected increase in the severity and frequency of droughts may lead to an increase of water scarcity, particularly in regions that are already water-stressed, and where overexploitation of available water resources can exacerbate the consequences droughts have. This may lead to (long-term) environmental and socio-economic impacts. Drought Monitoring and Forecasting are recognised as one of three pillars of effective drought management, and it is, therefore, necessary to improve both monitoring and sub-seasonal to seasonal forecasting for droughts and water availability, and to develop innovative indicators and methodologies that translate the data and information to underpin effective drought early warning and risk management.

This session addresses statistical, remote sensing, physically-based techniques, as well as artificial intelligence and machine learning techniques; aimed at monitoring, modelling and forecasting hydro-meteorological variables relevant to drought and water scarcity. These include, but are not limited to: precipitation, extreme temperatures, snow cover, soil moisture, streamflow, groundwater levels, and the propagation of drought through the hydrological cycle. The development and implementation of drought indicators meaningful to decision-making processes, and ways of presenting and integrating these with the needs and knowledges of water managers, policymakers and other stakeholders, are further issues that are addressed and are invited to submit to this session. Contributions focusing on the interrelationship and feedbacks between drought, low flows, and water scarcity, ; and the impacts these have on socio-economic sectors including agriculture, energy and ecosystems, are welcomed. The session aims to bring together scientists, practitioners and stakeholders in the fields of hydrology and meteorology, as well as in the fields of water resources and drought risk management. Particularly welcome are applications and real-world case studies, both from regions that have long been exposed to significant water stress, as well as regions that are increasingly experiencing water shortages due to drought and where drought warning, supported by state-of-the-art monitoring and forecasting of water resources availability, is likely to become more important in the future.

New observations about earthquakes keep accumulating that contribute to unveil every time a bit more our understanding of earthquake processes and related earthquake cycle. Methods have significantly improved in geophysics, in geodesy, and in paleoseismology-geomorphology. Hence, on one hand the number of earthquakes with well-documented rupture process and deformation pattern has increased significantly. Similarly, the number of studies documenting long time series of past earthquakes, including quantification of past deformation has also increased. On the other hand, the modeling communities, both numerical and analogue, which are working on rupture dynamics and/or earthquake cycle are also making significant progresses. Thus, this session is the opportunity to bring together these different contributions to foster further collaboration between the different groups focusing all on the same objective of integrating earthquake processes into the earthquake cycle and crustal deformation framework. Hence, in this session we welcome contributions documenting earthquake ruptures and crustal deformation processes, both for ancient events or recent events, from seismological, geodetic, or paleoseismological perspective. Contributions documenting deformation during pre-, post-, or interseismic periods, which are highly relevant to earthquake cycle understanding, are also very welcomed. Finally, we seek for any contribution looking at the earthquake cycle from the modeling perspective, especially including approaches integrating data and modeling.

Earthquakes are one of the most impactful natural phenomena responsible for many losses of life and resources. To minimize their effects, it is important to characterize the seismic hazard of the different areas, understanding the variables involved. To better estimate the seismic hazard, earthquake source(s) and seismicity need to be better understood. Moreover, local site conditions have to be characterized to produce a reliable model of the ground shaking in the sites of interest. The goal of this session is to understand what are the cutting-edge studies on the topics of seismic hazard, site effect, and microzonation.

In this session, studies related to the following topics, but not limited to, are welcome:
● Seismic hazard analysis
● Seismic source characterization
● Characterization of seismicity in seismic hazard analysis
● Ground motion prediction analysis
● Site effect and microzonation
● Earthquake-induced effects (e.g. lLiquefaction and landslide)
● 1D, 2D, and/or 3D nNumerical site effect modelingmodelling in 1D, 2D, and/or 3D medium
● Soil-structure interaction and analysis
● New approaches in seismic hazard characterization
● Machine learning for seismic hazard, site effect, and microzonation

Nature-based coastal solutions (NBCS) are gaining increasing traction by coastal scientists, managers and engineers as the way forward for managing vulnerable coastal environments. While there is evidence of NBCS – living shorelines, mangrove, saltmarsh and dune restoration, and artificial reefs – being successful in stabilising shorelines and coastal zones, enhancing habitat structures and biodiversity, facilitating carbon sequestration, improving water quality, and reducing flooding and erosion risk, there is limited to no evidence of the effectiveness of NBCS over the long-term. Herein, the long-term is defined as multi-decadal timescales, the timescales of concern for decision-making policies and strategies aimed at sustainable coastal zone management. The uncertainty regarding the long-term effectiveness of NBCS is further fuelled by the uncertainty on the spatial and temporal scales over which coastal systems respond to natural and human forcings. With NBCS being actively pushed for coastal management globally, we need to understand its long-term effectiveness and implications for coastal environments and the cultures, societies and economies that are explicitly linked to these environments. This requires evidence of NBCS successes and failures across spatio-temporal scales, with critical insights on potential uncertainties regarding its long-term impacts on coastal landscapes and socioeconomics in a future local, regional, and global environment.

We, therefore, welcome contributions that provide: (a) case study examples on the successes and failures of NBCS over various spatio-temporal scales across variations in coastal geomorphology, (b) critical insights on the future long-term implications of NBCS for coastal geomorphology and associated socioeconomics, and (c) methodological innovations (e.g., numerical modelling, systems dynamics mapping, smart technology, etc.) for assessing the long-term efficacy of NBCS.

Wildfires are a worldwide phenomenon with many environmental, social, and economic implications, which are expected to escalate as a consequence of climate change and land abandonment, management, and planning, further promoting land degradation and decreasing ecosystem services supply.
The current situation demands from the scientific community the study of wildfire effects on the ecosystems and the development of integrated tools for pre- and post-fire land management practices that reduce the vulnerability to wildfires and their impacts. However, this research urges the attention not only from researchers, but also from stakeholders and policy-makers all over the world, since basic resources such as raw materials, water, and soils as well as habitats are at stake.
This session aims at gathering researchers on the effects of wildfires on ecosystems, from wildfire prevention to post-fire mitigation. We kindly invite laboratory, field, and/or modelling studies involving the following topics:
i. prescribed and/or experimental fires;
ii. fire severity and burn severity;
iii. fire effects on vegetation, soil and water;
iv. post-fire hydrological and erosive response;
v. post-fire management and mitigation;
vi. socio-economic studies on pre- and post-fire land management;
vii. fire risk assessment and modelling.

In recent decades, extreme fire events have become increasingly common, exemplified by the recent fire seasons in Greece, Canada, Hawaii, California, Australia, Amazonia, the Arctic and the Pantanal. While these extremes and megafires have an exponential impact on society and all aspects of the Earth system, there is much to learn about their characteristics, drivers, links to climate change, and how to quantify their impacts, as well as mitigation and prevention strategies and tools.

One area of attention is how extreme fires are currently represented by different fire models. Due to their stochastic nature, uncertainty in observations, and the challenge of representing local processes within global models, extreme fires and their impacts still present a challenge to coupled modelling. The big data science models and machine learning approaches show promise in representing extremes but are weak in coupling feedbacks to vegetation, soils and the wider Earth System.

We also welcome case studies of regional extreme wildfire events, their impacts, and prevention and mitigation strategy experiences worldwide. We encourage contributions from a wide range of disciplines, including global, regional, and landscape modelling, statistical and process-based modelling, observations and field studies, science and social science studies on all temporal scales. In this session, we aim to share knowledge across multiple disciplines, from science to decision-makers and practitioners, to help overcome the challenges that wildfires pose to our models and our society.

We aim to explore the significance and interactions of extreme wildfires and their impacts on society and the earth system and identify the current gaps in our understanding to help us prepare for and mitigate future extreme wildfire events.

Fire is the main terrestrial ecosystem disturbance globally and a critical Earth system process. Fire research is rapidly expanding across disciplines, highlighting the need to advance our understanding of how fire interacts with land, atmosphere and society. This need is growing as fire activity increases in many world regions. This session invites contributions that investigate the role of fire within the Earth system across any spatiotemporal scale, using statistical (including AI) and process-based models, field and laboratory observations, proxy records, remote sensing, and data-model fusion techniques. We strongly encourage abstracts on fire's interactions with: (1) weather, climate, atmospheric chemistry, and circulation, (2) land physical properties, (3) vegetation composition and structure and biogeochemical cycle, (4) cryosphere elements and processes (such as permafrost, sea ice), and (5) human health, land management, conservation, and livelihoods. Moreover, we welcome submissions that address: (6) spatiotemporal changes in fire in the past, present, and future, 7) fire products and models, and their validation, error/bias assessment and correction, as well as (8) analytical tools designed to enhance situational awareness for fire practitioners and to improve fire early warning systems.

This session welcomes abstracts that consider how to observe, analyse and model feedbacks of people and water, and the effects of social and environmental changes on hydrological systems. It is organised by the International Commission on Human-Water Feedbacks (ICHWF) of the IAHS, which provides a home for interdisciplinary research on the dynamics of human-water systems, particularly involving the social sciences.
Examples of relevant topics include:
• Observations of human impacts on, and responses to, hydrological change
• Interactions of communities with local water resources
• Hydrological models that include anthropogenic effects
• Interdisciplinary qualitive and quantitative methods including theoretical models to isolate, conceptualize and/or simulate feedbacks in human water systems
• Creation of databases describing hydrology in human-impacted systems
• Data analysis and comparisons of human-water systems around the globe and especially in the global south
• Human interactions with hydrological extremes, i.e. floods, droughts and water scarcity
• The role of gender, age, disability status, primary language, nationality/refugee status and cultural background in the impacts of hydrological extremes, risk perception, and during/after crises and emergencies

Mountains are iconic landmarks, impressive sides, water sources, and home to many people. In the high elevation and over-steepened topography of the high mountain ranges such as the Alps, Himalayas, Andes, and Rocky’s, to name a few, catastrophic hazards unfold from high elevations, and trigger often associated events on their long way downstream, amplifying the effects even further. These events can be widespread or start in very confined and localized places. Typically, they are triggered by earthquakes, severe storms, and/or a concatenation of events like rapid warming of high-elevation snowpack, rain on frozen ground, the failure of a moraine-dammed lake, avalanches or landslides triggering further mass mobilization and so forth. As global warming progresses and equilibrium altitude lines of glaciers and freezing zones in general move upslope, large areas become ice-free and uncover large amounts of now mobile materials that were frozen and stable before. These freshly exposed, often easily erodible materials add now to the overall thread. Their location at high elevations and with the altitude-associated potential energy make these materials even more prone to compounding events in the future.

We welcome contributions investigating in space and time:

- catastrophic mobilization of sediments and cascading events
- hazards associated with deposition and runout features
- concepts of compounding and cascading dynamics
- connectivity between hillslopes and river networks
- feedback lopes of stabilizing and destabilizing processes on the slopes

We invite presentations that focus on observational, conceptual, methodological, or modeling approaches or a combination of those in all kinds of mountain environments and particularly encourage early career scientists to apply for this session.

Climate services have a well-recognised potential for empowering decision makers in taking climate-smart decisions, through the provision of climate-relevant information at sub-seasonal to seasonal scales, early warning of drought and water scarcity, and/or longer-term climate projections. Recent decades have seen significant advances that underpin the climate science data provided through such services, but despite these advances, crossing the last-mile in early warning proves to be challenging and barriers remain to actual uptake and use. These barriers include the lack of understanding of end-user needs and the options end-users have to respond; limited understanding of the decision-making processes of users, and a poor recognition of the local knowledge they hold and the role it can play in the provision and uptake of climate services.

Research shows, however, that more human-centred approaches and integration of local and traditional knowledges within climate services co-design and co-delivery can help establish services that are credible, salient and legitimate; leading to improved uptake and use. This is also recognised in recent initiatives such as the Early Warning for All launched recently by the United Nations.

This session addresses grounded research that advances the integration and combination of local and scientific knowledges in climate services, in particular in services that provide early warning to drought and water scarcity, heat waves, and advance information on water availability to support water resources management decisions across sectors such as water allocation, crop planning, reservoir operations (including hydropower) etc. We particularly encourage contributions that report action-based, multi-disciplinary research, involving multi-disciplinary researchers, and engagement with local stakeholders and communities. We encourage presentations that have had demonstrable impacts through improved uptake of advance warning, leading to better preparedness for climate extremes droughts and water scarcity, and better adaptation.