Landslides and slope instabilities induced by rainfall or snowmelt represent significant global hazards, causing substantial damage and loss of life annually. Despite this impact, the fundamental triggering mechanisms remain a key area of ongoing research. Landslide-prone areas and slope instabilities are characterized by complex, heterogeneous subsurface properties and dynamic processes operating across a wide range of timescales – from seconds to decades – and spatial scales – from grain size to slope dimensions. Effectively identifying and predicting instability processes and ultimately failure requires innovative approaches that account for these wide temporal and spatial variabilities. Furthermore, the prediction of such locations is of great importance for zonation purposes and for the design of early warning systems to prevent human casualties. Recent innovations in monitoring and modelling offer new avenues for investigating these multifaceted processes.

This session seeks contributions presenting novel methods, emerging trends, and case studies in landslide and slope instability reconnaissance, monitoring, and early warning. We particularly encourage submissions showcasing the integration of geophysical, geotechnical, geological, and remote sensing data to build a landslide model able to characterize the landslide architecture and track its evolution.

We especially invite abstracts demonstrating:

• Multi-method approaches combining geophysical, geotechnical, and remote sensing techniques.
• Applications of machine learning to landslide hazard assessment and prediction.
• Time-lapse geophysical surveys for monitoring subsurface changes.
• Determination of geomechanical parameters through integrated geological (e.g., borehole data, geotechnical surveys) and geophysical studies.
• Effects of climatic global changes and land use on the susceptibility and hazards towards shallow landslides.
• Field hydrological monitoring for the assessment of main pore-pressure build-up areas and triggering conditions of shallow landslides.

Recognizing the cross-disciplinary nature of this challenge, we welcome contributions addressing a broad range of slope instability types, including avalanches, natural and engineered slopes, and climate-induced failures.

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.

Under the influence of global climate change, urban expansion and human activities, landslides (and geo-hydrological hazards in general) occur frequently every year around the world, posing a great threat to human life and property safety. The global increase in damaging events has attracted the attention of governments, practitioners and scientists to develop functional, reliable and (when possible) low-cost monitoring and management strategies. Numerous case studies have demonstrated how a well-planned monitoring system of landslides (and ground deformation in general) 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 aerial platforms and satellites, with particular focus to new platforms (SAOCOM, Sentinel-1C, LuTan). All these techniques are adopted for the same final scope: measure 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 analysis, depending on the type of phenomenon, the selected monitoring tool and the acceptable level of risk.
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.
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 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 and Artificial Intelligence-based methods.

This combined session focuses on landslides and large mass movements in rock, debris, and ice, together with other types of ground failure such as liquefaction and subsidence, in settings where seismic activity plays a key role. Observations from recent earthquakes show that impacts are not confined to the coseismic phase, because damaging mass movements can also occur in the post-seismic period due to disturbances caused by earthquakes. These cascading hazards are often treated separately, even though an integrated approach is clearly desirable, and the session provides a forum for researchers and professionals to discuss processes, case histories, and hazard implications across both co-seismic and post-seismic phases.
Large-scale instabilities in rock, weak rocks, debris, and ice represent enormous risks and are complex systems that are difficult to describe, investigate, monitor, and model. Their evolution can range from slow to fast complex mass movements and depends on forcing factors, geological and hydrological boundary conditions, and the evolution in space and time of thermo-hydro-mechanical controls, as well as the properties of the unstable mass. Many aspects remain understudied and debated due to difficult characterization and the limited number of thoroughly studied cases, and regional and temporal distribution and relationships with controlling and triggering factors are often poorly understood, resulting in poor predictions of behaviour and evolution under present and future climates. The session welcomes contributions on case studies, monitoring and modelling approaches and tools, numerical and physical modelling of dynamic loading and instability, deterministic event scenarios and probabilistic evaluations, threshold definition and offline data analyses, advanced numerical modelling and machine learning techniques, innovative dating and investigation methods, site effects such as amplification and the influence of pre-existing landslide masses, and impacts on structures and infrastructures including tunnels, dams, and roads, with the goal of improving hazard assessment and supporting early warning systems.

Changes in the natural and/or artificial electric, magnetic and electromagnetic fields have been observed during the past few decades in relation with the earthquakes and with the tectonic processes. For example, disturbances in the ground electric currents, in the geomagnetic field, in the VLF-LF-MF radio signals as well the appearance of electromagnetic emissions in the frequency range from ULF to VHF have been revealed. Usually, these effects take place before the occurrence of earthquakes, so that seismic precursors can be pointed out. In particular, a clear lithosphere-atmosphere-ionosphere coupling appears. This session will focus on: (1) electric/magnetic signals and electromagnetic emissions related to seismic-tectonic activity; (2) disturbances in the electromagnetic wave propagation in the lithosphere, atmosphere and ionosphere related to the previous activity; (3) underlying mechanisms of lithosphere-atmosphere-ionosphere coupling; (4) seismic electric/magnetic and electromagnetic precursors revealed by ground/satellite data; (5) laboratory experiments and theoretical models. Reviews of the past worldwide results as well presentations of future research plans are welcome. Likewise results on different precursors of earthquakes observed in ground and atmospheric parameters as well by mathematical-statistical analysis are welcome.

Recent advances in physical and statistical modelling based on seismicity patterns provide new insights into the preparation of large earthquakes and the temporal, spatial, and magnitude evolution of seismicity.
Improvements in monitoring technologies now deliver seismic data of unprecedented quality and quantity. Earthquake catalogues are more complete and accurate than ever, and many are now publicly available, enabling analysing understudied regions and expanding global knowledge. New-generation catalogues, sometimes compiled with machine learning, reveal seismicity structures in ways not previously possible.
Additionaly, geodetic, geological, and geochemical data, fluid analyses, laboratory experiments, and earthquake simulators generating synthetic catalogues help refine models and test hypotheses. Integrating such multidisciplinary perspectives enhances our understanding of earthquake generation.
To exploit these datasets, statistical approaches and machine learning are essential. These tools uncover hidden relationships and clustering, and address challenges of data inhomogeneity, paving the way for deeper understanding and robust forecasting.
We invite contributions on developments in physical and statistical modelling and machine learning, including:
• Spatial, temporal, and magnitude properties of earthquake statistics
• Earthquake clustering analyses
• Effects of fluid diffusion and geodetic deformation on seismicity
• Physical and statistical models, including for understudied regions (e.g., Africa, Southeast Asia)
• Quantitative testing of models
• Data requirements and analyses for validation
• Machine learning applied to seismic data
• Uncertainty quantification in pattern recognition and machine learning
• Reliability and completeness of catalogues
• Time-dependent hazard assessment
• Software and methods for earthquake forecasting

Mountains are complex social–ecological systems (MSES) and natural laboratories where the impacts of global environmental change become particularly visible. Rapid climate warming, cryosphere loss, shifting hydrological regimes, land-use change, and socio-economic transformation are jointly reshaping mountain environments. These changes affect MSES or specific parts such as ecosystems, water resources, natural hazards, livelihoods, and human well-being, with consequences that extend far beyond mountain regions. As the planet’s water towers, mountains regulate freshwater availability along the mountain-to-lowland continuum and provide essential ecosystem-services. At the same time, mountain communities are often highly exposed and vulnerable to climate-related hazards such as floods, landslides, droughts, and compound or cascading events. Understanding how hazards, exposure, and vulnerability interact in space and time is therefore essential for effective climate risk management and long-term adaptation.
This session invites inter- and transdisciplinary contributions that examine past, present, and future environmental change in MSES and contributing from different perspectives to the understanding of MSES. Mountain regions present specific scientific and societal challenges.
Complex terrain remains difficult to adequately parameterize in models, high-elevation monitoring infrastructure is limited in many parts of the world, and socio-economic dynamics are often insufficiently captured in environmental assessments. Addressing these knowledge gaps is critical for developing robust and equitable adaptation strategies.
We particularly encourage contributions that integrate physical and social processes, explore cross-scale feedbacks and compound risks, advance high-elevation monitoring and remote sensing, apply climate downscaling approaches, and combine process-based, data-driven, and participatory methods. Studies engaging stakeholders, co-producing knowledge, and linking science to decision-making and policy are especially welcome.
By fostering dialogue across disciplines and between science and practice, this session aims to advance a systems-based understanding of MSES and support transferable approaches to sustainable adaptation under global environmental change.
This session is endorsed and supported by the Mountain Research Initiative and the Institute for Interdisciplinary Mountain Research of the Austrian Academy of Sciences.

Early Warning Systems (EWS) represent a critical cornerstone of disaster risk reduction as they provide an essential foundation for protecting lives and livelihoods through the timely provision of actionable information. However, the efficacy of EWS is dependent not only on scientific robustness but also on seamless integration across disciplines, from disaster risk knowledge and hazard detection to communication strategies and community response. Subsequently, these systems require innovative advancements across the warning chain to meet the ambitious targets outlined in the Early Warnings for All (EW4ALL) initiative action plan and the Sendai Framework towards multi-hazard, all-vulnerability, and impact-based EWS. This session aims to foster a dialogue on the implementation and methodological innovations surrounding EWS, particularly between researchers working toward more effective, inclusive, and actionable EWS.

This interdisciplinary session invites contributions from a wide range of disciplines and sectors involved with the full spectrum of EWS development and implementation, including but not limited to natural hazards science, atmospheric and hydrologic research, social sciences, and disaster management practice. We encourage submissions addressing the following key themes and sharing of lessons from successes and failures:
● Early warning and anticipatory action: Frameworks and multi-stakeholder implementation in translating early warnings/EWS into effective disaster response and preparedness mechanisms;
● Impact-based approaches: methodologies and approaches for design and implementation of impact-based EWS;
● Technological innovations: advances in AI, machine learning, Earth observation, IoT and other cutting-edge technologies in components of EWS;
● Risk communication and community engagement: strategies that integrate behavioral and psychological insights, building trust, and ensure effective warning communication and dissemination, particularly at the community level;
● Data integration and system interoperability: approaches to integrate diverse data sources that address challenges in cross-agency data sharing and platform integration.

Climate change and environmental degradation constitute a growing threat to the stability of societal and economical systems. The observed and anticipated escalation in the frequency and intensity of extreme weather events under future emission scenarios, combined with the projected long-term shifts in climate patterns and consequential impacts on biodiversity, have the potential to significantly affect specific sectors such as insurance and finance leading to significant economic damages on a local to global scale.

To accurately understand climate risks, baseline historical understanding of hazard is required and what large-scale factors influence this for different geographic regions. Then 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. To avoid an underestimation of future physical climate risks. Further challenges include the accurate representation of extreme events, their compounding and cascading effects, and the integration of non-linearities associated with tipping points in the climate system.

In recognition of this challenge climate risk assessments have experienced amplified attention in both the academic and private spheres and a growth in climate risk services aiming at setting standards and frameworks as well as the provision of comprehensive climate impact information for the private sector and financial institutions.

Therefore, providing a platform to foster interactions between scientists, risk modellers and assessors, economists and financial experts is urgently needed. With the goal of facilitating such dialogue, this session aims at providing a platform for actors from academia and the private sector to exchange information on strategies for assessing climate risk.

The session is organised under three main pillars:
-Physical Climate Risks: Trends, Processes and Modelling
-Identifying and Managing Climate Risks
-Quantifying Damages and Impacts from Climate Risks

We encourage submissions on a wide range of topics including innovative climate risk modeling and model evaluation, damage functions, integrated assessment modelling, bias adjustment and downscaling methods, climate emulators, climate hazard indicators and their projections for specific sectors (e.g. food, energy, insurance, real estate, supply chains), impact data collection and categorization.

Europe is warming faster than any other continent, with climate-related hazards such as heatwaves, droughts, floods, and wildfires becoming more frequent and intense. These events not only pose direct threats to human systems but also trigger cascading effects across ecosystems, biodiversity, and biogeochemical cycles. This panel discussion explores the complex interplay between climate change and compounding natural hazards—such as wildfires, landslides, and extreme weather—and their cascading impacts on ecological systems, biogeochemical processes, and carbon dynamics. It will examine how these interactions affect ecosystem services, resilience and adaptation, drawing on insights from ecological modelling, Earth observation, and multi-risk analysis.

To effectively address these complex and cascading risks, the session also draws on expertise in governance and science-policy communication, recognising that scientific insights must be translated into actionable strategies, informed decision-making, and inclusive policies that enhance societal and ecological resilience.

This session brings together experts in ecological modelling, Earth Observation, multi-risk assessment, governance, and science-policy communication, including members of the EGU Climate Hazards Task Force. Panellists will respond to questions from the chairs and the audience, addressing how scientific research can better inform policy, what tools are needed to anticipate complex hazard-ecosystem interactions, and how to foster resilience in the face of uncertainty. The session aims to bridge disciplinary boundaries and spark dialogue between scientists, policymakers, and civil society, encouraging a shift from reactive to proactive risk and ecosystem management.

Every year brings new observations about earthquakes with a level of detail never reached before. In parallel, observational and computational methods keep improving significantly in seismology, geodesy, and in paleoseismology-geomorphology. Hence, on one hand, the number of earthquakes with well-documented rupture processes and deformation patterns is increasing. On the other hand, the number of studies documenting long time series of past earthquakes, including quantification of past deformation, has also increased. In parallel, the modeling community working on rupture dynamics, including earthquake cycle, is also making significant progress. Thus, this session is the opportunity to bring together these different contributions to foster further collaboration between the different groups all focusing on the same objective of integrating earthquake processes into the earthquake cycle framework. In this session, we welcome contributions documenting earthquake ruptures and processes, both for ancient events or more recent ones, such as the 2023 Turkey sequence, the 2025 Myanmar earthquake, or the 2025 Kamchatka M 8.8 earthquake, from seismological, geodetic, or paleoseismological perspectives. Work combining different approaches is particularly welcome, as are contributions documenting deformation during pre-, post-, or interseismic periods, which are highly relevant to understanding earthquake cycles. Finally, we seek contributions looking at the earthquake cycle from the modeling perspective, both numerical or analogue, especially including approaches that mix data and modeling.

This session invites contributions focused on the understanding, modeling, and prediction of extreme events in weather, climate, and broader geophysical systems, from both theoretical and applied perspectives. We aim to bring together researchers from the traditional geophysical sciences with those working in mathematical, statistical, and dynamical systems approaches, fostering an interdisciplinary dialogue and discussions.
By highlighting the complementary nature of physical intuition and mathematical formalism, this session seeks to advance our understanding of the processes that give rise to extremes, improve predictive capabilities, and assess the extremes' societal and environmental impacts.
Topics of interest include, but are not limited to:
- Variability and projected changes in extremes under climate change
- Representation and performance of climate models in simulating extreme events
- Attribution of extreme events
- Emergent constraints on extreme behavior
- Predictability of extremes across meteorological to climate timescales
- Connections between extremes in dynamical systems and observed geophysical extremes
- Theoretical and applied studies of extremes in nonlinear and chaotic systems
- Downscaling techniques for extreme events
- Linking the physical dynamics of extreme events to their impacts on society and ecosystems.
We particularly encourage submissions that bridge disciplines, propose novel methodologies, or offer new insights into the mechanisms and consequences of extreme geophysical phenomena. We encourage submissions from the "Transdiscipinary Newtork to bridge Climate Science and Impacts on Society" (FutureMED) and the "Seasonal-to-decadal climate predictability in the Mediterranean: process understanding and services" (MEDUSSE) COST action communities.

Why this short course
Earth and environmental sciences thrive on data diversity: from ocean temperatures to biodiversity records, from climate indicators to geological observations. Yet, this very diversity can also be a barrier: different datasets are described with different standards, stored in different formats, and are difficult to connect across research infrastructures. The ENVRI-Hub provides a set of tools to overcome these challenges. It offers researchers a unified framework to discover, access, and reuse complex and multidisciplinary data.

This short course will give researchers a practical introduction to how ENVRI-Hub workflows can directly support their own projects, to build more reproducible and impactful science.

What researchers will learn
By joining this short course, researchers will:
- Get a clear picture of why Essential Variables matter in Earth and environmental sciences and how variable harmonisation improves scientific collaboration;
- Explore datasets through different pathways, including LLM-based search;
- Draft a mini workflow using curated Jupyter notebooks to map and query essential variables and visualise results;
- Share ideas with peers on how ENVRI-Hub workflows could advance their own research projects.

Interactive format
This 1h45min researcher-focused applied training session will blend live demonstrations, guided practice with curated tools, and participation discussions.

The interactive outline will engage participants by offering them an opportunity to:
- Navigate the ENVRI-Hub services and datasets: knowing what’s available and what fits their needs;
- Understand how to integrate ENVRI-Hub analytical tools into their research workflows: from data discovery and annotation to analysis and sharing;
- Present research use cases by reflecting on common challenges and benefits across domains

Who should join
This short course is tailored for:
- Researchers in Earth and environmental sciences, project coordinators, and data scientists looking to improve their data workflows;
- Anyone interested in applying interoperable approaches to interdisciplinary research;
- Anyone with basic familiarity with Python/Jupyter.

Land degradation - driven by natural hazards such as floods, droughts, wildfires and other factors - is one of the great challenges of the Anthropocene. It can lead to reduced ecosystem functions and services, biodiversity loss, and a decline in agricultural productivity. The challenge lies not only in halting land degradation but, even more importantly, in restoring degraded lands and soils - also in the framework of the new European regulation on environmental restoration.
In this debate, we will address challenges related to land and soil degradation and restoration, focusing on the impacts of Natural Hazards and adopting a Critical Zone perspective. We will discuss how to monitor, understand, model and manage critical zone processes and related natural hazards, with the goal of supporting the health of soils and land within a “one health” perspective that recognizes the interdependence of human and environmental well-being.

We here invite contributions highlighting the i) most recent advances in volcanic hazard assessment, both on recently active volcanic systems and on volcanoes with long lasting quiescence periods and ii) exploring the influence of educational strategies and, specifically, the role of Earth Science Museums and targeted research programmes including educational initiatives in modifying the adaptive response to, as well as the recovery of populations from volcanic disasters.
The purpose of the session is to discuss the contributions of new methodological and technological advances and the results arising from the integration of well-established methodologies, which have permitted major advances in the assessment of volcanic hazard in specific sites and to highlight both positive and negative impact of educational programs on preparedness, response, and overall influence on vulnerability.
The session will include studies presenting a critical analysis of the sources of uncertainty in volcanic hazard assessment and offering an integrated quantification of the multihazards associated with volcanic activity.

This session focuses on the role of hydrological processes on slopes for improving landslide hazard assessment and early warning. It addresses the analysis of hydrological processes at both local and large scales, combining field monitoring studies using novel measurement techniques with advanced and data-driven modeling approaches.
Water circulation within a catchment in both shallow and deep hydrological systems represents the most common factor controlling and triggering slope movements. Nevertheless, the integration of hydrological knowledge into landslide occurrence analysis, such as water storage, water-rock interactions, soil-bedrock exchange, preferential flows, and frost conditions, is still limited. Similarly, the incorporation of hydrological information into rainfall threshold development is still not fully developed or widely adopted. Researchers from all fields are warmly invited
to submit contributions ranging from field monitoring, modelling and novel data-driven approaches to advance the knowledge of processes leading to landslide occurrence.

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”. 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 underlined by the IPCC and IPBES, climate change and biodiversity loss are deeply interconnected and must be addressed jointly. This session therefore focuses on how NbS can serve as adaptation strategies to climate change, while simultaneously preserving or restoring biodiversity. Considering various ecosystems (marine and coastal, urban, cropland, mountainous, forest, rivers…), NbS as climate change adaptation solutions 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 discussion integrating multiple disciplines 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 risk of oversimplification, interconnection between NbS and complementary areas, consideration of uncertainties
- 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: bio-geophysical processes, spatial shift between the location of NbS and the beneficiaries one, modification under climate change (tipping point), co-benefits or negative effects
- Assessment and indicators: measurement and modelling protocols, capacity to measure the complexity, resilience and stability of NbS
- Co-development with stakeholders, engaging civil society, and integrating NBS into education, aligned with IAHS Helping Decade objectives

Climate- and weather-related losses continue to rise, even as scientific understanding and risk management efforts expand. While climate change intensifies the frequency and magnitude of many hazards, evolving exposure patterns and the multidimensional nature of vulnerability are equally decisive drivers of risk. This session examines the dynamic interplay of these factors across physical, social, environmental and institutional dimensions to understand how hazards, exposure, and vulnerability co-evolve in space and time, and how those dynamics shape risk outcomes in the Anthropocene.

We invite contributions that move beyond static assumptions and address nonstationarity, compounding events, and cascading failures. Hazard regimes are changing, and their interactions can amplify impacts in the built environment. Submissions that analyze triggers, propagation, and recovery processes are particularly welcome.

Exposure is growing as urbanization intensifies, economies expand, and infrastructure networks densify, yet its spatio-temporal dynamics remain under-characterized. We encourage work that maps and models exposure trajectories under shared socio-economic pathways, evaluates the effectiveness and unintended consequences of mitigation and land-use measures, and explores how mobility, land-use change, and supply-chain linkages redistribute risk.

Understanding the vulnerability of elements at risk is crucial, because it governs the severity of impacts from climate hazards and is key to reducing future losses. The challenges of the Anthropocene require widening definitions and assessing shifts across multiple interacting hazards and contexts to address the multidimensional, dynamic character of vulnerability. However, the growing complexity of managing multiple domains, scales, and disciplines can impede holistic perspectives. We welcome studies that integrate socio-ecological, behavioral, engineering, institutional, and contextual information. Interdisciplinary and mixed-method approaches that bridge datasets and improve data interoperability, validation of vulnerability functions, and synthesis of evidence are encouraged.

We aim to foster transferable, adaptive risk management that connects landscape processes with human activities and supports equitable climate adaptation. By integrating the dynamics of hazards, exposure and vulnerability, this session advances coherent pathways to manage climate risk in the Anthropocene.

Glaciers and ice sheets interact with volcanoes in several ways, including instances where volcanic/geothermal activity alters glacier dynamics or mass balance, via subglacial eruptions or the deposition of supraglacial tephra. Glaciers can also impact volcanism, for example by directly influencing mechanisms of individual eruptions resulting in the construction of distinct edifices. Glaciers may also influence patterns of eruptive activity when mass balance changes adjust the load on volcanic systems, the water resources and hydrothermal systems. However, because of the remoteness of many glacio-volcanic environments, these interactions remain poorly understood, although they are particularly important in polar and high-latitude regions, including coastal and marine settings where ice dynamics affect landscapes from frozen summits to shorelines and the seafloor.

Hazards associated with glacier-volcano interaction can vary from lava flows to volcanic ash, lahars, landslides, pyroclastic flows, submarine eruptions or glacial outburst floods. These can happen consecutively or simultaneously and affect not only the Earth, but also glaciers, rivers and the atmosphere. As accumulating, melting, ripping or drifting glaciers generate signals as well as degassing, inflating/deflating or erupting volcanoes, the challenge is to study, understand and ultimately discriminate these potentially coexisting signals. This challenge also extends to coastal and submarine environments, where coupled cryosphere–volcanic–oceanic processes can impact signals and deposition dynamics on the seafloor. We wish to fully include geophysical observations of current and recent events with geological observations and interpretations of deposits of past events.

We invite contributions that deal with the mitigation of the hazards associated with ice-covered volcanoes or studies focused on volcanic impacts on glaciers and vice versa. Research on recent activity is especially welcomed. This includes geological observations, e.g. of deposits in the field or remote-sensing data, together with experimental and modelling approaches. We particularly encourage abstracts that includes multi-scale and technology-driven approaches. We also invite contributions from any part of the world and other planets on past activity, glaciovolcanic deposits and studies that address climate and environmental change through glaciovolcanic studies.

The frequency and intensity of extreme floods are increasing worldwide, with direct consequences such as loss of life and property. Cutting-edge monitoring and simulation technologies are instrumental in guiding flood risk management. A variety of physical and conceptual hydrological and hydrodynamic models, as well as data-driven approaches (such as artificial intelligence, including machine learning), are available to inform flood risk assessment and management, including prevention, preparedness and recovery. These techniques provide the scientific community with a platform to explore the drivers of flood risk and develop effective flood risk reduction strategies. However, they also come with associated uncertainties.

This session aims to bring together experts, researchers, and practitioners to present and discuss recent developments in the field of flood risk mapping, assessment and management. Topics such as 1D, 2D and 3D modelling for flood risk assessment, emergency action planning and the analysis of dam and levees breaching, as well as the design of structural, non-structural and nature-based measures, are welcome. Research on the associated uncertainties, sensitivity analysis, and flood impact modelling is also relevant to the session.

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
- analysis of hydro-meteorological drivers to enhance forecasting
- warning models for issuing warning
- operational applications and performance analyses
- machine learning techniques applied for early warning purposes

The assessment of the earthquake hazard and risk and the enhancement of the society’s resilience are 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. Also welcomed to this session are 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.

Offshore geohazards including earthquakes, mass gravity flows, volcanic eruptions, and tsunamis are capable of significant loss of human life and economic disruption. Recent advances in geophysical imaging, scientific ocean drilling, and seafloor instrumentation have increased the understanding of offshore geohazards. However significant knowledge gaps remain in understanding the timing and interplay of geological processes at the origin of geohazards. For example, high-latitude regions are experiencing dynamic changes in response to global warming that can lead to geohazards but are complicated to predict. Forecasting and risk assessments including probabilistic approaches are complex given the uncertainties involved and therefore geohazard quantification is poorly constrained. The sedimentary record of past offshore and coastal hazardous events is often well preserved in marine and lacustrine environments and can be investigated in detail with high-resolution geological and geophysical tools. We welcome contributions that highlight new results, methodologies, monitoring techniques, and lessons learned from case studies in areas of paleoseismology, submarine landslides and sediment flows, tsunami generation, and volcanic processes. We invite contributions from all margins and environments, including lakes. The aim of this session is to bring together the scientific community, marine industry, and governmental agencies involved in geohazard research and management to promote cooperation and better understanding of offshore geohazards.

Over the past decade, geodetic and remote sensing techniques have experienced significant growth, driven by the expansion of GNSS-based networks and the launch of satellite missions such as Sentinel-1, ALOS-2, TerraSAR-X, LuTan-1, SAOCOM-1, NISAR, and various commercial satellites. This rapidly increasing volume of data enables the acquisition of continuous and spatially extensive datasets over large regions of Earth, offering unprecedented opportunities to improve our understanding of natural and human-induced geohazards across a wide range of temporal and spatial scales, including earthquakes, volcanic eruptions, landslides, glacier dynamics, underground fluid changes, sea-level rise, land (coastal) subsidence, and tsunamis.

This session invites contributions across various disciplines and techniques to quantify, monitor and model the above-mentioned natural and human-induced processes, with particular emphasis on coastal vertical land motion and subsidence-related hazards. Interdisciplinary studies bridging tectonics, geodesy, volcanology, engineering geology, remote sensing, hydrology, ocean sciences, geomorphology and AI for enhanced risk assessment are strongly encouraged. We welcome contributions on a wide range of topics, including but not limited to: 1) Novel algorithms for mitigating SAR/InSAR errors, including deep learning approaches; 2) Advanced strategies for processing and analyzing SAR big data; 3) Integration of AI and machine learning with GNSS and InSAR observations to improve time series interpretation, identify deformation patterns, and disentangle driving processes, 4) multi-sensor and in-situ monitoring using geomorphologic, geodetic, field-based, and modeling approaches; 5) hazard assessments and disaster risk reduction, focusing on vulnerability, capacity, and resilience.

Urban environments are at the frontline of risk, shaped by rapid expansion, climate shocks, informality, and socio-economic pressures. This session welcomes contributions that cover the full spectrum of urban risk - from physical monitoring and modelling, to dynamic vulnerability assessments, to urban governance frameworks and resilience policy. We particularly welcome contributions that (a) address urban risk in the Global South and (b) address risk in small urban centres, where much of the projected urban growth will occur.

Potential themes include:
-Multi-hazard profiles of urban centres: compiling case studies and theoretical evidence for potential hazard interrelationships at the city scale
-Smart sensing and digital twins: exploring the use of AI, crowd-sourced data and big data to understand urban risk dynamics
-Urban expansion and adaptation: understanding how both formal and informal growth of cities interact with the urban hazardscape
-Policy, governance and management aspects of urban risk and resilience
-Early warning systems and anticipatory action: methods to combine local knowledge and predictive capabilities to issue effective early warnings in cities

We welcome interdisciplinary approaches, including:

-Case studies
-Modelling
-Empirical data collection and monitoring
-Inclusive methods such as stakeholder engagement, citizen science and participatory approaches
-Innovative methods in AI and machine learning
-Frameworks and tools for measuring risk and resilience

This session provides an interdisciplinary forum for researchers, policy-makers, and practitioners to share cutting-edge research and practical insights, highlighting diverse approaches to understanding and reducing urban risk.

Assessing the impact of climate variability and changes on hydrological systems and water resources is crucial for society to better adapt to future changes in water resources, as well as extreme conditions (floods and droughts). However, important sources of uncertainty have often been neglected in projecting climate impacts on hydrological systems, especially uncertainties associated with internal/natural climate variability. From one model to another, or one model realisation to another, the impact of diverging trends and sequences of interannual and decadal variability of various internal/natural climate modes (e.g., ENSO, NAO, AMO) could substantially alter the impact of human-induced climate change on hydrological variability and extremes. Therefore, we need to improve both our understanding of how internal/natural climate patterns affect hydrological variability and extremes, and how we communicate these impacts. We also need to understand better how internal/natural variations interact with various catchment properties (e.g., vegetation cover, groundwater support) and land-use changes. Developing storylines of plausible worst cases, or multiple physically plausible cases, arising from internal climate variability can complement information from probabilistic impact scenarios.

We welcome abstracts capturing recent insights for understanding past, present, and future impacts of internal/natural climate variability on hydrological systems and extremes, as well as newly developed probabilistic and storyline impact scenarios. Results from model intercomparisons using large ensembles are encouraged.

Hydroclimatic extremes such as floods, droughts, storms, or heatwaves often affect large regions and can cluster in time, therefore causing large socio-economic damages. Hazard and risk assessments, aiming at reducing the negative consequences of such extreme events, are often performed with a focus on one location despite their spatially compounding nature. Also, temporal clustering of extremes is often neglected, with potentially severe underestimation of hazard. While spatial–temporal extremes receive a lot of attention by the media, it remains scientifically and technically challenging to assess their risk by modelling approaches.
This session aims to explore advances in the study and modeling of hydroclimatic extremes, embracing a broad perspective that includes—but is not limited to—their spatial and temporal characteristics. Key challenges include the definition of multivariate and compound events; the quantification of uncertainties, of spatial and temporal dependence together with the introduction of flexible dependence structures; the identification and integration of physical drivers and processes across scales; the handling of high-dimensional data and the estimation of occurrence probabilities. Improved representation of spatial–temporal dependence, clustering, and uncertainty is also critical for robust hazard and risk assessments, with direct implications for infrastructure design, disaster preparedness, climate adaptation strategies, and risk management in the (re)insurance sector.
We welcome contributions that enhance our understanding of the mechanisms driving hydroclimatic extremes, propose innovative modeling frameworks, or offer new insights into the prediction, attribution, and risk assessment of these events across space and time. Studies addressing extremes from statistical, physical, or interdisciplinary perspectives are particularly encouraged.

Computational earth science uses modelling to understand complex physical systems which cannot be directly observed. Over the last years, numerical modeling of earthquakes has provided new approaches to apprehend the physics of earthquake rupture and the seismic cycle, seismic wave propagation, fault zone evolution, and seismic hazard assessment. Recent advances in numerical algorithms and increasing computational power enable unforeseen precision and incorporation of multi-physics components in physics-based simulations of earthquake rupture and seismic wave propagation but also pose challenges in terms of fully exploiting modern supercomputing infrastructure, realistic parameterization of simulation ingredients, and the analysis of large synthetic datasets. Meanwhile, advances in laboratory experiments link earthquake source processes to rock mechanics.

This session brings together modelers and data analysts interested in the physics and computational aspects of earthquake phenomena and earthquake engineering. We welcome contributions spanning all aspects of seismic hazard assessment and earthquake physics - from slow slip events, fault mechanics and rupture dynamics, to wave propagation and ground motion analysis, to the seismic cycle and interseismic deformation and links to long-term tectonics and geodynamics - as well as studies advancing the state-of-the art in the related computational and numerical aspects.

About 90% of the Earth’s volcanism is associated with convergent or divergent plate boundaries and can thus be satisfactorily explained by plate tectonics. However, the origin of anomalous volcanism within both continental and oceanic plate interiors (i.e. intraplate volcanism) as well as unusual on-boundary volcanism (e.g. Iceland) is less advanced. This enigmatic volcanism was initially attributed to mantle plumes, but in recent years new models have been developed to explain its origins (e.g. edge-driven convection, sublithospheric drainage). Modern improvements in instrumentation, techniques, and data availability (e.g. spatial-temporal resolution) have greatly expanded our understanding of Earth dynamics and structure. Re-evaluation, refinement, and new models for the origin of intraplate and unusual on-boundary magmatism have also provided insights on deep mantle processes and the complex interactions between Earth’s asthenosphere, lithosphere, and surface. Understanding what triggers magmatism unrelated to plate boundaries is critical in understanding the evolution of Earth’s mantle, surface dynamics, volcanism, and chemistry through time, including the initiation of plate tectonics, climate, and life. It is also key to understanding lithospheric deformation in the presence of underlying magma, past and present volcanic catastrophes, and the environmental impacts of magmatism through time. With the rise of space exploration and the development of spacecraft data analysis, this knowledge is also crucial to the understanding of magmatism on other planetary bodies in the solar system and beyond. This session aims to bring together cross-disciplinary work on intraplate and unusual plate boundary magmatism to stimulate interactions between researchers with diverse ideas, observations, approaches, and backgrounds. We welcome contributions that apply any appropriate method including (isotope) geochemistry, petrology, geophysics, volcanology, seismology, numerical and analogue modelling, drilling, plate kinematics, tectonics, sedimentology, field and structural geology, or thermo- and geo-chronology. Studies focusing on Large Igneous Province (LIP) magmatism, wide magmatic rifted margins (e.g. Laxmi Basin), or magmatism associated with continental material far offshore (e.g. Rio Grande Rise) are particularly encouraged. We also encourage innovative studies, the spanning of spatio-temporal scales, and thought-provoking ideas that challenge conventions.

Recent advances in Large Language Models (LLMs) and Natural Language Processing (NLP) are rapidly changing geosciences research, offering new opportunities for knowledge discovery, data analysis, and real-time monitoring. At the same time, the increasing availability of digital text and image data—from scientific literature and newspaper articles to social media and historical archives—offers unprecedented opportunities to explore new data sources in geosciences research.

This session examines how geoscientists are using LLMs, NLP, and text-as-data approaches across various hydrology, natural hazards research, and the broader earth system sciences research fields. We invite contributions that showcase innovative uses of LLMs and NLP, discuss methodological challenges, or integrate text mining techniques into geoscientific workflows.

We particularly welcome submissions on topics including, but not limited to:
- Chatbots and AI assistants in geosciences
- Assessment of natural hazard impacts (e.g., floods, droughts, landslides, heatwaves, windstorms)
- Real-time disaster monitoring and early warning systems
- Evidence synthesis and literature mapping
- Public sentiment and perception analysis
- Policy tracking and narrative analysis
- Social media analyses
- Enhancement of metadata and data descriptions
- Automation of historical data rescue
- Integration of LLMs with remote sensing or image data
- Methodological challenges in using LLMs and NLP-based analyses, including bias, reproducibility, and interpretability

By sharing case studies, technical developments, and lessons learned, we aim to promote the effective use of these tools while also highlighting the challenges that newcomers may encounter, including issues with data coverage, quality control, and concerns about reproducibility. By sharing best practices, this session aims to inspire collaboration and innovation in harnessing LLMs, NLP, and text-as-data in geosciences.

This session concentrates on extreme rainfall events, surface water dynamics, and flood events, exploring innovative remote sensing, AI, and digital twin technologies for real-time monitoring, risk assessment, and mitigation. It invites submissions on advanced data integration, modeling approaches, early warning systems, and decision-support tools to improve understanding, forecasting, and management of flooding and related surface water hazards.

The integration of AI with digital twin improves the analytical and operational capabilities of geospatial systems, which through the analysis of historical data and the integration of real-time information (IoT) are able to highlight even “hidden patterns” in the data, identifying new models capable of improving forecasts with greater control over the quantification of uncertainty and the variability of the phenomenon analysed.

This session aims to focus on flood hazard and risk assessment, monitoring, and management. This Topic invites the submission of articles focused on, but not limited to, the following areas:
• Monitoring of extreme rainfall events and flood hazards for risk assessment and communication.
• Digital twins (DTs)/prototypes of DTs in flood hazard forecasting, early warning, monitoring, and supporting tools for urban governance.
• DSSs to extract meaningful information in the artificial intelligence era, eventually serving to reduce risk and provide support tools to mitigate flood hazards.
• The role of AI and digital twins to assess the economic impacts of flood hazards and the cost-effectiveness of various mitigation strategies.
• Novel techniques to analyse big data coming from Earth observation platforms, drones, and other geospatial data in order to provide timely information related to the extend, exposure, and impacts of flood hazards.