Extremes in temperature, especially 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. Specifically on health impacts from extremes in temperature, exposure to cold and heat remains as one of the leading causes of deaths from natural hazards globally, with the total (cold and heat)-related deaths projected to increase in a warming world. In recent years, extreme heat events in particular have tested the preparedness of public health services, with a recent study estimating over 70,000 heat-related excess deaths in Europe alone during the summer of 2022. While our understanding of city-level temperature-related health impacts in the present climate has improved, how future health-burden in a warming climate can evolve continues to remain a daunting challenge, especially when accounting for adaptation and changes in future socio-demographic factors at different spatial scales. Moreover, warming trends and the associated health risks vary regionally and are often associated with uncertainties emanating both from modelling strategies in health-impacts assessments and the projected temperatures from climate models.

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) explore the diverse socio-economic impacts of extreme heat events including vulnerability and exposure for example, on aspects relating to human health, economic productivity, or biodiversity; (iii) address forecasting and monitoring of extreme heat at seasonal to sub-seasonal time scales; (iv) focus on societal 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 to assess societal relevant heat extremes and their impacts.

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 occurring in 2023, to the ability of models to reproduce them and methods to forecast them or produce early warnings, 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 is increasing, causing dire 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 mechanistic hydrological and hydrodynamic computational models as well as data-driven models (e.g., Artificial Intelligence “AI” and Machine Learning “ML”) 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. Furthermore, recent advances in airborne remote sensing (include Drone “UAV”) and spaceborne remote sensing help to enhance the accuracy and efficiency of flood monitoring such as inundation mapping in real-time and offline mode.
The objective of this session to invite fundamental and applied research studies carried out through Remote Sensing (e.g., Drone “UAV", satellites), Mechanistic Hydrologic/Hydraulic/Hydrodynamic modelling, and Data-driven AI and ML, including their associated uncertainties for flood inundation mapping, flood hazard mapping, risk assessment, and flood risk management. Particular topics such as 1D, 2D and 3D modelling for flood risk assessment, Emergency Action Planning (EAP), Evacuation planning, Dam Break Analysis (DBA) are also welcome. The scope of the session also covers uncertainty quantification and sensitivity analyses at all stages of flood risk modelling.
Invited Speaker: Dr. Roos Wood from University of Bristol, UK. (https://research-information.bris.ac.uk/en/persons/ross-a-woods)

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

Hydrological extremes (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, develop robust methods for modelling and analyzing floods and droughts, 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 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

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 more Earth observation data than ever before, this progress is expected to increase.
We encourage presentations related to flood monitoring and mapping through remotely sensed data including: - 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.

Drought and water scarcity affect many regions of the Earth, including areas generally considered water rich. A prime example is the severe 2022 European drought, caused by a widespread and persistent lack of precipitation combined with a sequence of heatwaves from May onwards. 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 and physically-based techniques, aimed at monitoring, modelling and forecasting hydro-meteorological variables relevant to drought and water scarcity. These include, but are not limited to: precipitation, snow cover, soil moisture, streamflow, groundwater levels, and extreme temperatures. 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 and water scarcity, hydrological impacts, and society are also 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.

Water is a strategic issue in drylands, where ecosystems and their inhabitants strongly rely on the scarce and often intermittent water availability or its low quality. The characteristics of drylands increase their vulnerability to climate change and susceptibility to the impact of short- to long-term extreme events and processes, such as floods, droughts, and desertification. These events can reshape the landscape through the mobilisation of surface sediments, deposits of which preserve archives of past Earth system states, including changes in the extent of deserts. Over the last century, anthropogenic modifications of all kinds and intensities have affected surface conditions. In drylands and Mediterranean hydrosystems, agricultural water use is constantly increasing threatening the sustainability of the surface and groundwater reservoirs, and their hydrology is then continuously evolving. Nevertheless, the study of hydroclimatic processes in drylands remains at the periphery of many geoscientific fields. A proper understanding of the hydrological, hydrometeorological and (paleo)climatic processes in these regions is a cornerstone to achieving the proposed sustainable development goals we set for the end of this century.

This session welcomes contributions from scientific disciplines addressing any of the drylands' full range of environmental and water-related processes. The purpose is to foster interdisciplinary research and expand knowledge and methods established in individual subdisciplines. We will address hydrological issues across global drylands, and devote a section of our session to a geographical focus on the Mediterranean region to analyse the changes in hydrologic processes and fluxes unique to that region.

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 from a single model realization 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. Furthermore, model findings may contrast with insights that global satellite data provide, e.g. observations of hydrological change often do not support dry-gets-dryer and wet-gets-wetter patterns that global climate models suggest. 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 better understand how internal/natural climate variations interact with various catchment properties (e.g., vegetation cover, groundwater support) and land-use changes altering them. In this direction, storylines of plausible worst cases, or multiple physically plausible cases, arising from internal climate variability can complement information from probabilistic impact scenarios. In addition, a comparison of satellite data and model output can help close the gap in understanding wetting and drying patterns at the continental scale.

We welcome abstracts capturing recent insights for understanding past or 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. We also solicited presentations on improving our observing system (e.g. via new retrieval approaches, data assimilation, or developing new sensor systems) and on developing modelling frameworks.

Karst environments are characterized by distinctive landforms and unique hydrological behaviors. Karst systems are extremely complex, heterogeneous and very difficult to manage, because their formation and evolution are controlled by a wide range of geological, hydrological, geochemical and biological processes, and are extremely variable in time and space. Furthermore, karst systems are highly vulnerable to a variety of hazards, due to the direct connection between the surface and subsurface through the complex networks of conduits and caves.
In karst, any interference is likely to have irreversible impacts and disturb the natural balance of the elements and processes. The great variability and unique connectivity may result in serious engineering problems: on one hand, karst groundwater resources are easily contaminated by pollution because of the rapidity of transmission through conduit flow, and remediation action, when possible, could be very expensive and require a long time; on the other hand, the presence of karst conduits that weakens the strength of the rock mass may lead to serious natural and human-induced hazards. The design and development of engineering projects in karst environments thus should necessarily require: 1) an enhanced understanding of the natural processes governing the initiation and evolution of karst systems through both field and modelling approaches, and 2) specific interdisciplinary approaches aimed at mitigating the detrimental effects of hazardous processes and environmental problems.
This session calls for abstracts on research from karst areas worldwide related to geomorphology, hydrogeology, engineering geology, hazard mitigation in karst environments in the context of climate change and increasing human disturbance.

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 the spatially compounding nature of extreme events. Also, clustering of extremes in time 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. Key challenges in advancing our understanding of spatio-temporal extremes and in developing new modeling approaches include: the definition of multivariate events; the dealing with large dimensions; the quantification of spatial and temporal dependence, together with the introduction of flexible dependence structures; the identification of potential drivers for spatio-temporal dependence; the estimation of occurrence probabilities, and the linking of different spatial and temporal scales. This session invites contributions which help to better understand processes governing spatio-temporal extremes and/or propose new ways of describing and modeling compounding events at different scales.

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, as well as on future storm development under changed climate conditions. This will include storm predictability studies on different scales. Finally, the session will also invite studies investigating impacts related to storms: Papers are welcome dealing with vulnerability, diagnostics of sensitive social and infrastructural categories and affected areas of risk for property damages. Which risk transfer mechanisms are currently used, depending on insured and economic losses? Which mechanisms (e.g., new reinsurance products) are already implemented or will be developed in order to adapt to future loss expectations?

Forecasting the weather, in particular severe and extreme weather has always been the most important subject in meteorology. This session will focus on recent research and developments on forecasting techniques, in particular those designed for operations and impact oriented. Contributions related to nowcasting, meso-scale and convection permitting modelling, ensemble prediction techniques, and statistical post-processing are very welcome.
Topics may include:
 Nowcasting methods and systems, use of observations and weather analysis
 Mesoscale and convection permitting modelling
 Remote sensing and data assimilation
 Ensemble prediction techniques
 Ensemble-based products for severe/extreme weather forecasting
 Seamless deterministic and probabilistic forecast prediction
 Post-processing techniques, statistical methods in prediction
 Use of machine learning, data mining and other advanced analytical techniques
 Impact oriented weather forecasting
 Presentation of results from relevant international research projects of EU, WMO, and EUMETNET etc.

Key Words: Forecast technique, nowcasting, ensemble prediction, statistics, AI

Volcanoes are complex systems with potentially catastrophic impacts, able to generate and distribute vast sediment volumes to surrounding environments. Understanding, modelling and forecasting volcanic hazards is challenging, not least because of data issues. There is a need for the construction of robust and reliable models for forecasting volcanic hazards, both syn- and post-eruptive, and management of the resulting risks.

Syn-eruptive hazards include pyroclastic density currents, volcanic plumes and gas theoretically described by computational fluid dynamics, and experimentally modelled. But application of experimental results to large-scale natural processes is only possible via a thorough scaling analysis. Uncertainty is frequently cited as a major problem 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 is multi-scale, multi-dimensional and nonlinearly correlated, and often not representative of the volcano's potential behaviour. Additional knowledge is often required to provide the 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, and for assessing 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 numerical modelling approaches.

Addressing risks from volcanic eruptions requires interactions between volcanologists and decision-makers, and with pre-eruption mitigation activities. These present issues around timeliness, the use of data, administrative responsibilities, and the application of laws.

The session aims at advancing volcanic hazard estimation and response through multidisciplinary approaches including
• Better describing uncertainty in volcanic hazard estimates through the use of statistical, analogue, surrogate and synthetic data
• Field studies of volcanoclastic features in sedimentary records,
• Novel statistical, experimental and computational modelling approaches, and
• Examination of the role of the state in volcanic risk management

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 to evolution in space and time of hydro-mechanical controls . 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, failure propagation, leading to rapid mass movements . Nevertheless, these approaches are still phenomenological and have difficulty to explain the observed behavior. Impacts of such instabilities on structures represents a relevant risk but also an opportunity in terms of investigations and quantitative measurements of effects on tunnels, dams, roads. Design of these structures and knowledge of their expected performance is fundamental.
We invite to present case studies, sharing views and data, to discuss monitoring and modeling approaches and tools, to introduce new approaches for thresholds definition, including advanced numerical modeling, Machine Learning for streamline and offline data analyses, development of monitoring tools and dating or investigation techniques.

Across the world, a large part of slope instability phenomena of different type (e.g. landslides, rockfalls, debris flows) is recognized to be regulated 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). On the other hand, local modifications induced by human intervention: e.g. socio-economic induced land use/cover changes, reduced soil management due to land abandonment or implementation and maintenance of Nature Based Solutions are recognized playing a key role in slope instability risk. In turn, such local human-induced factors can be strongly influenced by weather dynamics: e.g. hydrological and thermal regime regulate vegetation suitability, then land cover and, in turn, landslide risk.
A clear and robust evaluation about how ongoing and expected global warming and resulting climate change can affect such factors and, therefore, landslide risk represents a clear need for practitioners, communities, and decision-makers.
The Session aims at presenting studies concerning the analysis of the role of climate-related variables and slope-atmosphere interaction on landslide/rockfall triggering/activity and/or effectiveness of protection measures, across different geographical contexts and scales. Test cases and investigations (by exploiting monitoring and modelling) carried out in different geographical contexts in evaluation of ongoing and future landslide activity are welcome. Furthermore, are greatly welcome investigations focused on data-driven approaches (e.g. Machine Learning, AI) through which the variations induced by climate and environmental changes on triggering, dynamics, and hazard are analysed.

Mountain regions are a complex system of different glacial, paraglacial and periglacial environments rapidly changing due to global warming. In this context, short-term landscape evolution is affected by glacier motion, by a variety of mass movements including slow rock slope deformations, rock and debris slides, rockfalls, as well as by periglacial features such as rock glaciers. These mass movements are driven be different processes, evolve at different rates and can pose different risks to lives, human activities and infrastructure. The physics of rock slope degradation and the dynamics of failure and transport define the hazards.

In this session we bring together researchers from different communities interested in a better understanding of the physical processes controlling mass movements mass around the world in glacial, paraglacial and periglacial environments, and investigating their evolution in a changing climate. Topics range from state-of-the-art methods for assessing, quantifying, predicting, and protecting against alpine slope hazards across spatial and temporal scales to innovative contributions dealing with mass movement predisposition, detachment, transport, and deposition. The selected contributions are expected to: (i) provide insights from field observations and/or laboratory experiments; (ii) apply statistical methods and/or artificial intelligence to identify and map mass movements; (iii) present new monitoring approaches (in-situ and remote sensing) applied at different spatial and temporal scales; (iv) use 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 and mitigation. We also aim at triggering discussions on effective countermeasures that can be implemented to increase preparedness and risk reduction, and studies that integrate social, structural, or natural protection measures.

The session strives to build a community and to grow networks at EGU and beyond.

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 four main components: monitoring, modelling, warning, response. However, tools, instruments, methods employed in the components 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 alert thresholds for evacuation or interruption of services. At regional scale rainfall thresholds are widely used to prepare a timely response of civil protection and first responders. For such systems, hydro-meteorological thresholds built combining different variables represent one of the most promising and recent advancement. Concerning the modeling techniques, analyses on small areas generally allow for the use of physically based models, while statistical models are widely used for larger areas.
This session focuses on LEWS at all scales and stages of maturity (i.e., 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. The session is not focused only on technical scientific aspects, and submissions concerning practical and social aspects are also welcome.

Contributions addressing the following topics will be considered positively:
- conventional and innovative slope-scale monitoring systems for early warning purposes
- conventional and innovative regional prediction tools for warning purposes
- innovative on-site instruments and/or remote sensing devices implemented in LEWS
- warning models for warning/alert issuing
- operational applications and performance analyses of LEWS
- communication strategies
- emergency phase management

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 minimally 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.
Novel geophysical methods represent valuable approaches in understanding landslides characteristics, especially when integrated with remote sensing, machine learning techniques and time-lapse surveys.
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 integration and synergic use of different techniques is welcomed, as well as newly developed tools or data analysis approaches, including big data management strategies. The session is expected to present case studies in which multi-temporal and multi-platform monitoring data are exploited for risk management and Civil Protection aims with positive effects in both social and economic terms. Specific relevance is given to the evaluation of the impact of landslides on cultural heritage.
The current session includes contributions deriving from the session NH3.3 – 'Landslide Imaging and Monitoring Using Geophysical Methods - Perspectives and Possibilities’.

Landslide Inventory Maps (LIMs) are the basic tool for spatially representing landslides, forming the cornerstone for subsequent analyses in landslide research. Traditional methods of landslide mapping have historically relied on heuristic interpretation, resulting in varied accuracy, coverage, and timeliness. Their reliability is influenced by mapping errors arising from diverse techniques and base data. Recent research emphasizes geographic accuracy, thematic accuracy, and completeness/statistical representativeness as key factors defining the quality of LIMs.
Classification of susceptibility adds to the complexity of mapping efforts. Conventional methods often struggle with differences between the types of landslides due to variations in morphological and environmental factors. The integration of Machine Learning (ML) has revolutionized landslide mapping and modeling. ML's capacity to extract critical patterns from heterogeneous data sources enables precise classification of landslides, addressing challenges faced by conventional methods. Additionally, ML techniques offer a comprehensive view of the landscape and its dynamic changes and a comprehensive solution for assessing and mitigating landslide hazards by addressing challenges related to threshold determination, classification accuracy, and uncertainty evaluation.
We invite contributions addressing:
• Metrics for evaluating mapping accuracy, errors, and uncertainty.
• Statistical modelling of mapping errors and ML-based classification.
• Quality assessment methods for Landslide Inventory Maps.
• Impact of error propagation on susceptibility models, hazard assessment, and risk evaluation.
• Model inter-comparisons
• Relating LIMs quality to use limitations and decision-making at different land-management levels.

Climate-induced or anthropogenically triggered soil-related 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 mimic natural or biological processes are increasingly being adopted to mitigate the triggering or propagation of such geohazards through improvement of the soil behaviour and its characteristics.

The use of vegetation on potentially unstable slopes and streambanks is an example of a Nature-Based Solution (NBS).
Microbiological activity can also modify soil behaviour. For example, microbially-induced calcite precipitation and biological exudates (such as vegetation mucilage or biopolymers) can change both soil strength and permeability. Furthermore, fungal activity can 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, while also maintaining/enhancing biodiversity and ecosystem services.

This session aims to stimulate interdisciplinary knowledge exchange of NBS and bio-based solutions for geohazard mitigation, with a particular focus on the topics of landslides and erosion.

Contributions could originate from the fields of geotechnical engineering, ecological engineering, biodiversity, 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 hydrological and/or mechanical reinforcement due to 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, practical approaches and frameworks demonstrating how NBS can be used to mitigate geohazards while providing additional co-benefits;
• Upscaling potential of laboratory data to slope and catchment scales;
• Case studies of restoration, stabilization works, or Eco-DRR, especially involving design principles and performance assessment;
• Guidelines, reviews, and data repositories on NBS for risk reduction, with focus on NBS for infrastructure protection.

Although snow may evoke pleasant childhood memories for many, it can also pose various hazards. Some common hazards associated with snowfall and accumulation include (1) disruption of traffic lines due to snow accumulations or bad visibility, (2) damage to infrastructure, such as buildings or power lines, from snow loads or snow creep, (3) (3) flooding due to rapid snowmelt and rain-on-snow, and (4) snow avalanches that can damage infrastructure or cause loss of life. In all these cases, the presence and accumulation of snow are key factors contributing to the hazards, and it is essential to recognize the impact these hazards can have, to better predict their occurrence and mitigate their risks.

The aim of this session is thus to improve our understanding of processes responsible for snow and avalanche hazards and share solutions to monitor and mitigate their impact. We welcome contributions from novel field, laboratory, and numerical studies as well as specific case studies. Topics relevant to snow and avalanche hazards include, but are not limited to, monitoring and predicting snowfall, drifting or blowing snow, meteorological driving factors, snow cover simulations, snow mechanics, avalanche formation and dynamics, forecasting and the impact of climate change.

Rock mass deformation and failure at different stress levels (from the brittle regime to the brittle-ductile transition) are controlled by damage processes occurring on different spatial scales, from grain (µm) to geological formation (km) scale. These lead to a progressive increase of micro- and meso-crack intensity in the rock matrix and to the growth of inherited macro-fractures at rock mass scale. Coalescence of these fractures forms large-scale structures such as brittle fault zones, rockslide shear zones, and excavation damage zones (EDZ) in open pit mining and underground construction. Diffuse or localized rock damage have a primary influence on rock properties (strength, elastic moduli, hydraulic and electric properties) and on their evolution across multiple temporal scales spanning from geological time to highly dynamic phenomena as earthquakes, volcanic eruptions, slopes and man-made rock structures. In subcritical stress conditions, damage accumulation results in brittle creep processes key to the long-term evolution of geophysical, geomorphological and geo-engineering systems.
Damage and progressive failure processes must be considered to understand the time-dependent hydro-mechanical behaviour of fault damage zones and principal slip zones, and their interplay (e.g. earthquakes vs aseismic creep), volcanic systems and slopes (e.g. slow rock slope deformation vs catastrophic rock slides), as well as the response of rock masses to stress perturbations induced by artificial excavations (tunnels, mines) and loading. At the same time, damage processes control the brittle behaviour of the upper crust and are strongly influenced by intrinsic rock properties (strength, fabric, porosity, anisotropy), geological structures and their inherited damage, as well as by the evolving pressure-temperature with increasing depth and by fluid pressure, transport properties and chemistry.
In this session we will bring together researchers from different communities interested in a better understanding of rock deformation and failure processes and consequence, as well as other related rock mechanics topics. We welcome innovative and novel contributions on experimental studies (both in the laboratory and in situ), continuum / micromechanical analytical and numerical modelling, and applications to fault zones, reservoirs, slope instability and landscape evolution, and engineering applications.

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 mitigation of disasters associated with geophysical hazards encompasses several components, including the identification, evaluation and reduction of related risks. Each component comprises multiple facets: a) The analysis of hazards, including its physical characteristics and its effects on built and natural environment and social systems. b) The assessment of vulnerability, exposure to hazards and resilience. c) Long-term preparedness and response following an event (e.g. earthquake, landslide, tsunami). Given the diverse nature of geophysical disaster mitigation, a variety of hazard and risk models have been developed at different time scales utilizing varius methodologies and datasets ( such as imagery, census data, geospatial datasets of built and natural environment, etc.) to provide timely and reliable information for effective disaster mitigation.

This session aims to address both theoretical and implementation challenges, along with considerations related to communication and science policy, focusing on various aspects of risk research and assessment, as well as their application in mitigating disasters. The session will encompass:
The development of physical/statistical models for risk, exposure and vulnerability assessment across various temporal and spatial scales.
1. The assessment of model accuracy against observations (from EO observations to non-traditional seismological data).
2. Time-dependent situational awareness information to assist with early warning and alerting for effective emergency management
3. Analyzing earthquake-induced cascading effects such as landslides and tsunamis, and conducting multi-risk assessments.
The interdisciplinary session encourages the exchange of knowledge and the sharing of good practices acquired through various methodologies. In doing so, it offers opportunities to enhance our understanding of disaster risk in all its facets including vulnerability, capacity, exposure of individuals and assets, hazard attributes and the environment. At the same time, it points out current deficiencies and indicate the way towards future research directions.

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.

One of the primary tasks of seismology is to predict ground motion for future earthquakes. In this regard, local site conditions, among various factors influencing ground motion, hold significant importance. 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. Accurately estimating these effects is crucial for mitigating seismic hazards and risks, as well as developing 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 topographic and stratigraphic amplification effects;
- Quantitative evaluation of seismic site response in 1D, 2D, and 3D configuration;
- Earthquake-induced ground effects, such as liquefaction and landslides;
- Soil-structure interaction and characterization of building response to seismic events.
Moreover, another goal of this session is to gather findings obtained through various geophysical methods, such as earthquake data analysis, surface wave prospecting, electrical resistivity tomography (ERT), ground-penetrating radar (GPR), and seismic refraction tomography, and explore their integration. Contributions regarding innovative methodologies as Distributed Acoustic Sensing (DAS) systems and dense arrays are well accepted.

Geological investigations on faults and the earthquakes they produce continue to advance our understanding of earthquake geology and of the associated seismic hazard.

The application of modern approaches has been shown to provide unprecedented and comprehensive pictures of the mechanics and dynamics of active faults over multiple temporal and spatial scales. Studying recent earthquakes can yield valuable information to characterize the earthquake source parameters and the coseismic behaviour of faults. Paleoseismological investigations extend the seismic record of active faults, providing information on past earthquakes and their recurrence intervals. Studies of the structural geology and tectonic geomorphology of active faults can help us defining their long-term behaviour. Geodesy may be used to complement studies that focus on decadal to multi-millennial timescales. Moreover, multidisciplinary approaches have demonstrated the interaction of faults within fault systems.

Incorporating the knowledge gained from active faults into suitable fault models for probabilistic seismic hazard assessments (PSHA) presents challenges, both in terms of ground motion and fault displacement hazard analysis (FDHA). Hence, this session aims to provide an open forum for recent studies concerning active faults, crustal deformation, PSHA, and FDHA.

In this Fault2SHA session, we welcome contributions describing and discussing different approaches to study active faults and to perform SHA. We are particularly interested in studies applying innovative and multidisciplinary approaches from observations on single earthquakes to geologic timescales. These methods may include, but are not limited to, structural analyses, paleoseismological trenching, high-resolution coring, geologic and morphotectonic studies, Quaternary dating, geophysical imaging, geodetic studies, and stress modelling. We encourage contributors to present studies that consider how fault data can be incorporated into models for seismic hazard assessment.

Understanding seismic activity and associated hazard of seismically active regions requires building comprehensive, multiscale models of earthquake deformation. From individual outcrops to regional scales, seismotectonic studies aim to link active faults mapped at the surface down to the base of the seismogenic layer. Despite significant technological advancements in geophysics (seismic reflection, seismology), laboratory and field structural geology (rock mechanics, rare earth elements and cosmogenic nuclides analysis, paleoseismology), remote sensing (SAR, LiDAR, photogrammetry), software and data (GIS, databases, artificial intelligence, big data), and modeling (analogue and numerical modeling, inversion), numerous questions remain about defining fault dimensions, displacements, segmentation, slip rates, and lithologies hosting seismicity. Among different structural settings, a better understanding of intraplate settings, subduction zones and the interplay between megathrust seismicity and earthquakes within both the oceanic slab at various depths and the upper plate, is needed.

This session aims to bring together the broad community interested in seismotectonics, including subduction zone earthquakes and intraplate settings. We invite contributions that integrate structural geological studies with geophysical and geological observations, laboratory experiments, and numerical models to explore the underlying mechanisms of earthquakes at different spatio-temporal scales. Additionally, we specifically encourage contributions that investigate the spatio-temporal relationships and interplay between interplate and intraplate seismicity in subduction zones, as well as their connection with subduction dynamics.

On New Year’s Day 2024, a shallow Mw 7.5 earthquake hit the Noto Peninsula on the back-arc side of Central Japan. Very intense shaking caused more than 200 casualties and widespread damage to the built infrastructure. The quake triggered a tsunami, numerous landslides, rockfall, and widespread liquefaction. The north of the Peninsula moved by several meters during the rupture. This earthquake is the largest event of a sustained seismic swarm that started in 2020. In this late special session, we will review early analysis of the earthquake, the associated tsunami, its effect on surface processes, and the consequences on the population, infrastructure, and emergency response.

Tsunamis can produce catastrophic damage on vulnerable coastlines, essentially following major earthquakes, landslides, extreme volcanic activity or atmospheric disturbances. 20 years after the disastrous Indian Ocean tsunami, tsunami science has been considerably renewed, expanding its scope to new fields of research, and also to regions where the tsunami hazard was previously underestimated. The 2022 Hunga Tonga - Hunga Ha'apai tsunami also provided a new and urging challenge, bringing new questions on modeling, hazard assessment and warning at different scales and evidencing again the need for a closer cooperation among different research and operational communities.

The spectrum of topics addressed by tsunami science nowadays encompass:
- analytical and numerical modelling of different generation mechanisms (from large subduction, to more local earthquakes generated in tectonically complex environments, from subaerial/submarine landslides to volcanic eruptions and atmospheric disturbances), and propagation and run-up,
- hazard-vulnerability-risk assessment, especially with probabilistic approaches able to quantify uncertainties,
early warning and monitoring, with a special focus on innovative marine and seafloor data that could help to improve early characterization of sources and detection of tsunamis,
- societal and economic impact of moderate-to-large events on coastal local and nation-wide coastal communities,
- present and future challenges connected to the global climate change.

This session welcomes multidisciplinary as well as focused contributions covering any of the aspects above-mentioned, encompassing field data, geophysical models, regional and local hazard-vulnerability-risk studies, observation databases, numerical and experimental modeling, real time networks, operational tools and procedures towards a most efficient warning, with the general scope of improving our understanding of the tsunami phenomenon, per se and in the context of the global change, and our capacity to build safer and more resilient communities.

Coastal areas are vulnerable to erosion, flooding and salinization driven by hydrodynamic hydro-sedimentary and biological processes and human interventions. This vulnerability is likely to be exacerbated in future with, for example, sea-level rise, changing intensity of tropical cyclones, increased subsidence due to groundwater extraction, tectonics, as well as increasing socio-economic development in the coastal zone. This calls for a better understanding of the underlying physical processes and their interaction with the coast. Numerical models therefore play a crucial role in characterizing coastal hazards and assigning risks to them. Drawing firm conclusions about current and future changes in this environment is challenging because uncertainties are often large, such as coastal impacts of likely and unlikely (also called high-end) sea-level changes for the 21st century. Furthermore, studies addressing coastal impacts beyond this century pose new questions regarding the timescale of impacts and adaptation activity. This session invites submissions focusing on assessments and case studies at global, regional, and local scales of potential physical impacts of tsunamis, storm surge, sea-level rise, waves, and currents on coasts. We also welcome submissions on near-shore ocean dynamics and on the socio-economic impact of these hazards along the coast.

Storm surges and tides are important drivers of coastal hazards, including flooding, erosion, and other impacts. They interact with each other, as well as with other coastal processes. Energy from the surface tide is also converted to internal tides, driving ocean processes. Both storm surges and tides show large seasonal and decadal variations. They are influenced by sea-level rise and climate change, and local anthropogenic changes such as dredging and alterations to estuaries. Flood defenses need to be designed and operated allowing for increasingly frequent coastal flooding due to sea-level rise, whilst understanding of tide and surge events is also critical for tidal energy generation. Changes in stratification may alter internal tides dynamics in coastal and global regions. This calls for an improved understanding of long-term trends and sea-level interactions. More precision is required of water level forecasts up estuaries and tidal rivers. Both observations (in-situ measurements and remote sensing) and models (numerical and data-driven) are important tools in understanding how storm surges and tide vary across space and time.

The aim of this session to share innovative approaches and recent advancements in understanding these complex processes and their implications for coastal regions globally. We welcome contributions that i) present novel approaches in measurement, numerical and empirical modelling of (surface and internal) tides and storm surges; ii) enhance our understanding of drivers of extreme sea level events and/or their interactions; iii) investigate the influence of past climate variability on storm surges, surface and internal tides, and their long-term variability; or iv) develop future projections of storm surges and tides and the impact of climate change.

Synthetic aperture radar (SAR) is an established remote sensing tool for the mapping and monitoring of ground deformation. The new generation of radar satellite constellations (e.g., NISAR, NovaSAR) along with a big data repository of historical observations is fostering comprehensive multi-sensor hazard analyses. New constellations’ capabilities rely on innovative techniques based on high-resolution/wide-swath and short-temporal Interferometric SAR (InSAR). While acknowledging the benefits brought by these recent developments, the scientific community is now defining a new paradigm of techniques capable of extracting relevant information from SAR imagery, designing proper methodologies for specific natural and anthropogenic hazards, managing large SAR datasets (e.g., National ground motion services, Copernicus EGMS), and integrating radar data with multispectral satellite observations.
In this session, we welcome contributions that focus on:
(1) New tools and approaches such as artificial intelligence to accurately or automatically analyze InSAR large datasets and displacement time series to detect and monitor seasonal, linear and non-linear ground deformations;
(2) InSAR support for the risk assessment of anthropogenic and natural hazards including mining, oil/gas production, fluid injection/extraction, land subsidence, critical infrastructure, sinkholes, land degradation and coastal erosion, peatlands, glaciers, permafrost, flooding, landslides, earthquakes, and volcanoes;
(3) InSAR-based modeling for a better understanding of the current and future impact of ground deformation.

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.

With the global context of climate change and the increasing human pressure, coasts and estuaries are becoming more vulnerable to environmental hazards and are currently facing an intensification of natural hazards including sea level rise and severe climate events.
These hazards have intensified in the last decade due to the overexpansion of urbanization and infrastructure that these areas are facing, together with the climate change effects, such as sea-level rise and the increase in storminess and droughts. Such drivers have often degraded coastal ecosystems triggering a larger exposure to hazards, consequently increasing the associated risk to coastal populations and reducing their natural resilience.
The assessment of multi-time scale dynamics within coastal zones and their corresponding resilience can be effectively conducted through a diverse array of remote sensing techniques. The use of such techniques depends on the spatial and temporal scales of interest (shoreline, morphological systems, wetlands, vegetation cover, estuaries and reefs), the physical process which could be resolved, and also the availability of measurements in the area of interest. The study on the interaction between several processes requires a coupling between different techniques to overcome the limitations exposed by each technique used separately.
The main objective of this session is to highlight the relevance of remote sensing for the assessment of resilience of coastal and estuarine systems exposed to various external and internal drivers and controlled by different physical and anthropogenic processes. This session particularly invites contributions aimed at the monitoring of coastal and estuarine resilience using approaches that focus on:

(1) Identifying the key variables that allow to assess the coastal resilience;
(2) Building openly accessible coastal and estuarine observation datasets from the use of different satellite missions and compiling them.
(3) Developing new approaches based on physics-based algorithms and/or artificial intelligence for compiling Remote Sensing dataset for the evaluation of resilience.
(4) Assessing the quality of remote sensing datasets in the different environments and their use at different time and spatial scales; and investigating the relevance of their combination with numerical models to evaluate the multi-timescale dynamics of coastal areas and their resilience.

This groundbreaking session merges the forefront of digital technology and explainable artificial intelligence (XAI) to redefine our approach to natural hazard management and resilience. As natural hazards such as earthquakes, floods, landslides, and wildfires become more frequent and severe, leveraging advanced digital solutions is crucial. This session delves into the synergistic application of remote sensing, machine learning, geographic information systems (GIS), IoT, quantum computing, digital twins, and VR/AR in understanding, predicting, and managing natural disasters.
We place a special emphasis on the role of eXplainable AI (XAI) in demystifying AI-driven predictive models. By exploring algorithms like SHapley Additive exPlanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME), we aim to make AI predictions in natural hazard assessment transparent and trustworthy. This approach not only enhances the predictive accuracy but also fosters trust and understanding among stakeholders.
Attendees will gain insights into cutting-edge research and practical applications, showcasing how these integrated technologies enable real-time monitoring, early warning systems, and effective communication strategies for disaster management. The session will feature case studies highlighting the successful application of these technologies in diverse geographic regions and hazard scenarios. This interdisciplinary platform is dedicated to advancing our capabilities in mitigating the risks and impacts of natural hazards, paving the way for safer, more resilient communities in the face of increasing environmental challenges.

Wildfires represent a hazardous and harmful phenomenon to people and the environment, especially in populated areas where the primary cause of ignition is related to human activities. This has motivated scientists to develop spatial-temporal datasets and to produce risk and prognostic maps for governments and managers. A key tool in this respect is to assess the fire spatial-temporal distribution and to understand their relationships with the surrounding environmental, climatological and socio-economic factors.
Innovative algorithms and methodologies developed in the computational science field have proved to be useful in analysing spatially and temporally distributed natural hazards and ongoing phenomena such as wildfires. Moreover, considering the fast-growing availability of high digital geo-referenced data, it is important to promote methods and new tools for their study and modelling, in a wide-range of scales. A new exciting challenge is to convert available datasets into meaningful and valuable information and make this information interesting to stakeholders.
This session aims to bring together fire scientists, researchers of various geo-environmental disciplines, economists, managers, people responsible for territorial and urban planning, and policymakers. The main goal is to improve the understanding of the fire regime and to discuss new strategies to mitigate the disastrous effects of wildfires. We welcome empirical studies, new and innovative technologies, theories, models, and strategies for fire research, seeking especially to identify and characterize the spatial-temporal patterns of wildfires.
Research topics include, but are not limited, to the following:
• development of methodologies based on expert knowledge and data-driven approaches, for the recognition, modelling and prediction of structured patterns in wildfires;
• pre- and post-fire assessment: fire incidence mapping and spatial distribution; fire severity and damages; fire risk management;
• long-term wildfires patterns and trends: relation between wildfires and global changes such as climate, socioeconomic and land use/ land cover changes;
• fire spread models and fire-weather relationships, ranging from case studies to long-term climatological assessments;
• post-fire vegetation recovery and phenology.

Fire is the primary terrestrial ecosystem disturbance globally and a critical Earth system process. Fire-related research is rapidly expanding across disciplines and sectors, reflecting the pressing need to deepen our understanding of fire phenomena. This need will likely grow as future fire activity increases. This session invites contributions that investigate the role of fire within the Earth system across any temporal and spatial 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 that deepen our comprehension of 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) spatial and temporal 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.

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.

The International Monitoring System (IMS) of the Comprehensive Nuclear-Test-Ban Treaty (CTBT) monitors the solid earth, the oceans and the atmosphere with a global network of seismic, hydroacoustic, and infrasound sensors as well as air sampling stations detecting radioactive traces in the atmosphere. The primary purpose of the acquisition and analysis of IMS data is for nuclear explosion monitoring regarding all aspects of detecting, locating and characterizing nuclear explosions and their radioactive releases. On-site inspection (OSI) technologies apply similar methods on smaller scales as well as geophysical methods such as ground penetrating radar and geomagnetic surveying with the goal of identifying evidence for a nuclear explosion close to ground zero.
This session invites contributions in the context of Nuclear-Test-Ban monitoring, using either IMS or OSI instrumentation, data, processing or methods. Furthermore, any contribution about the civil or scientific use of IMS data is welcome. Possible civil applications include disaster risk reduction by early warning or hazard assessments for earthquakes, tsunamis and volcano eruptions. Scientific applications include earth science topics like climate change, deep ocean temperatures, whale migration, earth core structure, atmospheric circulation, radionuclide sources, or acoustic wave propagation modelling.

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.

Increasing effects of climate change, urbanization, and increased interconnectedness between ecological, physical, human, and technological systems pose major challenges to disaster risk management in a globalised world. Economic losses from natural hazards and climate change are still increasing, and the recent series of catastrophic events across the world have manifested the need to shift from single-hazard and sectoral approaches to new and innovative ways of assessing and managing risks across sectors, borders and scales based on a multi-hazard and systemic risk lens.

Addressing the above challenges, this session aims to gather the latest research, empirical studies, and observation data that are useful for understanding and assessing the complex interplay between multiple natural hazards and social vulnerabilities to: (i) identify persistent gaps, (ii) propose potential ways forward, and (iii) inform resilience building strategies in the context of global change.

Today, we are challenged by substantial economic and non-economic losses resulting from natural disasters and the gradual encroachment of environmental changes. These challenges are expected to intensify, propelled by the complex interplay of climate change and the relentless expansion of urban areas. The question of how to adapt to the hazards of the future is therefore of great importance – not only for scientists, but also for practitioners. Nevertheless, a number of critical knowledge gaps exist in our scientific understanding of risk assessment and adaptation strategies. Currently the assessment of future risk trends is predominantly focused on scenarios of future hazards like sea level rise, floods and typhoons. Scenarios encompassing socio-economic changes and projections of exposure and vulnerability are often overlooked. This omission is significant and can lead to potentially flawed and imprecise estimations of future risk and adaptation needs. Furthermore, knowledge on the feasibility of various, often competing, adaptation options remain limited. Typically, such knowledge relies on a narrow set of evaluation criteria, such as economic costs and benefits, and a view towards singular adaptation measures.

We cordially invite submissions of theoretical, methodological, and empirical studies aimed at advancing our understanding of future risk and exploring potential adaptation strategies. We encourage contributions that encompass local case studies, regional insights and global perspectives from multi- and transdisciplinary research endeavors. Of particular interest are coastal cities with rapid growth dynamics and immense adaptation pressures, as can be observed in emerging economies.

The session aims to gather views on consequences of natural hazards, especially their costs as well as their impacts on infrastructure and natural and built heritage.
On the one hand, the session aims to highlight the challenges and advances in assessing the costs of natural hazards (e.g., storm, floods, droughts, earthquakes, fire) around three main topics: post-event data collection, assessment methods, and economic evaluation of risk management measures. The session will address methodological and empirical aspects of data collection and evaluation of various types of costs (direct damage, indirect damage, health impacts, risk reduction costs, environmental). We are interested in contributions that are concerned with both theoretical and practical aspects such as economic appraisal, risk reduction and transfer, adaptation, or dynamics of vulnerability and resilience.
On the other hand, the session addresses disaster risk management affecting built and natural heritage as a consequence of natural and human-made hazards. The whole disaster risk management cycle is covered in a sustainability and resilience approach, from preparedness and mitigation to emergency and rebuild. Particularly welcome are contributions addressing digital methods to map the impact of these hazards on heritage, at both object scale and at the larger neighbourhood, urban and regional scale, including the interaction between these levels. Both contributions addressing methods and lessons learned from case studies are welcome. Possible approaches include how the civil protection and urban planners use this knowledge for decisions. Apart of addressing decision stakeholders per se, the development of decision systems with the integrated scope of addressing (landscape) architectural and archaeologic heritage using digital methods are particularly welcome. Benefit-costs analysis must be part of any decision tree.

We would like to invite potential abstract authors to submit a full paper to the special issue: NHESS – Special issue – Natural hazards’ impact on natural and built heritage and infrastructure in urban and rural zones (https://nhess.copernicus.org/articles/special_issue1252.html).

The session aims to discuss how researchers, practitioners, and professionals can manage cities threatened by climate change-related natural disasters. These disasters, directly and indirectly, lead to effects on the population, energy networks, infrastructures, etc. This session will explore how resilience, adaptation, or transition can contribute to the development of new research approaches or the implementation of action to reduce urban risks. The session aims to highlight experiences in the management of urban systems under multi-risk scenarios in different countries.

We encourage abstracts to explore their conceptualization and operationalization that focus on:
- resilience, adaptation, transition: methods, frameworks and tools to reduce urban risks;
- risk assessment: modeling, simulation, index, and indicators;
- multi-hazard (flooding, heat wave, tsunami, winds, etc.) approach and risk management;
- green transition towards climate mitigation;
- optimization of the decision-making process: implementation, operationalization, simulation, etc.;
- geo-cartography techniques and approaches: risks mapping, hazard mapping, Geography Information Systems (GIS), City Information Modeling (CIM), etc.;
- case studies: framework application, disaster feedback, testing of design alternatives, etc.;
- cascading effects related to interconnections and interdependences between urban systems;
- climate-related impacts on urban technic networks, such as energy networks, transport networks, and water supply networks;
- multidisciplinary works on conceptual elements but also tangible applications.

Droughts pose a global challenge with profound consequences, demanding a comprehensive understanding of this water-related disaster risk. Its adverse effects (e.g. water scarcity, production loss) can cause disastrous impacts (e.g. market instability, hunger, conflict) and occur across interconnected systems (e.g. forestry, tourism, energy, health) at various scales (e.g. through virtual water transfers; caused by multi-year or flash droughts). As the frequency and severity of droughts, and especially of flash and rapidly emerging droughts, increases, the need for proactive risk management alternatives becomes increasingly urgent. The cascading consequences of droughts on diverse systems underscore the need for a holistic approach. Although progress has been made in sector-specific analyses, understanding the complex interplay between different types of droughts, and between its impacts and vulnerability dynamics, remains a persistent challenge.
A substantial portion of drought research to date has focused on the (monitoring of) drought hazard only. However this session seeks to bridge gaps in drought research by focussing on understanding and managing associated risks and impacts. It aims to bring together state-of-the-art transdisciplinary research on systemic drought risks, the emergence of flash droughts, interconnected vulnerabilities, multi-sectoral impact assessment, and implications for drought risk management and adaptation. We aim to discuss topics ranging from the unravelling of cascading and compounding drought risks and impacts to evaluating participatory tools supporting systemic drought resilience. The session will bring together advances on understanding the interactions between the human and water systems and their effect on impact propagation and trade-offs and synergies of drought risk reduction.
Scientists and practitioners specializing in the thematic fields outlined above are invited to contribute their worldwide case studies and meta-insights. We hope to discuss conceptual, methodological, and empirical studies, leveraging diverse methodologies from both the natural and social sciences. We encourage submissions presenting systemic risk assessments and socio-hydrological or hydrosocial contributions, and also welcome sector-specific reviews. By stimulating dialogue among researchers and other stakeholders, this session seeks to support participatory research and foster a community committed to identifying challenges and advancing drought risk research.

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 including greenhouse gases and pollutant, groundwater contamination, with 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.

Natural hazards are a major threat to societies as they produce strong socio-economic impacts and hinder sustainable development. With a projected increase in global urban population, risk mitigation strategies must consider the mutual interactions between the natural environment, social dynamics, and urban development. Urban expansion can amplify or reduce hazards, exposure and the vulnerability of populations. Urban activities should then be dynamically included within all the spheres of risk assessment, quantifying how they directly or indirectly influence hazard occurrence (cause) as much as they are influenced by them (consequence). In addition, the success of risk mitigation strategies strongly relies on citizens who have multiple roles in receiving, understanding, generating and disseminating risk-related information. The definition of mitigation and adaptation strategies should therefore involve multiple key actors (e.g. land use and urban planners) and actively engage citizens and communities through bottom-up approaches (e.g. citizen science, participatory mapping). These key actors can, in turn, support a better understanding of hazards (e.g. using local knowledge to calibrate models), exposure and vulnerabilities. However, disaster risk reduction strategies and their implementation can be disrupted by various obstacles. Among them is misinformation which influences risk perception and can reduce the acceptance of disaster risk reduction strategies and trust in the authorities implementing them. We aim to collect recent scientific advances in assessing and measuring the multifaceted societal contributions to disaster risk assessment and reduction and integrating these contributions into the current risk governance practice. We call for experiences that can contribute to developing such citizen-centered and science-based urban development strategies and policies, bringing evidence on:
- New strategies and data sources (e.g. remote sensing, crowdsourced, traditional or indigenous knowledge) and their integration through emerging technologies (e.g. machine learning and artificial intelligence).
- The impact of urban development on the occurrence and impact of natural hazards and multi-hazards.
- Successful risk mitigation strategies that involve modifying detrimental urban practices.
- Case studies and lessons learned on the active involvement of citizens and other stakeholders into risk assessment frameworks.

Hydrometeorological and geomorphological hazards account for 45% of the fatalities and 79% of global economic losses. Exacerbated by high seismic activity and rugged terrain, the mountainous landscape is particularly susceptible to generating these events, which often transform into cascading hazards—an initial event causes a downstream hazard chain, e.g. glacial lake outburst floods to debris flows. These hazards interfere with increasing population pressure and expansion of settlements along rivers and new infrastructure developments such as roads and hydropower projects. Rising temperatures and changes in weather patterns in the wake of global warming likely elevate risks from hazards such as landslides, glacial lake outbursts, riverine and flash floods. The complexity of these hazards and their underlying processes demand scientific efforts and approaches from multiple disciplines.
Multidisciplinary approaches and methodologies are essential to holistically estimate and predict hazard events and interactions of multiple hazards and to understand how vulnerable societies cope and respond to these hazards in mountainous regions.
This session aims to bring together expertise on approaches, methods, and data to advance the understanding of the impacts and changes in mountain landscapes, with a particular focus on the trends of hydro-geomorphological disasters and their societal impacts.

We welcome contributions from research topics (but not restricted to):
-Hydro-geophysical modelling (landslides, glacial lake outburst floods, riverine and flash floods)
-Extreme event modelling
-remote-sensing-based observations
-risk/vulnerability assessment
-theories and models of reducing vulnerabilities and adaptation to natural hazards
-Innovative data approaches to integrate natural and social science perspectives
-recovery to natural hazards, in particular, usage of longitudinal data methods
-Atmospheric Rivers/cloudbursts triggering Extreme Hydro-Meteo-geomorphological hazards
-Dams and Hydropower impacts

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 new International Commission on Human-Water Feedbacks (ICHWF) of IAHS that is providing a home for interdisciplinary research on the dynamics of human-water systems after the end of the Panta Rhei decade in 2023.
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, and cultural background in the impacts of hydrological extremes, risk perception, and during/after crises and emergencies

Geoscientists are actively engaged in advancing knowledge pertaining to current climate change and environmental crisis, and disseminating it to a broad audience, from the general public to policymakers and stakeholders.

To date, efforts to trigger radical transformations, whether by political, economic, or civil society actors, have overwhelmingly fallen short of the urgent actions recommended by scientific institutions such as the Intergovernmental Panel on Climate Change (IPCC) or the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES). Some scholars argue that the underlying issue lies not primarily in the absence of information (Oreskes, The trouble with the supply-side model of science, 2022), but rather in the power dynamics among various stakeholders and that recognizing this is fundamental (Stoddard et al., Three Decades of Climate Mitigation: Why Haven’t We Bent the Global Emissions Curve?, 2013).
This session targets the diverse roles that geoscientists can play in accelerating the radical transformation of our society to address the current ecological crisis.

Key questions include: How to engage with civil society, stakeholders and policymakers to ensure the implementation of research findings into appropriate policies? How to assess and reduce the ecological footprint of scientific institution, as to show exemplary pathways to the rest of society? How to expand outreach and training efforts, and towards who, the general public or specific stakeholders such as elected representatives, civil servants, economic actors, or even fellow academics? How to contribute and assist legal actions against private or public entities? Should scientists engage in disruptive actions and civil disobedience to transform their own institutions and press on problematic actors, such as the fossil fuel industry?
 
We invite contributions that address these questions, whether from a theoretical perspective or through firsthand experiences. We are particularly interested in examples of research projects or collaborations that have attempted to assess their impact on any of the strategies given above (e.g., ecological footprints, policies, litigation, communication, or pressing on relevant stakeholders). Interdisciplinary work, spanning fields like philosophy, history, sociology, and their application to science or broader societal aspects, is highly encouraged.

Science communication includes the efforts of natural, physical and social scientists, communications professionals, and teams that communicate the process and values of science and scientific findings to non-specialist audiences outside of formal educational settings. The goals of science communication can include enhanced dialogue, understanding, awareness, enthusiasm, improving decision making, or influencing behaviors. Channels can include in-person interaction, online, social media, mass media, or other methods. This session invites presentations by individuals and teams on science communication practice, research, and reflection, addressing questions like:

What kind of communication efforts are you engaging in and how you are doing it?
How is social science informing understandings of audiences, strategies, or effects?
What are lessons learned from long-term communication efforts?

This session invites you to share your work and join a community of practice to inform and advance the effective communication of earth and space science.

This session focuses on approaches to multi-hazard risk assessments and their components (hazard, exposure, vulnerability and capacity), and to explore their applications to disaster risk reduction, adaptation and management.

Effective disaster risk reduction practices and the planning of resilient communities requires the evaluation of multiple hazards and their interactions. This approach is endorsed by the UN Sendai Framework for Disaster Risk Reduction and the NextGenerationEU recovery plan. Multi-hazard risk and multi-hazard impact assessments look at interaction mechanisms among different natural hazards, and how spatial and temporal overlap of hazards influences the exposure and vulnerability of elements at risk. Moreover, the uncertainty associated with multi-hazard risk scenarios needs to be considered, particularly in the context of climate change and slow-onset hazards, such as Covid-19 and pandemics in general, characterized by dynamic changes in exposure and vulnerability that are challenging to quantify.

This session, therefore, aims to profile a diverse range of multi-hazard risk and impact approaches, including hazard interactions, multi-vulnerability studies, and multi-hazard exposure characterization. In covering the whole risk assessment chain, this session identifies potential research gaps, synergies and opportunities for future collaborations.

We encourage abstracts which present innovative research, case study examples and commentary throughout the whole disaster risk cycle on (i) multi-hazard risk methodologies which address multi-vulnerability and multi-impact aspects; (ii) methodologies and tools for multi-hazard risk management and inclusive risk-informed decision making and planning; (iii) methodologies and tools for multi-hazard disaster scenario definition and management for (near) real-time applications; (iv) cross-sectoral approaches to multi-hazard risk, incorporating the physical, social, infrastructural, economic, and/or environmental dimensions; (v) uncertainty in multi-hazard risk and multi-hazard impact assessment; (vi) evaluation of multi-hazard risk under future climate and slow-onset hazards, including pandemics; (vii) implementation of disaster risk reduction measures within a multi-hazard perspective.
Keywords: Disaster risk management, Multi-hazard (management, assessments, models), Multi-risk (management, assessments, models), Risk management, Risk/hazard Assessment (identification, Analysis and Evaluation)

Natural hazards in the Earth system, such as earthquakes, tsunamis, landslides, volcanic eruptions, cyclones, and extreme weather, primarily brew and occur in the lithosphere and troposphere, which often happen unexpectedly and impact human daily life. Tracing the atmospheric and ionospheric disturbances due to the hazards benefits nowcasting their occurrences. On the other hand, solar activities can induce geomagnetic storms that accompany the magnetosphere-ionosphere coupling and atmospheric disturbances, which impact satellite operation, global high-precision positioning and navigation, and damage the electric supply system near the Earth’s surface. Impacts of the hazards are not limited to a specific geosphere but often impact multiple geospheres, subsequently affecting daily life. 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 (hydrosphere), atmosphere, and space (LAS).

In this session, we invite scientists interested in studying the interaction between the lithosphere (hydrosphere), atmosphere, and space but it is not limited to natural hazards alone. 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. Observations of parameters in one geosphere interacting with others, methodologies for detecting signals related to changes in the other geospheres, and the construction of numerical models spanning multiple geospheres are all welcome. The session aims to integrate scientists studying distinct fields to improve and enhance our understanding of the LAS interactions. Ultimately, this research aims to mitigate the loss of human life and property coming with a higher risk of being affected by natural hazards from the Earth and space.

The use of technology can affect the impact of multi-hazards both positively and negatively. This session addresses how technology could play a role in assessing multi-hazard risk and analysing risk changes across space and time, and how innovative tools can support the development of risk mitigation strategies. We will discuss the needs and ways to develop tools that enable systemic risk assessment across sectors and geographical settings. A range of tools are already used to assess individual hazards or possible climate adaptation scenarios, but a tool that enables a combined assessment of them all does not yet exist.
We consider three main standpoints that could enhance the tools in the constantly evolving technological landscape. First, climate scenarios need to be combined with land use and socio-demographic and economic trends that will impact exposure and vulnerability. Second, the timeframe of decision support tools should move from short to long-term by including long-term dynamic scenarios. Third, co-development needs to be considered as a new way to overcome uncertainties to involve various perspectives.
Keeping in mind these three standpoints, we would like to invite contributions that present:
• Tools that support the preparedness of first and second responders in the face of multi-hazard events and reduce the risks related to impacts on various sectors;
• Open-source software for multi-hazard/risk scenario generation, policy recommendations to enable decision-makers and practitioners to adopt a new approach;
• Applications of cutting-edge artificial intelligence (AI) and Machine Learning (ML) tools in the context of climate change, multi-hazard and multi-sector risk and resilience analytics.
• Decision-support systems (DSS) for disaster risk management considering multiple interacting natural hazards and cascading impacts that accounts for forecasted modifications in the hazard (e.g., climate change), vulnerability/resilience (e.g., aging structures and populations) and exposure (e.g., population decrease/increase);
• Multi-disciplinary best practices that focus on the transferability of the developed innovations to different territorial contexts and hazards;
• Novel risk assessment methods that are co-developed by various stakeholders for multi-hazard, multi-sector, and systemic risk management;
• Innovative tools to communicate risks to facilitate deeper learning in complex contexts and enable participants to learn, i.e. serious games.

Hydrogeomorphic processes may naturally act together or interact in a given space or time, creating cascades. Many regions worldwide are already experiencing an increase in cascading processes, often driven by extreme events, with severe impacts that may worsen under future climatic and environmental changes. The physical response to these cascades is hardly predictable due to their complex nature, the interplay between different predisposing, triggering and controlling factors, and the rarity of these events.
Addressing the hazards and impacts resulting from the combination of multiple processes faces enormous challenges, primarily from a still incomplete process interaction understanding. In addition, expertise is scattered across disciplines (e.g., geomorphology, geology, hydrology, climate sciences) and beyond (e.g., civil engineering, social science). A better understanding of cascading processes under environmental changes and extreme events is of critical importance to deciphering impacts of past environmental changes and to develop and influence policy to face future challenges under a changing climate.

This interdisciplinary session aims to shed light on the current knowledge regarding cascading hydrogeomorphic processes and related hazards and to propose novel frameworks for understanding, monitoring, and modeling their complex feedback and interactions. A particular focus is paid on regions affected by diverse environmental changes and extreme events. We welcome scientific contributions in the domain of cascading processes, including (but not restricted to) the study of the link between extreme climatic forcing and hydrogeomorphic processes, and surface processes complexity, such as connectivity or dis-connectivity between hillslopes and fluvial processes. We welcome studies from all climates and at all temporal scales; from the event scale to the long-term integrated impact of cascading processes on the landscape. We invite contributions showing novel monitoring, experimental, theoretical, conceptual and computational modeling approaches. Proposed management strategies to assess cascading processes-related hazards will also be well received.

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.

The closed mines present several challenges for scientific and mines regions. Post-mining activities in the field of geosciences often involve addressing various geology, geotechnical environmental concerns and challenges in the research and application fields. Here are some key aspects related to post-mining and geosciences in the context of environmental considerations:
1. Hazards Evaluation: Ground Movement
o Subsidence can occur during and after mining operations, and the overlying strata collapse or settle into these voids, causing surface depressions. Geoscientists play a crucial role in assessing the potential for subsidence and its impact on the environment and infrastructure.
2. Hazards Mitigation Methods
o Reclamation Geoscientists work on reclamation plans to restore mined areas to their natural state or to suitable post-mining land uses.
o Geotechnical Engineering: Geoscientists and geotechnical engineers collaborate to develop stability assessments and engineering solutions to prevent or minimize ground movement hazards. Techniques such as backfilling, soil stabilization, and structural supports can be employed.
3. Energy and Post-Mine Challenges
o Mine Water Management: Geoscientists help design and implement water management strategies, including the treatment of acid mine drainage (AMD) and the utilization of mine water for geothermal heating or cooling.
o Renewable Energy development: Converting former mining sites into renewable energy facilities, such as solar or wind farms, is a sustainable post-mining option.
4. Storage energy and CO2 and Post-Mine
o Carbon Capture and Storage (CCS): Evaluating the geological and hydrogeological characteristics of potential storage sites is crucial for ensuring the safe and permanent sequestration of CO2.
o Post-Mine Site Selection: Post-mining sites that are no longer suitable for mining operations may be repurposed for CCS or other forms of carbon sequestration.
5. Development of open-pit lake: Geoscientists and hydrogeologists work define the long-term stability of the slope stability, define the reshaping of the land, replanting vegetation, and ensuring proper drainage to mitigate hazards like erosion and water quality degradation.
6. Revalorization of mining tailing storage facilities: The dumps can be both an environmental hazard and an asset for further reprocessing of tailings materials to further extract metals and elements.
7. Sustainable mine waste management strategies
8. Innovative tools and enhanced methodologies for mine waste sampling, characterization, and environmental assessment
9. Transformation of mine waste into energy
10. Reactivation and transition of post-mining repositories and new societal and economical perspectives

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
- Climate Hazard 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

Recent extreme events and climate conditions unprecedented in the observational record have had high-impact consequences globally. Some of these events would have arguably been nearly impossible without human-made climate change and broke records by large margins. Furthermore, compound behaviour and cascading effects and risks are becoming evident. Finally, continuing warming does not only increase the frequency and intensity of events like these, or other until yet unprecedented extremes, it also potentially increases the risk of crossing tipping points and triggering abrupt changes. In order to increase preparedness for high impact climate events, it is important to develop methods and models that are able to represent these events and their impacts, and to better understand how to reduce the risks.

To provide more actionable information for risk assessments, climate storylines have become a popular approach to complement probabilistic event attribution and climate projection. According to the latest IPCC-WG1 report, “the term storyline is used both in connection to scenarios or to describe plausible trajectories of weather and climate conditions or events”. Various types of storylines exist, such as event-based storylines, dynamical storylines of physically plausible climate change, or pseudo-global-warming experiments. This session aims to bring together the latest research on modelling, understanding, development of storylines and managing plausible past and future climate outcomes, extreme and low-probability events, and their impacts. Studies can range across spatial and temporal scales, and can cover compound, cascading, and connected extremes, worst-case scenarios, event-based and dynamical storylines, as well as the effect of tipping points and abrupt changes driven by climate change, societal response, adaptation limits, or other mechanisms (e.g., volcanic eruption).

We welcome a variety of methods aiming to quantify and understand high-impact climate events in present and future climates and, ultimately, provide actionable climate information. We invite work including but not limited to the variety of storyline approaches, model experiments and intercomparisons, insights from paleo archives, climate projections (including large ensembles, and unseen events), and attribution studies.

The session is further informed by the World Climate Research Programme lighthouse activities on Safe Landing Pathways and Understanding High-Risk Events.

Europe’s coastal, underwater, landscape and urban heritage is under threat. The growing climatic crisis and the related increase in the frequency and intensity of natural hazards alongside with anthropogenic pressure highlight the need to accelerate the incorporation of recent scientific and technological advancements to adapt current management practices to the changing climatic conditions. Reliable methods and systems to evaluate these threats are important for the efficient and proactive management of evolving risks for heritage. However, heritage assets are still managed following traditional procedures.
This session focuses on recent advances that contribute to the protection of heritage exposed to climatic, natural, and anthropogenic hazards and enhance the ability of heritage and connected communities to withstand and adapt to the era of extreme events. Potential contributions include, but are not limited, to the following:
•Models and data that advance the fundamental understanding of the effects of climate-change and natural hazards on heritage (e.g. complex phenomena like flow-soil-structure interaction)
•State-of-the-art techniques to identify, quantify and mitigate risks derived from natural, climatic, anthropogenic and biological hazards, including both single- and multi-hazard scenarios, at various types of heritage.
•Sensing solutions for monitoring risks based on in-situ, remote sensing, and terrestrial instruments.
•Monitoring ecosystems to assess risk and impact derived from expected and unexpected events.
•Early warning and decision support systems to optimize heritage management.
•Material characterization and advanced prediction capabilities for heritage deterioration.
•Participatory methods, immersive technologies and crowdsourcing applications to enhance the management of heritage and provide risk information (e.g., serious gaming, digital twins, mixed, virtual, and augmented reality).
•Post-disruption strategies to restore normal conditions to heritage sites, long-term strategic approaches for adaptation and policy tools for resilience and sustainability.
•Methods and tools to model, analyse, and improve the governance structures and management processes (e.g. network analysis or pathway approaches)
•Knowledge co-production and living lab approaches for risk and resilience assessments.

The session is co-organised by three Horizon Europe projects (THETIDA, TRIQUERTA, RescueME) funded under topic HORIZON-CL2-2022-HERITAGE-01-08.

Land–atmosphere interactions often play a decisive role in shaping climate extremes. As climate change continues to exacerbate the occurrence of extreme events, a key challenge is to unravel how land states regulate the occurrence of droughts, heatwaves, intense precipitation and other extreme events. This session focuses on how natural and managed land surface conditions (e.g., soil moisture, soil temperature, vegetation state, surface albedo, snow or frozen soil) interact with other components of the climate system – via water, heat and carbon exchanges – and how these interactions affect the state and evolution of the atmospheric boundary layer. Moreover, emphasis is placed on the role of these interactions in alleviating or aggravating the occurrence and impacts of extreme events. We welcome studies using field measurements, remote sensing observations, theory and modelling to analyse this interplay under past, present and/or future climates and at scales ranging from local to global but with emphasis on larger scales.

This session covers climate predictions from seasonal to multi-decadal timescales and their applications. Continuing to improve such predictions is of major importance to society. The session embraces advances in our understanding of the origins of seasonal to decadal predictability and of the limitations of such predictions, as well as advances in improving the forecast skill and reliability and making the most of this information by developing and evaluating new applications and climate services. The session welcomes contributions from dynamical as well as statistical predictions (including machine learning methods) and their combination. This includes predictions of climate phenomena, including extremes and natural hazards, from global to regional scales, and from seasonal to multi-decadal timescales ("seamless predictions"). The session also covers physical processes relevant to long-term predictability sources (e.g. ocean, cryosphere, or land) and predictions of large-scale atmospheric circulation anomalies associated to teleconnections as well as observational and emergent constraints on climate variability and predictability. Also relevant is the time-dependence of the predictive skill and windows of opportunity. Analysis of predictions in a multi-model framework and innovative ensemble-forecast initialization and generation strategies are another focus of the session. The session pays particular attention to innovative methods of quality assessment and verification of climate predictions, including extreme-weather frequencies, post-processing of climate hindcasts and forecasts, and quantification and interpretation of model uncertainty. We particularly invite contributions presenting the use of seasonal-to-decadal predictions for assessing risks from natural hazards, adaptation and further applications.

In this short course, we will introduce students and early-career researchers to the principles of Open Science, data, and software, as well as the benefits open practices can have for their own research careers, for science, and for society. Participants will have the opportunity to explore the practical impact of Open Science for their work. Participants will develop their digital presence, including using an ORCID to build a permanent profile of their work, and will make a plan to share their data, software, and publications as openly as possible. We will go over the open science outcomes and tools that advance research and collaboration and practice hands-on skills to advance participants’ careers through open science practices.
Participants in this short course will be able to define open science, discuss the benefits and challenges of open science, and identify practices that enable open science. Participants will develop their digital presence, including using an ORCID to build a permanent profile of their work, and will learn strategies for sharing research outputs, data, and software as openly as possible. This course is designed for students or other researchers new to open science; no previous experience with publishing research is required.