Artificial intelligence (in particular, machine learning) can be used to predict and respond to natural disasters. The ITU/WMO/UNEP Focus Group AI for Natural Disaster Management (FG-AI4NDM) is building a community of experts and stakeholders to identify best practices in the use of AI for data processing, improved modeling across spatiotemporal scales, and providing effective communication. This multidisciplinary FG-AI4NDM-session invites contributions addressing challenges and opportunities related to the use of AI for the detection, forecasting, and communication of natural hazards and disasters. In particular, it welcomes presentations highlighting innovative approaches to data collection (e.g., via sensor networks), data handling (e.g., via automating annotation), data storage and transmission (e.g., via edge- and cloud computing), novel modeling or explainability methods (e.g., integrating quantum computing methods), and outcomes of operational implementation.

Recent advances in the field of Artificial Intelligence, Machine Learning and Data Assimilation have been massively applied to model, anticipate, and predict the natural catastrophes, such as earthquakes, floods, landslides, volcanic eruptions, tsunamis, wildfires, glacier instabilities, in addition to multi-hazard and cascading effects due to climate change. However, the adopted algorithms require a solid inductive bias, provided by the physics of the phenomenon at stake (or at least the understanding of it). Furthermore, due to simplified assumptions, analytical models might encounter limits while modeling these natural catastrophes. Therefore, several hybrid strategies, utilizing the growing computational resources, are currently being developed, to achieve more flexibility and full synergy between numerical physics-based simulations, machine learning and data-driven approaches.
The hybrid modeling of natural hazards benefits from the interpretability of numerical simulations and from the extrapolation and generalization capabilities of advanced Machine Learning methods. This synergy leads to multi-fidelity predictive tools that leverage all the available knowledge on the phenomenon at stake. Moreover, to tackle lack of data and representation, observational databases can be integrated with the synthetic results for re-analysis and for training machine learning algorithms on never-before-seen disaster scenarios. This multidisciplinary session invites contributions addressing hybrid solutions to predict and to mitigate natural catastrophes. It also welcomes presentations on hybrid tools for vulnerability assessment.

Both society and industry are becoming increasingly aware of the physical risks and potential knock-on impacts posed by climate change. This awareness is leading to an increased demand for specific and actionable information about such risks across a wide range of sectors and domains. Awareness of and demand for data on climate-related impacts across multiple different hazards and across large geographical areas is also rising - in many nations this is driven by new and upcoming legislation requiring businesses or governments to understand and be prepared for any and all climate risk. Although researchers in climate and geosciences are best-informed to provide expertise, traditional research outputs such as publications and corresponding data are not necessarily useable by non-experts within these domains. In this session, we explore how focusing on the needs of non-expert users and decision makers changes the way in which research is carried out, disseminated, and scaled.

We welcome abstracts across all natural hazard types and climate impacts on a broad range of themes, including: how to work effectively with stakeholders and other users; how user-engagement and data-delivery requirements change the way
science goals are set and met; and how to scale climate risk research to provide information beyond localised case-studies.

High-impact climate and weather events typically result from the interaction of multiple hazards as well as vulnerability and exposure across various spatial and temporal scales. Such compound events often cause more severe socio-economic impacts than single-hazard events, rendering traditional univariate extreme event analyses and risk assessment techniques insufficient. It is therefore crucial to develop new methodologies that account for the possible interaction of multiple physical drivers when analysing high-impact events. Such an endeavour requires (i) a deeper understanding of the interplay of mechanisms causing compound events and (ii) an evaluation of the performance of climate/weather, statistical and impact models in representing compound events.

We invite papers studying all aspects of compound events, which might relate to (but are not limited to) the following topics:

Synthesis and Analysis: What are common features for different classes of compound events? Which variables need to be assessed jointly in order to address related impacts? How much is currently known about the dependence between these variables?
Stakeholders and science-user interface: Which events are most relevant for stakeholders? What are novel approaches to ensure continuous stakeholder engagement?
Impacts: What are the currently available sources of impact data? How can they be used to link observed impacts to climate and weather events?
Statistical approaches, model development and evaluation: What are possible novel statistical models that could be applied in the assessment of compound events?
Realistic model simulations of events: What are the physical mechanisms behind different types of compound events? What type of interactions result in the joint impact of the hazards that are involved in the event? How do these interactions influence risk assessment analyses?

Heat extremes are already one of the deadliest meteorological events and they are projected to increase in intensity and frequency due to rising CO2 emissions. Also vulnerability and exposure of the events are likely to change, yet have to be assessed at a very local scale. The resulting risks of extreme heat events to society may increase dramatically with large regional differences, and society will need to adapt locally if the worst impacts are to be avoided. This session therefore welcomes a broad range of new research addressing the challenge of extreme heat and its impacts. Suitable contributions may: (i) assess 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 or economic productivity); (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 Heat-Health Early Warning Systems for disaster risk reduction and (v) introduce transdisciplinary research frameworks for the assessment of societal relevant heat extremes and its impacts particularly in the Global South.

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 assessment of their risk (economic losses, infrastructural damages, human fatalities, pollution), and their future changes, 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.

Flood is the foremost natural hazard around the world that affects human life and property (directly and indirectly). In the current era, many hydrologic and hydraulic modelling techniques are available for flood risk assessment and management, as well as for flood risk prevention and preparedness. Such techniques provide a platform for the scientific community to explore the causes of floods and to build up efficient methods for flood mitigation.
This session invites in-depth and applied research work carried out through flood modelling including hydrological modelling, flood hydrodynamic modelling, flood inundation mapping, flood hazard mapping, risk assessment, flood policy, and flood mitigation strategy. It also welcomes studies dealing with various uncertainties associated with different stages of modelling and exploring modern techniques for model calibration and validation. In addition, real-time flood inundation mapping is an important aspect for evacuating people from low-lying areas and reducing death tolls. Real-time data information through UAV-based flood inundation mapping and analysis of associated uncertainty in real-time aerial surveying are also welcome.

NB: please, see also the special issue recently released in NHESS linked with this session ( https://nhess.copernicus.org/articles/special_issue1218.html)

Floods are considered as one of the most devastating natural hazards globally and their impact is expected to increase as a result of climate change. Particularly, flooding in urban areas will result in greater impacts due to increased population residing in cities which is expected to be about 70% by 2050. There have been various enhancements in urban flood risk management in the last decade creating the opportunity to reduce risk to life and properties in cities. This special session is focused on these - advances in urban flood risk management, including but not limited to:
- improved representation of risk and its management (e.g. dynamic consideration of hazard and exposure);
- evacuation modelling and management;
- impact modelling to critical urban infrastructure, including cascading effects;
- new modelling techniques in flood risk management (such as application of emulators);
- new application and use of new data sources in flood modelling (such as remote sensing and real-time data, crowd-source data);
- application of nature-based solutions for urban stormwater management.

Lightning is the energetic manifestation of electrical breakdown in the atmosphere, occurring as a result of charge separation processes operating on micro and macro-scales, leading to strong electric fields within thunderstorms. Lightning is associated with tropical storms and severe weather, torrential rains and flash floods. It has significant effects on various atmospheric layers and drives the fair-weather electric field. It is a strong indicator of convective processes on regional and global scales, potentially associated with climate change. Thunderstorms and lightning 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
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

Hydrometeorological extremes are prevailing in most parts of the world, and their severity is rapidly increasing. Therefore, modeling practices to understand, predict and mitigate those extreme events are paramount. Among the many intervention measures, nature-based solutions such as restoring wetlands, applying green infrastructure in urban environments, and giving land back to nature (floodplains) are emerging. The application of nature-based solutions is a rapidly developing field of research in which many challenges and open questions are still central.
Hence, we would like to invite scholars (Professors, post-doctoral researchers, independent researchers, Ph.D. students, M.Sc. students, stakeholders, water companies, water managers, etc.) to take part in this nature-based solutions session during the EGU conference. We invite you all to submit your abstracts with the following main themes but in a broader context:
• Nature-based solutions for drought mitigation
• Nature-based solutions for flood mitigation
• Nature-based solutions integration in geohydrological modelling
• Frameworks to understand/evaluate effectiveness of nature-based solution applications
• Remote sensing to identify possible nature-based solution areas
• Nature-based solutions as climate change adaptation strategies
• Pilot projects and their implementation stage
• Effect of nature-based solutions on water quality and ecosystem services in general
• Ecosystem service quantification after the application of nature-based solutions
• Socio-economic value and community involvement for nature-based solution successfulness, etc.

Urban hydrological processes are characterized by high spatial variability and short response times resulting from a high degree of imperviousness. Therefore, urban catchments are especially sensitive to space-time variability of precipitation at small scales. High-resolution precipitation measurements in cities are crucial to properly describe and analyses urban hydrological responses. At the same time, urban landscapes pose specific challenges to obtaining representative precipitation and hydrological observations.

This session focuses on high-resolution precipitation and hydrological measurements in cities and on approaches to improve modeling of urban hydrological response, including:
- Novel techniques for high-resolution precipitation measurement in cities and for multi-sensor data merging to improve the representation of urban precipitation fields.
- Novel approaches to hydrological field measurements in cities, including data obtained from citizen observatories.
- Precipitation modeling for urban applications, including convective permitting models and stochastic rainfall generators.
- Novel approaches to modeling urban catchment properties and hydrological response, from physics-based, conceptual and data-driven models to stochastic and statistical conceptualization.
- Applications of measured precipitation fields to urban hydrological models to improve hydrological prediction at different time horizons to ultimately enable improved management of urban drainage systems (including catchment strategy development, flood forecasting and management, real-time control, and proactive protection strategies aimed at preventing flooding and pollution).
- Strategies to deal with upcoming challenges, including climate change and rapid urbanization.

Urban areas are at risk from multiple hazards, including urban flooding, droughts and water shortages, sea level rise, disease spread and issues with food security. Consequently, many urban areas are adapting their approach to hazard management and are applying Green Infrastructure (GI) solutions as part of wider integrated schemes.

This session aims to provide researchers with a platform to present and discuss the application, knowledge gaps and future research directions of urban GI and how sustainable green solutions can contribute towards an integrated and sustainable urban hazard management approach. We welcome original research contributions across a series of disciplines with a hydrological, climatic, soil sciences, ecological and geomorphological focus, and encourage the submission of abstracts which demonstrate the use of GI at a wide range of scales and geographical distributions. We invite contributions focusing on (but not restricted to):

· Monitored case studies of GI, Sustainable Drainage Systems (SuDS) or Nature Based Solutions (NBS), which provide an evidence base for integration within a wider hazard management system;

· GIS and hazard mapping analyses to determine benefits, shortcomings and best management practices of urban GI implementation;

· Laboratory-, field- or GIS-based studies which examine the effectiveness or cost/benefit ratio of GI solutions in relation to their wider ecosystem potential;

· Methods for enhancing, optimising and maximising GI system potential;

· Innovative and integrated approaches or systems for issues including (but not limited to): bioretention/stormwater management; pollution control; carbon capture and storage; slope stability; urban heat exchange, and; urban food supply;

· Catchment-based approaches or city-scale studies demonstrating the opportunities of GI at multiple spatial scales;

· Rethinking urban design and sustainable and resilient recovery following crisis onset;

· Engagement and science communication of GI systems to enhance community resilience.

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, and mitigation.
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, the 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
- 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
This session is linked to an active special issue in Natural Hazards and Earth System Sciences (NHESS): https://nhess.copernicus.org/articles/special_issue1203.html

Understanding and further predicting the incidence and severity of hydrometeorological hazards, such as floods, droughts, land slides and storm surges, are a key measure for risk mitigation, building resilience and supporting sustainable socio-economic development. This has become more important when our societies are facing climate change alongside the pressures induced by population growth, urbanisation and land use change. While traditionally physically based modelling approaches remain as a major tool base for studying the prognostics and diagnostics of these hazards, the ever high level of complexity of the underlying process and the interaction between the nature and human interface, and more importantly, the increasingly availability of new observations datasets, have necessitated many applications of tools and methods in the domain of hydroinformatics, such as data-driven modelling, machine learning, data fusion, alongside conventional sptial-temporal statistical analysis tools.

The aim of this session is to provide a platform and an opportunity to demonstrate and discuss innovative and recent advances of hydroinformatics applications and methodologies for analysing and producing diagnostics and prognostics of hydrometeorological hazards. It also aims to provide a forum for researchers from a variety of fields to effectively communicate their research. Submissions related to the following non-exhaustive topics are particularly welcome.
1. Spatial and temporal analysis of the incidence and distribution of hydrometeorological hazards;
2. Machine learning (e.g., CNN, GNN) in analysing and predicting hydrometeorological hazards.
3. Uncertainty quantification of coupled models, such as atmospheric-hydrological/hydrodynamic in the applications of diagnosing and predicting hydrometeorological hazards;
4. Development in quantitative methods for analysing compound hydrometeorological hazards;
5. Data assimilation and fusion of heterogeneous observations in hazards modelling, e.g., satellite-borne sensors and rainfall radars;
6. HPC (GPU) based algorithms and practice dealing with very large size datasets in prognostic modelling of hydrometeorological hazards, e.g., climate projections.
7. Modelling interface with human interactions in decision making, mitigation and impact studies.

Flash floods triggered by heavy precipitation in small- to medium-sized catchments often cause catastrophic damages, which are largely explained by the very short response times and high unit peak discharge. Often, they are also associated with geomorphic processes such as erosion, sediment transport, debris flows and shallow landslides. The anticipation of such events is crucial for efficient crisis management. However, their predictability is still affected by large uncertainties, due to the fast evolution of triggering rainfall events, the lack of appropriate observations, the changes due to a warming climate, the high variability and non-linearity in the physical processes, the high variability of societal exposure, and the complexity of societal vulnerability.
This session aims to illustrate current advances in monitoring, modeling, and short-range forecasting of flash floods and associated geomorphic processes, including their societal impacts.
Contributions related to recent and significant floods are particularly encouraged.
This session aims to specifically cover the following scientific themes:
- Monitoring and nowcasting of heavy precipitation events based on radar and remote-sensing systems (satellite, lightning, ..), to complement rain gauge networks
- Short-range (0-6h) heavy precipitation forecasting based on NWP models and/or ML-based approaches, with a focus on seamless forecasting strategies, and ensemble or probabilistic strategies for the representation of uncertainties.
- Understanding and modeling of flash floods, rainfall-induced hydro-geomorphic processes and their cascading effects, at appropriate space-time scales.
- Development of integrated hydro-meteorological forecasting chains and new modeling approaches for predicting flash floods and/or rainfall-induced geomorphic hazards in gauged and ungauged basins.
- New direct and indirect (proxy data) observation techniques and strategies for the observation or monitoring of hydrological reactions and geomorphic processes, and the validation of forecasting approaches.
- Development of impact-based modeling and forecasting approaches, including inundation mapping and/or specific impacts modeling approaches for the representation of societal vulnerability.

Hydro-meteorological extremes such as floods, droughts, storms, or heatwaves often affect large regions therefore causing large damages and costs. 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. While spatial extremes receive a lot of attention by the media, little is known about their driving factors and it remains challenging to assess their risk by modelling approaches. Key challenges in advancing our understanding of spatial extremes and in developing new modeling approaches include the definition of multivariate events, the quantification of spatial dependence, the dealing with large dimensions, the introduction of flexible dependence structures, the estimation occurrence probabilities, the identification of potential drivers for spatial dependence, and linking different spatial scales. This session invites contributions which help to better understand processes governing spatial extremes and/or propose new ways of describing and modeling spatially compounding events at different spatial scales.

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. In the worst case, this can lead to long-term environmental and socio-economic impacts. Drought Monitoring and Forecasting are recognized 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. 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.

The Sendai Framework for Disaster Risk Reduction (SFDRR) and its seventh global target recognizes that increased efforts are required to develop risk-informed and impact-based multi-hazard early warning systems. Despite significant 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 understanding of the reliability of forecast tools and implementation barriers in combination with the development of new risk-informed processes. It also requires a commitment to create and share risk and impact data and to co-produce impact-based forecasting models and services. To deal with the problem of coming into action in response to imperfect forecasts, novel science-based concepts have recently emerged. As an 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 as a result of increasing international effort by several organizations such as the WMO, World Bank, IFRC and UNDRR to reduce disaster losses and ensuring reaching the objectives of SFDRR. This session aims to showcase lessons learnt and best practices on impact-based multi-hazards early warning system from the perspective of both the knowledge producers and users. It presents novel methods to translate forecast of various climate-related and geohazards into an impact-based forecast. The session addresses the role of humanitarian agencies, scientists and communities at risk in creating standard operating procedures for economically feasible actions and reflects on the influence of forecast uncertainty across different time scales in decision-making. Moreover, it provides an overview of state-of-the-art methods, such as using Artificial Intelligence, big data and space applications, and presents innovative ways of addressing the difficulties in implementing forecast-based actions. We invite submissions on the development and use of operational impact-based forecast systems for early action; developing cost-efficient portfolios of early actions for climate/geo-related impact preparedness such as cash-transfer for droughts, weather-based insurance for floods; assessments on the types and costs of possible forecast-based disaster risk management actions; practical applications of impact forecasts.

This session brings together scientists, forecasters, practitioners and stakeholders interested in exploring the use of ensemble hydro-meteorological forecast and data assimilation techniques in hydrological applications: e.g., flood control and warning, reservoir operation for hydropower and water supply, transportation, and agricultural management. It will address the understanding of sources of predictability and quantification and reduction of predictive uncertainty of hydrological extremes in deterministic and ensemble hydrological forecasting. Uncertainty estimation in operational forecasting systems is becoming a more common practice. However, a significant research challenge and central interest of this session is to understand the sources of predictability and development of approaches, methods and techniques to enhance predictability (e.g. accuracy, reliability etc.) and quantify and reduce predictive uncertainty in general. Ensemble data assimilation, NWP preprocessing, multi-model approaches or hydrological postprocessing can provide important ways of improving the quality (e.g. accuracy, reliability) and increasing the value (e.g. impact, usability) of deterministic and ensemble hydrological forecasts. The models involved with the methods for predictive uncertainty, data assimilation, post-processing and decision-making may include machine learning models, ANNs, catchment models, runoff routing models, groundwater models, coupled meteorological-hydrological models as well as combinations (multimodel) of these. Demonstrations of the sources of predictability and subsequent quantification and reduction in predictive uncertainty at different scales through improved representation of model process (physics, parameterization, numerical solution, data support and calibration) and error, forcing and initial state are of special interest to the session.

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.

Biogeomorphology addresses the two-way interaction between abiotic and biotic elements that shape landscapes at various spatio-temporal scales.

One key biogeomorphic interaction happens in fluvial ecosystems between wood, flow and sediment. Many river systems show disruptions in their natural wood regime and consequently deficits in habitat structures, biodiversity, and ecosystem functions. Large wood (LW) jams create upstream regions of slower, deepened water that may enable deposition and storage of nutrients. In addition, downstream regions of faster flow are created as flow diverges around LW jams and may increase transport of bedload sediment and aid flushing of fine particles from clogged gravels. During floods, the amount of transported LW may increase, jams can form at river infrastructure thus posing an additional flood risk. LW mobility is also important in the carbon cycle. Having highlighted the multiple active functions that LW may have on energy and matter fluxes, a cross-disciplinary effort is required to improve our understanding of the complex interactions of wood with flow and sediment in fluvial ecosystems.

Across all landscapes and ecosystems, investigation of biogeomorphic feedbacks remains poorly understood and quantitatively constrained. Improved understanding of abiotic-biotic interaction across scales improves the scientific basis for environmental management aiding climate change mitigation and adaptation, response to natural hazards, and design of nature-based solutions to increase system resilience.

This session combines the investigation of wood-flow-sediment interactions in fluvial ecosystems with a general biogeomorphic perspective on biotic-abiotic feedbacks across all landscapes and ecosystems. It aims for a broad representation of the scientific communities focusing on geomorphic, hydraulic, ecological, and human aspects associated with wood in rivers and biogeomorphology. We invite presenters to share recent scientific advances in our understanding and management of wood in fluvial ecosystems using field, laboratory, or numerical approaches. Likewise, we provide a platform for all aspects of biogeomorphology, including fundamental science and applied studies. This year we specifically invite contributions focusing on both the short (process-scale) and longer-terms (> centennial) relevance of biogeomorphology to the carbon cycle.

Worldwide, many areas are experiencing broad climatic and  environmental changes that lead to significant geomorphic impacts. These changes are manifested, for example, by changes in rainfall properties and in the frequency of extreme events. Especially naturally fragile arid to sub-humid areas are particularly sensitive to such changes. This makes them ideal areas to study such processes and their interactions for the recent and former periods, the latter being documented in different kinds of sediment archives. Recent technological advancements, and particularly a better understanding of the links between climate environmental changes and the surface dynamics, have made it possible to better recognize the impact of climatic and environmental triggers on geomorphic landscape processes during the last years.

This session will focus on contributions that discuss the  transformation of current and former climatic and environmental changes into geomorphic surface processes, from the scale of mountain ranges to watersheds and individual streams, as well as in aeolian, gravitational, and biological systems. We especially welcome studies that focus on geomorphic responses to changes in climate, extreme events and on their imprints on the landscape through erosion and sediment movement. We welcome studies from individual regions, different sediment archives and review studies. Modeling approaches that explicitly examine the effects of environmental changes on the landscape dynamics are highly encouraged, as well as studies dealing with novel methods to acquire chronological frameworks, process rates, and the impact of such processes on current and previous societies.

Sediment transport is a fundamental component of all geomorphic systems (including fluvial, aeolian, coastal, hillslopes and glacial), yet it is something that we still find surprisingly difficult both to monitor and to model. Robust data on where and how sediment transport occurs are needed to address outstanding research questions, including the spatial and temporal controls on critical shear stress, the influence of varying grain size distributions, and the impact of large magnitude events. Recent developments have provided a) new opportunities for measuring sediment transport in the field; and b) new ways to represent sediment transport in both physical laboratory models and in numerical models. These developments include (but are not limited to) the application of techniques such as seismic and acoustic monitoring, 3D imaging (e.g. CT and MRI scanning), deployment of sensors such as accelerometers, replication of field topography using 3D printing, use of luminescence as a sediment tracer, remote sensing of turbidity, discrete numerical modelling, and new statistical approaches.

In this session we welcome contributions from all areas of geomorphology that develop new methods for monitoring and modelling all types of sediment transport, or that showcase an application of such methods. Contributions from ECRs and underrepresented groups are particularly encouraged.

This session investigates mid-latitude to subtropical cyclones and storms on both hemispheres. We invite studies considering cyclones in different stages of their life cycles from the initial development, to large- and synoptic-scale conditions influencing their growth to a severe storm, up to their dissipation and related socioeconomic impacts. We also welcome studies investigating these weather systems and their climate controls in subtropical regions of both hemispheres.

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?

Volcanic gas emissions can constitute a permanent hazard in volcanic areas not only during eruptions, but also in post-eruptive and quiescent periods. Carbon dioxide is one of the main hazardous volcanic gases due to its characteristics (odourless, invisible, density higher than air at STP) and asphyxiate effect. However, we highlight also the presence of other gases, such as hydrogen sulphide and radon. In fact, several incidents with gases have been reported both indoor and outdoor in various countries during non-eruptive periods: USA, Argentina, Italy, Portugal, Greece, Congo, and Indonesia, just to give some examples.
High CO2 concentrations have been recently detected in some villages in La Palma (Canary Islands) and Vulcano (Italy) posing a threat to population and restricting the access to dwellings. We aim at contributions that show strategies to monitor, prevent and manage these silent hazards, which are quite challenging. Development of new sensors and study cases are welcome.

The panel's objective is to examine the multiple dimensions associated with risk by adopting a perspective examining the reference regulatory framework and the organizational and procedural repercussions of a vision in which risk (its assessment) is assumed to be a necessary component of administrative decision-making.
The consideration of risk must find an appropriate place within the processes of defining the planning lines of the territories, following a line of continuity that from it passes through the decision to find the balance between the possibility of an event occurring and the costs related to the adoption of prevention and precautionary measures often relegate the consideration of risk to a secondary level.
The aim is to verify, with specific reference to volcanic risk, the different dimensions mentioned above, going in search of the degree of risk assessment at the regulatory, programmatic, and planning stage and the regulatory and procedural instruments aimed at guaranteeing the effectiveness of the dialogue between law and technique, a prerequisite for the correct application, and therefore the effectiveness, of the principles of precaution and prevention.
This relation will be examined in depth, highlighting, for example, the role that permanent monitoring and observation systems, possibly also in collaboration with the operational groups envisaged for seismic emergencies, can play in defining that framework of knowledge and procedures for the dissemination and transmission thereof, which is indispensable for proper territorial planning. A focus will be reserved for the data collected from the observations of the monitoring networks to verify the degree of penetration they have within public decision-making processes, including urban planning decisions and specific planning decisions for managing emergencies such as plans and red evacuation zones.
The analysis of the data, which includes the verification of the costs that failure to consider volcanological risk entails, is functional to the formulation of proposals for the identification of guidelines that define tools and methods through which to ensure stability and convergence between administration, prevention and technical knowledge from the volcanic risk perspective, drawing on recent experience to renew the vision of a truly resilient administration and response.

Monitoring of volcanic hazards by combining field observations, satellite data and numerical models, presents extraordinarily challenging problems, from detecting and quantifying hazardous phenomena during eruptive events to forecasting their impact to assess risks to people and property. This session welcomes contributions addressing unresolved challenging questions related to complex geophysical flow modeling, including physical-mathematical formulations, numerical methods and satellite data analysis as well as contributions that cross-fertilize efforts in traditional volcano monitoring with new technological innovations from statistical methods and artificial intelligence. Goals for the session include: (i) expanding knowledge of complex volcanic processes and their space-time dynamics; (ii) monitoring and modeling volcanic phenomena; (iii) evaluating model robustness through validation against real case studies, analytical solutions and laboratory experiments; (iv) quantifying the uncertainty propagation through both forward (sensitivity analyses) and inverse (optimization/calibration) modeling in all areas of volcanic hazard; (v) investigating the potential of machine learning techniques to process remote sensing data for developing a better understanding of volcanic hazards.

Volcanoes release gas effluents and aerosol particles into the atmosphere during eruptive episodes and by quiescent emissions. Volcanic degassing exerts a dominant role in forcing the timing and nature of volcanic unrest and eruptions. Understanding the exsolution processes of gas species dissolved in magma, and measuring their emissions is crucial to characterise eruptive mechanism and evaluate the sub-sequent impacts on the atmospheric composition, the environment and the biosphere. Emissions range from silent exhalation through soils to astonishing eruptive clouds that release gas and particles into the atmosphere, potentially exerting a strong impact on the Earth’s radiation budget and climate over a range of temporal and spatial scales. Strong explosive volcanic eruptions are a major natural driver of climate variability at interannual to multidecadal time scales. Quiescent passive degassing and smaller-magnitude eruptions on the other hand can impact on regional climate system. Through direct exposure and indirect effects, volcanic emissions may influence local-to-regional air quality and seriously affect the biosphere and environment. Volcanic gases can also present significant hazards to populations downwind of an eruption, in terms of human, animal and plant health, which subsequently can affect livelihoods and cause socio-economic challenges. Gas emissions are measured and monitored via a range of in-situ and remote sensing techniques, to gain insights into both the subterranean-surface processes and quantify the extent of their impacts. In addition, modelling of the subsurface and atmospheric/climatic processes, as well as laboratory experiments, are fundamental to the interpretation of field-based and satellite observations.

This session focuses on the state-of-the-art and interdisciplinary science concerning all aspects of volcanic degassing and impacts of relevance to the Volcanology, Environmental, Atmospheric and Climate sciences (including regional climate), and Hazard assessment. We invite contributions on all aspects of volcanic plumes science, their observation, modelling and impacts. We welcome contributions that address issues around the assessment of hazards and impacts from volcanic degassing both in crises and at persistently degassing volcanoes.

Over the past few years, major technological advances significantly increased both the spatial coverage and frequency bandwidth of multi-disciplinary observations at active volcanoes. Networks of instruments, both ground- and satellite-based, now allow for the quantitative measurement of geophysical responses, geological features and geochemical emissions, permitting an unprecedented, multi-parameter vision of the surface manifestations of mass transport beneath volcanoes. Furthermore, new models and processing techniques have led to innovative paradigms for inverting observational data to image the structures and interpret the dynamics of volcanoes. Within this context, this session aims to bring together a multidisciplinary audience to discuss the most recent innovations in volcano imaging and monitoring, and to present observations, methods and models that increase our understanding of volcanic processes.
We welcome contributions (1) related to methodological and instrumental advances in geophysical, geological and geochemical imaging of volcanoes, and (2) to explore new knowledge provided by these studies on the internal structure and physical processes of volcanic systems.
We invite contributors from all geophysical, geological and geochemical disciplines: seismology, electromagnetics, geoelectrics, gravimetry, magnetics, muon tomography, volatile measurements and analysis. The session will include in-situ monitoring and high- resolution remote sensing studies that resolve volcanic systems ranging from near-surface hydrothermal activity to deep magma migration.

The session deals with the documentation and modelling of the tectonic, deformation and geodetic features of any type of volcanic area, on Earth and in the Solar System. The focus is on advancing our understanding on any type of deformation of active and non-active volcanoes, on the associated behaviours, and the implications for hazards. We welcome contributions based on results from fieldwork, remote-sensing studies, geodetic and geophysical measurements, analytical, analogue and numerical simulations, and laboratory studies of volcanic rocks.
Studies may be focused at the regional scale, investigating the tectonic setting responsible for and controlling volcanic activity, both along divergent and convergent plate boundaries, as well in intraplate settings. At a more local scale, all types of surface deformation in volcanic areas are of interest, such as elastic inflation and deflation, or anelastic processes, including caldera and flank collapses. Deeper, sub-volcanic deformation studies, concerning the emplacement of intrusions, as sills, dikes and laccoliths, are most welcome.
We also particularly welcome geophysical data aimed at understanding magmatic processes during volcano unrest. These include geodetic studies obtained mainly through GPS and InSAR, as well as at their modelling to imagine sources.

The session includes, but is not restricted to, the following topics:
• volcanism and regional tectonics;
• formation of magma chambers, laccoliths, and other intrusions;
• dyke and sill propagation, emplacement, and arrest;
• earthquakes and eruptions;
• caldera collapse, resurgence, and unrest;
• flank collapse;
• volcano deformation monitoring;
• volcano deformation and hazard mitigation;
• volcano unrest;
• mechanical properties of rocks in volcanic areas.

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 and design of mitigation measures, including early warning systems. In addition, the impacts of climate change on debris-flow activity must be considered and carefully analyzed, as the number of mountain areas prone to these events may increase in future.
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 hazards maps and modeling. 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.
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, modeling, 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 impacting on the socio economic tissue. These complex systems are difficult to describe, investigate, monitor and model. Hence a reliable model of these phenomena requires acquisition and analysis of all the available data. This is the key to support successive steps up to the management of Early Warning systems.
Large instabilities affect all the 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 the difficult characterization and few cases thoroughly studied. Regional and temporal distribution and relationships with controlling and triggering factors are poorly understood resulting in poor predictions of their behavior and evolution under present and future climate. Relationships among geological and hydrological boundary conditions and displacements are associated to mechanical controls, hydraulic response and evolution in space and time. Even for well studied and active phenomena warning thresholds are mostly qualitative, based on semi-empirical approaches and do not consider all available data. Then a multidisciplinary approach and a robust set of monitoring data are needed. Many modeling approaches can be applied to evaluate instability and failure, considering triggerings (e.g. rain, seismicity, eruption, snowmelt), failure propagation, leading to rapid mass movements (rock, debris, ice avalanches, flows). Nevertheless, the applied approaches are still phenomenological in most cases 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 structures (e.g. tunnels, dams, roads). Design of these structures and knowledge of their expected performance represent an important element.
We invite all the researchers 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 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). Furthermore, weather dynamics largely influence land use/cover playing a key role in the slope-atmosphere interaction. All the mentioned variables are subject to changes due to the observed and expected global warming and resulting climate change. Finally, in recent years, the design, implementation and maintenance of Nature Based Solutions as protection measures for landslide events, heavily connected with weather dynamics, gained a well-deserved interest.
The overall impacts of weather variables (and their changes) depend on the region, spatial scale, time frame, and socio-economic context addressed. However, although even the simple identification of the weather patterns regulating the occurrence of landslide activity represents a not trivial issue, also assuming steady conditions, the expected variations induced by unequivocal global warming make the issue highly complex and require further in-depth investigation.
To support hazards’ monitoring, predictions, and projections, last-generation and updated datasets with high spatio-temporal resolution and quality - as those from the Copernicus Services’ Portals - are useful to feed models, big-data analytics, and indicators’ frameworks enabling timely, robust, and efficient decision making.
The Session aims at presenting studies concerning the analysis of the role of climate-related variables and slope-atmosphere interaction on landslide triggering/activity and/or effectiveness of protection measures, across different geographical contexts and scales. Modelling and monitoring investigations to properly evaluate the energy and water fluxes at the interface and improve the current generation of predictive models are encouraged. Furthermore, are greatly welcome investigations focused on innovative approaches through which the variations induced by climate change on landslide triggering, dynamics, and hazard are analysed. Either studies including analyses of historical records and related climate variables, or modelling approaches driven by future climate exploiting downscaled output of climate projections fit the Session’s purposes. Studies assessing variations in severity, frequency, and/or timing of events and consequent risks are valuable.

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

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

Landslides are ubiquitous geomorphological processes that can have disastrous consequences. Landslides can cause more deaths than any other natural hazard in a number of countries. Predicting landslides is a challenging problem that is important for scientific interest and societal impact because it has the potential to safeguard lives, individual assets, and shared resources. The session's main focus is on cutting-edge approaches and strategies for predicting landslides, including the location, timing, magnitude, and destructiveness of single and multiple slope failures. All landslide types—from fast rockfalls to rapid debris flows, from slow slides to very rapid rock avalanches—are taken into account, from the local to the global scale. Contributions looking at theoretical aspects of predicting natural hazards, with a focus on landslide forecasting, are of interest. These include contributions examining conceptual, mathematical, physical, statistical, numerical, and computational problems, as well as applied contributions showing, with examples, whether it is possible or not to predict individual or multiple landslides, or specific landslide characteristics. Abstracts that evaluate the quality of landslide forecasts, compare the efficiency of various forecasting models, use landslide forecasts in operational systems, and investigate the potential for exploitation of new or emerging technologies, are welcome as well. We anticipate that, in case of a successful session, the most relevant contributions will be collected in the 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.
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.

Mountain regions are a complex system of different glacial and non-glacial environments rapidly adapting to a changing climate. In this context, short-term landscape evolution is affected by, e.g. glacier motion and a variety of mass movements driven by different processes, evolving at different rates and potentially ending in catastrophic failures. In some cases, deposits may block rivers and form landslide dams that might fail and cause flood waves travelling far from the initial source areas. Such cascading events can pose risks to lives, human activities and infrastructures. With the current state of knowledge, it is very challenging to forecast the exact timing, location and magnitude of such events, raising important scientific and societal questions in terms of when, where and how big the next catastrophic failure may be.

In this session, we bring together researchers from different communities interested in a better understanding of the physical processes controlling mass movements and their associated hazards. The main goals are to present: (i) new examples of large catastrophic slope failures, in particular those causing river-damming; (ii) hitherto unpublished inventories of landslide dams, including statistical analyses of datasets and detailed analyses of case studies, which could be included in a Springer book currently being compiled, iii) insights from field observations and/or laboratory experiments; (iv) statistical and/or artificial intelligence methods to identify and map mass movements; (v) new monitoring approaches (in-situ and remote sensing) applied at different spatial and temporal scales; and (vi) models (from conceptual frameworks to advanced numerical models) for the analysis and interpretation of the governing physical processes.
The session also aims at triggering discussions on strategies applicable for hazard assessment and mitigation and on effective countermeasures that can be implemented to increase preparedness and risk reduction.

Landslides, debris flows and avalanches are common types of unsteady bulk mass movements. Globally, the risk from these mass movements is expected to increase, due to changes in precipitation patterns, rising average temperatures and continued urbanisation of mountainous regions. Climate change also reduces the power of site-specific empirically-based predictions, requiring updated approaches for effective and robust management of the associated risk.

Given sustained improvements in computational power, the techniques involving artificial intelligence and explicit hydromechanical modelling are becoming more and more widespread. Both techniques have the advantages of reducing our dependence on empirical approaches. This session thus covers two main domains:

1) New approaches and state-of-the-art artificial intelligence techniques on remote sensing data for creating and updating landslide inventories.
2) Advances in hydromechanical numerical models and digital tools for geophysical mass flows.

The ultimate goal of both is integration into the wider context of hazard and/or risk assessment and mitigation.

Contributions to this session may involve:
(a) Regional scale analysis for landslide detection and applications for establishing multi-temporal inventories.
(b) Data processing, fusion, and data manipulation, as well as novel AI model tuning practices.
(c) Evaluating the quality of landslide detection through AI techniques.
(d) Comparing the performance of different AI segmentation models.
(e) Novel constitutive and hydromechanical modelling of flows, both at the field- and laboratory-scales.
(f) Hydromechanical modelling of the interaction of mass movements with structural countermeasures.
(g) Advances in risk analysis through the integration of digital technologies and multidisciplinary viewpoints (potentially including combining AI and hydromechanical modelling techniques).

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.

Snow avalanches range among the most prominent natural hazards which threaten mountain communities worldwide, in particular also in the context of climate change. Snow avalanche formation involves complex interacting processes starting with failure processes at the scale of snow crystals and ending with the release of a large volume of snow at a scale of up to several hundred meters. The practical application of avalanche formation is avalanche forecasting, requiring a thorough understanding of the physical and mechanical properties of snow as well as the influence of meteorological boundary conditions (e.g. precipitation, wind and radiation).

This session aims to improve our understanding of avalanche formation processes and to foster the application to avalanche forecasting. We welcome contributions from novel field, laboratory and numerical studies as well as specific case studies. Topics include, but are not limited to, snow micro-mechanics, snow cover simulations, meteorological driving factors including drifting and blowing snow, spatial variability, avalanche release mechanics, remote avalanche detection, avalanche forecasting and the impact of climate change. While the main focus of this session is on avalanche formation, detection and forecasting, it is closely linked to the session ‘Snow avalanche dynamics: from driving processes to mitigation strategies’, which addresses avalanche dynamics, risk assessment and mitigation strategies.

Landslide susceptibility, the spatial likelihood of occurrence of landslides, is the subject of countless scientific publications. They use heterogeneous data, and apply many different methods, mostly falling under the definition of statistical and/or machine learning with the common feature of considering many input variables and a single target output, denoting landslide presence. It is a classification problem: given N input variables assuming different values, each combination associated with a 0/1 possible outcome, a model should be trained on some dataset, tested, and eventually it applied to unseen data.
Relevant input data (“predictors”, “factors”, “independent variables”) is usually a mixed set of topographic, morphometric, environmental, climatic, and a landslide inventory. Choice of a specific method depends on software availability, personal background, and existence of relevant literature in the area of interest. New methods are proposed regularly and very often is difficult to judge their relative performance based with respect to existing methods.
A meaningful comparison of many different methods would require a common dataset – a benchmark - to train and test each of them in a systematic way. This is a standard procedure in machine learning science and practice, for virtually all the fields: benchmark datasets exist for medical sciences, image recognition, linguistics, and in general any classification algorithm. The “Iris dataset” is a famous example of a benchmark in classification of numerical data into three different variants of the flower Iris. This session aims at establishing one or more benchmark datasets that could be helpful in landslide susceptibility research, to compare the plethora of existing methods and new methods to come.
We propose an interactive session: the organizers will single out benchmark datasets, share them with participants at due time, prior to the conference venue. We expect abstract proposals to describe the method(s) they intend to apply, the type of data it requires, and an independent case study for which the method proved successful. Participants should be ready to disclose minimal computer code (in any major programming language) to run their method, to apply the code to the benchmark dataset prior to the conference, and present their results. We aim at collecting all of the results in a journal publication, including datasets, benchmark and computer codes in collaboration with the participants.
Download dataset at: http://dx.doi.org/10.31223/X52S9C

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.

Earthquake disaster mitigation involves different elements, concerning identification, assessment and reduction of earthquake risk. Each element has various aspects: a) analysis of hazards (e.g. physical description of ground shaking) and its impact on built and natural environment, b) vulnerability and exposure to hazards and capacity building and resilience, c) long-term preparedness and post-event response. Due to the broad range of earthquake disaster mitigation various seismic hazard/risk models are developed at different time scales and by different methods, heterogeneous observations are used and multi-disciplinary information is acquired.
We welcome contributions about different types of seismic hazards research and assessments, both methodological and practical, and their applications to disaster risk reduction in terms of physical and social vulnerability, capacity and resilience.
This session aims to tackle theoretical and implementation issues, as well as aspects of communication and science policy, which are all essential elements towards effective disasters mitigation, and involve:
⇒ the development of physical/statistical models for the different earthquake risk components (hazard, exposure, vulnerability), including novel methods for data collection and processing (e.g. statistical machine learning analysis)
⇒ earthquake hazard and risk estimation at different time and space scales, verifying their performance against observations (including unconventional seismological observations);
⇒ time-dependent seismic hazard and risk assessments (including contribution of aftershocks), and post-event information (early warning, alerts) for emergency management;
⇒ earthquake-induced cascading effects (e.g. landslides, tsunamis, etc.) and multi-risk assessment (e.g. earthquake plus flooding).
The interdisciplinary session promotes knowledge exchange, sharing best practices and experience gained by using different methods, providing this way opportunities to advance our understanding of disaster risk in "all its dimensions of vulnerability, capacity, exposure of persons and assets, hazard characteristics and the environment", while simultaneously highlighting existing gaps and 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.

The estimation of ground motion for future earthquakes is one of the main tasks of seismology. Among the processes affecting ground motion, local site conditions play a significant role. Earthquake site effects include several phenomena: ground shaking amplification due to local stratigraphic and topographic conditions, liquefaction phenomena, ground failures and cavity collapse, earthquake-induced landslides. The estimate of these effects is a necessary step for seismic hazard and seismic risk mitigation as well as to build effective strategies for urban planning and emergency management.
The goal of this session is to collect contributions on case studies and general perspectives concerning new advances on earthquake site effect estimation, both using numerical simulations and empirical approaches.
We also welcome contributions with a special focus on the characterization of building’s response and their interaction with soil. We encourage multidisciplinary contributions at the boundary between seismology, geology, geotechnics and engineering.
Topics of interest are the following:
- Site characterization and seismic microzonation;
- Empirical/experimental evaluation of topographic/stratigraphic amplification effects;
- Quantitative assessment of seismic site response (1D-2D-3D);
- Earthquake-induced effects on the ground (including historical case studies or inventories): liquefaction, cavity collapse, landslides;
- Buildings’ response characterization;
- Analysis of historical and cultural heritage sites;
- Datasets and databases of building/soil data.
The session also aims to collect results based on different geophysical techniques (e.g., earthquake data, surface wave prospecting, ERT, GPR, seismic refraction tomography, etc.) and their integration.

Deformation zones and faulting processes develop in several geodynamic environments, involving deep and/or shallow crust. In active tectonics contexts, either if they are in subarea or subaqueous environments, unravelling the faults’ long-term evolution has a crucial impact for seismic and tsunami hazard assessment. In case of subaqueous environments, over the last years, new geological and geophysical instrumentation has made possible the acquisition data with unprecedented detail and resolution, providing for a better definition of offshore fault systems and seismic parameter calculations. Moreover, multiple parameters are expected to control fault evolution, such as the tectonic and geodynamic setting, erosion, the amount of sediments deposited on the hanging wall, fluids circulation, or lithology. While the effects of some of these parameters are well established, many others are still poorly constrained by actual data.
This session aims to better define the properties of faults and deformation zones, and to understand how their characteristics change over time. At the same time, this session also aims to compile studies that focus on the use of geological and geophysical data to identify subaqueous active structures, attempting to quantify the seafloor deformation, evaluating their seismogenic and tsunamigenic hazards. We invite contributions dealing with faulting and deformation processes (normal, reverse and strike-slip) worldwide, in different geodynamic contexts, from the scale of the outcrops to mountain ranges, from offshore to lakes, and from the long-term to single seismic events. Since a multidisciplinary approach is the key to deep understanding, studies providing new perspectives and ideas in subaqueous active tectonics or involving diverse methods such as field-data analysis, paleoseismic trenching, stable isotopes, low temperature thermochronology, syn-kinematic U/Pb dating, cosmogenic exposure dating, petrographic analysis, or analogue/numerical modelling are welcome.

The session focuses on research aimed at defining the geometry, kinematics, and associated stress- and deformation fields of active faults, as well as building up tectonic and seismotectonic models, in all tectonic regimes, including volcanic areas. Assessing the geometry and kinematics of faults, key to seismic hazard assessment, can be often challenging due to the possible paucity of quantitative data, both at the near-surface and at seismogenic depths.
Tackling this challenging issue is nowadays possible by combining data from different approaches and disciplines, with the aim of obtaining a more detailed characterization/imaging of single active faults, as well as reliable seismotectonic models. In addition, technological advances in data collection and analysis provide a significant contribution. As an example, photogrammetry and LIDAR-derived models enable collecting a great deal of geological data even in inaccessible areas; these data can then be integrated with field (structural), seismological and geophysical data with the purpose of a better understanding of active faults geometry. Also, the improvement in data processing allows to enhance seismic catalogues in areas with low-level seismicity, as well as collect new and more detailed data from geophysical, geodetic, or remote-sensing analysis.
Contributions dealing with the following topics are welcome: i) active faults, including volcanic areas; ii) classical to innovative multiscale and multidisciplinary geological, seismological and geophysical approaches; iii) new or revised seismological, geophysical, field-and remotely-collected datasets; iv) faults imaging, tectonic-setting definition and seismotectonic models; v) numerical and analogue modelling.

Slow earthquakes are widely observed in subduction zones, where they episodically release the tectonic strain built-up in the brittle-ductile transition zone. Given their proximity to the seismogenic megathrust, a comprehensive understanding of slow earthquakes may shed light on the stress condition of the megathrust fault. With improved quantities of data and advanced technologies, the nature of slow earthquakes has been intensively investigated in a variety of tectonic environments over the past decades. This session aims to offer a broad space for discussion of the recent advances in slow earthquakes.
We seek studies ranging from lab to volcanic and tectonic scales and from diverse geological and geophysical (including but not limited to seismic and geodetic) observations to imaging and modeling. We welcome abstracts focused on earthquake detection, scaling, source, rupture process, and fluid or/and heterogeneity effects. Within the larger context of this session, we also seek abstracts illuminating the connection between slow and fast earthquakes.

This session will focus on three approaches for investigating the physics of earthquakes: imaging, numerical simulations, and machine learning. We solicit abstracts on works to image rupture kinematics, simulate earthquake dynamics using numerical methods, and those using Machine Learning (ML) to improve understanding of the physics of earthquakes. We invite in particular works that aim to develop a deeper understanding of earthquake source physics by linking novel laboratory experiments to earthquake dynamics, and studies on earthquake scaling properties. We also encourage works that illuminate the physics behind and transferability to Earth of studies showing that acoustic emissions can be used to predict characteristics of laboratory earthquakes and identify precursors to labquakes. Other works show progress in imaging earthquake sources using seismic data and surface deformation measurements (e.g. GPS and InSAR) to estimate rupture properties on faults and fault systems.

We want to highlight strengths and limitations of each data set and method in the context of the source-inversion problem, accounting for uncertainties and robustness of the source models and imaging or simulation methods. Contributions are welcome that make use of modern computing paradigms and infrastructure to tackle large-scale forward simulation of earthquake process, but also inverse modeling to retrieve the rupture process with proper uncertainty quantification. We also welcome ML-based works on a broad range of issues in seismology and encourage seismic studies using data from natural faults, lab results and numerical approaches to understand earthquake physics.

Damaging earthquakes create massive devastation in two ways: the loss of property and the loss of human life, out of which loss of human life can be easily reduced by interventions from earthquake early warning systems. Therefore, along with hazard, risk, and mitigation planning, earthquake prevention, prediction, early warning, and probability monitoring are crucial. Early warning systems have been deployed and are in operation in many nations including China, Taiwan, Japan, the USA, and Chile etc. Most of the systems work on classical regression equations and due to their inability to produce reliable data, old methodologies are no longer employed in the contemporary hazard assessment, earthquake early waring and monitoring of earthquakes. AI/ML techniques have made in roads for better understanding the nonlinear behavior and are capable of relatively more realistic predictions of the attributes, more so when data paucity has gone. The most recent method for earthquake prediction, probability evaluation and earthquake early warning is machine learning. Machine learning (ML) techniques have been extensively used in recent years to monitor earthquakes and analyze seismic data, including seismic detection, seismic classification, seismic denoising, phase picking, phase association, earthquake location, magnitude estimation, ground motion prediction, earthquake early warning, source inversion, and subsurface imaging. Due to its impressive accuracy and efficiency, ML-based phase picking has received a lot of interest and has been widely used for earthquake monitoring at local and regional scales, although global and regional ML phase pickers have received less attention.
This session appreciates contributions on the recent advancement in seismic hazard and risk assessment and earthquake early warning methods. We also, welcome the contribution on the application of ML in earthquake source dynamics, wave attenuation characterization and Seismic tomography.

Computational earth science often relies on modelling to understand complex physical systems which cannot be directly observed. Over the last years, numerical modeling of earthquakes provides new approaches to apprehend the physics of earthquake rupture and the seismic cycle, seismic wave propagation, fault zone evolution and seismic hazard assessment. Recent advances in numerical algorithms and increasing computational power enable unforeseen precision and multi-physics components in physics-based simulations of earthquake rupture and seismic wave propagation but also pose challenges in terms of fully exploiting modern supercomputing infrastructure, realistic parameterization of simulation ingredients and the analysis of large synthetic datasets while advances in laboratory experiments link earthquake source processes to rock mechanics. This session aims to bring together modelers and data analysts interested in the physics and computational aspects of earthquake phenomena and earthquake engineering. We welcome studies focusing on all aspects of seismic hazard assessment and the physics of earthquakes — from slow slip events, fault mechanics and rupture dynamics, to wave propagation and ground motion analysis, to the seismic cycle and inter seismic deformation — and studies which further the state-of-the art in the related computational and numerical aspects.

Tsunamis can produce catastrophic damage on vulnerable coastlines, essentially following major earthquakes, landslides, extreme volcanic activity or atmospheric disturbances.
After the disastrous tsunamis in 2004 and 2011, tsunami science has been continuously growing and expanding its scope to new fields of research in various domains, and also to regions where the tsunami hazard was previously underestimated.

The tsunami following the eruption of Hunga Tonga - Hunga Ha'apai in January 2022 provided a new and urging challenge, being an event with an extremely complicated source process and a consequently non-trivial global propagation, posing new questions in terms of modeling, hazard assessment and warning at different scales and evidencing the need for a closer cooperation among different research communities.

The spectrum of topics addressed by tsunami science nowadays ranges from the “classical” themes, such as analytical and numerical modelling of different generation mechanisms (ranging from large subduction earthquakes to local earthquakes generated in tectonically complex environments, from subaerial/submarine landslides to volcanic eruptions and atmospheric disturbances), propagation and run-up, hazard-vulnerability-risk assessment, especially with probabilistic approaches able to quantify uncertainties, early warning and monitoring, to more “applied” themes such as the societal and economic impact of moderate-to-large events on coastal local and nation-wide communities, as well as the present and future challenges connected to the global climate change.

This session welcomes multidisciplinary as well as focused contributions covering any of the aspects mentioned above, 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.

The scope of this session includes different aspects of large-amplitude wave phenomena in the ocean such as freak or rogue waves, surface and internal waves, as well as waves trapped by currents and bathymetry. The session is focused on the understanding of the physical mechanisms which cause extreme events, the derivation of appropriate mathematical models for their description and advanced methods for their analysis. An essential part of such studies is the validation of new models and techniques versus laboratory and in-situ data. Special attention is paid to the description of wave breaking processes, and the interaction of large-amplitude waves with marine structures in offshore and coastal areas.

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. One valuable source of information is the study of past extreme events, which can be reconstructed by combining modelling approaches and field observations. Numerical models also play a crucial role in characterizing future coastal hazards and their associated risks. Drawing firm conclusions about current and future risks 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 physical and socioeconomic impacts of tsunamis and, storm surge, sea-level rise, waves, and currents on coasts. We also welcome submissions on aspects of paleo-tsunami and paleo-storm surge research, including studies that use established methods or recent interdisciplinary advances to reconstruct records of past events, or forecast the probability of future events.

Synthetic aperture radar (SAR) remote sensing is an established tool for natural and anthropogenic hazards mapping and monitoring. The new generation of radar satellite constellations along with a consistent 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 hazards, managing large SAR datasets (e.g. National ground motion services, Copernicus EGMS), and integrating radar data with multispectral satellite observations.

This session aims to explore the synergistic Use of SAR constellations' data exploitation for Earth Science, Civil Engineering and Natural Hazard response.

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 provide 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. During the preparedness and prevention phase, EO revealed, fundamental for hazard, vulnerability, and risk mapping. EO data intervenes both in the emergency forecast and early emergency response, thanks to the potential of rapid mapping. EO data is also increasingly being used for mapping useful information for planning interventions in the recovery phase, and then providing the assessment and analysis of natural hazards, from small to large regions around the globe. In this framework, Committee on Earth Observation Satellites (CEOS) has been working from several years on disasters 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.
In addition to the points above, UAS/drone acquisitions and processing techniques have demonsted their benefits in EO sciences and in particular to study all Geological & Geomorphological objects in terms of 2D/3D geometries (description, location, characterization, quantification, modelisation...) to better constrain Earth Sciences processes. This includes not only classical photogrammetric technics using aerial photographs but also new techniques such as UAS-Lidar acquisition, and/or new UAS-interferometric acquisitions. Many case studies can be taken into account, e.g. DTM/DSM reconstruction, analogs of sandstones or limestones reservoirs, active sedimentological processes in shoreline areas, geodetic measurements as well as 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 multi-platform EO for natural hazards, risk management and geological/geomorphological studies.
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
- New methodologies and results from UAV/Drone acquisitions for geological and geomorphological analyses;
- Share UAS/drone experiences on the study of various geological, geomorphological objects and their associated Natural Hazards.

The use of different types of remote sensing data (e.g. thermal, visual, radar, laser, and/or the fusion of these) and 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, 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, 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; and (3) 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.

Environmental systems often span spatial and temporal scales covering different orders of magnitude. The session is oriented toward collecting studies relevant to understand multiscale aspects of these systems and in proposing adequate multi-platform and inter-disciplinary surveillance networks monitoring tools systems. It is especially aimed to emphasize the interaction between environmental processes occurring at different scales. In particular, special attention is devoted to the studies focused on the development of new techniques and integrated instrumentation for multiscale monitoring of high natural risk areas, such as volcanic, seismic, energy exploitation, slope instability, floods, coastal instability, climate changes, and another environmental context.
We expect contributions derived from several disciplines, such as applied geophysics, geology, seismology, geodesy, geochemistry, remote and proximal sensing, volcanology, geotechnical, soil science, marine geology, oceanography, climatology, and meteorology. In this context, the contributions in analytical and numerical modeling of geological and environmental processes are also expected.
Finally, we stress that the inter-disciplinary studies that highlight the multiscale properties of natural processes analyzed and monitored by using several methodologies are welcome.

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 sensin