Union-wide
Community-led
Inter- and Transdisciplinary Sessions
Disciplinary sessions

NH – Natural Hazards

Programme Group Chair: Heidi Kreibich

MAL7-NH
Arne Richter Award for Outstanding ECS Lecture by Mariana Madruga de Brito
Convener: Heidi Kreibich
MAL25-NH
Plinius Medal Lecture by Annegret Henriette Thieken
Convener: Heidi Kreibich
MAL29-NH
Sergey Soloviev Medal Lecture by Sergio M. Vicente-Serrano
Convener: Heidi Kreibich
NH0.1

Artificial Intelligence (AI) is transforming the way natural hazards are assessed and managed, providing innovative tools for early warning systems, risk assessments, and response strategies. AI-based solutions accelerate and semi-automate the processing and interpretation of (big) data for the benefit of society and the environment. However, these advancements bring ethical challenges, including the need to ensure transparency, equity, and sensitivity to local contexts and vulnerable populations.
By addressing biases, safeguarding data privacy, and upholding principles of fairness, responsible AI strengthens resilience, reduces vulnerabilities, and supports sustainable recovery efforts. For the community engaged in natural hazard research and management, AI offers transformative yet ethically complex capabilities. Given the significant impact of AI-driven decisions on people's lives, particularly in vulnerable settings, fostering dialogue on responsible and ethical AI practices is critical. The aim is to ensure that AI technologies not only enhance efficiency but also align with fundamental human values, advancing equitable and sustainable solutions. In this session, we will discuss the challenges and opportunities of responsible AI for natural hazards assessment and management from different perspectives. The session consists of a panel discussion.

Convener: Kasra Rafiezadeh Shahi | Co-conveners: Maria Vittoria GargiuloECSECS, Heidi Kreibich

NH1 – Hydro-Meteorological Hazards

Sub-Programme Group Scientific Officer: Cristina Prieto

NH1.1 EDI

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

Convener: Martha Marie VogelECSECS | Co-conveners: Ana CasanuevaECSECS, Tom Matthews, Jonathan Buzan
NH1.2

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

Including Sergey Soloviev Medal Lecture
Convener: Athanasios Loukas | Co-conveners: Maria-Carmen Llasat, Uwe Ulbrich, Hadas Saaroni, Silvia Kohnová
NH1.3 EDI

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

Convener: Dhruvesh Patel | Co-conveners: Cristina PrietoECSECS, Benjamin Dewals, Dawei Han
NH1.4 EDI

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

Solicited authors:
Hayley Fowler
Co-organized by CL2/HS13, co-sponsored by IAHS
Convener: Alberto Viglione | Co-conveners: Susanna Corti, Enrico Arnone, Larisa TarasovaECSECS, Giuseppe Zappa
NH1.5 EDI | PICO

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

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

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

Topics of interest include, but are not limited to:

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

Co-organized by HS13
Convener: Tim BuskerECSECS | Co-conveners: Sergiy Vorogushyn, Davide Zoccatelli, Daniela Rodriguez CastroECSECS, Thijs EndendijkECSECS
NH1.6 EDI

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. Lightning is also responsible for a vast number of wildfires, burned area, and fire emissions to the atmosphere. It has significant effects on various atmospheric layers and drives the fair-weather electric field. It is a strong indicator of convective processes on regional and global scales, potentially associated with climate change. Lightning produces nitrogen oxides, which are a precursor to ozone production. Thunderstorms and lightning are essential parts of the Global Electrical Circuit (GEC) and control the fair weather electric field. They are also associated with the production of energetic radiation up to tens of MeV on time scales from sub-millisecond (Terrestrial Gamma-ray Flashes) to tens of seconds (gamma-ray glows).

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

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

Solicited authors:
Marrick Braam,Ralph Lorenz
Co-organized by AS1, co-sponsored by AGU-ASE
Convener: Yoav Yair | Co-conveners: Karen Aplin, Xiushu Qie, Kelcy BrunnerECSECS, David Sarria, Jose V. Moris
NH1.7 EDI

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

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

Solicited authors:
Ana Mijic
Co-organized by BG8/GM3/HS13, co-sponsored by AGU
Convener: Isabella SchalkoECSECS | Co-conveners: Barry Hankin, Elizabeth FollettECSECS, Hannah ChampionECSECS

NH2 – Volcanic Hazards

Sub-Programme Group Scientific Officer: Andrea Di Muro

NH2.2 | PICO

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

Convener: Loredana Nada Elvira Giani | Co-conveners: Annarita Iacopino, Vinicio Brigante, Federico Valentini, Vanessa Manzetti
NH2.3 EDI

When a volcano erupts, providing information on hazardous volcanic phenomena, their effects to communities and enviornmentes, and the eruption's duration is crucial to inform risk mitigation strategies. However, eruptions are complex phenomena governed by interactions of many processes, which are often nonlinear and stochastic. Numerous uncertainties in the involved parameters make precise predictions of specific events in time and space usually unattainable; that is, volcanic eruptions can be intrinsically unpredictable. Despite these limitations, significant progress has been made in forecasting volcanic hazards and, in specific circumstances, in making predictions. Understanding and predicting volcanic phenomena requires a comprehensive approach that integrates satellite observations, field measurements, and advanced modelling techniques. This has led to the increased use of data-driven approaches, including artificial intelligence (AI) techniques, to address volcanic hazards. Looking to the future, AI models can be combined with physical constraints to bridge the gap between data-driven methods and physical modeling, thereby increasing the interpretability of AI predictions. This offers an alternative approach to dealing with the strongly nonlinear and time-dependent character of volcanic phenomena.
This multidisciplinary session seeks to bring together contributions focusing on enhancing traditional ground-based volcano monitoring systems through technological innovation in satellite remote sensing and computational methods, integrating deep-learning, data-driven, physical and statistical modelling approaches, to better understand and forecast volcanic hazards. By fostering discussions and sharing insights, we aim to drive forward the development of more comprehensive and integrated approaches to volcanic hazard assessment and risk mitigation.

Solicited authors:
Nantheera Anantrasirichai,Mike Burton
Co-organized by GMPV9, co-sponsored by AGU
Convener: Ciro Del Negro | Co-conveners: Alessio Alexiadis, Eleonora AmatoECSECS, Silvia Massaro, Leonardo Mingari, Pablo TierzECSECS, Federica TorrisiECSECS
NH2.8

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

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

Solicited authors:
Junli Zhang
Co-organized by GD4/GMPV4
Convener: Marianne Conin | Co-conveners: Paola Vannucchi, Mathilde Radiguet, Thomas P. FerrandECSECS, Marco Scambelluri

NH3 – Landslide and Snow Avalanche Hazards

Sub-Programme Group Scientific Officer: Veronica Pazzi

NH3.1 EDI

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

Solicited authors:
Shiva P. Pudasaini
Convener: Alessandro Leonardi | Co-conveners: Jacob HirschbergECSECS, Marcel Hürlimann, Shuai Li, Sara SaviECSECS
NH3.2

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

Co-organized by GM3
Convener: Giovanni Crosta | Co-conveners: Irene ManzellaECSECS, Christian Zangerl
NH3.3 EDI

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

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

We invite presentations that investigate mass movements using seismic and/or infrasound techniques as well as other geophysical or remote-sensing techniques. Topics of interest include source detection, location, characterization, modeling, and classification; precursory signal analysis; monitoring; innovative instrumentation; and hazard mitigation.

Solicited authors:
Adrian Flores Orozco,Mirko Pavoni,Małgorzata Chmiel
Co-organized by ESSI4
Convener: Artur MarciniakECSECS | Co-conveners: Liam ToneyECSECS, Veronica Pazzi, Sebastian Uhlemann, Cedric Schmelzbach, Emanuele Marchetti, Jon Chambers
NH3.4 EDI | PICO

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

Co-organized by GM3
Convener: Gianvito Scaringi | Co-conveners: Séverine Bernardie, Stefano Luigi Gariano, Roberta Paranunzio, Alfredo Reder, Guido Rianna
NH3.5 EDI

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

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

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

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

Co-organized by GM3
Convener: Anne Voigtländer | Co-conveners: Axel Volkwein, Michael Krautblatter, Mylene Jacquemart
NH3.6 EDI

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

Contributions are encouraged in the following areas:

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

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

Co-organized by GM3
Convener: Filippo Catani | Co-conveners: Ugur OzturkECSECS, Mateja Jemec Auflič, Anne-Laure ArgentinECSECS, Tolga Gorum
NH3.7 EDI

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

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

Convener: Luca Piciullo | Co-conveners: Tina Peternel, Stefano Luigi Gariano, Neelima Satyam, Samuele Segoni
NH3.8 EDI

Under the influence of global climate change, urban expansion and human activities, landslides (and geo-hydrological hazards in general) occur frequently every year around the world, posing a great threat to human life and property safety. The global increase in damaging events has attracted the attention of governments, practitioners and scientists to develop functional, reliable and (when possible) low-cost monitoring and management strategies. Numerous case studies have demonstrated how a well-planned monitoring system of landslides (and ground deformation in general) is of fundamental importance for long and short-term risk reduction.
Today, the temporal evolution of a landslide is addressed in several ways, encompassing classical and more complex in situ measurements or remotely sensed data acquired from satellite and aerial platforms. All these techniques are adopted for the same final scope: measure motion over time, trying to forecast future evolution or, at least, reconstruct its recent past. Real time, near-real time and deferred time strategies can be profitably used for landslide analysis, depending on the type of phenomenon, the selected monitoring tool and the acceptable level of risk.
This session follows the general objectives of the International Consortium on Landslides, namely: (i) promote landslide research for the benefit of society, (ii) integrate geosciences and technology within the cultural and social contexts to evaluate landslide risk, and (iii) combine and coordinate international expertise.
The session is expected to present various topics of innovative applications of remote sensing techniques, as well as case studies in which multi-temporal and multi-platform data are exploited for risk management. The integration and synergic use of different techniques is welcomed, as well as newly developed tools or data analysis approaches, including big data management strategies.
The current session includes contributions deriving from the sessions NH6.4 (EGMS data for natural and man-made induced geohazards) and NH11.1(Geo-hydrological hazards and landscape evolution in climate change scenarios - co-sponsored by AIGeo), thus broadening the original topic and encompassing contributions dealing with the use of satellite interferometry to monitor different kinds of geohazards and all facets of geo-hydrological hazard in the context of climate variability.

Solicited authors:
Istvan Szakolczai
Co-sponsored by AIGeo
Convener: Federico Raspini | Co-conveners: Stefano Morelli, Matteo Del Soldato, Veronica Tofani, Peter Bobrowsky, Mateja Jemec Auflič, Qingkai Meng
NH3.10 | PICO

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

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

Solicited authors:
Graziella Devoli
Convener: Michele Santangelo | Co-conveners: Federica Fiorucci, Petra Jagodnik, Khamarrul Azahari Razak, Kate Allstadt
NH3.12 EDI

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

Convener: Hakan Tanyas | Co-conveners: Kate Allstadt, Tolga Gorum, Xuanmei Fan, Tom Robinson
NH3.13 EDI

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

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

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

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

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

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

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

Convener: Vittoria CapobiancoECSECS | Co-conveners: Alessandro FraccicaECSECS, Manuela Cecconi, Zhun Mao, Anthony Leung
NH3.15 EDI

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

Co-organized by SSS10
Convener: Massimiliano Bordoni | Co-conveners: Ilenia Murgia, Emir Ahmet Oguz, Thom BogaardECSECS
NH3.16 EDI

Effective landslide risk reduction and response efforts require reliable detection, informed process understanding, and accurate prediction. Advances in data-driven landslide detection are accelerating post-event mapping and leading to a growing availability of multi-temporal landslide inventories. These datasets, in turn, are allowing researchers to obtain a deeper understanding of the causes and triggers that influence landslide activity from hillslope to regional scales. For example, in combination with hydroclimatic models, re-analysis products, and meteorological observations, such inventories are enabling improved quantification of dynamic hydro-meteorological conditions that trigger weather-related landslides. Similar efforts are revealing indicators of co-seismic landslide hazard and underlying causes of slope instability. These insights are being integrated into data-driven, predictive models that can inform hazard assessments, increase situational awareness, and aid warning.

This session aims to spur future research advances and operational application development by bringing together a wide range of perspectives from geomorphology, hydrology, meteorology, remote sensing, data science and beyond. We will additionally explore how artificial intelligence (AI) and other data-driven approaches can enhance traditional methodologies, offering new insights for landslide detection, process understanding, and prediction.

Topics may include:
• Detecting and mapping landslide activity with remote sensing data and/or point source terrestrial data
• Linking trends and variability in landslide activity to hydro-meteorological, geological, morphological, or other conditions to improve process understanding
• Development and testing of new methods and approaches, including statistical, machine learning, and AI-based approaches, to support landslide hazard assessment, prediction, and early warning

Solicited authors:
Thom Bogaard
Co-organized by GM3/HS13
Convener: Lisa LunaECSECS | Co-conveners: Sansar Raj MeenaECSECS, Luca Piciullo, Minu Treesa AbrahamECSECS, Luca Ciabatta, Oriol Monserrat, Yaser Peiro
NH3.17 EDI

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

Solicited authors:
Dario Gioia
Convener: Luigi MassaroECSECS | Co-conveners: Ciro CerroneECSECS, Chiara Varone, Giuseppe CorradoECSECS, Nicușor NeculaECSECS

NH4 – Earthquake Hazards

Sub-Programme Group Scientific Officer: Ioanna Triantafyllou

NH4.1 EDI

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

Solicited authors:
Giuseppe Petrillo,Franco Pettenati,Vitor Silva
Co-organized by OS4/SM8
Convener: Gianfranco Vannucci | Co-conveners: Ioanna TriantafyllouECSECS, Laura Gulia
NH4.3 EDI

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

Convener: Adriana Fatima Ornelas AgrelaECSECS | Co-conveners: Mario Arroyo SolórzanoECSECS, Federica Ghione, Vitor Silva
NH4.4 EDI

Mitigating earthquake disasters involves several key components and stages, from identifying and assessing risk to reducing their impact. These components include: a) Long-term and time-dependent analysis of hazards: anticipating the space-time characteristics of ground shaking and its cascading events. b) Vulnerability and exposure assessment c) Risk management: preparedness, rescue, recovery, and overall resilience. A variety of seismic hazard and risk models can be adopted, at different spatial and temporal scale, that incorporate diverse observations and require multi-disciplinary input. Testing and validating these methodologies, for all risk components, is essential for effective disaster mitigation.
From the real-time integration of multi-parametric observations is expected the major contribution to the development of operational time-Dependent Assessment of Seismic Hazard (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, 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 includes studies on various aspects of seismic risk research and assessment, observations and/or data analysis methods within the t-DASH and Short-term Earthquakes Forecast perspectives:
- Studies on time-dependent seismic hazard and risk assessments
- Development of physical/statistical models and studies based on long-term data analyses, including different conditions of seismic activity
- Application of AI to assess earthquake risk factors (hazard, exposure, and vulnerability). Exploring innovative data collection and processing techniques, such as statistical machine learning
- Estimating earthquake hazard and risk across different temporal and spatial scales and assessing the accuracy of these models against available observations
- Earthquake-induced cascading effects such as landslides and tsunamis, and multi-risk assessments
- Studies devoted to the description of genetic models of earthquake’s precursory phenomena
- Infrastructures devoted to maintain and further develop our present observational capabilities of earthquake related phenomena also contributing to build a global multi-parametric Earthquakes Observing System (EQuOS) to complement the existing GEOSS initiative

Solicited authors:
Dimitar Ouzounov,Taner Sengor,Qinghua Huang
Co-organized by EMRP1/ESSI2/GI6, co-sponsored by JpGU and EMSEV
Convener: Valerio Tramutoli | Co-conveners: Pier Francesco Biagi, Antonella Peresan, Carolina Filizzola, Nicola Genzano, Katsumi Hattori, Rajesh Rupakhety
NH4.5 EDI

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

Solicited authors:
Paulina Janusz
Convener: Enrico Paolucci | Co-conveners: Giulia Sgattoni, Janneke van GinkelECSECS, Francesco Panzera, Sebastiano D’Amico
NH4.6 EDI

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

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

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

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

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

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

Solicited authors:
Maximilian Werner
Convener: Stefania Gentili | Co-conveners: Álvaro González, Filippos Vallianatos, Piero BrondiECSECS

NH5 – Sea & Ocean Hazards

Sub-Programme Group Scientific Officer: Filippo Zaniboni

NH5.1 EDI

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

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

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

Solicited authors:
Jean Roger,Clea Denamiel,Tatsuya Kubota
Convener: Jadranka Sepic | Co-conveners: Rachid Omira, Musavver Didem Cambaz, Fabrizio Romano, Hélène Hébert

NH6 – Remote Sensing, AI, data science & Hazards

Sub-Programme Group Scientific Officer: Kasra Rafiezadeh Shahi

NH6.1 EDI

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

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

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

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