The Open Session on Geosciences Instrumentation is the European forum with an open call for professional conference papers in the field of Geosciences Instrumentation, Methods, Software and Data Systems. The session aims to inform the scientific and engineering geosciences communities about new and/or improved instrumentation and methods, and their related new or existing applications. The session also deals with new ways of utilizing observational data by novel approaches and the required data infrastructure design and organization.

The session is open to all branches of geoscience measurement techniques, including, but not limited to, optical, electromagnetic, seismic, acoustic and gravity. The session is intended as an open forum and discussion between representatives of different fields within geosciences is strongly encouraged. Past experience has shown that such mutual exchange and cross-fertilization between areas have been very successful and can open up for a breakthrough in frontier problems of modern geosciences.

The session is also open for applications related to environmental monitoring and security providing, like archeological surveys, rubbish deposit studies, unexploded ordnance and/or mines detection, water dam inspection, seismic hazards monitoring, etc.

This session is devoted to a scientific/technological survey of observational strategies and sensing technologies for improving the quality of life and ensuring inclusivity of people in challenging social and economic contexts, such as marginal and degraded areas. Examples of the beneficial role of technological tools regarding the monitoring and protection of critical infrastructures (water, energy, transport) to ameliorate the inclusivity and ensure a more right exploitation of the resources, independently from the social level of the people in the urban areas. Another example regards the possibility of exploiting natural and cultural resources to improve the economy and quality of life in marginal areas, which in many cases are rural areas. Furthermore, attention will be devoted to the development and exploitation in real world of low cost and scalable/portable sensing solutions of interest for the monitoring of both large urban areas as well as poorly covered zones. Attention will be given to abstracts/presentations regarding the definition of the social and economic needs that impact on the development of new standalone solutions or on the integration of assessed methodologies/technologies.

Instrumentation and measurement technologies are currently playing a key role in the monitoring, assessment and protection of water resources.
This session focuses on measurement techniques, sensing methods and data science implications for the observation of water systems, emphasizing the strong link between measurement aspects and computational aspects characterising the water sector.
This session aims at providing an updated framework of the observational techniques, data processing approaches and sensing technologies for water management and protection, giving attention to today’s data science aspects, e.g. data analytics, big data, cloud computing and Artificial Intelligence.
Building a community around instrumentation & measurements for water systems is one of the aims of the session. In particular, participants to the EGU2020 edition of this session contributed to this book: A. Di Mauro, A. Scozzari & F. Soldovieri (eds.), Instrumentation and Measurement Technologies for Water Cycle Management, Springer Water, ISBN: 978-3-031-08261-0, 2022.
We welcome contributions about field measurement approaches, development of new sensing techniques, low cost sensor systems and measurement methods enabling crowdsourced data collection.
Therefore, water quantity and quality measurements as well as water characterization techniques are within the scope of this session. Remote sensing techniques for the monitoring of water resources and/or the related infrastructures are also welcome. Contributions dealing with the integration of data from multiple sources are solicited, as well as the design of ICT architectures (including IoT concepts) and of computing systems for the user-friendly monitoring of the water resource and the related networks.
Studies about signal and data processing techniques (including machine learning) and the integration between sensor networks and large data systems are also very encouraged.

This session, which is co-organised by the Green Cluster (TRIQUETRA, THETIDA, RescueME, STECCI Horizon Europe projects funded under topic HORIZON-CL2-2022-HERITAGE-01-08) and the FPCUP action, aims to host discussions focused on the identification and quantification of the impacts of Climate Change on Cultural Heritage, using novel and state-of-the-art techniques. At the same time, the session serves as an opportunity to showcase the latest advances in the field of Cultural Heritage protection and preservation, through systematic monitoring and documentation, while simultaneously encouraging citizen engagement and the development of crowdsourcing applications and activities. The session will also highlight the importance of EU initiatives and funding in the field of Cultural Heritage, which faces a series of new challenges as a result of Climate Change. Finally, presentations will provide all interested parties with valuable insight into new strategies and applied technologies that may serve as paradigms moving forward.

Pangeo (pangeo.io) is a global community of researchers and developers that tackle big geoscience data challenges in a collaborative manner using laptop to HPC and Cloud infrastructure. This session's aim is:
to motivate researchers who are using or developing in the Pangeo ecosystem to share their endeavours with a broader community that can benefit from these new tools.
to contribute to the Pangeo community in terms of potential new applications for the Pangeo ecosystem, containing the following core packages: Xarray, Iris, Dask, Jupyter, Zarr, Kerchunk and Intake.

We warmly welcome contributions that detail various Cloud computing initiatives within the domains of Earth Observation and Earth System Modelling, including but not limited to:
- Cloud federations, scalability and interoperability initiatives across different domains, multi-provenance data, security, privacy and green and sustainable computing.
- Cloud applications, infrastructure and platforms (IaaS, PaaS SaaS and XaaS).
- Cloud-native AI/ML frameworks and tools for processing data.
- Operational systems on the cloud.
- Cloud computing and HPC convergence and workload unification for EO data processing.

Also, presentations using at least one of Pangeo’s core packages in any of the following domains:
- Atmosphere, Ocean and Land Models
- Satellite Observations
- Machine Learning
- And other related applications

We welcome any contributions in the above themes presented as science-based in other EGU sessions, but more focused on research, data management, software and/or infrastructure aspects. For instance, you can showcase your implementation through live executable notebooks.

Sitting under a tree, you feel the spark of an idea, and suddenly everything falls into place. The following days and tests confirm: you have made a magnificent discovery — so the classical story of scientific genius goes…

But science as a human activity is error-prone, and might be more adequately described as "trial and error", or as a process of successful "tinkering" (Knorr, 1979). Thus we want to turn the story around, and ask you to share 1) those ideas that seemed magnificent but turned out not to be, and 2) the errors, bugs, and mistakes in your work that made the scientific road bumpy. What ideas were torn down or did not work, and what concepts survived in the ashes or were robust despite errors? We explicitly solicit Blunders, Unexpected Glitches, and Surprises (BUGS) from modeling and field or lab experiments and from all disciplines of the Geosciences.

Handling mistakes and setbacks is a key skill of scientists. Yet, we publish only those parts of our research that did work. That is also because a study may have better chances to be accepted for publication in the scientific literature if it confirms an accepted theory or if it reaches a positive result (publication bias). Conversely, the cases that fail in their test of a new method or idea often end up in a drawer (which is why publication bias is also sometimes called the "file drawer effect"). This is potentially a waste of time and resources within our community as other scientists may set about testing the same idea or model setup without being aware of previous failed attempts.

In the spirit of open science, we want to bring the BUGS out of the drawers and into the spotlight. In a friendly atmosphere, we will learn from each others' mistakes, understand the impact of errors and abandoned paths onto our work, and generate new insights for our science or scientific practice.

Here are some ideas for contributions that we would love to see:
- Ideas that sounded good at first, but turned out to not work.
- Results that presented themselves as great in the first place but turned out to be caused by a bug or measurement error.
- Errors and slip-ups that resulted in insights.
- Failed experiments and negative results.
- Obstacles and dead ends you found and would like to warn others about.

--
Knorr, Karin D. “Tinkering toward Success: Prelude to a Theory of Scientific Practice.” Theory and Society 8, no. 3 (1979): 347–76.

Large engineering infrastructures, such as flood embankments, rails and road networks, dams or bridges, play a vital role in our society. Due to changes in climate and microclimate, infrastructures that have performed well for the last decades can reveal changes in their behaviour, especially in case of weather extremes such droughts, heavy raining or heat waves. It is therefore becoming increasingly important to be able to monitor and model the behaviour of man-made structures under operational or extreme conditions to ensure safety, reliability and efficiency. Today's rapidly evolving technological landscape is offering different solutions (in terms of hardware and software) to monitor and model the behaviour of large-scale infrastructures.
This section welcomes new (low-cost) hardware technologies and software tools, including open-source devices, AI methods or integrated solutions, to monitor man-made infrastructures, perform anomaly detection or failure prediction in complex systems. Contributions that develop on top of or complement a monitoring system with modelling methods are also welcome. The session will therefore cover key topics such as sensor networks, digital twins, IoT solutions, big data analytics, Cloud-based platforms and decision support systems (DSS), providing insights into their applications across sectors like infrastructure monitoring, transportation, energy and urban development. Participants will gain a comprehensive understanding of how these innovations are reshaping the management of large infrastructures, improving decision-making, and optimizing long-term maintenance strategies.

Cloud-based services support users in viewing, downloading, and analysing geospatial data. Many of these web-based services expand their functionalities to provide advanced data processing tools, online data repositories, interactive and collaborative computing environment for creating and sharing live code. Over the last two decades, the larger EO sector has seen many cloud services and EO Platforms come and go. A few solutions have prevailed, and a set of technologies today are finding widespread adoption. Recent geospatial platforms are designing their services to function as a digital ecosystem, where integrated services now communicate with a network of interconnected web-services, building on the concept of federations. Therefore, this distributed infrastructure can offer much more and to a larger range of customers with different skills (e.g., service consumers and service providers).
For example, Destination Earth (or DestinE) is an initiative of the EC’s DG-CNECT, for developing and exploiting a highly accurate digital model of the Earth, with the objectives of monitoring and predicting the interactions between natural phenomena and human activities. DestinE Platform (platform.destine.eu) integrates and operates an open ecosystem of services to support users to exploit a large portfolio of Earth Science data, including high-resolution data from ECMWF’s Digital Twins, and create services and applications on top of them.
Other relevant platform is openEO. At its core it comprises a set of processes, client libraries, and used with a REST API and a set of predefined endpoints. OpenEO allows abstracting complex EO workflows to be executed in different cloud environments. Initially openEO API was supported by H2020 funding, now the operation is under ESA funding (openeo.cloud). Several additional industry owned and operated openEO supporting backends exist today, forming a larger federation of resources.
EarthCode, an open-source architecture leveraging EOEPCA+, builds on top of existing EO cloud services to serve the downstream Earth Science community. It aims to make FAIR and Open Science practice, offering tools for the management of FAIR data and code, long-term access to community-developed scientific results, and cross-platform reproducible implementations of scientific algorithms.
This session invites all types of platform providers and users to evidence the benefits of any kind of cloud-based services for geospatial activities.

Climate study related experiments and observational stations are getting bigger and number of sensors and instruments involved is growing very fast. Large scale experiments like NEON have to deal with hundreds of sensors and instruments. The most effective way to manage such large installations is to incorporate all equipment in to a network. At this session we would like people to share their experience in establishing, maintaining, and managing a fixed environmental sensor networks on or near surface measurements (it does not cover remotely sensed data - satellite imagery, aerial photography, etc.). This session is open for all works about an existing system, planning a completely new network, upgrading an existing system, improving streaming data management, and archiving data.

In recent years, technologies based on Artificial Intelligence (AI), such as image processing, smart sensors, and intelligent inversion, have garnered significant attention from researchers in the geosciences community. These technologies offer the promise of transitioning geosciences from qualitative to quantitative analysis, unlocking new insights and capabilities previously thought unattainable.
One of the key reasons for the growing popularity of AI in geosciences is its unparalleled ability to efficiently analyze vast datasets within remarkably short timeframes. This capability empowers scientists and researchers to tackle some of the most intricate and challenging issues in fields like Geophysics, Seismology, Hydrology, Planetary Science, Remote Sensing, and Disaster Risk Reduction.
As we stand on the cusp of a new era in geosciences, the integration of artificial intelligence promises to deliver more accurate estimations, efficient predictions, and innovative solutions. By leveraging algorithms and machine learning, AI empowers geoscientists to uncover intricate patterns and relationships within complex data sources, ultimately advancing our understanding of the Earth's dynamic systems. In essence, artificial intelligence has become an indispensable tool in the pursuit of quantitative precision and deeper insights in the fascinating world of geosciences.
For this reason, aim of this session is to explore new advances and approaches of AI in Geosciences.

The radioactive materials are known as polluting materials that are hazardous for human society, but are also ideal markers in understanding dynamics and　physical/chemical/biological reactions chains in the environment. Therefore, man-made radioactive contamination involves regional and global transport and local reactions of radioactive materials through atmosphere, soil and water system, ocean, and organic and ecosystem, and its relations with human and non-human biota. The topic also involves hazard prediction, risk assessment, nowcast, and countermeasures, , which is now urgent important for the nuclear power plants in Ukraine.

By combining long monitoring data (> halftime of Cesium 137 after the Chernobyl Accident in 1986, 13 years after the Fukushima Accident in 2011, and other events), we can improve our knowledgebase on the environmental behavior of radioactive materials and its environmental/biological impact. This should lead to improved monitoring systems in the future including emergency response systems, acute sampling/measurement methodology, and remediation schemes for any future nuclear accidents.

The following specific topics have traditionally been discussed:
(a) Atmospheric Science (emissions, transport, deposition, pollution);
(b) Hydrology (transport in surface and ground water system, soil-water interactions);
(c) Oceanology (transport, bio-system interaction);
(d) Soil System (transport, chemical interaction, transfer to organic system);
(e) Forestry;
(f) Natural Hazards (warning systems, health risk assessments, geophysical variability);
(g) Measurement Techniques (instrumentation, multipoint data measurements);
(h) Ecosystems (migration/decay of radionuclides).

The session consists of updated observations, new theoretical developments including simulations, and improved methods or tools which could improve observation and prediction capabilities during eventual future nuclear emergencies. New evaluations of existing tools, past nuclear contamination events and other data sets also welcome.

Addressing global environmental and societal challenges requires interdisciplinary, data-driven approaches. Today’s research produces unprecedented volumes of complex data and an increasing number of interactive data services, putting traditional information management systems to the test. Collaborative infrastructures are challenged by their dual role of advancing research and scientific assessments while facilitating transparent data and software sharing.

We invite abstracts from all data stakeholders that highlight innovative platforms, frameworks, systems, and initiatives designed to enhance access and usability of data for research on topics such as climate change, natural hazards, sustainable development, etc. We welcome presentations describing collaborations across national and disciplinary boundaries on infrastructure, standards, governance, best practices, and future directions for building trustworthy and interoperable data networks, guided by UNESCO’s Open Science recommendations, the FAIR and CARE data principles, that enable researchers worldwide to address pressing global problems through data.

Almost a decade ago, the FAIR data guiding principles were introduced to the broader research community. These principles proposed a framework to increase the reusability of data in and across domains during and after the completion of e.g. research projects. In subdomains of the Earth System Sciences (ESS), like atmospheric sciences or partly geosciences, data reuse across institutions and geographical borders was already well-established, supported by community-specific and cross-domain standards like netCDF-CF, geospatial standards (e.g.OGC). Further, authoritative data producers such as CMIPs were already using Persistent Identifiers and corresponding handle systems for data published in their repositories – so it was often thought and communicated this data is “FAIR by design”.

However, fully implementing FAIR principles, particularly machine-actionability—the core idea behind FAIR—has proven challenging. Despite progress in awareness, standard-compliant data sharing, and the automation of data provenance, the ESS community continues to struggle to reach a community-wide consensus on the design, adoption, interpretation and implementation of the FAIR principles.

In this session, we invite contributions from all fields in Earth System Sciences that provide insights, case studies, and innovative approaches to advancing the adoption of the FAIR data principles. We aim to foster a collaborative dialogue on the progress our community has made, the challenges that lie ahead, and the strategies needed to achieve widespread acceptance and implementation of these principles, ultimately enhancing the future of data management and reuse.

We invite contributions focusing on, but not necessarily limited to,
- Challenges and solutions in interpreting and implementing the FAIR principles in different sub-domains of the ESS
- FAIR onboarding strategies for research communities
- Case studies of successful FAIR data implementation (or partial implementation) in ESS at infrastructure and research project level
- Methods and approaches to gauge the impact of FAIR data implementation in ESS
- Considerations on how AI might help to implement FAIR
- Future direction for FAIR data in ESS

This session explores the transformative potential of large language models (LLMs) in geosciences. LLMs are revolutionising the field by enabling researchers to process and interpret complex geological, climatological, environmental, hydrological and other earth systems data with unprecedented speed and accuracy, leading to new discoveries and insights. Presenters are encouraged to share how LLMs have accelerated research by analysing vast datasets, automating data interpretation, and uncovering hidden patterns. Case studies highlighting breakthroughs in geology, climate science, and environmental monitoring are particularly welcome. This session will provide a platform for geoscientists to discuss the integration of LLMs into their workflows, enhancing both efficiency and discovery while addressing challenges such as model accuracy and data bias. We invite presentations that explore the transformative potential of large language models (LLMs) in the geosciences. Join us in contributing to this cutting-edge dialogue and helping shape the future of geosciences through AI.

Performing research in Earth System Science is increasingly challenged by the escalating volumes and complexity of data, requiring sophisticated workflow methodologies for efficient processing and data reuse. The complexity of computational systems, such as distributed and high-performance heterogeneous computing environments, further increases the need for advanced orchestration capabilities to perform and reproduce simulations effectively. On the same line, the emergence and integration of data-driven models, next to the traditional compute-driven ones, introduces additional challenges in terms of workflow management. This session delves into the latest advances in workflow concepts and techniques essential to address these challenges taking into account the different aspects linked with High-Performance Computing (HPC), Data Processing and Analytics, and Artificial Intelligence (AI).

In the session, we will explore the importance of the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles and provenance in ensuring data accessibility, transparency, and trustworthiness. We will also address the balance between reproducibility and security, addressing potential workflow vulnerabilities while preserving research integrity.

Attention will be given to workflows in federated infrastructures and their role in scalable data analysis. We will discuss cutting-edge techniques for modeling and data analysis, highlighting how these workflows can manage otherwise unmanageable data volumes and complexities, as well as best practices and progress from various initiatives and challenging use cases (e.g., Digital Twins of the Earth and the Ocean).

We will gain insights into FAIR Digital Objects, (meta)data standards, linked-data approaches, virtual research environments, and Open Science principles. The aim is to improve data management practices in a data-intensive world.
On these topics, we invite contributions from researchers illustrating their approach to scalable workflows as well as data and computational experts presenting current approaches offered and developed by IT infrastructure providers enabling cutting edge research in Earth System Science.

In environmental and climate science, solving complex challenges requires holistic approaches, emphasising the need for effective data integration and interoperability. While these terms may initially sound like buzzwords, they become crucial once a measurement is digitised, and physical phenomena are translated into models, which are eventually encoded into software. As environmental and climate scientists, our expertise is essential in addressing ecological challenges and mitigating climate-related risks. This responsibility extends to our engagement with research- and e-infrastructures that support our excellent science. Just as humans communicate effectively to share insights, machines must seamlessly exchange data. In the era of big data, scientific research demands increasingly advanced methodologies and machine-to-machine (M2M) actionable data and services. Data repositories, High-Performance Computing (HPC) facilities, cloud service providers and other infrastructures empower researchers with more tools and (FAIR) technical solutions to drive scientific process. Currently in Europe a wealth of operational infrastructures such as the Environmental Research Infrastructures (ENVRIs), the European Open Science Cloud (EOSC), and e-Infrastructures like EGI, offer these services, contributing to scientific progress.
This session aims to gather real-world examples from environmental and climate research across multi- and interdisciplinary domains (atmosphere, marine, ecosystems, solid earth), data product developers, data scientists and engineers. You will demonstrate research outcomes, showcase research or scientific development projects, discuss challenges, and propose best practices with successful infrastructure support. We welcome contributions from data-driven research, presenting aspects of data analytics, visualisation, data collection and quality control. We also invite use cases of interoperable infrastructures and enhanced collaborations with cloud services. Experiences from Virtual Access and/or Transnational Access programs, and innovative projects embracing the transformative potential of digital twins are also welcome. Join us as we explore how seamless data sharing and integration are accelerating climate science, enabling faster, more accurate models and solutions to pressing global environmental challenges.

Recent Earth System Sciences (ESS) datasets, such as those resulting from very high resolution numerical modelling, have increased both in terms of precision and size. These datasets are central to the advancement of ESS for the benefit of all stakeholders, public policymaking on climate change and to the performance of modern applications such as Machine Learning (ML) and forecasting.

The storage and shareability of ESS datasets have become an important discussion point in the scientific community. It is apparent that datasets produced by state-of-the-art applications are becoming so large that even current high-capacity data centres and infrastructures are incapable of storing, let alone ensuring the usability and processability of such datasets. The needs of ongoing and upcoming community activities, such as various digital twin centred projects or the 7th Phase of the Coupled Model Intercomparison Project (CMIP7) already stretch the abilities of current infrastructures. With future investment in hardware being limited, a viable way forward is to explore the possibilities of data reduction and compression with the needs of stakeholders in mind. Therefore, the use of data compression has grown in interest to 1) make the data weight more manageable, 2) speed up data transfer times and resource needs and 3) without reducing the quality of scientific analyses.

Concurrently, replicability is another major concern for ESS and downstream applications. Being able to reproduce the most recent ML and forecasting results and analyses thereof has become mandatory to develop new methods and integrated workflows for operational settings. On the other hand, the data accuracy needed to produce reliable downstream products has not yet been thoroughly investigated. Therefore, research on data reduction and prediction interpretability helps to 1) understand the relationship between the datasets and the resulting prediction and 2) increase the stability of prediction.

This session discusses the latest advances in both data compression and reduction for ESS datasets, focusing on:
1) Approaches and techniques to enhance shareability of high-volume ESS datasets: data compression (lossless and lossy) or reduction approaches.
2) Understanding the effects of reduction and replicability: feature selection, feature fusion, sensitivity to data, active learning.
3) Analyses of the effect of reduced/compressed data on numerical weather prediction and/or machine learning methods.

GNSS Interferometric Reflectometry (GNSS-IR) is an emerging ground-based remote sensing technique that uses reflected GNSS signals. This technique has been applied to measure a variety of variables including water level, significant wave height, snow accumulation, permafrost melt, soil moisture, vegetation water content and coastal subsidence. As the number of developers and users of GNSS-IR continues to grow, this session seeks to highlight advances in the (near real-time) acquisition, processing, analysis and application of GNSS-IR data in environmental sensing. The session welcomes contributions related to the algorithmic and technical improvement of GNSS-IR models, as well as the development of open-source hardware and software. We encourage discussions on GNSS-IR delivery products and their validation, the optimal exploitation of geodetic and affordable GNSS sensors for applications in interferometric reflectometry and initiatives for (near) real-time monitoring of environmental variables.

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

The ever-increasing demand for accurate and reliable oceanographic data has made advancements in ocean instrumentation systems crucial for understanding the complexities of marine environments. Ocean instrumentation systems are at the core of modern oceanographic research, enabling scientists to monitor, explore, and diagnose physical, chemical, and biological processes in oceans. However, these systems face significant challenges in deployment, maintenance, data accuracy, and long-term sustainability in harsh oceanic conditions.
Contributions from researchers, engineers, and industry leaders working on sensor design, real-time monitoring systems, and autonomous platforms such as AUVs (Autonomous Underwater Vehicles) and ROVs (Remotely Operated Vehicles) are encouraged. Additionally, the session will cover diagnostic techniques for ensuring the reliability and functionality of ocean instrumentation, addressing issues like sensor drift, biofouling, power limitations, and the impact of extreme environmental conditions.

This session aims to provide a comprehensive platform for discussing the latest advancements in lunar science, exploration, and sustainable utilization.
We will cover critical aspects of lunar science, including the deep interior, subsurface structure, surface morphology, up to atmospheric dynamics and the solar wind interaction. Such studies can make use of lunar mission data, lunar samples, meteorites, terrestrial analogues, laboratory experiments, and / or modeling efforts.
Furthermore, highlighting results from past and current space missions, this session seeks to explore innovative ideas for future exploration, including insights on forthcoming space missions and instrumentation aiming to greatly advance our understanding of the Moon in the next decades. In addition, the session will focus on identifying strategic knowledge gaps crucial for the safe and sustainable exploration of cis-lunar space and the lunar surface by astronauts.
We welcome all relevant contributions — spanning theoretical models, observational data, and experimental findings — from experts of different fields including science and engineering. As such, the session aims to foster a comprehensive dialogue on the status and future of lunar exploration.

This session invites contributions to new or improved instrumentation and methods for space and planetary exploration, including novel and established applications. The session is open to all branches of planetary and space measurement tools and techniques, including, but not limited to optical, electromagnetic, seismic, acoustic, and gravity measurements. This session is also intended as an open forum, where discussion between representatives of different fields within planetary, space and geosciences will be strongly encouraged, looking for a fruitful mutual exchange and cross fertilization between scientific areas.

The accessibility of user-friendly, low-cost instruments remains a major challenge in Earth observation. Most existing equipment is difficult to deploy, expensive to operate, and requires specialized technical skills. Additionally, despite efforts by global organizations, a unified observation program has yet to be established.
To meet monitoring and research needs, sensors must easily integrate with data acquisition and transmission systems while meeting accuracy and stability requirements. Recent technological advances have created opportunities to enhance sensors, platforms, and communication systems, paving the way for IoT solutions and significantly improving Earth observation capabilities. Furthermore, low-cost and easy-to-deploy instrumentation is essential to Citizen Science, enabling public participation in scientific investigations and enhancing data acquisition.
This session welcomes studies on new low-cost instruments, methods, and data transmission applications. We invite general, technical, and applied studies of Earth observation applications from any discipline, including oceanography and marine sciences, atmospheric sciences, forestry, and land sciences. Examples include:
• Low-cost technologies applied to marine science
• Low-cost technologies applied to land science
• Open-source and open-access observation devices
• Development of networks to support connected objects
• Citizen science applications

Light-weight uncrewed aerial vehicles (UAVs) have been developed in recent decades, and their potential usage in science has been widely researched. High spatial resolution UAV imaging, multispectral images, gas analyzers, and samplers mounted on UAV became a standard data source for many scientific activities. Recent advances in accessible and fast communication protocols, lightweight and powerful onboard computing devices, and novel sensor developments provide remarkable opportunities for the use of UAVs in new, creative, and original ways. The advances were underpinned by new platforms for processing data coming off UAVs. We would like to hear about novel, non-standard uses of UAVs and underlying data processing platforms that help enable science and inspire innovative approaches for our fellow scientists.

This session invites contributions on the latest developments and results in lidar remote sensing of the atmosphere, covering • new lidar techniques as well as applications of lidar data for model verification and assimilation, • ground-based, airborne, and space-borne lidar systems, • unique research systems as well as networks of instruments, • lidar observations of aerosols and clouds, thermodynamic parameters and wind, and trace-gases. Atmospheric lidar technologies have shown significant progress in recent years. While, some years ago, there were only a few research systems, mostly quite complex and difficult to operate on a longer-term basis because a team of experts was continuously required for their operation, advancements in laser transmitter and receiver technologies have resulted in much more rugged systems nowadays, many of which are already operated routinely in networks and several even being fully automated and commercially available. Consequently, also more and more data sets with very high resolution in range and time are becoming available for atmospheric science, which makes it attractive to consider lidar data not only for case studies but also for extended model comparison statistics and data assimilation. Here, ceilometers provide not only information on the cloud bottom height but also profiles of aerosol and cloud backscatter signals. Scanning Doppler lidars extend the data to horizontal and vertical wind profiles. Raman lidars and high-spectral resolution lidars provide more details than ceilometers and measure particle extinction and backscatter coefficients at multiple wavelengths. Other Raman lidars measure water vapor mixing ratio and temperature profiles. Differential absorption lidars give profiles of absolute humidity or other trace gases (like ozone, NOx, SO2, CO2, methane etc.). Depolarization lidars provide information on the shapes of aerosol and cloud particles. In addition to instruments on the ground, lidars are operated from airborne platforms in different altitudes. Even the first space-borne missions are now in orbit while more are currently in preparation. All these aspects of lidar remote sensing in the atmosphere will be part of this session.

Cosmic rays carry information about space and solar activity, and, once near the Earth, they produce isotopes, influence genetic information, and are extraordinarily sensitive to water. Given the vast spectrum of interactions of cosmic rays with matter in different parts of the Earth and other planets, cosmic-ray research ranges from studies of the solar system to the history of the Earth, and from health and security issues to hydrology, agriculture, and climate change.
Although research on cosmic-ray particles is connected to a variety of disciplines and applications, they all share similar questions and challenges regarding the physics of detection, modeling, and the influence of environmental factors.

The session brings together scientists from all fields of research that are related to monitoring and modeling of cosmogenic radiation. It will allow the sharing of expertise amongst international researchers as well as showcase recent advancements in their field. The session aims to stimulate discussions about how individual disciplines can share their knowledge and benefit from each other.

We solicit contributions related but not limited to:
- Health, security, and radiation protection: cosmic-ray dosimetry on Earth and its dependence on environmental and atmospheric factors
- Planetary space science: satellite and ground-based neutron and gamma-ray sensors to detect water and soil constituents
- Neutron and Muon monitors: detection of high-energy cosmic-ray variations and its dependence on local, atmospheric, and magnetospheric factors
- Hydrology and climate change: low-energy neutron sensing to measure water in reservoirs at and near the land surface, such as soil, snowpack, and vegetation
- Cosmogenic nuclides: as tracers of atmospheric circulation and mixing; as a tool in archaeology or glaciology for dating of ice and measuring ablation rates; and as a tool for surface exposure dating and measuring rates of surficial geological processes
- Detector design: technological advancements in the detection of cosmic rays and cosmogenic particles
- Cosmic-ray modeling: advances in modeling of the cosmic-ray propagation through the magnetosphere and atmosphere, and their response to the Earth's surface
- Impact modeling: How can cosmic-ray monitoring support environmental models, weather and climate forecasting, agricultural and irrigation management, and the assessment of natural hazards

Satellite measurements of our Earth from space are essential to our study of global
climate and weather patterns. Teasing out complexities in our Earth system requires a
framework of calibrated and curated remote sensors that can operate in space over
decadal periods. These instruments cover a variety of spectral, spatial, angular,
polarized, and coherent regimes and target specific Earth phenomena in the
atmosphere, surface, or oceans.

A comprehensive remote sensor calibration is required in order to
retrieve decadal and actionable climate trends with high accuracy and confidence.
Instrument teams follow an exhaustive pre-launch, on-orbit, vicarious, and cross-
calibration plan. Validating these efforts against radiative transfer simulations,
measurement trends over pseudo-invariant Earth targets, and dedicated field
campaigns with ground-network, airborne, or satellite-based intercomparisons help to
enhance and extend the original pre-launch characterization.

New and planned progressive missions with multi-angle polarimetry and/or multi-
instrument synergy are changing the way we understand our Earth system and how we
measure our observables. This session welcomes new research in pre-launch, on-orbit,
vicarious, and cross calibration activities on data from recently launched missions such
as PACE and EarthCARE and recent field campaigns, such as PACE-PAX, ARCSIX,
and ORCESTRA. Expected on-orbit performance studies for upcoming missions with
multi-angle polarimetry and/or multi-instrument synergy, such as 3MI, MAIA, and CO2M,
are highly encouraged as well.

Remote sensing has played a vital role in analyzing and mitigating the impacts of climate change and human activities on ecosystems. For the past three decades, satellite remote sensing has been a key tool for monitoring large areas at low cost with regular revisits. However, as the frequency of natural hazards increases, new technologies in remote and proximal sensing have emerged, aimed at improving data collection flexibility and resolution. One such technology is uncrewed aerial systems (UASs), equipped with various sensors (optical, microwave, thermal, etc.), bridging the gap between spaceborne and ground-based sensing. UASs offer ultra-high-resolution data and flexibility in flight scheduling, making them indispensable for natural and human-induced environmental risk prevention and decision-making.
UASs are particularly effective in mapping environmental changes caused by climate change, including erosion, slope instability, and riverbank degradation due to tectonic or human activities. They also support precision agriculture, monitoring crop impacts from extreme weather events, and enabling sustainable farming practices. The flexibility of UAS technology allows high-resolution data acquisition before and after events, facilitating risk detection and tailored recovery efforts.
This session will highlight the synergies between sensing technologies in the geoscience community, focusing on how these collaborations address the United Nations' Sustainable Development Goals (SDGs). Presentations are encouraged on topics such as the integration of satellite and UAS data, UAS applications in agriculture, and advancements in UAS configurations. Additionally, the session will discuss trends in UAS sensor technology and best practices for UAS operations in volcanic regions, offering a platform for showcasing the latest research and innovations in remote sensing.

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.

Critical zones (CZ) are natural and anthropogenic environments where air, water, soil, and rock interact in complex ways with ecosystems and society. Groundwater is the largest reservoir in this integrated system, but it is often overlooked due to the challenges of accessing it and its slower movement compared to other CZ components. However, dedicated CZ observatories (e.g. eLTER and CZEN) and intensively instrumented study areas provide extensive and detailed data on groundwater flow under contrasting climates, geology, vegetation and land use, and offer the opportunity for comprehensive multi-site studies.. This session aims to showcase contributions that highlight such studies, which enhance our understanding of water fluxes within the critical zone and their crucial role in energy and material cycles.

We invite presentations that address key research questions, such as (i) How do components across different scales—from the vertical column, including the atmosphere, vegetation, soil, and bedrock, to large-scale hydrosystems, spanning headwaters and 2D hillslopes, and from surface waters and the vadose zone to the deeper limits of groundwater—interact and interconnect?, (ii) How can we bridge the gap between rapid subsurface and slow groundwater flow processes with longer-term environmental changes that collectively shape the critical zone? (iii) What are the potential consequences of climate warming, extreme weather events, and wildfires on groundwater recharge, discharge processes, and water quality?

This session aims to bring together researchers and scientists from diverse backgrounds to advance our understanding of groundwater’s role in the critical zone. We seek to illustrate how combining observations and numerical experiments can help delineate future predictions for groundwater systems under various climate and land-use evolution scenarios.

Transport of sediments in geophysical flows occurs in mountainous, fluvial, estuarine, coastal, aeolian and other natural or man-made environments on Earth, while also shapes the surface of planets such as Mars, Titan, and Venus. Understanding the motion of sediments is still one of the most fundamental problems in hydrological and geophysical sciences. Such processes can vary across a wide range of scales - from the particle to the landscape - which can directly impact both the form (geomorphology) and, on Earth, the function (ecology and biology) of natural systems and the built infrastructure surrounding them. In particular, feedback between fluid and sediment transport as well as particle interactions including size sorting are a key processes in surface dynamics, finding a range of important applications, from hydraulic engineering and natural hazard mitigation to landscape evolution, geomorphology and river ecology.

A) particle-scale interactions and transport processes:
- mechanics of entrainment and disentrainment (fluvial and aeolian flows)
- momentum (turbulent impulses) and energy transfer between turbulent flows and particles
- upscaling and averaging techniques for stochastic transport processes
- granular flows in dry and submerged environments
- grain shape effects in granular flow and sediment transport
- interaction among grain sizes in poorly sorted mixtures, including particle segregation
- discrete element modelling of transport processes and upscaling into continuum frameworks
B) reach-scale sediment transport and geomorphic processes
- links between flow, particle transport, bedforms and stratigraphy
- derivation and solution of equations for multiphase flows (inc. fluvial and aeolian flows)
- shallow water hydro-sediment-morphodynamic processes
- highly unsteady and complex water-sediment or granular flows
- flash floods, debris flows and landslides due to extreme rainfall
C) large-scale landscape evolution, geohazards, and engineering applications
- natural and built dam failures and compound disasters
- coastal processes, e.g., long-shore and cross-shore sediment transport and the evolution of beach profile/shoreline
- reservoir operation schemes and corresponding fluvial processes
- design of hydraulic structures such as fish passages, dam spillways, also considering the impact of sediment
- dredging, maintenance and regulation for large rivers and navigational waterways

Aeolian processes act on planetary surfaces throughout the Solar System, yielding similar landforms and patterns across a wide range of spatial scales despite differences in atmospheric and surface properties. They are typically associated with the movement of sediments driven by an atmospheric flow but can also be controlled by other modes of matter transport such as ice sublimation. The combination of terrestrial and extra-terrestrial experiments and observations, as well as analogue studies, provides the opportunities as well as challenges for improving our fundamental theories and numerical models for better understanding of these aeolian environments. Innovations in instrumentation and experimental techniques continue to yield novel insights on Earth, while space missions and remote probes constantly deliver new and surprising evidence from aeolian environments on other planetary bodies. This session welcomes research on all aspects of aeolian processes and landforms on planetary surfaces, employing a variety of techniques, including, but not limited to, short- and long-term field experiments, laboratory experiments, numerical simulations, and remote sensing of aeolian landform features.

Sustainable agriculture and forestry face the challenges of lacking scalable solutions and sufficient data for monitoring vegetation structural and physiological traits, vegetation (a)biotic stress, and the impacts of environmental conditions and management practices on ecosystem productivity. Remote sensing from spaceborne, unmanned/manned airborne, and proximal sensors provides unprecedented data sources for agriculture and forestry monitoring across scales. The synergy of hyperspectral, multispectral, thermal, LiDAR, or microwave data can thoroughly identify vegetation stress symptoms in near real-time and combined with modeling approaches to forecast ecosystem productivity. This session welcomes a wide range of contributions on remote sensing for sustainable agriculture and forestry including, but not limited to: (1) the development of novel sensing instruments and technologies; (2) the quantification of ecosystem energy, carbon, water, and nutrient fluxes across spatial and temporal scales; (3) the synergy of multi-source and multi-modal data; (4) the development and applications of machine learning, radiative transfer modeling, or their hybrid; (5) the integration of remotely sensed plant traits to assess ecosystem functioning and services; (6) the application of remote sensing techniques for vegetation biotic and abiotic stress detection; and (7) remote sensing to advance nature-based solutions in agriculture and forestry for climate change mitigation. This session is inspired by the cost action program, Pan-European Network of Green Deal Agriculture and Forestry Earth Observation Science (PANGEOS, https://pangeos.eu/), which aims to leverage state-of-the-art remote sensing technologies to advance field phenotyping workflows, precision agriculture/forestry practices and larger-scale operational assessments for a more sustainable management of Europe’s natural resources.

Recent advances in sensing technology have resulted in the development of a range of ground-based methods which can “sense” cryospheric environments at high spatial (millimetre to centimetre scale) and temporal (minutes to hours) resolutions. Such close-range sensors can be used to observe rapidly evolving processes (e.g. iceberg calving, glacial lake outburst floods, supraglacial lake drainage events, snow accumulation/melting) as well as cryospheric environment at small spatial scales (e.g. small glaciers, glacierets, snow patches, rock glaciers). Such processes and environments cannot be observed using satellite Earth Observation techniques due to their coarse spatial resolution and long revisit times. In particular, close-range sensors are flexible in their deployment in the field and can observe cryospheric phenomenon from a range of viewing angles which is particularly beneficial in environments with complex topography which are commonplace across the cryosphere. Close-range sensors are therefore critical for improving process understanding but also for monitoring cryospheric hazards and the development of hazard warning systems.

In this session, we welcome contributions related to a variety of close-range sensing methods, including, but not limited to, uncrewed aerial vehicles (UAVs), radar, time-lapse photography, TLS and LiDAR. Contributions may include field-based applications, laboratory experiments, development of new systems (e.g. payloads, sensors), novel sensing networks, and new approaches related to the processing and analysis of these data. We strongly welcome case studies from all parts of the cryosphere, including glaciers (both land-based or calving), ice sheets, snow and firn, glacial and periglacial environments, and sea ice. The focus of this session will be to share experiences of developing and applying close-range sensors for cryospheric research in order to showcase the latest developments in the evolving field of research.

This session aims to present recent advances in the analysis of environmental and soil contaminations using Applied Geophysics, Remote Sensing and Artificial Intelligence.
Characterizing and understanding the surface and subsurface is a challenge for many scientific areas.
Applied Geophysics investigates underground using a variety of non-invasive, and non-destructive techniques such as ground-penetrating radar, magnetics, electrical resistivity tomography, electromagnetic induction, and seismics. Remote Sensing uses methods such as photogrammetry, LIDAR, GNSS, and satellite hyperspectral data to determine physical properties at a distance. Some remote sensing technologies can also provide information from the subsurface or interior of structures. Artificial Intelligence, namely Machine Learning, can be a useful tool to manage information using as input data provided by different methods, allowing the calculation of new contamination maps, that can help in the analysis of contamination areas.
Knowledge in these fields can be applied to a variety of research topics, in addition to laboratorial chemical analysis procedures, namely, to evaluate environmental pollutants (e.g. potentially toxic metals), and contributing to increasing knowledge about contaminated areas. When combined with other methods, they enable the development of integrated models of environmental management of contaminated areas, allowing the development of environmental risk maps, and contributing to the reduction of sampling and operational costs, as well as the reduction of assessment times in the management of contaminated areas.
The potential for replicability of this approaches is high, and can be applied in mines, landfills, industry and intensive agriculture.
This session will collect the contributions from Applied Geophysics, Remote Sensing, and Artificial Intelligence on the following topics:
- Environmental studies: characterization of the soil contamination by potentially toxic metals.
- Innovations in data acquisition, and processing of Geophysical, Remote Sensing and AI methods.

The precise positioning at centimeter level with GPS has been available for decades, which is lately strengthened by the emerging Global Navigation Satellite Systems (GNSS), such as the European Galileo, Chinese BeiDou, and Russian GLONASS, making positioning cost-effective and compact. OEM boards of various qualities and single-board microcontrollers allow construction of low-cost/mass-market/consumer-grade GNSS receivers that are used for applications requiring precise positioning, sensor synchronisation, GNSS reflectometry, phase time delay and signal attenuation. These applications are spread over fields such as geodesy, hydrology, (hydro-)meteorology, volcanology, natural hazards, cryospheric and biospheric sciences and (urban) navigation. Moreover, they are valuable for deriving and monitoring geophysical phenomena such as sea-level rise, crustal or surface deformation. We solicit abstracts on instrumentation and innovative applications in different fields of research, as well as algorithms, and sensor calibration and integration. We welcome any other contributions that highlight the challenges of using low-cost GNSS receivers and antennas.

Agriculture is pivotal in the European economy and the global food supply. Europe is a significant producer of diverse crops, contributing significantly to feeding the world's population. The quality and characteristics of agricultural products are closely linked to the specific environmental conditions in which they are grown. These environmental factors, including climate, soil, and water, can vary significantly across regions and are increasingly influenced by the challenges of climate change.
Understanding the spatial and temporal variability of environmental factors is crucial for managing and preserving agricultural landscapes and adapting to climate change's current and future impacts.
This requires a deep understanding of plants’ mechanisms for acclimation, keeping in mind that functional traits (e.g., phenology,etc.) can be indicators and proxies of plant status, plasticity and resilience. Moreover, it involves applied research and technological innovation in agriculture, including the use of sensors to monitor environmental variables, remote sensing and drones for crop monitoring, predictive models for yield and disease, and advanced methods to study nutrient cycles and soil health.
Furthermore, growing public awareness of the importance of ecosystem health and sustainability has led to adopting quantitative approaches to understand the link between agricultural practices and ecosystem services, which are crucial for achieving long-term environmental goals. Agroecological approaches, such as cover cropping, organic amendments, and integrated pest management, are being increasingly adopted to enhance biodiversity, soil health, water and nutrient retention, and resilience to climate change.
On these bases, the session will delve into:
- Quantifying and Spatially Modeling Environmental Factors: Examining the complex interplay of climate, soil, and water and their influence on plant growth, yield, and quality.
- Agricultural Resilience to Climate Change: Exploring the adaptability of agricultural systems in the face of a changing climate and identifying strategies for adaptation and mitigation.
- Sustainable Agricultural Practices and Ecosystem Services: Analyzing the impact of diverse agricultural practices on soil and water quality, biodiversity, and related ecosystem services.
- Precision Agriculture and Technological Innovation: Utilizing advanced technologies to optimize resource use, improve crop management, and enhance sustainability.

Uncrewed Aircraft Systems (UAS) are an emerging technology, significantly expanding observational capabilities in atmospheric and climate related sciences. This expansion is enabled by the increased availability and deployment of UAS. The rapid development of these platforms in recent years, combined with advances in miniaturised sensors, has led to a growing dataset that supports various aspects of atmospheric research in different environmental domains with linkages to hydrology, ecology, volcanology or geochemistry as well as applied sciences such as wind energy or transport of pollutants and aerosol particles.
This session invites abstracts discussing scientific contributions in atmospheric and climate sciences using various platforms, including fixed-wing UAS, multicopters, and tethered balloon/kite systems (TBS) etc. The topics could include presentations on the development of novel platforms and instrumentation, recent measurement efforts leveraging UAS systems, deployment of UAS to enhance the weather and climate prediction and monitoring networks, data analysis and synthesis from past UAS field campaigns, and other scientific interpretations of UAS-based datasets to improve process understanding, numerical model prediction, data assimilation and parameterisation development.

This session will cover applied and theoretical aspects of geophysical imaging, modelling and inversion using active- and passive-source seismic measurements as well as other geophysical techniques (e.g., gravity, magnetic, electromagnetic) to investigate properties of the Earth’s lithosphere and asthenosphere, and explore the processes involved. We invite contributions focused on methodological developments, theoretical aspects, and applications. Studies across the scales and disciplines are particularly welcome.

Among others, the session may cover the following topics:
- Active- and passive-source imaging
- Full waveform inversion developments and applications
- Advancements and case studies in 2D and 3D imaging
- DAS imaging
- Interferometry and Marchenko imaging
- Seismic attenuation and anisotropy
- Developments and applications of multi-scale and multi-parameter inversion
- Joint inversion of seismic and complementary geophysical data

Rapid population growth, with more than 70% of the world's population expected to live in cities by 2050, is making
urban areas and civil infrastructures crucial elements of the modern society. On the other hand, natural hazards
associated with climate change are making urban areas and civil infrastructures more and more exposed and
vulnerable to extreme events. Accordingly, the strategic programs for the sustainability and resilience of cities and civil
infrastructures (e.g. bridges, dams, lifelines) are promoting the development of novel strategies and methodologies for
non-destructive and not, or minimally, invasive surface and subsurface geophysical exploration and monitoring.
The session aims at presenting and discussing recent technological and methodological advances in urban geophysics.
Particular attention will be towards novel and effective modalities of performing surveys by means of seismic and electromagnetic methods, innovative sensors (e.g. fibre optics, MEMS) for dense and distributed geophysical network arrays, the use of AI-based algorithms and machine learning technologies for data processing and analysis, monitoring approaches based on augmented vision strategies of geophysical data. Furthermore, great attention
will be devoted to the presentation of applicative case studies, to the analysis of the interaction between subsurface, soil and built environment, and to the discussion of the contribute provided by the applied geophysics in urban programs for the “compact cities”, representing a new challenge
for avoiding urban sprawl and adaptation to climate change. The session also aims at promoting the activities of Early Career Scientists (ECS) in facing open challenges in the framework of urban geophysics.

Sustainability and resilience have become mainstream goals of political agendas globally, contrasting the causes of climate change and mitigating its effects, respectively. Built environment issues, infrastructure maintenance and rehabilitation, urbanisation and environmental impact are pushing for broader-scale goals, like climate change assessment and natural disaster prediction and management. In this context, Non-destructive testing (NDT) and Earth Observation (EO) methods lend themselves to be instrumental at developing new monitoring and maintenance approaches.
Despite the technological maturity reached by NDT and EO, important research gaps on standalone technologies and their integration are still unexplored. One challenging issue is the development of monitoring systems based on the integration of sensing technologies with advanced modelling, ICT and position/navigation topics up to IOT and the new concept of citizen engineer. The goal is to provide stakeholders with handy and user-friendly information to support maintenance and controlling major risks.
This Session primarily aims at disseminating contributions from state-of-the-art NDT and EO methods, promoting stand-alone technology and their integration for the development of new investigation/monitoring methods, applications, theoretical and numerical algorithms, and prototypes for sustainable and resilient infrastructure and built environments.
The followings are areas of interest and priority for this Session:
- sensor types, systems and working modes (acoustic/electric/electromagnetic/nuclear/radiography/thermal/optical/vibration sensors; remote and ground-based, embedded sensing systems; stand-alone and integrated multi-source sensing modes);
- advanced processing methods and information analysis techniques (multi-dimensional signal processing; image processing; data processing and information analysis; inversion approaches, AI);
- multi-sensor, multi-temporal and multi-modal data fusion and integration (image fusion; spatio-temporal data fusion; AI and machine learning for data fusion and integration);
- ICT for spatial data infrastructure, distributed computing and decision support systems;
- citizens as “sensors” for defect detection and data collection;
- new NDT applications and EO missions for downstream implementations;
- NDT and EO for new standards, policies and best practices;
- case studies relevant to built environment diagnostics and monitoring.

This session is focused on processes occurring within the lithosphere in the framework of the environmental systems, and it is oriented toward collecting studies relevant to understand the multiscale aspects of these systems and in proposing adequate multi-platform and inter-disciplinary tools for their monitoring.
The session is especially aimed to emphasize the interaction between the different environmental processes occurring at various spatial and temporal scales, which can also involve several orders of magnitude. Special attention is devoted to the studies focused on the development of techniques of data analysis and collection through new algorithms and technologies for multiscale monitoring of natural area characterize by different hazard, such as associated to volcanic processes, seismic events, energy exploitation, slope instability, floods, coastal instability, climate changes, and any other environmental context.
We expect contributions derived from several disciplines, as applied geophysics, geology, seismology, geodesy, geochemistry, remote and proximal sensing, volcanology, applied geology, soil science, marine geology, oceanography, climatology, and meteorology. In this context, the contributions in analytical and numerical modeling of geological and environmental processes are welcome, as well as the inter-disciplinary studies that highlight their multiscale properties.
The session includes, but not limited to, the following topics:
-Strategies of monitoring of the environmental systems in the space-time domain;
-Modeling methods for the simulation of environmental processes and optimization of their representative parameters;
-Laboratory experiments and field activities to study and model the sources, transport and effect of traditional and emerging contaminants in the environments;
-Environmental impact and risk analyses, uncertainty estimates and vulnerability/resilience assessment.

The low field NMR technique is emerged as one of the most important tool for the geophsyical prospecting including the resource exploration and development, the pore size description, the groundwater detection , as well as the carbon capture and geological storage. However, there are now many difficulties when using the low field NMR instrument and data due to the complex geological bodies and the extreme measurement environments. The topics of interests include but are not limited to,
(1) Theory and numerical simulations on the low field NMR technique.
(2) Denoising and inversion of the low field NMR data.
(3) Laboratory low field NMR measurements and data manipulation.
(4) Quantitative processing and machine learning on the low field NMR data.
(5) Application and case studies of low field NMR data

The quest to identify optimal methodologies for the observation of geological and environmental processes at the Earth's surface and for analyzing related data presents a significant challenge for numerous researchers. The spatial and temporal dimensions of a given process, along with the selected observational scale, can profoundly influence the comprehensive understanding of the phenomenon in question. Additionally, the unique structural characteristics of geochemical data, which detail the composition of the matrices employed, often obscure meaningful relationships among elements, leading to misleading correlations.
The primary objective of this session is to facilitate a comparative analysis of various methods, encompassing both cutting-edge monitoring and data processing techniques, to offer a real-time assessment of the advantages and disadvantages associated with the diverse approaches presented. Researchers utilizing geochemical data for the assessment of the impact of human activities on the environment or for exploration purposes are encouraged to participate in this session.
While studies focusing on individual matrices are welcomed, research that derives insights from integrated plans involving multiple matrices, including biological ones, is particularly sought after.
Contributions that emphasize data processing techniques utilizing multivariate analysis, machine learning, geostatistics, and other spatial or non-spatial analytical methods are especially encouraged, particularly when they address the compositional nature of geochemical data.

The session covers all methods and case histories related to measuring, processing and modelling potential field anomalies for geological, environmental and resources purposes. It will concern gravity and magnetic data from satellite missions to airborne and detailed ground-based arrays. Contributions presenting instrumental, theoretical and computational advances of data modelling/processing techniques as well as new case studies of geophysical and geological interest are welcome. This session will also encourage presentations on compilation methods of heterogenous data sets, multiscale and multidisciplinary approaches for natural resources exploration and geological gas storage purposes, and other environmental applications. Potential field applications in exploration and geological interpretation of magnetic anomalies, jointly with other geodata, are warmly welcome.

Modelling the subsurface structure of planetary bodies using gravity and magnetic data has been extensively applied across a range of celestial bodies, including the Earth, Moon, terrestrial planets (i.e., Mars, Mercury, Venus), and icy satellites (e.g., Ganymede, Europa, Callisto and Enceladus). In combination with measurements of surface topography and shape, the interior properties of celestial bodies, such as thickness and density of internal layers, can be inferred. These studies are pivotal for the understanding of their geological evolution. This session will explore the latest methods and approaches in developing planetary gravity and magnetic field models, conducting topographical analyses, and carrying out data modelling techniques to unravel the internal structures of planets and satellites. Contributions spanning various aspects of planetary research, including theoretical studies, observational data, and the development of potential field solutions are welcome. Additionally, presentations on innovative data processing and interpretation methods, advances in subsurface modeling techniques, and specific case studies of geological interest are encouraged. New insights from the analysis of potential field data from past missions, combined with contributions on the preparation and anticipated findings from recent and upcoming missions (e.g., BepiColombo, JUICE, Europa Clipper, Veritas, EnVision), as well as advanced applications, will offer the community a comprehensive understanding of this dynamic area of planetary research.

Observing soil moisture at the ground is essential to assess plant available water, manage water resources and calibrate, validate satellite products and conduct climate impact studies. Unfortunately, the availability of in situ observations is very limited in space and time. Whereas the spatial distribution is biased towards the global North, the average temporal variability of soil moisture time series is on average 10 years as can be seen from the largest archive of in situ soil moisture, the International Soil Moisture Network (ISMN). Apart of the data availability issues, a substantial amount of the in situ observations face data quality issues that might result from sensor deployment, sensor calibration, data processing or other error sources.
This session is meant to address issues in the development and deployment of state-of-the-art soil moisture observation networks, the financing of its long-term operation, data quality assurance, as well as sensor deployment and assessments of differences between these deployments. We further encourage contributions presenting developments of novel measurement techniques including citizen science initiatives and studies utilizing in situ soil moisture for water availability assessments.

Earth’s cryosphere demonstrates itself in many shapes and forms, but we use similar geophysical and in-situ methods to study its wide spectrum: from ice-sheets and glaciers, to firn and snow, sea ice, permafrost, and en-glacial and subglacial environments.
In this session, we welcome contributions related to all methods in cryospheric measurements, including: advances in radioglaciology, active and passive seismology, geoelectrics, acoustic sounding, fibre-optic sensing, GNSS reflectometry, signal attenuation, and time delay techniques, cosmic ray neutron sensing, ROV and drone applications, and electromagnetic methods. Contributions can include field applications, new approaches in geophysical or in-situ survey techniques, or theoretical advances in data analysis processing or inversion. Case studies from all parts of the cryosphere, including snow and firn, alpine glaciers, ice sheets, glacial and periglacial environments, alpine and arctic permafrost as well as rock glaciers, or sea ice, are highly welcome.
This session will give you an opportunity to step out of your research focus of a single cryosphere type and to share experiences in the application, processing, analysis, and interpretation of different geophysical and in-situ techniques in these highly complex environments. This session has been running for over a decade and always produces lively and informative discussion. We have a successful history of PICO and other short-style presentations - submit here if you want a guaranteed short oral!

The preservation, protection, and fruition of cultural heritage are closely related to the scientific knowledge of the component materials, their history and surrounding environment, and how these affect the characteristics and transformation of historical objects, structures, and sites. Geosciences represent a valuable partner for studies in conservation science and archaeometry, providing a solid background for addressing a number of questions revolving around natural and artificial geomaterials (stones, ceramics, mortars, pigments, glasses, metals, etc.), their features and settings. This session welcomes contributions showcasing the application of geosciences to the following topics:
- properties, provenance, production, use, and durability of historical materials;
- weathering processes, simulations, modeling, vulnerability assessment, and risk scenarios;
- field and laboratory methods of analysis and testing, especially by non-destructive and non-invasive techniques;
- novel and sustainable methods and products for conservation and restoration;
- impact of environmental variables (related to microclimate, climate, climate change, and composition of air, waters, and soils) outdoors, indoors, underground, or underwater;
- identification of possible adaptation measures;
- hardware/software design for collecting and processing compositional and environmental databases.

A wide range of geo-electromagnetic methods, including natural source magnetotelluric, time-domain, and frequency-domain controlled source EM, as well as DC resistivity and induced polarization are uniquely sensitive to the Earth’s electrical properties and are capable of probing from shallow depths near the surface to even hundreds of kilometers into the Earth's crust. They are invaluable for revealing subsurface structures, fluid distributions, mineral resources, tectonic features, and even engineered infrastructure. Traditionally essential in resource exploration, geo-electromagnetic methods are now becoming increasingly relevant in addressing new global challenges related to energy systems, the impacts of climate change, environmental problems, and urban development and resilience.

This session serves as an annual platform for showcasing the latest advancements in geo-electromagnetic research. We encourage contributions from a broad range of topics, including methodological breakthroughs, novel field observations, theoretical advancements, and case studies. This year, we particularly welcome submissions that highlight innovative uses of geo-electromagnetic methods in emerging areas—whether through state-of-the-art instrumentation, unconventional applications, or studies with significant societal or environmental relevance.

Geological and geophysical data sets convey observations of physical processes governing the Earth’s evolution. Such data sets are widely varied and range from the internal structure of the Earth, plate kinematics, composition of geomaterials, estimation of physical conditions, dating of key geological events, thermal state of the Earth to more shallow processes such as natural and "engineered" reservoir dynamics in the subsurface.

The complexity in the physics of geological processes arises from their multi-physics nature, as they combine hydrological, thermal, chemical and mechanical processes. Multi-physics couplings are prone to nonlinear interactions ultimately leading to spontaneous localisation of flow and deformation. Understanding the couplings among those processes therefore requires the development of appropriate numerical tools.

Integrating high-quality data into physics-based predictive numerical simulations may lead to further constraining unknown key parameters within the models. Innovative inversion strategies, linking forward dynamic models with observables, and combining PDE solvers with machine-learning via differentiable programming is therefore an important research topic that will improve our knowledge of the governing physical parameters.

We invite contributions from the following two complementary themes:

#1 Computational advances associated with
- Alternative spatial and/or temporal discretisation for existing forward/inverse models
- Scalable HPC implementations of new and existing methodologies (GPUs / multi-core)
- Solver and preconditioner developments
- Combining PDEs with AI / Machine learning-based approaches (physics-informed ML)
- Automatic differentiation (AD) and differentiable programming
- Code and methodology comparisons (benchmarks)

#2 Physics advances associated with
- Development of partial differential equations to describe geological processes
- Inversion strategies and adjoint-based modelling
- Numerical model validation through comparison with observables (data)
- Scientific discovery enabled by 2D and 3D modelling
- Utilisation of coupled models to explore nonlinear interactions

The research output presented in this session can be submitted to the ongoing Special Issue (SI) in the EGU journal of Geoscientific Model Development (GMD): https://www.geoscientific-model-development.net/articles_and_preprints/scheduled_sis.html

Continuous monitoring of natural physical processes is crucial for understanding their behaviour. The variety of instruments available enhances data collection, aiding in the comprehension of these processes. Long-term data collection reveals trends and patterns, such as seasonal variations, multi-year cycles, and anthropogenic impacts (e.g., deforestation, urbanization, pollution). Conversely, short-term monitoring is vital for real-time decision-making, improving hazard assessment, risk management, and warning systems. Effective data analysis and innovative instrumentation contribute to developing mitigation and adaptation strategies. This session highlights the application of geosciences and geophysical instrumentation, including sensors in natural and laboratory environments, for monitoring natural phenomena and utilizing data systems to study these processes.
The session disseminates advanced research on natural physical processes and the use of scientific principles to address future challenges, including extreme climatic conditions. It encourages novel, interdisciplinary approaches to monitoring, aiming to establish historical baselines. This session seeks to bridge scientific knowledge and technological advancements to improve monitoring and understanding of natural physical processes. The session is inter- and transdisciplinary (ITS), covering topics such as:

1. Destructive and Non-Destructive Sensing Techniques, including contactless and remote sensing methodologies.
2. Monitoring System Developments for understanding hydro-meteorological processes, glaciers, soil erosion, settlements, liquefaction, landslides, earthquakes, volcanic events, and wildfires.
3. Real-Time Monitoring Systems, integrating geoscience data with Building Information Modelling (BIM), digital twins, robotic monitoring, and automation for improved decision-making.
4. Advances in Data Systems for efficient real-time monitoring and processing of large data volumes using Cloud Data Platforms, Distributed and Scalable Data Systems, Real-Time Data Processing, AI, Machine Learning, Data Privacy and Security, and Edge Computing.
5. Storage Technologies and Data Integration, including advancements in Graph Databases, Data Interoperability, and Multi-Model Databases.
6. Intelligent data analysis approaches to analyse accurate and precise interpretation of big data sets driven by various technologies.

Remote sensing measurements from ground, UAV, aircraft and satellite platforms have increasingly become established technologies to study and monitor Earth’s surface, to perform comprehensive analysis and modeling, with the final goal of supporting decision making. The spectral, spatial and temporal resolutions of remote sensors have been continuously improving, making environmental remote sensing more accurate and comprehensive than ever before. Such progress enables understanding of multiscale aspects of high-risk natural phenomena and development of multi-platform and inter-disciplinary surveillance monitoring tools. The session welcomes contributions focusing on present and future perspectives in environmental remote sensing, from multispectral/hyperspectral optical and thermal sensors. Applications are encouraged to cover, but not limited to, the monitoring and characterization of environmental changes and natural hazards from volcanic and seismic processes, landslides, and soil science. Specifically, we are looking for novel solutions and approaches including the topics as follows: ecosystem assessment and monitoring, land use/cover changes, coastal environments and climate change, techniques for data fusion (spectral, spatial and temporal), disaster monitoring, new sensors and platforms for environmental studies.

Robust multi-platform approaches are essential in thermal studies within active geothermal and volcanic environments, spanning various spatial and temporal scales. The proposed session's aim is to integrate thermal data from several platform, including satellites, unmanned aerial vehicles (UAVs), in-situ sensors, and laboratory analyses encouraging the integration of the thermal data with other multiparametric datasets. The session will highlight the synergies between different environmental process scales and the technological advancements in data acquisition and numerical modeling. Special emphasis will be placed on pioneering studies that introduce new methods or enhance numerical modeling and integrated systems for monitoring areas affected by geothermal and volcanic activity. These initiatives are crucial for advancing our ability to predict and manage the natural risks associated with these dynamic environments. In conclusion, this interdisciplinary approach is aimed at enhancing our predictive capabilities and developing more effective strategies for managing natural phenomena in geothermal and volcanic settings, improving response strategies and predictive capabilities for these dynamic environments.
We invite contributions from several of disciplines, including remote sensing, applied geophysics, geothermics, volcanology, geochemistry.

Imaging the Earth’s surface and reconstructing its topography to study the landscape and (sub-) surface processes have strongly evolved during the past two decades, sometimes separately in different scientific disciplines of geosciences. New generations of satellites, Uncrewed Aerial Vehicles (UAVs), LiDAR systems, Structure-from-Motion (SfM) methods and deep learning approaches have made 2D, 3D and 4D (time series) data acquisitions easier, cheaper, and more precise. The spatial, temporal and spectral resolutions of the measurements cover wide ranges of scales, offering the opportunity to study the evolution of the ground surface from local to regional scale with unprecedented details. Coupled with the development of optimized workflows to digitize and process analogue data, such as historical aerial photographs, geoscientists now have various sets of tools to better understand our rapidly changing environments and distinguish the anthropogenic and natural causes of these changes.

However, challenges still exist at both methodological and application levels. How to properly acquire images and 3D data in harsh, remote or non-ideal environments? How to deal with complex camera distortions? How to process unknown, damaged and/or poorly overlapping digitized analogue photographs? How to properly assess the precision of these measurements and take these estimates into account in our results and interpretation? How to deal with heterogeneous time series? These questions exemplify situations commonly faced by geoscientists.

In the present session, we would like to gather contributions from a broad range of geoscience disciplines (geomorphology, glaciology, volcanology, hydrology, bio-geosciences, geology, soil sciences, etc.) to share our views and experience about the opportunities, limitations and challenges that modern 2D/3D/4D surface imaging offers, no matter the physical process or environment studied. Contributions can cover any aspects of surface imaging, from new methods, tools and processing workflows to precision assessments, time series constructions and specific applications in geosciences. We would like to especially emphasize contributions that cover 1) novel data acquisition and processing approaches (including image matching, camera distortion correction, complex signal/image and point cloud processing, and time series construction), 2) data acquisition in complex and fast-changing environments, and 3) innovative applications in geosciences.

Fast and reliable access to large datasets is the fundament of hydrological research. According to the FAIR principles, sustainable research data should be findable, accessible, interoperable, and reusable in a way that the reproducibility of research experiments is guaranteed. There are several global and regional hydrological databases that are providing harmonized data from different data sources. Thereby they serve as archives, as well as an intermediate between data providers and users. The great value of the databases is shown in the diversity of studies, assessments and data products originating from the provided data, supporting the integrative understanding of the hydrologic cycle. At national and international levels, these databases are also used for the assessment of water resources for policy guidance.
This session aims to show ideas, concepts, efforts and challenges in developing data products as well as demonstrating the benefit of setting up, maintaining networks, and sharing data in order to support the data acquisition ambitions of data centres. This session contributes to IHP IX (2022 - 2029) goal, which puts science, research and management into action for a water secure world. We invite contributions on the following topics:
1. Data services: processing, quality assurance and data discovery
- Methods and challenges of collection and provision of reliable data and metadata to the science community
- Improvement in database services e.g. versioning, dissemination or integration of new features that are relevant to science and research applications
- Development of ontologies and reference datasets showing how metadata can be used to streamline data findability
2. Tools and data-derived products for integrative observation of the hydrologic cycle
- Integrated data products derived from the analysis of existing databases
- Tools and platforms for data exchange and exploration
- Collaborative and interoperable data platforms to create a contextual and unified analysis for better decision making
3. From data to action: role of data services in operational hydrology
- Data-driven studies and projects that aim to support decision making and policy formulation
- Studies showing the contribution of large data services to assessing water resources at national, regional and global scales
- Case studies demonstrating the benefits of operational observation networks to improve local, regional and global hydrological products and services

After the joint ESA/JAXA mission BepiColombo completed 4 successful swingbys of Mercury with closest approaches of only 200 km, spacecraft observations and numerical modelling give us insight into the unexplored regions around the innermost terrestrial planet. Together with data obtained by the late NASA mission MESSENGER, BepiColombo’s swingbys and orbit phase will lead to new understanding about the origin, formation, evolution, composition, interior structure, and magnetospheric environment of Mercury. This session hosts contributions to planetary, geological, exospheric and magnetospheric science results based on spacecraft observations by Mariner 10, MESSENGER, BepiColombo, and Earth-based observations, modelling of interior, surface and planetary environment and theory.
In particular, studies investigating the required BepiColombo observations during the nominal mission to validate the existing theoretical models about the interior, exosphere and magnetosphere are welcome, as well as presentations on laboratory experiments useful to confirm potential future measurements.

The MacGyver session focuses on novel sensors made, or data sources unlocked, by scientists. All geoscientists are invited to present:
- new sensor systems, using technologies in novel or unintended ways,
- new data storage or transmission solutions sending data from the field with LoRa, WIFI, GSM, or any other nifty approach,
- started initiatives (e.g., Open-Sensing.org) that facilitate the creation and sharing of novel sensors, data acquisition and transmission systems.

Connected a sensor to an Arduino or Raspberri Pi? Used the new Lidar in the new iPhone to measure something relevant for hydrology? 3D printed an automated water quality sampler? Or build a Cloud Storage system from Open Source Components? Show it!

New methods in hydrology, plant physiology, seismology, remote sensing, ecology, etc. are all welcome. Bring prototypes and demonstrations to make this the most exciting Poster Only (!) session of the General Assembly.

This session is co-sponsered by MOXXI, the working group on novel observational methods of the IAHS.

Sedimentary archives can be found across diverse environments worldwide, allowing investigation and disentanglement of past environmental processes over different setting. However, one key limitation in the investigation of such records is deciphering the complexity of how the different forcings acting in a natural system are manifested in the environment and consequently propagated into the studied archives. Interpretations derived from any sedimentary archive thus depend on a our understanding of the surrounding natural system itself and its web of feedbacks, the investigated sedimentary record, and the utilized proxies. Such interpretations often call for the integration of different disciplines, the development of new tools for sampling, novel laboratory methodologies and modelling.

For this session we welcome any contribution that integrates sedimentological, geochemical, biological, and geochronological methods, as well as modelling approaches, novel laboratory experiments and monitoring, for the interpretation of sedimentary systems, with a special focus on mechanism-oriented interpretation. Contributions that either focus on the development and calibration of novel proxies, analytical approaches (either destructive or non-destructive) and data analysis (statistics, machine learning, AI), or present interesting case studies, are welcome as well.

The LEO space environment is far more crowded than ever before, with mega-constellations of commercially owned satellites comprising a large proportion of operational LEOsats providing vital services including Earth observation, climate monitoring, and communications. LEO residents also include debris and include rocket bodies, defunct satellites, and fragments of destroyed satellites. Despite commitments to the removal of satellites from the LEO protected region within 5 years of end of mission, through deorbit or transfer to a graveyard orbit, this will only limit the growth of space debris, not actively reduce it. In order to maintain the safety, sustainability and accessibility of LEO orbits and beyond, work across a broad range of disciplines must be done to enable successful global coordination of space traffic management. This session aims to highlight ongoing computational and experimental research aimed at achieving a sustainable space future, including but not exclusive to: improving space situational awareness, understanding satellite re-entry and its impacts on the upper atmosphere, and identifying and disposing of space debris.

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

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.

Sitting under a tree, you feel the spark of an idea, and suddenly everything falls into place. The following days and tests confirm: you have made a magnificent discovery — so the classical story of scientific genius goes…

But science as a human activity is error-prone, and might be more adequately described as "trial and error", or as a process of successful "tinkering" (Knorr, 1979). Thus we want to turn the story around, and ask you to share 1) those ideas that seemed magnificent but turned out not to be, and 2) the errors, bugs, and mistakes in your work that made the scientific road bumpy. What ideas were torn down or did not work, and what concepts survived in the ashes or were robust despite errors? We explicitly solicit Blunders, Unexpected Glitches, and Surprises (BUGS) from modeling and field or lab experiments and from all disciplines of the Geosciences.

Handling mistakes and setbacks is a key skill of scientists. Yet, we publish only those parts of our research that did work. That is also because a study may have better chances to be accepted for publication in the scientific literature if it confirms an accepted theory or if it reaches a positive result (publication bias). Conversely, the cases that fail in their test of a new method or idea often end up in a drawer (which is why publication bias is also sometimes called the "file drawer effect"). This is potentially a waste of time and resources within our community as other scientists may set about testing the same idea or model setup without being aware of previous failed attempts.

In the spirit of open science, we want to bring the BUGS out of the drawers and into the spotlight. In a friendly atmosphere, we will learn from each others' mistakes, understand the impact of errors and abandoned paths onto our work, and generate new insights for our science or scientific practice.

Here are some ideas for contributions that we would love to see:
- Ideas that sounded good at first, but turned out to not work.
- Results that presented themselves as great in the first place but turned out to be caused by a bug or measurement error.
- Errors and slip-ups that resulted in insights.
- Failed experiments and negative results.
- Obstacles and dead ends you found and would like to warn others about.

--
Knorr, Karin D. “Tinkering toward Success: Prelude to a Theory of Scientific Practice.” Theory and Society 8, no. 3 (1979): 347–76.

In the evolving landscape of sensor networks, the demand for energy-efficient and autonomous systems has never been more critical. The ability to power sensors through energy harvesting and off-grid energy production, for example, from hidden and untapped hydro resources, is pivotal for the continuous and autonomous operation of monitoring systems in remote and challenging environments. To push the boundaries of current research and development in this field, we invite the submission of abstracts for research papers that explore innovative solutions, technologies, and methodologies in energy harvesting and off-grid energy production to enhance self-powered sensors.
Topics of Interest:
We are seeking original research contributions that address, but are not limited to, the following topics:
1) Energy Harvesting Technologies:
* Hydro, solar, wind, thermal, and kinetic energy harvesters
* Novel materials and devices for efficient energy conversion
* Hybrid energy harvesting systems
* Development of electromagnetic and piezoelectric harvesters
2) Off-Grid Energy Production:
* Micro and nano-scale energy generators
* Autonomous energy systems for remote sensor networks
* Integration of renewable energy sources in sensor networks
3) Self-Sustaining Sensor Networks:
* Design and optimization of energy-autonomous sensors
* Power management strategies for off-grid sensor systems
* Case studies of self-supplying sensor deployments in challenging environments
4) Applications and Case Studies:
* Environmental monitoring in remote areas
* Industrial IoT and smart agriculture applications
* Healthcare monitoring in off-grid settings

This session is an initiative from the H-HOPE Horizon project: https://h-hope.eu/

The growing demand for raw material, coupled with the need to reduce the environmental footprint of the resource sector, highlights the importance of accurately characterizing both primary (ore) and secondary (recycled) material streams.

Improved efficiency requires detailed resource data to (1) effectively concentrate and extract valuable materials, (2) minimize and manage waste, and (3) reduce the total energy consumption and CO2 footprint. Advances in digitalisation and automatisation offer solutions to these challenges, through robotic data-collection platforms, data-driven resource, and process modelling tools.

These technologies facilitate real-time, precise decision-making, improving the efficiency of exploration, mining, and recycling processes while contributing to a more sustainable circular economy.

This session will explore cutting-edge mineral exploration and resource characterisation tools, including techniques that integrate multi-scale, multi-source, and multidisciplinary approaches. These include, but are not limited to, X-ray sensors (e.g., XRF, XRT), spectroscopy and hyperspectral techniques, LIBS, electromagnetic, seismic, and potential-field geophysics, combined with machine learning, AI models, and efficient mechatronic solutions.

Topics of interest include:
- Field based and analytical approaches to understand and map resources at multiple scales (e.g. geophysical and/or geochemical mapping, isotopic characterization, digital outcrops and hyperspectral imaging);
- Non-destructive techniques, featuring core scanners, in-line sensor systems, and the use of ground-based and airborne sensors for precise and efficient resource identification and characterisation;
- Automated, real-time data processing that optimize ore sorting, processing, and recycling;
- Data-driven quantification and predictive modelling of mineral systems and contained resources;
- Innovative methods for data integration and visualization from diverse sources to enhance accuracy and efficiency of resource characterization.

By bringing together experts from various disciplines, this session aims to foster collaboration and inspire innovative approaches that will shape the future of sustainable resource exploration and management.

The role of natural hydrogen (a.k.a. “geological”, or “white” hydrogen) as a potential major contributor to a decarbonized energy system in the future has sparked significant debate in recent years. Geological helium resources, independent of co-production with fossil fuels, have similarly attracted the attention of both scientists and industry professionals, especially when co-located with hydrogen.

To date, a truly interdisciplinary scientific understanding of the subsurface natural hydrogen/helium system is lacking, with knowledge being fragmented across disciplines, and exploration/assessment workflows in their infancy. This session aims to address key subsurface aspects of geological hydrogen/helium systems, soliciting contributions from a broad range of disciplines, covering solid earth geosciences, geochemistry, hydrology, remote sensing and soil system sciences. In particular, the session aims to address:

- Generation potential and migration/possible accumulation processes and fluid pathways
- Geological history of such systems through the Wilson cycle
- Source rock/origin and conversion kinetics, flux estimates and relation to emplacement/host environment through geological time
- Spatial characteristics of geological hydrogen/helium systems - distribution, 3D geometry and their activity through geological time.
- Measurement and instrumentation aspects to detect, characterize, and quantify source, fluxes, shallow subsurface interactions and surface leakage of H2 and He.
- Natural hydrogen/helium occurrences and recent discoveries

While the need for global cooperation in the face of global trends is obvious, funding mechanisms for environmental research and monitoring are still largely organised on a national and regional basis. Despite declared intentions to improve cooperation and thematic coordination in the formulation of related research and infrastructure programmes, concrete cooperation is hampered by a lack of resources and time for consultation, even in the case of thematically appropriate calls. This affects not only collaborative projects but also the improvement of interoperability and, ultimately, the concerted development and sustainable operation of services. Initiatives such as the G8 Group of Senior Officials (GSO) with its Recommendations for Global Research Infrastructures (GRI) have not led to a structural improvement of the situation. Still, Environmental Research Infrastructures (ENVRIs), have become a key instrument in environmental science and science-driven environmental politics.
Contributions to this session should present successful examples, experienced constraints and derived recommendations for action. They might address the value chain from open standardised observations and experiments data via scientific analysis towards societal impact through actionable knowledge, but also refer to,basic ENVRI activities like access to long-term operated in-situ facilities. An Impact Lecture will introduce the Global Ecosystem Research Infrastructures Initiative, in which SAEON/South Africa, TERN/Australia, CERN/China, NEON/USA, ICOS/Europe and eLTER/Europe will present their work on harmonised data systems, training and development, and collaboration in the use case 'ecological drought'.

Carbon dioxide, methane and nitrous oxide emissions are the primary greenhouse gases (GHGs) driving climate change and severely impacting the environment. It is essential to first control and reduce these emissions, and then implement novel engineering techniques such as carbon dioxide, methane capture, destruct and sequestration to further decrease their atmospheric levels. This session aims to connect science-based measurements, engineering approaches, industrial measurement-based studies and policy to provide an environment for exploring the potentials for reducing, destructing and storing emissions and atmospheric greenhouse gases abundances. Measurement-based emission quantification methods are key due to the EU Methane regulation and OGMP2.0 (level 5 = site level) for emission reduction regulation. Top-down and bottom-up emission quantification reconciliation is core of efforts for framing the emissions rates in well order; i.e. measurements, monitoring, reporting and verification.

Measurement-based methods are crucial for gaining a better understanding of emission sources, which can inform policymakers and engineers in developing relevant policies and engineering solutions to address both anthropogenic and natural emissions. While greenhouse gas emission sources are known, accurately quantifying their emissions remains a challenge. For this session abstracts are invited from studies focusing on campaign planning strategies, challenges, measurement-based studies, emission reduction cases, engineering techniques for capturing or storing emissions, the impact of legislation on emission reduction, flux-inversion modelling, integrations between methods and the relationship between GHG emissions and health.

This session welcomes contributions that utilize multi-scale observational data to enhance emission estimates, with a specific focus on methodologies, case studies, and implications for climate change mitigation. Researchers from academia and industry, policymakers, and practitioners are encouraged to share their findings and insights on the use of advanced automated and non-automated observational techniques to improve our understanding, management and engineering of GHG emissions from onshore and offshore sources.